Guidebook for Data and Information Systems for Transportation Asset Management (2021)

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Appendices P A R T I I I

C O N T E N T S III-3 Appendix A Specify and Standardize Data: Element-Level Response Templates III-19 Appendix B Collect Data: Element-Level Response Templates III-31 Appendix C Store, Integrate, and Access Data: Element-Level Response Templates III-47 Appendix D Analyze Data: Element-Level Response Templates III-53 Appendix E Act as Informed by Data: Element-Level Response Templates III-60 Appendix F Detailed Organizational Practices III-72 Appendix G Implementation Support: Case Studies III-84 Appendix H Facilitator Materials III-110 Appendix I TAM Data Assistant Quick Reference Guide III-122 Appendix J Detailed Literature Review III-201 Appendix K Research Implementation

III-3 A P P E N D I X A Specify and Standardize Data: Element-Level Response Templates This appendix offers element-level response templates for Area A: Specify and Standardize Data. Note: Use of the TAM Data Assistant is recommended; however, these templates are provided for informal use or pen-and-paper assessment.

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.1.a – Asset Inventory Data Model1-Inventory, Condition, and Performance Element Description Standardized asset categories, component breakdowns and core attributes, providing the foundation for asset inventory information tracking, integration, summary, and reporting. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 There are no commonly adopted definitions or methodologies for tracking inventory information for a given asset or asset type. The asset has been defined, and the approach for asset inventory has been established e.g., sampling versus full inventory; itemize each asset versus counts). An asset breakdown structure has been established to define various asset subtypes and components. There are clear criteria for assigning sub-types and identifying components. A minimum set of required inventory attributes have been identified (e.g., unique identifier, location, install date, asset subtype, size/measure). Additional recommended and optional data elements have been identified. The desired extent of collection has been established. A detailed asset information model has been defined that supports direct integration with project and maintenance information, contracts and/or design files. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define the “asset” and determine how the asset inventory should be recorded to support current/desired practice. Develop the “asset breakdown structure”, providing clear criteria for identifying various asset “sub- types” and “components”. Specify detailed inventory data elements for each asset, sub-type, and component. Set required, recommended, and optional inventory data. Document a detailed asset information model facilitating direct integration of asset inventory with maintenance work orders and project files. Coordinate with field and office staff to identify current inventory data collection practices and standards. Evaluate existing inventory standards to identify gaps or inconsistencies in current standards for improvement. Specify minimum levels of inventory data coverage to meet decision-making, communication, and reporting needs. Routinely evaluate the asset information model to ensure alignment with TAM, project, and maintenance development needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.1.b – Asset Condition and/or Performance Data Model1-Inventory, Condition, and Performance Element Description Standardized asset condition and performance data types, detailed attributes, and summary indices, ratings, or scores that are useful in asset related decision-making and communication. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Condition or performance data elements and collection methods have not yet been defined for the asset or asset type. General condition or performance data elements have been defined for the asset or asset type. General condition or performance categories and/or ratings have been defined for the asset or asset type. Specific data attributes related to the condition or performance measures have been established (e.g., observation date, detailed data attributes, overall rating). A methodology has been defined to evaluate asset specific condition or performance information against a common, cross asset performance metric (typically associated with net benefit, value, contribution, or need based on the agency’s overarching strategic framework). Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define the various condition and performance data types and associated/anticipated collection methodologies. Document general condition or performance groupings and general criteria (e.g., condition ranges) for these groupings. Specify detailed data elements for each condition or performance rating or categorization. Set required, recommended, and optional data elements. Establish detailed methodology to evaluate asset condition, performance, or contribution to overarching agency strategic priorities. Coordinate with field and office staff to identify current condition and performance data collection practices and standards. Evaluate existing condition or performance standards to identify gaps or inconsistencies in current standards for improvement. Specify minimum levels of condition or performance data coverage to meet decision- making, communication, and reporting needs. Routinely evaluate the condition and performance standards to ensure alignment with TAM business needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.1.c – Design Model Standards 1-Inventory, Condition, and Performance Element Description CADD standards consistent with asset inventory standards (asset categories and component breakdowns) to support linkage and data exchange with project information with asset inventory and management systems Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 CADD standards are not defined for the asset. CADD standards are defined for the asset, however they are not related to established asset categories or components. CADD standards are defined with base objects aligned with asset categories and components in a manner that allows for extraction of asset information from project files with a project specific, manual effort to reconcile differences. CADD standards are defined with base objects aligned with asset categories and components, in a manner that allows for extraction of asset information from project files through standardized processes. Data exchange protocols are defined for the asset, allowing direct integration of project files and asset inventory and/or management systems. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish uniform standards and procedures for development of electronic design and survey plans Define CADD standards that align based objects with asset types, sub-types and components Define a detailed project information model that contains detailed asset attribution needed for asset management. Define detailed data exchange protocols which support transformation of asset information into CADD design files, and vice versa. Develop training to communicate design standards. Develop training to communicate CADD standard alignment with asset information. Develop training to communicate detailed project information model and uses in asset management. Develop training to raise awareness of data exchange protocols and requirements. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: Specify and Standardize Data A.1.d – Location Referencing 1-Inventory, Condition, and Performance Element Description Standardized location referencing for asset inventory and condition data to enable mapping and integration with other agency data for analysis. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Location referencing methods and data standards for the asset have not been defined. Location referencing methods and data standards have been established for the asset, but they cannot be readily transformed to the established enterprise location referencing standard. Location referencing methods and data standards have been established for the asset and can be readily transformed to the agency’s enterprise location referencing standard. Location referencing methods and data standards have been established for the asset and are consistent with the agency’s enterprise location referencing standard. Location referencing of asset information is kept up-to-date in (near) real time as the enterprise location referencing definitions are updated. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Evaluate agency enterprise location referencing standards and identify a method(s) which best support asset needs. Standardize location referencing in a manner that can be transformed to the agency enterprise standard. Standardize location referencing in a manner that is consistent with the agency’s enterprise standard. Fully integrate asset data systems, tools, and records with the agency’s enterprise location referencing system. Examine current inventory, condition, and performance data standards to identify various location referencing methodologies in current use. Document clear processes and business requirements for transformation of any location references not meeting the enterprise standard. Develop specifications for tools to support accurate identification of location based on current enterprise location referencing system definitions. Routinely evaluate the agency location referencing systems to ensure alignment with TAM business needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.2.a – Treatment and Work Data Model2-Treatments and Work Element Description Standardized asset treatment/work categories and attribution to enable information collection, integration, and consistent reporting. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 There are no consistently defined treatment/work categories for the asset. Treatment and work categories impacting asset condition or performance have been defined (e.g., replacement, corrective maintenance, preventive maintenance). Specific treatment types and work activities have been identified for the asset, and classified according to established categories. Standard methods for tracking work accomplishments are in place. A standard set of minimum attributes for tracking maintenance activities and projects (e.g., work completion date, cost, location) have been established. Required, recommended, and optional fields have been identified for various treatments and work types. Impacts of projects affecting multiple assets are tracked for each individual asset. Asset treatment and work data models are periodically adjusted to reflect changes in project delivery methods. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define what are considered “work accomplishments” for the asset. Develop lists of standard activities and project types, providing criteria for grouping specific work into these activity and project types. Specify detailed treatment and work data elements for various project and activity types. Establish required, recommended, and optional data elements. Integrate methods for tracking impacts of projects affecting multiple assets (e.g., pavement projects that upgrade guardrails) into the treatment and work data models to capture information needed for the assessed asset. Coordinate with field and office staff to identify current project types and maintenance activities impacting the asset. Evaluate existing treatment and work data standards to identify gaps or inconsistencies for improvement. Determine minimum levels of treatment and work data coverage to meet decision-making, reporting, and communication needs. Establish a program to routinely evaluate asset treatment and work data models to ensure they continue to meet agency needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.2.b – Treatment and Work Location Referencing 2-Treatments and Work Element Description Standardized location referencing for planned and completed work to enable accurate collection, mapping, and integration with other agency data for analysis. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Treatment or work data associated with the asset do not include location references and are not mappable. Some treatment or work types are tracked with location referencing but location referencing methods are not consistent across work types or over time. Consistent standards for location referencing are established for the asset’s project or maintenance treatment data types (where applicable), however these standards cannot be readily transformed to the established enterprise location referencing standard. Consistent standards for location referencing are established for the asset’s project or maintenance treatment data types (where applicable) in a manner that can be readily transformed to the agency’s enterprise location referencing standard. The agency’s enterprise location referencing standards are in place for all the asset’s project and maintenance treatment data types (where applicable). Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Evaluate agency enterprise location referencing standards, identifying methods that best support asset work tracking needs. Standardize location referencing in a manner that is transformable to the agency enterprise standard. Standardize location referencing in a manner that is consistent with the agency’s enterprise standard. Integrate asset work tracking data systems, tools, and records with the agency enterprise location referencing system. Examine current work accomplishment tracking data standards to identify location referencing methodologies in current use. Document clear processes and business requirements for transformation of any location referencing methodologies not meeting the enterprise standard. Develop specifications for useful tools to support accurate identification of location based on current location referencing system definitions. Routinely evaluate the agency location referencing systems to ensure alignment with treatment and work tracking needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.2.c – Process Documentation and Management 2-Treatments and Work Element Description Established and documented responsibilities and business processes for updating asset information as assets are installed, maintained, upgraded, and replaced or removed. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Business processes for updating asset inventory, condition and work history information are ad- hoc and undocumented. Business processes for updating asset information are established but not yet documented. Business processes for updating asset information are documented in a general fashion based on a standard practice. Documentation is not shared in a consistent, highly visible and accessible place. Business processes for updating asset information are documented in detail and include explicit information on when and how different data entities are created, updated, and deleted or archived. Documentation is stored in a highly visible, accessible place. Business process documentation for updating asset information includes detailed business rules suitable for monitoring and/or automating data updates and exchange. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Coordinate with field and office staff to identify current asset data updates based on asset work accomplishment. Develop standard operating procedures relating to primary asset maintenance activities and project types. Include steps for asset data updates. Augment standard operating procedures to include detailed responsibilities and instructions for asset data updates reflecting work accomplishment. Document detailed business rules for how individual asset data elements are adjusted based on work data. Establish metrics that can be used to evaluate process execution. Coordinate with field and office staff to identify various business practices relating to asset work accomplishment tracking. Evaluate current business practices to identify where there are significant gaps in asset data updates relating to work accomplishment. Develop detailed process documentation identifying when various asset data entities are or should be created, updated, deleted, or archived. Define detailed exchange protocols facilitating automation of asset data updates based on capture of work accomplishment information. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.3.a – Prioritization Factors3-Resource Allocation and Prioritization Element Description Use of asset tiers, condition or performance levels, work types or other prioritization factors to support high-level decision-making. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Investment prioritization factors are not defined for this asset. General investment prioritization factors have been established for the asset (e.g. functional classification) but do not include key factors of concern to asset managers. Specific investment prioritization factors have been established for the asset that address key factors of concern to asset managers. However, they don’t address concerns of other key stakeholders or other agency business processes (e.g. safety planning). Investment prioritization factors have been established that address factors of concern to asset managers as well as concerns of other key stakeholders and other agency business processes. Investment prioritization factors have been distinguished for both internal asset level decision-making as well as cross-asset or cross- program investment prioritization. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Identify basic geographical, organizational or network information useful in determining how to prioritize needed work on assets. Expand prioritization factors to include asset specific information such as asset type, utilization, condition category. Expand prioritization factors to include stakeholder input such as asset performance requirements, or risks, impacts and/or need in other asset or business areas. Expand prioritization factors to include individual asset contributions to agency goals or objectives (e.g. safety). Communicate general expectations for what information should be considered in deciding how work is to be prioritized. Document a methodology for prioritization factor use in distribution of asset-related resources. Update resource distribution methodology as appropriate. Document factor use in external investment decisions (e.g. when an asset must/should be included in an unrelated asset improvement or project). Develop a methodology for calculating prioritization factors that can be used across different programs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.3.b – Analysis Parameters3-Resource Allocation and Prioritization Element Description Established analysis parameters (e.g., asset deterioration and treatment benefit models, treatment unit costs, analysis time horizons) supporting resource allocation analysis and decision-making. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Analysis is ad hoc and therefore there is no recognized need for standardizing analysis parameters. Simple analysis parameters (e.g., unit costs or service life) are standardized to support asset decision-making and resource allocation. These are only useful for general, network-level analysis. Condition or performance-based analysis parameters (e.g., improvement benefits of various treatment types or asset deterioration models) are standardized to support asset decision-making and resource allocation. These are typically only useful for network-level analysis or rough project-level estimates. Condition or performance-based analysis parameters are standardized to support asset decision-making and resource allocation. These are useful for both network- and project-level analysis. Analysis parameters are defined consistently across assets, supporting cross- asset resource allocation analysis. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Identify base parameters supporting estimation of annual needs (e.g., asset service life, typical treatment unit costs, or annual life- cycle maintenance costs). Expand parameters to support condition or performance based forecasting (e.g., asset deterioration and improvement benefit models). Work with field asset managers to expand analysis parameters to support individual asset level needs assessment and investment optimization. Expand analysis parameters to include asset specific contributions to agency goals or objective areas. Communicate general expectations for asset-related needs or investment analysis. Document a methodology for asset needs forecasting. Document a methodology for application of network-level analysis for project-level field decisions. Examine analysis methodologies across different assets and develop a consistent approach to analysis parameter definition (e.g., service life) to enable cross-asset analysis. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.4.a – Data Dictionary Standards and Guidelines4-Metadata Element Description Standardized data dictionaries documenting data element definitions, calculation methods, formats and value domains. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 There are no requirements or standards for data dictionaries to document data element definitions. Data dictionaries may be required for new systems, but data dictionary elements are not standardized beyond those required for technical database design (e.g. field name, data type, format). Data dictionaries' requirements are defined and specifications for key content (field description, allowable values) are defined. Guidance, training and quality assurance processes are in place to ensure that data dictionaries contain useful information for both business and IT staff and that they are maintained in a known, designated location. Policies or guidelines for creating and maintaining data dictionaries ensure updates as changes to databases are made. They are stored and managed at enterprise level, enabling identification of similar data elements across databases. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish basic scope, elements and needs for development of data dictionary content. Document metadata policy for new IT projects or system enhancements. Define a standard format and required, recommended, and optional fields. Develop guidance and training to ensure metadata standards meet business and IT needs. Develop standard operating procedures for maintaining metadata. Work with IT and business owners to document data dictionary content for critical asset data. Work with IT and business owners to document data dictionary content for remaining asset data. Develop requirements for and implement a standardized metadata repository to store, manage, and provide access to agency metadata. Improve functionality of metadata repository, enhancing data search and identification functionality. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.4.b – Dataset Metadata Standards and Guidelines4-Metadata Element Description Standardized dataset-level metadata documenting dataset contents, collection methods, coverage, and limitations. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 There are no requirements or standards for dataset level metadata documenting dataset contents, collection methods, coverage and limitations. Dataset-level metadata requirements are defined, however detailed standards for content are not in place or are not consistently defined. Dataset-level metadata requirements are defined and specifications for key metadata elements are defined. Guidelines, training and quality assurance processes ensure that dataset level metadata contain useful information for both business and IT staff and that they are maintained in a known, designated location. Processes are in place to ensure updates to dataset metadata as changes occur. Dataset metadata are stored and managed at enterprise level, supporting creation of data catalogs and data search capabilities. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish basic scope, elements and needs for development of dataset level metadata content. Document dataset metadata policy for new IT projects or system enhancements. Define a standard format and required, recommended, & optional fields. Develop guidance, training and quality assurance processes to ensure that metadata meets business and IT needs. Develop metadata standard operating procedures. Work with IT and business owners to document dataset level metadata for critical asset datasets. Work with IT and business owners to document dataset level metadata content for remaining asset datasets. Develop requirements for and implement a standardized metadata repository to store, manage, and provide access to agency metadata. Develop easily navigated, searchable data catalogs for the asset and key asset related business processes. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.5.a – Data Stewardship5-Governance Element Description Established data governance structures and data stewardship roles. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No formal data governance structures or specified data stewardship roles and responsibilities for asset data. Contact people for data related to different assets are generally known, but roles and responsibilities have not been explicitly defined or formalized. Steering committees or similar structures formed to manage enterprise data systems (e.g., GIS or data warehouses); data stewards with responsibility for asset data in these systems have been designated. One or more agency data governance bodies has been formed with responsibility for establishing governance processes and stewardship roles. Stewardship roles may have been defined but are not yet implemented. Data governance bodies are well-established and are actively working to strengthen data management practices in the agency. Data stewards have been designated and are performing their intended functions. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define base concepts and organization of governance structures, roles, and responsibilities. Engage business experts and leaders to participate in the governance program. Define governance bodies with stewardship responsibilities (e.g., data quality accountability, developing curated master data). Identify an asset steward and system owners. Document clear responsibilities for strengthening governance and data management. Engage executives and business management in discussion of governance functions and implementation. Complete self-assessment and action planning exercises to identify gaps and prioritize action. Periodically reevaluate. Establish communities of interest in priority business areas and functions. Capture business needs, terminology, rules, etc. Implement enterprise systems to manage and provide access to governance products (e.g., a rules engine or glossary repository). Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.5.b – Data Standards & Guidelines Development/Adoption Processes5-Governance Element Description Formal processes for the development, review, improvement and adoption of new data standards and guidelines. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 The agency has no data standards or practices for standardizing data elements. Existing external data standards are considered for new system development, and some internal agency data elements adhere to “de-facto” standards. Data standardization initiatives have been undertaken and results of these efforts have been disseminated. However, a formal adoption process has not been established. A formal process for nominating, adopting, and publishing data standards has been established. Roles, responsibilities and processes have been established to ensure that data standards are being followed and facilitate updates to standards based on experience. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define processes and formats for creating data standards. Undertake a pilot effort to create a data standard for a high priority data element (e.g., project ID or location reference). Define formal processes for nominating, adopting, and publishing data standards. Incorporate responsibilities for established processes within new or existing governance bodies. Document existing external (e.g., federal) data standards and internally used formats and definitions for priority data elements. Complete self-assessment and action planning exercises to identify gaps and prioritize action. Periodically reevaluate. Advance initiatives to create standards for priority data elements. Organize communities of interest around established standards to ensure they are maintained and implemented. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.5.c – Data Collection Approval/Coordination Processes5-Governance Element Description Formal processes for the evaluation, approval, and coordination of new data collection processes - to reduce or eliminate duplicate data collection and ensure that the value of new data collection is maximized. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Decisions about data collection are made independently by individual business units with little or no coordination. Decisions about data collection are made independently by individual business units but some level of informal communication and coordination occurs to avoid duplication. Guidelines for data collection have been created or adopted and disseminated to promote following best practices. A formal process has been established to evaluate and approve new data collection or acquisition. This process has been applied on a limited basis. A formal process for evaluating and approving new data collection or acquisition efforts is in place and is being followed. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish guidance for data collection decision-making which includes coordination to avoid duplication and identify potential added value. Engage business experts and leaders to participate in data collection best practice initiatives. Define formal processes for evaluating new data collection or acquisition. Incorporate responsibilities for established processes within new or existing governance bodies. Encourage informal data collection collaboration between business units. Complete self-assessment and action planning exercises to identify gaps and prioritize action. Periodically reevaluate. Provide training to key data collection decision-makers regarding formal processes for new data collection evaluation. Organize communities of interest around key data collection to ensure the data meet agency needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: A-Specify and Standardize Data A.5.d – Change Control (Systems and Data) Processes5-Governance Element Description Formal processes to manage change in data and information systems to ensure that limited resources are effectively leveraged and reduce unanticipated impacts to downstream systems and users. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Communication about planned or actual changes to data and information systems is limited and downstream consequences of these changes on reports or other systems are not anticipated or planned for. Communication about changes generally occurs but is not formalized. Data change management guidelines have been documented but are not always consistently followed. Formal change control committees are in place and consistently follow established procedures to minimize downstream impacts of database changes. Change control processes are periodically reviewed and improved based on stakeholder feedback. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish guidance for communication regarding planned or actual data or information system changes. Document policy for communication regarding planned or actual data or information system changes. Define formal processes for proactively evaluating proposed system or data changes with known stakeholders. Organize communities of interest around key data and systems. Include change control as recurring topic of discussion. Identify primary users of current asset related data and systems. Identify extended and/or downstream users of current asset related data and systems. Incorporate responsibilities for established processes within new or existing governance bodies. Integrate change control processes with a formal, enterprise change management program. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

III-19 A P P E N D I X B Collect Data: Element-Level Response Templates This appendix offers element-level response templates for Area B: Collect Data. Note: Use of the TAM Data Assistant is recommended; however, these templates are provided for informal use or pen-and-paper assessment.

Date: Participating Members: Assessment Context: B-Collect Data B.1.a – Inventory, Condition, & Performance Collection 1-Inventory, Condition, and Performance Element Description Coverage and level of detail for asset inventory, condition, and/or performance data aligned with current and anticipated business needs and established data models. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Data are not collected. Inventory, condition and/or performance data collected to meet a one-time need and not aligned with ongoing data needs. Established inventory, condition and/or performance data collection practices, but not fully in line with business needs (coverage is either insufficient or overly detailed) and/or not aligned with the established data model. Established inventory, condition and/or performance data collection practices in line with current business needs and data model. Regular strategic planning process to anticipate emerging needs and adjustment of data collection scope to meet these new needs. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Determine whether asset inventory, condition, and/or performance data collection is warranted (establish the business case). Work with stakeholders to understand data requirements to meet decision support needs. Review existing data collection plans and assess whether the data are being used as intended and providing value and whether there are remaining gaps to consider. Confirm the business case and value of new data collection with key stakeholders. Conduct an annual or bi- annual review of data collection plans to ensure alignment with current and emerging business needs. Examine existing data and data collection programs for potential efficiencies. Confirm the business case for new data collection and establish a “best practical” collection scope based on current capabilities and funding. Review existing data collection plans for consistency with established data model. Consider modifications to achieve consistency. Examine opportunities to “optimize” collection scope. If warranted, engage stakeholders to adjust data model for future needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.1.b – Inventory, Condition, and Performance Automation1-Inventory, Condition, and Performance Element Description Efficient and effective use of technology for asset data collection (such as sensing technology, video, LiDAR, field collection tools) Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Primarily pen/paper collection. Collection in digital form but through largely manual processes that could be further automated (e.g., stand-alone, electronic forms or spreadsheets). Data collection using primarily automated/semi-automated techniques (e.g., custom applications with GPS location detection, voice recognition, bar codes/QR codes) Data collection using primarily automated/ semi-automated techniques with capabilities to efficiently adapt tools to meet varied data collection requirements across multiple data collection business processes or asset types. Application of state-of-the- art computer vision and change-detection techniques for data extraction and efficient updating. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Document business cases for automation through internal practice, peer agency, and best practice reviews. Pilot and implement a vehicle-based data collection solution for individual assets (e.g., video imagery extraction) Pilot and implement vehicle- based data collection solutions for multiple assets (e.g., video image collection/LiDAR) Use change detection to automate and/or focus collection. Leverage changes in base inventory, work accomplishments, condition forecasting, and other techniques to eliminate or reduce collection in low value areas. Implement simple solutions to move away from pen & paper collection (e.g., digital forms or spreadsheet tools) Pilot and implement semi-automated field collection tools (e.g., mobile data collection applications) Pilot and implement field collection tools useful for multiple data collections (e.g., standardized apps or enterprise asset management system tools) Conduct periodic evaluation and pilot testing of cutting-edge applications or capabilities to asset data collection programs. Implement identified collection solutions as appropriate. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.1.c – Inventory, Condition, and Performance Quality1-Inventory, Condition, and Performance Element Description Established processes to assess and improve asset inventory, condition and performance data quality. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Quality is not defined. Expectations for data accuracy, valid values and completeness are established. A plan has been produced including activities and roles for data quality management before, during and after data collection. Formal data collector certification and data acceptance criteria and processes are in place. Data collection and quality management processes are regularly reviewed and revised based on prior experience. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish general data collection requirements (e.g., conditions appropriate for collection) Develop a data quality management plan, including documented quality management activities and roles. Establish formal data collection training and collector certification processes. Automate data quality checks to streamline quality management process and ensure consistency of quality review. Document business rules for evaluation of accuracy, completeness, and validity of collected data. Evaluate data collection best practices and lessons learned from other internal and external data collection programs. Document a comprehensive collection business process with clear data acceptance criteria and error resolution procedures. Incorporate outcomes from quality control and assurance processes and routine evaluation of lessons learned to prevent systemic errors and improve ongoing collection processes. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.2.a – Project Information Coverage2-Project Information Element Description Processes to capture project work accomplishment information in a manner consistent with the project data model and with sufficient coverage to meet asset management analysis, decision-making, reporting, and communications needs. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Project work accomplishment data is not available in a useful form for asset management. Project work accomplishment data is collected to support non-asset management purposes (e.g., contract payment) in a manner that is only useful to asset management for aggregate, network-level summary reporting. Project work accomplishment data is collected in a manner that provides an understanding of what types of work have been completed at particular locations. Project work accomplishment data collection includes associated asset information in a format that is useful to management and upkeep of the asset inventory or condition history. Project work accomplishment data collection includes detailed asset related information (e.g., products/component models or standards, specific treatment materials) useful for detailed asset management decision-making and project design improvement. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Evaluate and implement opportunities to summarize general project information useful to high-level asset decision-making or reporting (e.g., annual investment levels or quantities). Implement a data collection plan to capture project locations and general activities performed within those limits (e.g., preventative maintenance, rehabilitation, or replacement). Implement a data collection plan to capture individual asset locations/IDs and associated work activities, accomplishments and results. Implement a data collection plan which captures detailed asset information from work activities/accomplishments (e.g., specific materials, products, or applications). Document general asset management use cases for project information. Establish a “best practical” collection scope based on current capabilities and funding. Examine current practices to “right size” collection scope to meet current needs and established data model. Examine best practices to “optimize” collection scope. If warranted, engage stakeholders to adjust data model for future needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.2.b – Project Information Automation2-Project Information Element Description Processes and technologies used to automate collection and processing of project work accomplishment data. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Pen/paper collection Stand-alone, standardized electronic forms or spreadsheets are used to facilitate collection. Data are not automatically populated into the source system of record. Data collection using primarily automated/semi-automated techniques through specialized solutions (e.g., custom applications with GPS location detection, voice recognition, bar codes/QR codes). Data collection using primarily automated/semi-automated techniques with capabilities to efficiently adapt tools to meet varied data collection requirements across multiple data collection business processes or asset types. Application of state-of-the-art computer vision and change- detection techniques for data extraction and efficient updating. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Document business cases for project data collection automation through internal practice, peer agency, and best practice reviews. Pilot and implement semi- automated field collection tools (e.g., mobile data collection applications) for project data. Pilot and implement field collection tools useful for multiple data collections (e.g., standardized apps or enterprise asset management system tools) Use change detection to automate and/or focus collection of project work accomplishment data Implement simple solutions to move away from pen & paper collection of project data (e.g., digital forms or spreadsheet tools). Evaluate opportunities to pre-populate high-level activity or asset information based on contract or design information. Evaluate opportunities to pre- populate detail asset or work accomplishment data based on contract or design information. Conduct periodic evaluation and pilot testing of cutting edge project data collection applications or capabilities. Implement solutions as appropriate. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.2.c – Project Information Quality2-Project Information Element Description Established processes to assess and improve project data quality Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Quality is not defined. Expectations for data accuracy, valid values and completeness are established. A plan has been produced including activities and roles for data quality management before, during and after data collection. Formal data collector certification and data acceptance criteria and processes are in place. Data collection and quality management processes are regularly reviewed and revised based on prior experience. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish general project data collection requirements (e.g., conditions appropriate for collection). Develop a data quality management plan, including documented quality management activities and roles for project data. Establish formal project data collection training and collector certification processes. Automate data quality checks to streamline quality management process and ensure consistency of quality review of project data. Document business rules for evaluation of accuracy, completeness, and validity of collected project data. Evaluate project data collection best practices and lessons learned from other internal and external data collection programs. Document comprehensive collection business processes with clear data acceptance criteria and error resolution procedures for project data. Incorporate outcomes from quality control and assurance processes and routine evaluation of lessons learned to prevent systemic errors and improve ongoing collection processes. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.3.a – Maintenance Information Coverage3-Maintenance Information Element Description Processes to capture maintenance activity information in a manner consistent with the work order data model and with sufficient coverage to meet asset management analysis, decision-making, reporting, and communications needs. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Data on work orders is not consistently available and/or is not collected in a standardized fashion. Work order and maintenance contract data are collected to support non-asset management purposes (e.g., contract payment) in a manner that is only useful to asset management for aggregate, network-level summary reporting. Work order and maintenance contract data are collected in a manner supporting understanding of activities performed at individual work locations. Work order and maintenance contract data collection includes associated asset information in a format that is useful to management and upkeep of the asset inventory or condition history. Work order and maintenance contract data collection includes detailed asset related information (e.g., products/component models or standards, specific treatment materials) useful for detailed asset management decision-making and project design improvement. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Evaluate/implement oppor- tunities to summarize work or- der information useful to high- level asset decision-making or reporting (e.g., annual invest- ment levels or quantities). Implement a data collection plan to capture work order locations and general activities performed within those limits (e.g., preventive maintenance, minor repairs) Implement a data collection plan which captures individual asset locations/IDs and associated work activities and accomplishments. Implement a data collection plan which captures detailed asset information from work activities/ accomplishments (e.g., specific materials, products, or applications). Document general needs and uses for work order information. Establish a “best practical” collection scope based on current capabilities and funding for work order collection. Examine current practices to “right size” collection scope to meet current needs and established data model. Examine best practices to “optimize” work order collection scope. If warranted, engage stakeholders to adjust data model for future needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.3.b – Maintenance Information Automation3- Maintenance Information Element Description Processes and technologies used to automate collection and processing of maintenance activities, work orders, and work accomplishment data. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Pen/paper collection Stand-alone, standardized electronic forms or spreadsheets are used to facilitate collection. Data are not automatically populated into the source system of record. Data collection using primarily automated/semi-automated techniques through specialized solutions (e.g., custom applications with GPS location detection voice recognition, bar codes/QR codes). Data collection using primarily automated/semi-automated techniques with capabilities to efficiently adapt tools to meet varied data collection requirements across multiple data collection business processes or asset types. Application of state-of-the-art computer vision and change- detection techniques for data extraction and efficient updating. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Document business cases for automation of work order data collection through internal practice, peer agency, and best practice reviews. Pilot and implement semi- automated field collection tools (e.g., mobile data collection applications) for work order data collection. Pilot and implement field collection tools useful for multiple data collections (e.g., standardized apps or enterprise asset management system tools). Use change detection to automate and/or focus collection of work order and/or maintenance work accomplishment data. Implement simple solutions to move away from pen & paper collection (e.g., digital forms or spreadsheet tools) for work order data collection. Evaluate opportunities to pre-populate high-level activity or asset information based on work order or contract/task information. Evaluate opportunities to pre- populate detailed asset or work accomplishment data based on work order or contract/task information. Conduct periodic evaluation and pilot testing of cutting-edge data collection applications or capabilities. Implement solutions as appropriate. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.3.c – Maintenance Information Quality3-Maintenance Information Element Description Processes to assess and improve maintenance activity and cost data quality. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Quality is not defined. Expectations for data accuracy, valid values and completeness are established. A plan has been produced including activities and roles for data quality management before, during and after data collection. Formal data collector certification and data acceptance criteria and processes are in place. Data collection and quality management processes are regularly reviewed and revised based on prior experience. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish general data collection requirements (e.g., conditions appropriate for collection) for maintenance. Develop a data quality management plan, including documented quality management activities and roles for maintenance data. Establish formal data collection training and collector certification processes for maintenance data. Automate data quality checks to streamline quality management process and ensure consistency of quality review of maintenance data. Document business rules for evaluation of accuracy, completeness, and validity of collected maintenance data. Evaluate maintenance data collection best practices and lessons learned from other internal and external data collection programs. Document a comprehensive collection business process with clear data acceptance criteria and error resolution procedures for maintenance data. Incorporate outcomes from quality control and assurance processes and routine evaluation of lessons learned to prevent systemic errors and improve ongoing collection processes. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.4.a – Public Perceptions4-Priority Criteria and Values Element Description Capture and use of information about how the public perceives different conditions, treatment options, or other TAM-related factors. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Public perception data is not captured. Public perception is generally evaluated against internal thresholds established through expert opinion (e.g., minimum program or service standards set based on internal DOT input). Customer complaints or requests related to asset condition and service are compiled, but there is no specific guidance on how this information should be used. Public perception information is gathered through proactive methods, and there are clear expectations for how this input will be used. Public perception information is gathered through proactive methods that are coordinated across assets and program areas. Processes for considering and resolving conflicting perspectives are in place. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Define customer-oriented service levels and minimum expectations for asset related programs and services through expert opinion. Implement a data collection plan to track complaints, work requests, or other reactive metrics of public perception. Implement a data collection plan to use proactive methods of gathering general public perceptions of asset condition and service (e.g., surveys or opinion polls.) Implement a data collection plan to capture detailed information (e.g., through focus groups) to expand upon general public perception data. Evaluate asset related program and service levels against expectations. Flag if minimum levels are not met. Develop agency or program- level guidance on approaches to capturing public perceptions to support asset-related decision-making. Define how public perception data will be incorporated into asset- related decision-making. Document processes to resolve conflicting perspectives or input received through public engagement. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: B-Collect Data B.4.b – Decision Maker Values4-Priority Criteria and Values Element Description Capture and use of information about how DOT decision-makers (at both program and executive levels) perceive and value different asset performance levels, management strategies, or other factors. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 DOT asset program managers and executives don’t engage in discussions about the impacts of different asset performance levels. DOT asset program managers and executives informally discuss impacts of different asset performance levels. DOT asset program managers and executives have regular (annual or quarterly) meetings to review current and projected asset performance levels and discuss funding priorities. DOT asset program manager and executive values and preferences are captured in a quantitative fashion (e.g . through stated preference or scoring methods). Decision-maker values are captured in a quantitative fashion that supports cross- asset/cross-program resource distribution and/or investment prioritization. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Organize informal meetings to discuss impacts of different asset performance levels. Set up regular meetings to review asset performance and discuss priorities. Research alternative methods for quantifying decision maker values and preferences. Research alternative methods for cross-asset/cross-program resource allocation or investment prioritization. Identify and document key decision maker concerns and tradeoffs. Compile data that helps decision-makers assess the implications of different performance levels (e.g. pavement roughness on vehicle operating costs) Set up peer-to-peer discussions with agencies that have successfully applied methods for quantifying decision maker values and preferences. Pilot test available tools for cross-asset/cross-program resource allocation or investment prioritization. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

III-31 A P P E N D I X C Store, Integrate, and Access Data: Element-Level Response Templates This appendix offers element-level response templates for Area C: Store, Integrate, and Access Data. Note: Use of the TAM Data Assistant is recommended; however, these templates are provided for informal use or pen-and-paper assessment.

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.1.a – Efficient Storage1-Databases Element Description Data storage methods that enable and facilitate efficient data access, analysis and transformation. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Asset inventory, condition and work information are primarily in paper form - not digitized. Asset inventory, condition and work information is digital but stored in disparate database types and locations. Most databases with asset inventory, condition and work information are stored on a server and can be accessed and managed centrally. Materialized views and automated transformations are used to provide efficient access to data of interest. Information is stored for efficient access by leveraging cloud-based options (as appropriate). Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Work with information technology staff to examine current practices and identify database solutions aligned with business need and agency recommended practices. Identify and implement source systems of record for storage of asset inventory, condition, and work data. Eliminate duplicate data by providing curated authoritative data for analysis and reporting. Work with information technology staff to identify needs and solutions for cloud-based data storage. Migrate asset data from paper to simple database formats. Store locally or on central servers if no formal system of record is available. Develop and execute a migration plan for paper, decentralized, and/or locally stored data desired for ongoing retention and use. Work with information technology staff to incorporate anticipated future asset data, systems, and analysis tools in the enterprise architecture. Implement cloud data storage solutions as appropriate to provide optimized and efficient access for internal and external users. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.1.b – Database Linkages1-Databases Element Description Data integration to facilitate analysis and reporting requiring use of multiple data sources. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 There are no established linkages across different databases that store asset information. Data across different databases can be linked based on standard location references. Data across different databases can be linked based on shared asset, project, and/or work order identifiers. Processes are in place to update location references and IDs as changes occur to the agency's authoritative sources for these data elements. Roles and responsibilities have been established to ensure that databases are designed to enable efficient integration to support analysis and reporting. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Standardize location referencing within asset databases. Review existing location, asset, project, and work order identifiers with asset SMEs. Flag inconsistences across programs and processes. Integrate authoritative sources for location, asset, project, and work order information with asset databases. Assign roles and responsibilities for identifying and updating integration requirements for asset databases, systems, and tools. Review existing location, asset, project, and work order identifiers with asset subject matter experts (SMEs). Flag inconsistencies within individual programs or processes. Standardize use of asset, project, and work order unique identifiers within asset databases. Develop processes to ensure location referencing and unique identifiers are maintained against authoritative data sources. Proactively identify asset management business needs for data integration and translate these needs into data, application and technology architecture requirements. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.1.c – Document Linkages1-Databases Element Description Processes and technologies for linking documents to assets, projects, and locations. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Documents related to specific assets or projects may be filed in folders for the asset or project but are not directly linked through metadata or other methods. Selected document types can be linked to associated assets, projects, and locations. Approaches may vary across document types or systems. Standardized approaches are used to connect documents to assets, projects, locations but there are no established business processes or roles to ensure execution. An electronic document management system is integrated with asset management, project management, location referencing systems and tools. Business processes and roles for document management are documented, but may not be monitored. An electronic document management system is integrated with asset management, project management, location referencing systems and tools. Business processes are documented and monitored to ensure application. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Review existing document standards and metadata with asset Subject Matter Experts (SMEs). Flag opportunities to incorporate linkages to assets, projects and locations within individual processes. Review existing document standards and metadata with asset SMEs. Flag opportunities to incorporate linkages across processes and programs. Develop an electronic document management system with defined metadata providing linkages for priority documentation. Document and apply detailed document metadata business rules useful in flagging documentation that has been improperly tagged. Take advantage of available document management systems to establish metadata elements for asset ID, project ID and location. Standardize use of asset, project, work order unique identifiers and location referencing within key asset related documentation. Document business processes, roles and responsibilities for applying standard metadata during document creation and/or update. Routinely evaluate document metadata practices to ensure they are meeting business needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.1.d – Data Storage Capacity1-Databases Element Description Processes to provide sufficient storage capacity to meet current and likely future needs, considering collection of imagery, LiDAR, backups, archiving, and other data storage requirements. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Data storage needs are not systematically assessed, and requests for additional storage are not reliably met. Data storage requirements are evaluated as part of new information system development processes, but space requirements are not routinely reassessed after initial system deployment. A process exists for business areas to request additional storage to meet needs related to growth in data or new data collection efforts. The organization has a data storage management strategy that includes considerations of retention, backup requirements, structured and unstructured data, disaster recovery, etc. based on current needs. The organization has a forward-looking data storage management strategy that includes considerations of retention, backup requirements, structured and unstructured data, disaster recovery, etc., based on current and future needs. Strategy includes tactics to manage costs in alignment with needs (e.g., tiered storage, appropriate use of cloud vs. on premises). Strategy aligns with/is actively managed in coordination with the business. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish requirements for data storage requirement evaluation as part of new IT system planning & development. Establish process for system owners and/or business leads to request additional storage capacity. Create a five year, forward looking data storage plan in collaboration with IT and business leads. Develop a data storage management strategy that examines and quantifies risks and identifies data storage solutions aligned with risk tolerance and budget. Examine and document IT process for securing additional storage capacity. Communicate lead time required for IT to reliably meet legitimate requests for additional data storage. Investigate and incorporate targeted cloud storage applications. Document a comprehensive cloud storage policy and associated storage solutions. Integrate cloud storage tactics in broader strategy. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.2.a – Asset Management Data to Project or Work Order2-Asset Life-Cycle Data Integration Workflows Element Description Established data flows from asset management systems to maintenance work order systems or project development systems. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between asset management systems and/or scoping and project development. Data views are defined to facilitate access to, and review of, asset inventory, condition, and analysis information. This data is presented in a manner intended for use in downstream project scoping activities. Simple data flows are implemented, allowing pre-population of key administrative and project-level information (e.g., asset identifiers, recommended project/activity, project limits) into base project scoping documents. More detailed data flows are implemented, allowing individual assets and/or activity details to be pre-populated into the project scoping documents. Asset management system information automatically flows into maintenance management/project planning systems. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop standard views or reports to expose asset inventory, condition, and analysis information for use in project scoping processes. Transform key data stored in asset systems to support direct integration of information into project scoping products. Transform detailed data stored in asset systems to support direct integration of asset and activity details into project scoping products. Transform detailed data stored in asset systems to support direct and complete integration into project scoping products. Engage Subject Matter Experts (SMEs) from asset management and project planning and scoping to identify opportunities for improved coordination. Pilot test and implement simple, manual or semi- automated data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.2.b – Project Planning to Project Development2-Asset Life-Cycle Data Integration Workflows Element Description Established data flows from project planning (scoping) to project development. Consider both maintenance/operations activities and construction projects. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between project planning and/or scoping and project development. Data views are defined to facilitate access to, and review of, planning and scoping information. This data is presented in a manner intended for use in downstream design and/or project development activities. Simple data flows are implemented, allowing pre- population of key administrative and project-level information (e.g., project identifiers, project/ activity type, project limits) into base project, work order, or design documents. More detailed data flows are implemented, allowing individual assets and/or activity details (such as work location, scope, estimated cost, and schedule milestones) to be pre- populated into the project, work order, and/or design documents. Planning/scoping information automatically populates contract and design documents. Project development activities, participants, and/or documentation are automatically populated as appropriate to the scope. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop standard views or reports to expose planning and scoping information for use in project development activities. Transform key data stored in scoping and planning systems to support integration of data into project development products. Transform detailed data stored in scoping and planning systems to support integration of information into project development products. Assess and refine existing data flows to include additional detail (or reduce detail). Develop specifications for direct and complete integration of planning/scoping details into project development products. Engage Subject Matter Experts (SMEs) from planning and development to identify opportunities for improved coordination. Pilot test and implement simple, manual or semi- automated data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.2.c – Project Development to Project Delivery2-Asset Life-Cycle Data Integration Workflows Element Description Established data flows from project development to project delivery. Consider both maintenance/operations activities and construction projects. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between project development and project delivery/construction. Data views are defined to facilitate access to, and review of, project development information. This data is presented in a manner intended for use in downstream project delivery/construction activities. Simple data flows are implemented, allowing pre- population of key administrative and project-level information (e.g., project identifiers and limits, bid items and charge codes, general work activities) into base project delivery tools and systems. More detailed data flows are implemented, allowing individual assets and/or activity details to be pre-populated into the project delivery tools and systems, including asset acceptance inspection systems and work accomplishment tracking tools. Design information automatically populates delivery/construction information. Work accomplishment information is largely pre-populated based on design documents to facilitate direct acceptance or modification with limited data entry. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop standard views or reports to expose design information for use in project delivery (e.g., acceptance inspection or payment). Transform key data stored in design systems/documents to support integration into project delivery processes. Transform detailed data stored in design systems/documents to support integration into project delivery processes. Assess and refine existing data flows to include additional detail (or reduce detail). Develop specifications for direct and complete integration into project delivery processes. Engage Subject Matter Experts (SMEs) from project development and delivery to identify opportunities for improved coordination. Pilot test and implement simple, manual or semi- automated data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other:

Self-Assessment: Specify and Standardize Data: Governance Data and Information Systems for Transportation Asset Management Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.2.d Project Delivery to Asset Management Data2-Asset Life-Cycle Data Integration Workflows Element Description Established data flows from project delivery to asset management systems to ensure up-to-date, accurate inventory, condition, and work history information. Consider both maintenance/operations activities and construction projects. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between project delivery/construction and asset inventory, condition, performance and work history databases. Data views are defined to facilitate access to, and review of, as-built or inspection information. This data is presented in a manner intended for easier review and update into asset management systems and/or databases. Simple data flows are imple- mented, allowing pre-population of key administrative and project- level information (e.g,. project identifiers and limits, asset identifiers, general work activities) into asset databases for more detailed attribution or update. More detailed data flows are implemented, allowing individual assets and/or activity details to be pre- populated into the asset databases, allowing most data to be pre-populated prior to finalization. Delivery/construction information automatically flows to asset management systems. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop standard views or reports to expose project delivery (e.g., acceptance inspection) information for review in asset data update. Transform key data stored in as-built or inspection systems/ documents to support integration into asset databases. Transform detailed data stored in as-built or inspection systems/documents to support integration into asset databases. Assess and refine existing data flows to include additional detail (or reduce detail). Develop specifications for direct and complete integration into asset databases. Engage Subject Matter Experts (SMEs) from project delivery and asset management to identify opportunities for improved coordination. Pilot test and implement simple, manual or semi- automated data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.3.a – Financial (Revenue, Budget, Expenditure) Data3-Other Data Integration Workflows Element Description Established data flows from financial systems to systems used for asset management, work planning and tracking. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between asset management systems and financial systems. Data views are defined to facilitate access to, and review of, financial data supporting asset management decision-making. This data is presented in a manner intended for use in asset improvement optimization and selection, work planning and tracking. Simple data flows are implemented, allowing pre- population of current budget limits into asset management optimization analysis and/or work planning tools. More detailed data flows are implemented, allowing current budget limits, total expenditures, remaining funds, and future funding forecasts to be pre-populated by discrete fund, project, or work categories into asset management optimization analysis and/or work planning tools. Budget and expenditure information automatically flows to systems used for asset management, work planning and tracking. Updated information is available in real time or updated on a daily basis. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop standard views or reports to expose financial data for use in asset management processes. Summarize data stored in financial systems to support integration into optimization and work planning tools. Transform detailed financial system data to support integration into optimization and work planning tools. Assess existing data flows and identify refinements to include additional detail (or reduce detail). Develop specifications for direct integration into optimization and work planning tools. Engage Subject Matter Experts (SMEs) from asset management and financial business units to identify opportunities for improved coordination. Pilot test and implement simple, manual or semi-automated financial data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer financial data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer financial data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.3.b – Demand and/or Utilization Data3-Other Data Integration Workflows Element Description Established data flows from travel demand, travel monitoring systems, or other systems quantifying demand or utilization to systems used for asset management decision support. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow between asset management systems and travel demand or utilization data systems. Data views are defined to facilitate access to, and review of, demand/utilization data supporting asset management decision-making. This data is presented in a manner intended for use in asset improvement optimization, prioritization, and planning, and asset communication and reporting. Simple data flows are implemented, allowing processing of current demand or utilization against specific assets or network segments. More detailed data flows are implemented, facilitating useful prioritization and/or risk evaluation within asset management decision- making systems, tools, and analysis. Travel demand and utilization information automatically flows to systems used for asset management decision support. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Identify travel demand or facility/service utilization data useful to asset management. Develop standard views or reports. Summarize demand and/or utilization data to support asset prioritization and improvement decision. Directly integrate these into asset systems/tools. Examine asset risk and prioritization evaluation needs. Transform key demand/util- ization data and directly integrate for these purposes. Examine real-time decision- making priorities and needs. Transform detailed demand/ utilization data and directly integrate for these purposes. Engage Subject Matter Experts (SMEs) from asset management and travel demand or facility/ service utilization data producers to identify opportunities for improved coordination. Pilot test and implement manual or semi-automated demand data/utilization integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer demand/utilization data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer demand/utilization data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.3.c – Environmental Data3-Other Data Integration Workflows Element Description Established data flows from environmental information systems to systems used for asset management decision support. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No defined data flow from environmental data systems to asset management and project development systems. Data views are defined to facilitate access to, and review of, environmental data supporting asset management and project development. Data is presented for use in asset improvement optimization and selection, work planning, and project scoping and development. Simple data flows are implemented, allowing processing of available environmental data against specific assets or network segments in a manner that is useful to asset improvement selection and/or project scoping and development. More detailed data flows are implemented, facilitating prioritization and/or risk evaluation within asset management decision-making systems, tools, and analysis. Detailed environmental data automatically flows to systems used for asset management and/or project scoping and development. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Identify environmental data useful to asset management. Develop standard views or reports. Summarize environmental data to support improvement selection and project development. Directly integrate into asset systems/tools. Examine detailed project development and asset management process and risk evaluation needs. Examine real-time decision- making priorities and needs. Transform detailed environmental data and directly integrate for these purposes. Engage Subject Matter Experts (SMEs) from asset management, project development, and environmental units to identify opportunities for improved coordination. Pilot test and implement manual or semi-automated environmental data integrations. Provide quality assessment tools to support informed data use. Pilot test and implement batch processes to transfer environmental data. Integrate quality assessment tools to ensure appropriate data use. Pilot test and implement fully automated processes to transfer environmental data. Integrate quality assessment tools to ensure appropriate data use. Other: Other: Other: Other: Assessment Notes: Improvement Notes: Transform key env. data and directly integrate for these purposes.

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.4.a – Field Access to Data4-Data Access Element Description Technologies, data structures and processes to enable access to agency asset and work management system data from the field. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Field staff are not equipped with mobile technology. Field staff are equipped with laptops and can bring copies of needed files to the field - no data connectivity. Field staff are equipped with mobile devices with data connections capable of retrieval only. Field staff are equipped with mobile devices capable of two- way connectivity with the ability to retrieve and send information to office systems. Next generation technology is used in field business processes. Examples include tools allowing hands free retrieval and sending of data, real- time remote assistance, 3D/4D/5D visualization of data, or visualization as part of an Augmented or Virtual Reality (AR/VR) experience. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Provide basic computer and internet access at base field offices or locations. Identify positions requiring mobile computing. Provide smart phones, tablets, and/or laptops (consider mobile data plans as appropriate). Identify positions requiring mobile computing with data connectivity. Provide smart phones, tablets, and/or laptops (include mobile data plans, if data connectivity is needed). Provide seamless access across firewall and in the field for all asset (and related) data, systems, and tools. Develop budget for supplying mobile devices to field staff. Consider Bring-Your-Own-Device (BYOD) policies. Develop mobile friendly views of key asset information (e.g., asset inventory, work recommendations or history). Develop comprehensive mobile solutions for key systems, tools, analysis, and information. Support real- time field data update and creation. Explore and pilot next generation mobile tools that can support asset business processes. Implement as appropriate. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.4.b – Public Access to Data4-Data Access Element Description Technologies, data structures and processes to enable public access to agency condition and asset performance information and planned projects. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 A publicly accessible repository of asset/project information does not exist. A website is available with contact information. A website is available with summary data and some downloadable data, reports, or reference materials. A website with a dashboard is available to reflect project level performance metrics and comparison to project goals, updated periodically. A website with a dashboard is available to reflect performance metrics and comparison to organization goals, updated in near real time. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop public facing website providing general overview of asset related programs and contacts. Provide access to public facing data, reports, and supporting materials through program website(s). Develop and share asset performance metrics, targets, and other information through a public facing dashboard. Implement data and system integrations to provide near real time updates of asset data shared in the public dashboard. Examine agency public facing website and identify appropriate locations to share or link asset specific website(s). Develop a public data portal where curated data and reports can be uploaded for public access. Develop messaging and materials to share context for asset performance with public. Upload to public website(s). Develop messaging and materials to relate asset performance with overarching organization goals. Upload to public website(s). Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: C-Store, Integrate, and Access Data C.4.c – Access Security4-Data Access Element Description Management of access to asset and project data to ensure data security and the proper flow of information. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Available digital data is not access-restricted. Access is managed on an ad hoc basis, with no designated responsibilities or accountability. Roles and accountabilities for granting access have been established, but without clear policies or guidance. Access is managed based on established roles and documented policies and protocols. Access is managed using role-based authentication within business systems. Single sign on is used to minimize separate logins and centralize management of credentials. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Audit access controls in place for key asset data, systems, and tools. Identify system improvements. Document general processes and procedures for authorizing access to key asset data, systems, and tools. Document clear procedures and associated responsibilities for authorizing access to asset data, systems, and tools. Develop an access request/ management system to support efficient processing and tracking of access requests. Conduct a risk assessment to prioritize implementation of access controls. Identify typical system roles and users. Document general roles and responsibilities for authorizing access. Designate and train individuals who will be responsible for managing access. Provide single sign on functionality for asset related data, systems, and tools. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

III-47 A P P E N D I X D Analyze Data: Element-Level Response Templates This appendix offers element-level response templates for Area D: Analyze Data. Note: Use of the TAM Data Assistant is recommended; however, these templates are provided for informal use or pen-and-paper assessment.

Date: Participating Members: Assessment Context: D-Analyze Data D.1.a – Analysis Environment1-Data Exploration, Reporting and Visualization Element Description Creation and maintenance of data processing, analysis and reporting environments (e.g., staging areas, data warehouses, data marts, data lakes). Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No central data analysis environments have been set up. Data from different sources is brought together into a central platform for access, with little or no transformation or summarization. Data are transformed in a limited fashion and made available for analysis; additional data manipulation is required to meet specific analysis needs. Data are transformed, summarized and made available in a convenient form to meet the most common analysis and reporting needs; data are structured and documented to support more specialized queries. A "big data" environment is available supporting sophisticated exploration, cleansing, visualization and analysis of large, heterogeneous datasets. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Create a data warehouse to make data centrally available for analysis. Apply basic data transformations supporting data exploration, reporting, and visualization needs. Apply more complex and/or additional data transformations needed to meet specialized analysis needs. Provide a “big data” environment with data profiling tools – include functions to generate random sampling of large data sets, provide graphical insight into data distributions and outlier values. Identify initial priority datasets supporting asset analysis and reporting needs to make available within a central data warehouse. Provide standard analysis and reporting views combining data from different sources for asset related analysis. Develop data marts meeting specific asset related business analysis and reporting needs. Develop user capability to share data and analysis products through the environment. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: D-Analyze Data D.1.b – Analysis Practices1-Data Exploration, Reporting and Visualization Element Description Procedures, standard reports, templates, and training to ensure valid and productive analysis of current data. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No standard reports or agency reporting procedures have been established. Limited standard reports are available within the agency's individual asset management systems. Reports are produced on request. A regular process has been established to produce and make available standard reports. A regular process of data exploration and analysis has been established to identify patterns in the data, explore hypotheses and derive actionable information. Staff conducting this analysis receive appropriate training in statistics and data analysis techniques. Based on inputs from data analysts, data and analysis environments are continually improved to enhance the agency's ability to derive valuable insights from data. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Configure agency asset management systems and tools to provide standard reporting for asset SMEs. Put standard operating procedures in place to develop reporting commonly needed outside the asset area. Integrate data science practices within asset related analysis. Develop a data science program to share and develop techniques to generate quantifiable, data-drive insights among data scientists and analysts. Identify ad hoc data exploration, reporting, and visualization practices in use in asset related business. Document and promote useful analysis techniques to deliver on common needs. Document and promote useful techniques to communicate complex asset management analysis results. Develop training plans for data analysis and data science practices and applications. Routinely evaluate to ensure alignment with staff needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: D-Analyze Data D.1.c – Analysis Tools1-Data Exploration, Reporting and Visualization Element Description Tools supporting productive analysis and reporting practices (e.g., GIS, charting, reporting, dashboards). Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No tools exist. Tools for data exploration, reporting, and visualization are available in the agency but they are geared to expert users and requests for reports, dashboards or maps involve a request process with substantial lead time for service. Limited tools are procured by individual business units that can be used to meet basic reporting and mapping needs. There is no training (or support for training) on proper application of these tools. A variety of tools for data exploration, reporting, and visualization are available for use, and training is available to ensure that the capabilities of these tools is fully leveraged. Standard tools for data exploration, reporting, and visualization are available across the agency, and meet the needs of asset management staff. The agency provides training and support for these tools and undertakes periodic improvements/upgrades to ensure they evolve with changing business and technology. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop agreements and/or process for use of analysis tools and/or expert analysts in support of priority analysis needs. Implement analysis tools allowing internal asset program staff to meet basic reporting and mapping needs. Transition existing analysis to standard business intelligence/analysis tools. Implement data profiling tools supporting random sampling of large datasets and provide graphical insights into data distributions and outlier values. Inventory in-house asset management, reporting, business intelligence, dashboarding and other tools useful to asset related analysis. Document simple user instructions for available analysis tools. Develop training materials supporting application of standard tools to individual program analysis, reporting, and mapping needs. Develop detailed training plans for analysis tool uses and applications. Routinely evaluate to ensure alignment with staff needs. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: D-Analyze Data D.2.a – Asset Performance Prediction2-Modeling Element Description Capabilities for development and application of asset performance models. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Asset performance models have not been developed. Predictive models have been developed for key asset condition or performance measures. There is limited confidence in these models for applications outside of network-level performance prediction or needs analysis. Predictive models have been developed for key condition or performance measures. These models are generally trusted and applied in project-level decision- making. However, these models are not routinely validated and/or evaluated for improvement. Predictive models have been developed for key condition or performance measures. These models are trusted, integrated into project-level decision- making and are periodically validated and improved using project-level and/or asset specific information. Prediction and model building leverage asset component and/or very specific location or asset information. Available information is used to tailor model input to the specific asset, with built in methodologies to revert to network level models when asset specific data is not available or trusted. Models and assumptions are regularly validated. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop predictive models for key condition or performance data using historical data and/or expert opinion. Improve predictive modeling through evaluation of available condition or performance data, reducing reliance on expert opinion as a key input to the models. Improve predictive modeling through integration of data sources beyond condition or performance data (e.g., utilization/environmental data). Develop performance modeling based on data collected for a specific asset or location. Develop methodology for use of predictive models in forecasting network-level needs. Develop methodology for use of predictive models in project-level investment decision-making. Document processes for use. Validate and improve methodology for use of models in project-level decision-making. Document processes for use. Develop analytical tools to identify discrepancies between actual and anticipated performance. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: D-Analyze Data D.2.b – Optimization/Prioritization2-Modeling Element Description Capabilities for development and application of prioritization and optimization techniques. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Asset investment prioritization is not conducted. Investment prioritization/ optimization methodology exists for individual assets. This methodology does not use information on work history and planned work. Investment prioritization/ optimization methodology exists for individual assets and uses information on work history and planned work. Results from individual asset investment optimizations are used to discuss investment tradeoffs across assets; however, there is no quantitative approach to cross-asset optimization. A quantitative approach to cross-asset resource optimization is in use. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop treatment selection criteria, associated improvement benefit and cost models, and methodology for investment optimization and prioritization. Improve treatment selection criteria, benefit and cost models, and prioritization through analysis of historical data and expert opinion. Improve treatment selection, benefit and cost models, and prioritization with non-asset data (e.g., utilization/environmental data). Develop method to tie asset investments to overarching “benefit” or “value” against agency objectives, supporting a quantitative cross-asset resource optimization approach. Document key factors input as constraints to optimization analysis (e.g., performance constraints, available funding), identify values/data sources. Identify data sources for planned work and define method for incorporating these data into existing investment analysis. Produce asset specific investment optimization/prioritization analysis results in a format useful in an overarching investment optimization and prioritization decision process. Develop analytical tools to identify where discrepancies are identified between actual and anticipated performance of asset investments and improvements. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

III-53 Act as Informed by Data: Element-Level Response Templates A P P E N D I X E This appendix offers element-level response templates for Area E: Act Informed by Data. Note: Use of the TAM Data Assistant is recommended; however, these templates are provided for informal use or pen-and-paper assessment.

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.1.a – Performance Targeting1-Resource Allocation and Prioritization Element Description Processes for establishing performance targets and aligning asset investment decisions with targets. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No consideration of asset performance/condition in resource allocation. Asset performance/condition is considered as a part of resource allocation decisions. Asset performance/condition targets are set based on review of trend data, and resources are allocated to achieve established targets. However, resource allocations are not adjusted based on monitoring of actual performance. An annual monitoring and adjustment process is in place to keep targets and resource allocations in line with observed performance. Processes for performance target setting, resource allocation, and monitoring are periodically reviewed and improved. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop basic summaries of asset information (e.g., trends in asset allocations, inventory, condition, or performance) to inform resource allocation decisions. Establish targets for asset condition or performance. Allocate available funding based on needs to meet targets. Incorporate information about asset life cycles into resource allocation processes. Monitor field investments against recommendations. Integrate asset specific allocation decisions into a cross- asset resource allocation program. Optimize allocations across all areas against agency goals and objectives. Initiate a process of reviewing asset condition or performance trends as part of resource allocation business processes. Document resource allocation decision-making processes, including methods for considering needs or targets in fund distribution. Document desired and expected condition and/or performance outcomes based on fund distribution. Develop a dashboard to communicate resource allocation targets and decisions. Flag where decisions are not aligned with expectations. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.1.b – Project Prioritization1-Resource Allocation and Prioritization Element Description Use of a data-driven prioritization methodology to select asset maintenance, rehabilitation and replacement projects for funding. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No formal approach to project prioritization; design making criteria are not transparent. Formal criteria and methodologies for project prioritization are established based on the primary asset. Prioritization is primarily based on qualitative factors. Limited or no consideration of impacts to other assets or projects. Formal criteria and methodologies for project prioritization are established based on the primary asset using data on unit costs, exposure (e.g., traffic or ridership), and predicted condition improvement. Formal criteria and methodologies for project prioritization are established based on agency goals and objectives and the project scope. Approaches support tracking of aggregate work accomplishment and performance targets. Formal criteria and methodologies for project prioritization are established and support comprehensive evaluation against agency goals and objectives. Targets for project development, work accomplishment, and performance outcomes are managed by formal procedures that involve input from cross-functional business and management teams. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop simple summaries of asset information (e.g., trends in asset allocations, inventory, condition, or performance) to inform project selection. Apply funding, treatment benefit and cost models and other factors to constrain project selection to identified priorities. Incorporate life-cycle planning analysis outcomes into project selection. Monitor field investments against recommendations. Integrate asset specific project priorities a multi- objective project prioritization program. Optimize project selection in all areas against agency goals and objectives. Establish criteria for identifying and prioritizing candidate projects based on current asset or external information. Document project prioritization and selection decision-making practices. Document desired and expected condition and/or performance outcomes based on planned projects. Develop a dashboard to communicate project priorities and investment decisions. Flag where decisions are not aligned with expectations. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.2.a – Data-Driven Project Planning and Scoping2-Project Planning, Scoping, and Design Element Description Use of asset inventory, condition, work history and treatment recommendation data to inform project planning and scoping. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Project planning and scoping are performed with little or no consideration of asset inventory, condition, work history or treatment recommendation information. Project planning and scoping are based on field observation of asset inventory and condition information. Project planning and scoping considers selected asset inventory and condition information available within the agency's business systems. Project planning and scoping is conducted based on documented procedures for use of asset inventory, condition, work history, and treatment recommendations. Templates for project scopes are developed and tailored to common asset life-cycle conditions and analysis recommendations. These are managed in a library that supports reuse and continuous improvement to project scoping and planning outcomes. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Develop checklists or standard forms to gather field observations of asset inventory and condition during project planning and scoping. Develop guidance for project scoping/planning based on available asset inventory and condition. Incorporate available asset life-cycle and/or utilization data and analysis into project planning and scoping processes. Develop project scoping/planning templates tailored to life-cycle analysis outcomes and scoping requirements and practice. Document best practices for using asset data for project planning and scoping. Develop materials (e.g., case studies) to illustrate and share these practices. Promote awareness of project scoping/planning expectations through targeted outreach and communication. Develop and implement a training program and materials for asset data-informed project planning and scoping. Provide a formal repository to store project scoping/planning templates, supporting integration with life-cycle analysis outcomes. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.2.b – Data-Driven Project Design2-Project Planning, Scoping, and Design Element Description Selection of materials and design features based on observed performance and maintenance/operational needs. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 Asset performance and cost information is not considered in the design process. Anecdotal (qualitative) information about asset performance and cost information is considered in the design process. Selected quantitative asset performance information (e.g., material performance) is available to designers but use of this information is not a formally established part of the design process. There are established, documented design procedures for use of asset performance data. Field performance is verified by experimentation, and proper statistical practices are followed (e.g., minimum sample size, etc.). There are automated processes for retrieval of relevant performance data from business systems at design inception. Performance data gathered via sensor or similar technology is analyzed and used to optimize material selection and other design elements. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Document expert opinion regarding benefits and best uses of design alternatives. Summarize typical costs. Perform statistical evaluation of design outcomes using asset information. Document high and low performing options. Institute routine evaluation of project-level performance outcomes. Incorporate findings into design process/ decisions. Implement monitoring tools to capture detailed performance data that can inform future design improvement. Document agency best practices relating to asset data use in project design. Develop communication materials (e.g., case studies) to share practice. Promote awareness of project design expectations through targeted outreach and communication. Develop and implement a training program and materials for asset data-informed design decision-making and processes. Establish a formal program for evidence-based design and construction practice improvement. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.3.a – Infrastructure Maintenance3-Maintenance Element Description Infrastructure maintenance program informed by asset life cycle modeling and analysis. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No regular preventive or scheduled maintenance program. Limited maintenance based on industry standards or norms. Limited maintenance informed by life cycle analysis. Regular maintenance programs with dedicated funding based on analysis of life cycle costs and benefits. Tracking of costs and benefits is established but may not yet be producing usable information. Maintenance program is based on life cycle analysis with adjustments based on data-driven assessment of program costs and benefits, for example, through asset-specific modeling or through incorporation of contracting and/or programming efficiencies. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Document maintenance practices among peer agencies. Develop simple policy/guidance for field staff. Develop network screening protocol/tools that support identification of maintenance opportunities. Establish formal maintenance programs. Use life-cycle analysis to establish funding and targets and associated reporting. Expand/improve decision- making through collection of detailed performance and reliability information. Develop simple check lists, time-based protocol, or other tools to improve proactive maintenance decisions. Promote awareness of maintenance expectations through targeted outreach and communication. Track and examine costs and benefits of preventive and other maintenance treatment alternatives. Track and examine benefits of strategies to improve programming efficiencies (e.g., coordinated investment across multiple assets or programs). Other: Other: Other: Other: Assessment Notes: Improvement Notes:

Date: Participating Members: Assessment Context: E-Act as Informed by Data E.3.b – Equipment Maintenance 3-Maintenance Element Description Use of equipment life cycle, maintenance history and cost information to inform planning and budgeting for equipment maintenance. Benchmark Level 0 Benchmark Level 1 Benchmark Level 2 Benchmark Level 3 Benchmark Level 4 No regular equipment preventive or scheduled maintenance program. Equipment maintenance is performed based on age, a prescribed frequency or cycle, or manufacturer recommendations. Equipment maintenance costs and reliability are tracked and considered in planning for equipment maintenance and replacement for selected high-risk assets. Equipment maintenance costs and reliability are tracked and considered in planning for equipment maintenance and replacement for all essential equipment assets. Maintenance and replacement cycles are based on data about individual pieces of equipment gathered in an automated fashion. Current: Desired: Current: Desired: Current: Desired: Current: Desired: Current: Desired: Establish proactive equipment maintenance policy based on manufacturer recommendations. Track service history and use information to identify low reliability equipment for replacement. Expand equipment history tracking to include maintenance costs and productivity. Use these data for maintenance and replacement decisions. Expand/improve decision- making through collection of detailed performance and reliability information. Develop simple checklists, time-based protocol, or other tools to improve proactive maintenance decisions. Implement an equipment inventory and maintenance history tracking system. Establish a formal preventive/routine equipment maintenance program. Set funding, responsibilities, targets, and associated reporting. Implement automated work ordering tools to automatically generate work orders based on established practices. Other: Other: Other: Other: Assessment Notes: Improvement Notes:

III-60 A P P E N D I X F Detailed Organizational Practices This appendix offers supplementary materials on organizational practices to support implementation of TAM data and information improvements.

Detailed Organizational Practices III-61 Strategic Planning Creating agency business plans to guide development and investment. Useful for addressing time, resource, expertise, coordination, and change challenges. Performance Management Establishing objectives and measures at the agency, business unit, and employee level and a tool to provide focus and guide improvements. Most valuable for coordination and change challenges. Enterprise Architecture Providing an integrated view of agency business process, data, application, and information technology infrastructure that will support the agency’s desired level of integration and standardization. Applicable to time, resource, coordination and change challenges. Strategic Management Strategic management is an umbrella term covering strategic planning and decision-making structures and processes that are used to set priorities and allocate resources (including time, funding, staff capacity and capabilities). Strategic management practices provide a way to establish alignment across different business units and tools reinforcing organizational priorities and tracking progress towards established objectives. Additionally, these practices provide a means to evaluate organizational structures and roles to ensure they remain aligned with changing expectations and requirements. Typical strategic management strategies include:

III-62 Guidebook for Data and Information Systems for Transportation Asset Management Enterprise Risk Management Instituting systematic practices to control uncertainty and variability on strategic objectives by managing risks at enterprise, program, project, and activity levels. Helpful for time, resource, coordination, and change challenges. Strategic Governance Forming the decision-making structures, roles, and responsibilities used to make enterprise level decisions within the agency business, information technology, and management programs. Very useful in addressing time, resource, coordination, and change challenges. Typical Strategy Details Strategic Planning Agency and IT strategic planning are useful to assess the current state of the organization and develop strategies to move forward, tracking progress towards a desired state. Agency Strategic Planning Utilize agency strategic planning to understand the current situation and future outlook. Identify strategic issues to address, seek input from stakeholders, customers, and employees, and synthesize current strengths, weaknesses, opportunities, and threats (SWOT). Then create or update the agency’s mission, values, vision, goals, and objectives. Develop agency wide strategies to achieve the objectives and cascade these down to the Division and Program levels. Set Key Performance Indicators (KPIs) to measure progress and establish a schedule for monitoring and updating the plan. Communicate the plan across the agency. IT Strategic Planning Develop an IT strategic plan following a similar process as described for agency strategic planning, building off of those outcomes. Assess the current state, identify issues and trends affecting future needs, and establish goals, objectives, and supporting strategies and tactics. The IT strategic plan should identify categories of investment needed to achieve objectives and provide guidance for project selection – it should not be a fixed project list. An IT strategic plan may also address workforce capacity building needed to successfully meet future needs.

Detailed Organizational Practices III-63 Typical Strategy Details (continued) Performance Management Develop performance measures, targets, and management plans, and track and communicate KPIs indicating progress towards performance goals. Transportation Asset Management Plans As a part of (or in addition to) creating federally required Transportation Asset Management Plans, agencies may establish a TAM policy or strategy to set priorities for investment, identify key infrastructure management and service delivery processes, define roles and responsibilities, and set direction for continuous improvement of TAM practices. Performance Dashboards Create performance dashboard communicating KPIs that can be reasonably measured and tracked to provide a meaningful indication of progress towards agency strategic goals and plans. Consider using a balanced scorecard approach to include multiple perspectives on performance: financial, customer/stakeholder, internal process efficiency and quality, and organizational capacity, learning, and growth. Establish a desired reporting interval and put in place measurement and reporting processes. Acquire or build tools automating data processes, and provide online access. Communicate how and why the dashboard was created and how it should be used. Enterprise Architecture Clarify the desired level of business process integration and standardization across the agency (the Operating Model) and use this to drive identification of core business and supporting IT capabilities. Use these capabilities to guide prioritization and selection of strategic initiatives to strengthen the agency’s foundation for execution. Train and integrate architects within the project teams. Create models of as-is and to-be business capabilities, processes, data, applications and technology infrastructure to support transition from the current to desired future state. Enterprise Risk Management Define responsibilities and processes for identifying, tracking, and mitigating risks at the agency, program, project, and activity levels. Use an established risk management framework (e.g., ISOP 31000) to establish standard risk management processes, including risk identification, risk analysis (identify root causes and assess likelihood and consequences), risk evaluation (ranking), taking appropriate action (mitigation, termination, acceptance, transfer), and communication and monitoring. Strategic Governance Establish agency decision-making bodies, roles, and responsibilities. Develop charters to ensure clear process and procedures for reaching consensus and mechanisms for escalation where consensus cannot be reached. Engage stakeholders to ensure informed participation and decision-making, and regularly evaluate decision-making authority to ensure it is meeting current agency needs and is aligned with the strategic vision and enterprise.

III-64 Guidebook for Data and Information Systems for Transportation Asset Management Strategic Management References Below are key references available if a deeper understanding or application of strategic management is needed. • NCHRP Report 331: Strategic Planning and Management Guideline for Transportation Agencies • NCHRP Synthesis 326: Strategic Planning and Decision Making in State DOTs • TCRP Synthesis 59: Strategic Planning and Management in Transit Agencies • NCHRP Project 20-24(83): Alternative DOT Organizational Models for Delivering Service • NCHRP Report 08-93: Managing Risk Across the Enterprise: A Guide for State DOTs • NCDOT Research Report: Adopting a Culture for Performance Management at the Nevada DOT • FHWA Noteworthy Practices: North Carolina Refining a Performance Management System • Harvard Business Review Press: Enterprise Architecture as a Strategy: Creating a Foundation for Business Execution

Detailed Organizational Practices III-65 Workforce Planning Identifying workforce composition based on retirements, hiring, and other organizational and environmental trends. Best for expertise, coordination, and change challenges. Talent Acquisition and Retention Creating hiring and retention practices and a corporate image that successfully attracts and retains the interest of target employees. Best for expertise and change challenges. Succession Management Proactively planning for successors to existing senior employees, and, where allowed, pursuing dual incumbency to ensure critical positions remain filled. Best for expertise and change challenges. Employee Development Developing onboarding, career development, organizational ladders, leadership training, and performance review practices to ensure staff have Talent Management Talent management incorporates workforce planning, recruiting and retention, succession planning, and employee development practices which help organizations identify, hire, and develop the skilled staff needed to design, deploy, and integrate these improvements into the complex systems, tools, and associated business practices of the DOT. As new technologies, tools, and practices are implemented, the skills required by the TAM workforce will change, requiring techniques to identify changing staff and job requirements as well as provide the training necessary to develop these capabilities in existing staff. Typical strategic management strategies include:

III-66 Guidebook for Data and Information Systems for Transportation Asset Management opportunities to identify and build upon current skills and address areas needing development. Best for expertise, coordination, and change challenges. Typical Strategy Details Workforce Planning Support the future sustainability and performance of the agency by anticipating workforce needs and planning to fill gaps in skills and expertise, ensuring the agency employs the right people, with the right skills, at the right time. Start by identifying the current workforce composition of the agency, analyzing the organizational structure, composition, and rate of change (e.g., capturing number of entry level vs. upper management employees, amount of new hires vs. long term staff, and the percentage of the workforce that is likely to retire in the next 5-10 years). Next, assess the organizational trends, technology changes, and other external forces that may create gaps in skills and capabilities at the agency. Identify the current skills and capabilities that the agency must maintain in the future and the new skills and capabilities that will be needed as trends change. Based on the current workforce composition and the predicted gaps in skills, develop a plan for hiring people to fill those gaps in the coming years. Talent Acquisition and Retention Support the agency’s workforce and mission by generating interest and enthusiasm in target employees and successfully acquiring and retaining the talent needed to effectively carry out its goals. After developing a hiring plan to fill skills and capabilities gaps, perform a market analysis to determine the needs and desires of skilled potential and current employees. Analyze current agency policy, then determine the areas where improvement is needed to make the work environment more attractive to prospective and current employees. For example, allow for flexible work hours or remote working options, provide appealing technology options, streamline the hiring process, or work towards competitive salaries. As improvements are made, highlight these in the recruitment and retention activities. Consider engaging local universities and provide opportunities for summer internships or part-time work during the school year. These can be either paid opportunities or for college credit. Raise awareness of jobs in transportation by attending career fairs and holding information sessions. Show the wide variety of work available in transportation and demonstrate the path toward full employment. Additionally, evaluate the ways the agency stands out from private sector employers or other public sector agencies (e.g., benefits, work-life balance, flexible work hours, agency culture, agency mission, etc.). These should be highlighted in all recruitment activities. Develop a workplace identity/brand to appeal to employees that fit the culture of the organization. Use performance reviews to communicate progress and areas for further growth to employees.

Detailed Organizational Practices III-67 Talent Management References Below are key references available if a deeper understanding or application of talent management is needed. • Vermont Agency of Transportation: Employee Retention and Knowledge Management • NCHRP Synthesis 323: Recruiting and Retaining Individuals in State Transportation Agencies • TRB Special Report 275: The Workforce Challenge • NCHRP Synthesis 362: Training Programs, Policies, and Practices • Alaska Department of Transportation: Serving Future Transportation Needs • NCHRP Report 685: Guide to Implementing Strategies to Attract and Retain a Capable Transportation Workforce • Transportation Research Record: Millennials in the Transportation Workforce • NCHRP 20-05 Topic 49-10: Transportation Workforce Planning and Development Strategies (not published) Typical Strategy Details (continued) Succession Management Ensure that critical positions in the agency are filled and knowledge is transferred effectively as workers change jobs. Identify the critical positions within the agency and develop a succession plan for these positions. Identify the skills and training required for these positions and work to build that experience in people who may be able to fill the role in the future. Succession Planning is an iterative process and the plan will change as new people fill different roles, as roles change, or as the skills required for the roles evolve. Employee Development Provide training and opportunities for growth to help engage employees, build skills, and prepare for the future. Develop an onboarding training program to help new employees feel informed and prepared and also set the expectation of continued training throughout an employee’s time at the agency. Offer training classes to develop new skills and highlight the career development steps needed to move up in the organization. Hold regular performance reviews to communicate progress and areas for further growth to employees.

III-68 Guidebook for Data and Information Systems for Transportation Asset Management Portfolio Management Creating processes, practices, and tools to scope, schedule, monitor, adjust, and coordinate across projects and other initiatives. Track, manage, and coordinate a set of projects and other initiatives to maximize value to the organization, manage risks, and maintain a balance between commitments and available resources. Best for time/resources, expertise, coordination, and change challenges. Organizational Change Management Applying processes, practices, and techniques to address employee and organizational resistance to changes. Prepare, equip, and support people in an organization to successfully adapt to changes in business processes, tools or management structures. Best for change and coordination challenges. Process Improvements Evaluating and improving performance of existing business processes. Modify Initiative Management Initiative management includes a range of business, process, and program management techniques which enable the organization to effectively deliver upon its priorities. This is essential as DOTs are complex organizations, with wide ranging, interdependent programs and strategic initiatives requiring planning and management for effective execution. Establishing standard tools, techniques, processes, roles and responsibilities for documenting and delivering upon detailed business cases for program and process improvement is critical to undertaking the complex data, information system, and business improvement projects recommended in this guidance. Typical Initiative management strategies include:

Detailed Organizational Practices III-69 business processes to create more value, increase speed and efficiency and produce more consistent results. Best for time/resources, coordination, and change challenges. Typical Strategy Details Portfolio Management Start by identifying the types and sizes of initiatives you want to track. For example, an agency’s initiative portfolio might include IT projects, new data collection or purchases, and new program or policy implementation efforts. Then, define the information to collect and maintain for each initiative. This information should enable traceability to the need that triggered the initiative and the organizational goals and objectives it supports. It is also helpful to track resource needs, timelines, key milestones, major dependencies and risks. Create or acquire a system to manage the portfolio information. Establish responsibilities for reporting and updating information. Finally, put in place processes that use this information to prioritize candidate initiatives, improve coordination across related initiatives and balance work with available resources. Use roadmaps to gain consensus on a path forward, describe steps needed to get from the current state to the desired future state, and identify and understand dependencies across related efforts. The process of developing a roadmap is as important as the end product as it helps establish alignment across different players. Organizational Change Management Establish an organizational change management capability within the agency. Adopt a proven change management model such as ADKAR (Awareness, Desire, Knowledge, Ability, Reinforcement). Include a change management component within projects or other initiatives that require significant adjustments to current processes or responsibilities. Keep in mind that initiative-based change management may not be effective without ongoing attention to organizational culture and employee engagement. Be sure to provide opportunities for changes to be initiated from the bottom up, not just top down. Use roadmaps to ensure that the end goal, and the path to that goal, is clear. Process Improvements Develop internal agency expertise in Lean or other established business process improvement techniques or identify external resources that can be brought in for this. Increase awareness of these techniques across the organization so that managers understand their value and seek out services when they recognize opportunities for improvement. Encourage application of business process improvement techniques prior to or in conjunction with introduction of new IT applications. Establish business analyst positions within the agency. These positions may be located within the information technology unit and/or within business units. Train and equip business analysts to perform business process modeling (e.g., flowcharts, swim-lane diagrams), business case analysis, requirements elicitation and management, use case analysis, user stories, conceptual data models, data flow diagrams, business rules analysis, test case development and other business analysis techniques. Encourage the use of RACI (Responsible-Accountable-Consulted-Informed), and similar models in conjunction with new initiatives, or in cases where roles and responsibilities are ambiguous and need clarification.

III-70 Guidebook for Data and Information Systems for Transportation Asset Management Knowledge Capture and Dissemination Identifying agency knowledge assets and gaps and creating processes to capture and document critical knowledge and organize/manage it so it can be discovered. Support planning for how to build the necessary expertise required to implement and sustain improvements and then disseminating that information throughout the organization. Best for expertise, coordination, and change challenges. Collaboration and Peer to Peer Learning Facilitating collaboration and learning through establishing communities and fostering connections to experts. Best for expertise and change challenges. Knowledge Development Building in opportunities for learning through initiatives and as a part of routine business processes. Best for expertise challenges. Knowledge Management Knowledge management encompasses a range of techniques for building, leveraging and sustaining the know-how and experience of an organization’s employees. Some agencies choose to pursue knowledge management as a strategic, agency-wide practice; others implement knowledge management techniques without central coordination – as an integral part of staff management, project management, information management, or research/innovation activities. Typical knowledge management strategies include:

Detailed Organizational Practices III-71 Typical Strategy Details Knowledge Capture and Dissemination Knowledge Capture To support building the necessary expertise required to implement and sustain improvements, capture the critical knowledge within and missing from the organization. Through interviews and surveys, perform a knowledge audit to identify current knowledge resources and gaps. Capture and document specialized or unique knowledge from experts through knowledge interviews. Create a structures questionnaire for knowledge interviews and identify and train one or more individuals to conduct the interviews. Establish criteria to help identify and prioritize situations where knowledge interviews would be beneficial, such as the pending retirement of a senior engineer. Knowledge Dissemination To support continuous improvement in practices for data standardization, collection, analysis, and use, create a searchable repository for documenting critical knowledge and lessons learned. Promote the use of this repository during the planning stage of new initiatives. Collaboration and Peer to Peer Learning Peer Collaboration Support collaboration and learning within groups that perform similar roles but may not normally interact in the course of day to day business by defining an agency-sanctioned process for groups to come together to brainstorm, problem solve, and share experiences. Ensure that teams embarking on improvement initiatives benefit from the experience of their peers by organizing and facilitating a work session that brings together peers to share their experiences and knowledge with a team that needs help meeting an upcoming challenge. Expertise Directory Support new initiatives and ongoing business processes by developing an expertise directory to provide a way to recognize agency experts in specialized areas that can be consulted for advice or expert knowledge. Create a process for identifying these experts in selected topic areas and enlist their participation. Publish an online directory of these experts with contact information. Knowledge Development To support maintaining critical agency knowledge and addressing knowledge gaps, create a program to teach employees critical knowledge through seminars, training, and other methods and to acquire outside critical knowledge where gaps exist through hiring, outside help, or other means. When outside help is sought to address knowledge gaps, ensure access to the knowledge is properly maintained.

III-72 A P P E N D I X G Implementation Support: Case Studies This appendix provides practical examples of real projects completed by state DOTs that can serve as best-practice references. These references can be used in conjunction with improvement recommendations to support projects and initiatives to enhance data management maturity in accordance with the guidebook (Part I of this report).

Implementation Support: Case Studies III-73 Step 1: Perform Maturity Assessment ODOT contracted a study to measure the department’s maturity in data governance. A survey was created and administered to key ODOT data business owners. Recommendations from this study were to create a data governance framework and supporting policy and standards. Step 2: Establish Governance Framework A data governance structure was defined with oversight by the Chief Data Officer and a Data Governance Committee. Step 3: Create Governance Standards, Roles, and Responsibilities The Data Governance Committee led a project to implement enterprise data standards, define governance roles and responsibilities, and establish metadata management practices. Step 4 (Future State): Treat Data as an Asset Through increased awareness of governance processes, make ODOT a data-driven organization emphasizing data quality, availability, integrity, and usability. Ohio DOT: Establishing a Governance Framework Responding to in-house and third-party software applications with limited integration capabilities, the Ohio DOT (ODOT) developed a data governance framework to improve data management efficiencies and reduce data duplication. This governance framework was established and applied through the following approach: Specify and Standardize Data Governance Value Delivered Consistent quality, availability, integrity and usability of data Leadership Executive endorsement and vision from onset IT collaboration and integration in project Expertise Technical expertise in big data and industry standards Coordination Identify and leverage data governance champions Cross-department communication Change Change management focus on value derived from the change

III-74 Guidebook for Data and Information Systems for Transportation Asset Management Ohio DOT: Establishing a Governance Framework Data Governance Maturity Gap Chart – Spider diagram showing areas with lowest maturity levels to target governance needs. Data Governance Framework - Recognizing management of data centered on People, Process and Technology – a culture change impacting nearly all ODOT staff. Proposed implementation phases focused on a new agency-wide approach to data governance (based on calendar year).

Implementation Support: Case Studies III-75 Step 1: Inventory Assessment UDOT engaged a service provider to collect mobile LiDAR data of its entire roadway system. During the initial phases of data collection, UDOT encountered various challenges with asset coding and the sheer scope of the data collection. UDOT addressed these challenges individually. Step 2a: Developing a Data Dictionary The data collection vendor did not have sufficient documentation to properly code all the assets being collected. UDOT prepared a Data Dictionary on asset coding to drive consistent, higher quality data extraction. This required bringing together individuals from across the organization to agree upon a single set of attributes for each asset. Step 2b: Establishing Asset Tiers With an overwhelming amount of enterprise-wide data, UDOT focused TAM decision-making, by establishing asset tiers. Tier 1 assets, such as pavements and bridges, were targeted for data-informed decision-making. Step 3: Maintain Asset Database UDOT is now working to complement the enterprise wide asset data collections using mobile applications in a newly procured asset management system. The new mobile tools replace pen and paper tracking, allowing UDOT to understand the real cost to maintain assets over their life cycle. These tools will also assist in maintaining a more up to date asset database by providing live asset updates instead of waiting for statewide collection every two years. Utah DOT: Statewide Vehicle- Based Data Collection Utah DOT (UDOT) found that many asset owners were collecting data but there was no single repository for that information. This was creating data management challenges and an inability to quantify an enterprise-wide asset inventory and value to improve data driven decisions. To address this, UDOT determined it would collect a statewide LiDAR survey of its entire roadway system every two years. Collect Data Inventory, Condition, and Performance Collection Value Delivered Standardization and ease-of-use for asset data Leadership Executive endorsement and vision from onset Division level engagement Expertise Technical expertise to troubleshoot and optimize workflows Asset performance subject expertise to identify data requirements Coordination Cross-functional teams to make asset priority decisions Change New data management practices shifting to single repository for data access

III-76 Guidebook for Data and Information Systems for Transportation Asset Management Step 1: Defining Information Flow CDOT documented the information flow from raw data collection through submittal to the FHWA HPMS. They created a flowchart to visually represent the information flow and to support user understanding. They then documented the technical components of the collection program (Steps 2a-2d). Step 2a: Standards and Protocols CDOT documented the standards and protocols for collection and characterization of the Federal pavement condition metrics as well as other data elements collected for state pavement management purposes. Step 2b: Training and Certification CDOT documented the training and certification of all personnel involved in the production of data, including field data collection, data processing, and manual distress rating. Step 2c: Collection Equipment CDOT documented calibration procedures and quality checks conducted on data collection equipment before and during collection. Step 2d: Collected Data Quality checks applied Federal metrics and individual data elements and associated procedures were documented. Step 3: Staff Accountability As a final step, CDOT required signatures of all designated staff acknowledging acceptance and accountability for adherence to the plan. Collect Data Inventory, Condition, and Performance Collection Value Delivered Compliance with FHWA standards Leadership Executive endorsement Expertise Data collection equipment Data quality control and sampling Coordination Cross-functional teams & training Central office, field, and support staff External collection contractor Change Governance Impact to field collection staff workflows and processes Data issues were exposed requiring new quality control practices Colorado DOT: Data Quality Management Plan Development The Colorado DOT (CDOT) developed a Quality Management Program (QMP) document in response to federal requirements. This document reports processes performed by CDOT and by the data collection contractor to address the quality of all data reported to the FHWA’s Highway Performance Monitoring System (HPMS). The QMP ensures collected pavement condition data is reliable, accurate, complete, and reasonable.

Implementation Support: Case Studies III-77 Colorado DOT: Pavement Data Quality Management Plan A flowchart of CDOT Pavement Data QMP provides users an overall view of data flow and interdependencies. Data certification thresholds are a critical component of the pavement data QMP and set the standards for internal and external collection requirements. Pavement Data QMP allows for higher accuracy life cycle forecasting to support funding requests.

III-78 Guidebook for Data and Information Systems for Transportation Asset Management Step 1: Standard Work and Life- Cycle Definitions VDOT defined what would and would not qualify as work accomplishments. They also defined how to record these accomplishments to accurately capture desired performance metrics. Step 2: Assign Work and Budget VDOT assessed the quantities of each asset and used life-cycle assumptions to determine how much maintenance work (and budget) to assign to each category per year. Step 3: Track Work in Real Time VDOT Maintenance Division devised an approach to incorporate HMMS data entry of work “accomplishments” into routine field business practices to support real time tracking. Step 4: Engage Stakeholders To engage stakeholders and manage change, VDOT prepared guidance documents and job aids for data entry protocols and metric quantification methodology. VDOT also instituted monthly performance reporting. Virginia DOT: Mobile Field Data Collection Implementation Virginia DOT (VDOT) embarked on an asset management system replacement project in 2016. Among other needs, VDOT sought to support field collection of asset information, work orders, inspections, and work accomplishments. Full procurement and implementation of a commercial off the shelf solution took approximately 3 years, but their new Highway Maintenance Management System (HMMS) was implemented statewide and across multiple departments. With the system in place, VDOT began capturing field maintenance information in a standardized manner and using this information to better understand and communicate how much money was being spent on maintenance activities and the results that are being achieved. Collect Data Maintenance Information Collection Value Delivered Compliance with FHWA standards Leadership Executive endorsement and vision from onset Expertise Knowledge of tools and software to support required configurations for data requirements Coordination Feedback from local offices to central office Central office, field, and support staff Change New tools and processes required of field staff Lack of awareness of statewide needs and uses for work accomplishment data

Implementation Support: Case Studies III-79 Virginia DOT: Mobile Field Data Collection Implementation Example GPS enabled mobile devices and map-based tools support efficient collection of maintenance work accomplishment information in the field. Use of pick lists and other standardized data entry support analysis and reporting of statewide performance measures.

III-80 Guidebook for Data and Information Systems for Transportation Asset Management Step 1: Export Data to GIS UDOT will export the 3D model data from Bentley software using FME to bring the features and all the model attributes into a 2D GIS representation. Step 2: Locate Asset The model data will be loaded onto mobile field devices and utilized by field personnel to locate the asset and update attributes. If the location is not accurate, an updated features location can be collected. Mobile devices are connected via s-built Bluetooth to rovers to support the required level of location accuracy. One important consideration made by UDOT was to determine an acceptable level of tolerance for each asset type so that field personnel can make consistent judgments around whether new location collection is or is not required. Step 3: Upload Asset Attributes The updated, as-constructed attributes and locations, if required, will then be uploaded to the primary enterprise database in the organization’s master GIS repository, UPlan, as a new layer allowing users to see the as-built asset condition. Going forward, UDOT will be able to construct 3D representations of the asset using the Z coordinates retained from the original 3D model. Utah DOT: Mobile LiDAR and BIM/CADD Integration UDOT has made significant investment in 3D design with a goal of streamlining the data flow and management from pre- construction through to maintenance. Since 2016, UDOT has awarded 11 projects with the 3D design model as the legal document (MALD). In 2018, UDOT awarded it first MALD project without cutting sheets (which were previously included on MALD projects for information only). UDOT is now looking to develop a repeatable process to maintain the 3D model data through construction and beyond using mobile devices in the field to capture as-built details. Store, Integrate and Access Data Asset Management System Integration with CADD Value Delivered LiDAR data as asset baseline 3D digital representation of assets Leadership Executive endorsement and vision from onset Expertise Knowledge of tools and software to support required integration requirements Coordination Cross-divisional coordination is required to drive consensus and understand target use Change New processes for how asset data is stored, managed and accessed

Implementation Support: Case Studies III-81 Utah Mobile LiDAR and BIM/CADD Integration Examples A 3D model of underground utilities and a culvert. Inspectors use a rover and a tablet to collect survey data electronically. A 3D model of a T intersection showing clash detection and utilities. A 3D model showing topography and a bridge.

III-82 Guidebook for Data and Information Systems for Transportation Asset Management Step 1: User Needs and Use Case Documentation User needs and use cases for the proposed decision support tool were developed by a cross-functional team. Recommendations were provided through 1) a series of workshops with individual business and data subject matter experts, 2) engagement of executive management to establish decision-making values and priorities, and 3) review of tools of peer agencies. Step 2: Develop Data Sources Enterprise data needs were identified and associated reference and master data sets were developed from source systems. Step 3: Configure Off-the-Shelf Business Intelligence Tools Requirements for a configurable, off- the-shelf solution were developed to ensure long-term sustainability. A custom solution was identified as a risk. Step 4: User Engagement and Training Staff were allowed dedicated time away from routine business responsibilities. An agile approach was used for delivery. Step 5: Data Quality Improvement Integrating data and formalizing metrics exposed data quality issues. Resources and responsibilities for quality were assigned. Ohio DOT: TAM Decision Support Tool Case Study The Ohio DOT developed a Transportation Asset Management Decision Support Tool to provide a mechanism for ODOT managers to make decisions on adequate information for optimizing the performance and cost-effectiveness of infrastructure assets. This tool supports investment decisions and demonstrates the return on those investments both quantitatively and qualitatively. The tool was developed and implemented through the following approach: Act as Informed by Data Project Planning, Scoping, and Design Value Delivered Centralized portal for data access Leadership Executive endorsement and vision from onset Expertise Business Engagement Data Architecture & Management BI Software & Dashboards Coordination Cross-functional teams & training Central office, field, and support staff Change Impacts to Roles and Responsibilities Accountability for data-informed decisions Data Issues Exposed

Implementation Support: Case Studies III-83 Ohio TAM Decision Support Tool Content Examples A landing page allows efficient access to data and reports, with options to filter, review maps, and generate reports. Filtering tools provide the ability to narrow the reported data by location as well as asset characteristics. Condition maps provide network level screening based on color coded features, and to allow access to detailed asset information through an “Asset Inspector” tool. Standard reporting is provided across a range of information areas, including inventory, condition, performance, investment, maintenance, and planning. A report showing forecasted pavement conditions. A report showing total expenditure by selected assets.

III-84 A P P E N D I X H Facilitator Materials This appendix offers supplementary materials to support the organization and preparation for formal application of the guidebook by a DOT. Supplemental materials are organized around: Participant Engagement, Kickoff Meeting, Self- Assessment and Improvement Identification, and Improvement Evaluation.

Facilitator Materials III-85 Outcome: Focus for the process is selected and target participants identified. Supporting Material: Part I, Chapter 2, Use Case Overview and Value Guidance Instructions: The project sponsor and assessment facilitator should establish a specific scope (or focus) for improvement. The focus should be identified based on the Chapter 2, Use Case Selection materials and the known needs and priorities of the agency or sponsoring business or technical area. Activity 1 – Initial Scoping Initial Scoping Preparation Materials "Use Case Overview and Value" Chapter 2 “Key Roles and Responsibilities” Chapter 2

III-86 Guidebook for Data and Information Systems for Transportation Asset Management Outcome: Targeted participants are informed of the need and value of their involvement. Assessment team membership finalized. Supporting Material: Appendix H, Participant Engagement Materials and Meeting Agenda Part I, Chapter 2, Key Roles and Responsibilities Guidance Instructions: Once a focus is selected, the facilitator must identify the desired membership of the assessment team with the input of the project sponsor. 1 Invite targeted participants to a preliminary engagement meeting. 2 Deliver a preliminary engagement meeting to share details of the commitment, answer questions, and identify any additional recommendations for team membership. 3 Secure commitment from the participants, for the full process, including potential implementation support. Additional Supporting Guidance: At the preliminary engagement meeting the facilitator should: • Communicate the specific nature of the planned assessment activities and an expectation for the level of effort involved. • Identify the targeted focus area and anticipated value of improvements. • Answer questions from the targeted participants (including how and why they were identified for involvement). • Secure participant commitment and identify any additional recommendations for involvement. • Make participants aware that they may also be asked to assist with implementation (for example, by supporting business or IT requirements development or by advocating for priority improvements impacting their business or technical area). Before holding the preliminary meeting, the facilitator should be familiar with the guidebook process and general organization. It is important the Participant Engagement Materials Key Roles and Responsibilities Chapter 2 Activity 2 – Participant Engagement

Facilitator Materials III-87 facilitator can clearly discuss the identified need or motivation, as well as the specific process that will be followed by the team. The facilitator should encourage any questions and discussion that might develop over the course of the meeting and also ask if any additional participants are recommended for inclusion in the team (noting that additional perspectives are always valuable, however the size of the group should be managed to allow for maximum engagement from all participants).

III-88 Guidebook for Data and Information Systems for Transportation Asset Management Outcome: Share context and establish a self- assessment meeting schedule with the assessment team. Ensure participants are prepared for the upcoming self-assessment activities. Supporting Material: Appendix H, Kickoff Meeting Materials and Meeting Agenda Part I, Chapter 2, Key Roles and Responsibilities Guidance Part I, Chapter 3, Self-Assessment Framework and Materials Overview Guidance Instructions: Once the assessment team has been engaged and the commitments of individual participants secured, hold a kickoff meeting. The facilitator should: 1 Provide a high-level overview of the process and upcoming activities of the group. 2 Detail the role of the facilitator to • Guide the group activities. • Record, summarize, and share group consensus and notes. 3 Explain individual roles sharing expectations and desired perspectives from each individual participant in the team. 4 Review key guidebook content(such as the guidebook framework and element-level response templates) used during assessment and improvement identification activities. 5 Share participant “homework”that will be required for detailed self-assessment and improvement identification meetings. 6 Establish a meeting schedulebased on participant availability and the recommended meeting duration and frequency. 7 Introduce the digital support toolhighlighting key contents, usefulness in preparation for upcoming meetings, and encouraging individual review after the meeting. Additional Supporting Guidance: Meetings should be kept to a maximum of 90 minutes (typically 1–2 meetings per week). This allows for sufficient Kickoff Meeting Materials Key Roles and Responsibilities Chapter 2 Self-Assessment Framework and Materials Overview Chapter 3 Sample Kickoff Meeting Agenda and Supporting Materials Appendix H Activity 3 – Kickoff Meeting

Facilitator Materials III-89 preparation and avoids participant fatigue. With proper preparation and facilitation, a small group should expect to be able to complete self-assessment and improvement identification with approximately 10 minutes of discussion per element, allowing assessment of one area in a typical meeting. Given the wide range of perspectives on the team, the facilitator should acknowledge that, where agreement cannot be reached across all participants, the facilitator will have to make a final decision for the purposes of the effort, and that other views or perspectives will be captured in the detailed notes. At the end of the kickoff meeting, the facilitator should identify when the first assessment meeting will be held, and communicate which guidebook sections should be reviewed in preparation for that discussion.

III-90 Guidebook for Data and Information Systems for Transportation Asset Management Outcome: Complete self-assessment activities. Document the current and desired state of practice within the selected focus. Identify potential improvements that close performance gaps. Supporting Material: Appendix H, Self-Assessment Meeting Materials and Meeting Agenda Part I, Chapter 3, Area-Level and Section-Level Self-Assessment Guidance and Support Material Appendix A-E, Element-Level Response Templates Instructions: After the kickoff meeting has completed, organize and hold self- assessment meetings. 1 Prior to a meeting:• Coordinate schedules and send meeting invites. • Communicate the Area(s) that will be the focus of individual meetings. • Identify Chapter 3 materials that should be reviewed prior to the meeting. • Encourage individual completion of element-level response templates prior to the meeting. 2 During the meeting:• Use the TAM Data Assistant. • Navigate the assessment framework, facilitating benchmarking and improvement selection discussion. • Capture group consensus and any assessment or improvement specific notes and context. 3 After the meeting:• Summarize and share meeting outcomes. • Identify action items or specific clarification or context that were requested during the meeting’s activities. Assessment Guidance and Support Area and Section-Level Assessment Support Materials Chapter 3 Sample Self- Assessment Meeting Agenda and Support Materials Appendix H Element-Level Response Templates Appendix A-E Facilitator Tips: Self-Assessment Meetings Practical Considerations Plan no more than 1-2 meetings per week and avoid extensive gaps between meetings. Target Discussion Focus on no more than two assessment areas in a meeting. Meeting Duration: ≤ 90 min. Activity 4 – Self-Assessment

Facilitator Materials III-91 Outcome: Complete improvement evaluation activities. List improvements prioritized for implementation. Document potential implementation challenges, improvement impact and effort, and associated priority of individual improvements. Supporting Material: Appendix H, Improvement Evaluation Meeting Materials and Meeting Agenda Part I, Chapter 4, Improvement Evaluation Guidance Instructions: Once the self-assessment activities are complete, evaluate and prioritize the selected improvements for implementation. Organize and hold an improvement evaluation meeting. 1 Prior to a meeting:• Coordinate schedules and send meeting invites. • Highlight improvement evaluation concepts and needs. • Request individual review of the Chapter 4 materials. • Export and share all identified improvements with participants. • Request individual review of improvements, identifying no more than five implementation priorities. • Evaluate individual responses to identify the group’s priorities and prepare to facilitate a focused improvement evaluation discussion. Improvement Evaluation Materials Improvement Evaluation Chapter 4 Sample Improvement Evaluation Meeting Agenda and Supporting Materials Appendix H Facilitator Tips: Improvement Evaluation Practical Constraints Focus on improvements at the current performance level, do not attempt to “leap frog” multiple performance levels. Target Discussion Use individual priorities to focus discussion. Begin priorities identified from individual responses. Move forward with other improvements as time allows. Meeting Duration: ≤ 90 min. Activity 5 – Improvement Evaluation

III-92 Guidebook for Data and Information Systems for Transportation Asset Management 2 During the meeting:• Use the TAM Data Assistant. • Navigate improvements, facilitating prioritization, impact vs. effort, and challenge identification and discussion. • Capture group consensus and evaluation notes or context. 3 After the meeting:• Summarize and share meeting outcomes. • Identify action items resulting from meeting activities.

Facilitator Materials III-93 Outcome: Executive engagement and support for implementation priorities. Supporting Material: Part I, Chapter 4, Current and Desired State Summary Part I, Chapter 4, Improvement Evaluation Part I, Chapter 4, Executive Communication Instructions: Clear, effective communication of the current and desired state, key performance gaps, and priority improvements are essential to capturing support for improvement. 1 Develop summary materials thateffectively communicate to the executive audience, in coordination with the Project Sponsor. 2 Build support, encouraging theassessment team to engage their management and stakeholders. 3 Meet with decision-makerssharing the process, priorities for investment, and consensus and support from cross-functional team members and stakeholders. Additional Supporting Guidance: If the TAM Data Assistant has been used, the facilitator can export summary charts as well as detailed assessment and improvement information in order to support these communication needs. Further detail is provided in the guidance materials documented in Chapter 4, Evaluation and Summary of Results. Summary and Communication Materials Current and Desired State Summary Chapter 4 Improvement Evaluation Chapter 4 Executive Communication Chapter 4 Activity 6 – Summary and Communication

III-94 Guidebook for Data and Information Systems for Transportation Asset Management Outcome: Improvement delivery. Successful, long-term implementation. Supporting Material: Part I, Chapter 5, Implementation Support Guidance and Materials Instructions: The Chapter 5, Implementation Support materials share organizational practices and case study materials which can be very useful in guiding agency implementation efforts. All participants should review these materials and actively work to ensure the contexts and challenges identified in the initial assessment, improvement identification, and improvement evaluation activities are raised and that potential solutions are recommended. Implementation Support Materials Organizational Practices Chapter 5 Case Studies Chapter 5 Activity 7 – Implementation Support

Facilitator Materials III-95 Participant Engagement Preliminary Meeting Invitation Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Preliminary Meeting; <Process Focus> To: <Desired Members of Assessment Team> Cc: <Project Sponsor> You are invited to attend a preliminary meeting to discuss the process of examining our data and information system practices within <Process Focus>. This process will help our organization improve how data is defined, collected, accessed, analyzed, and used in the decision-making process specific to this asset. You are being asked to be a part of the assessment team for this process. This preliminary meeting will review the planned assessment process, the roles & responsibilities, and expected level of involvement for team members. This meeting will hopefully receive your commitment as a part of this important effort. The <Insert Duration> minute meeting is scheduled for <Meeting Date and Time> at <Meeting Location>. Please reach out if you will not be able to attend or if you have any questions. Thank you, <Assessment Facilitator>

III-96 Guidebook for Data and Information Systems for Transportation Asset Management Participant Engagement <Process Focus> Preliminary Meeting Agenda <Meeting Date> <Meeting Location> Objectives: Establish process need, inform participants of their need and value of involvement, finalize assessment team 5 Minutes Welcome and Meeting Overview Ÿ Welcome and introductions Ÿ Meeting objectives 15 Minutes Assessment Process Context Ÿ Process need and focus area context Ÿ Anticipated value of improvements 15 Minutes Roles and Responsibilities of Team Members Ÿ Roles and expected level of involvement 15 Minutes Assessment Team Implementation Ÿ Assessment team establishment Ÿ Additional team members and contributors 10 Minutes Questions and Feedback

Facilitator Materials III-97 Kickoff Meeting Kickoff Meeting Invitation Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Kickoff Meeting; <Process Focus> To: <Members of Assessment Team> Cc: <Project Sponsor> Thank you for being a part of the <Process Focus> Assessment Team. This important effort will help our organization improve how data is defined, collected, accessed, analyzed, and used in the decision-making process for this asset. You are invited to attend the kickoff meeting for <Process Focus>. This meeting will give you a high-level overview of the process. It will introduce the guidebook framework, the element-level response template, and the digital tool. This meeting will also establish future meeting schedules and prepare you for the upcoming self-assessment activities. The 90-minute meeting is scheduled for <Meeting Date and Time> at <Meeting Location>. Please reach out if you will not be able to attend or if you have any questions. Thank you, <Assessment Facilitator>

III-98 Guidebook for Data and Information Systems for Transportation Asset Management Kickoff Meeting Sample Kickoff Meeting Agenda <Meeting Date> <Meeting Location> Objectives: Establish self-assessment meeting schedule and prepare participants for upcoming self-assessment activities 10 Minutes Process Status Review and Meeting Objectives Ÿ Previous meeting review & current meeting objectives 20 Minutes Assessment Process Overview Ÿ High-level overview of process Ÿ Upcoming activities of the group 20 Minutes Roles of Team Members Ÿ Explanation of expectations and desired perspectives from individual participants 20 Minutes Introduction to Guidebook Content and Digital Tool Ÿ Framework and element-level response template walk-through Ÿ Introduction to digital tool, highlight of key contents and use 10 Minutes Meeting Schedule and Preparations Ÿ Meeting duration and frequency Ÿ Preparations for self-assessment activities 10 Minutes Questions and Feedback

Overview Assess the Current and Desired State Understand available data and information systems, tools, technologies, and practices for a specific asset or element within the data life-cycle. Identify associated data and information system improvements. Prioritize Improvements Evaluate identified improvements. Establish priority, relative impact, effort, and organizational challenges associated with potential improvement. Communicate Improvements and Support Implementation Create effective communication of the current and desired state, performance gaps, and priority improvements. Support implementation to realize successful, long-term improvements. Key Roles Asset Program Lead Participant will be a program lead from within the selected TAM focus area. Typically, participants will be central office program management, project managers, analysts, or engineers who understand asset management decision-making needs from a policy perspective. Several such individuals should be included. Field Asset Management Leads Typically, participants will be District asset managers, engineers, or maintenance supervisors who are involved in day-to-day decision making and execution. Must be able to share the practical realities, challenges, priorities, and constraints of field asset management staff. Several such individuals should be included. Information Technology and Staff Key IT staff who have an understanding of existing technologies, applications, and priorities within the targeted area. Typically, participants will be IT relationship managers, system administrators, project managers, or business and technical analysts. Should be able to share data, technology, or application related context as business needs are discussed. Should be able to raise awareness of solutions leveraged in other business functions. Expected to share technical process, challenges, and constraints that would be anticipated when delivering IT solutions. Data Life-Cycle Area Subject Matter Experts Subject matter experts as appropriate to the asset program or specific data life-cycle areas; other key perspectives should be represented. Kickoff Meeting: Overview and Roles

Data Life-Cycle Framework

Facilitator Materials III-101 Kickoff Meeting Kickoff Meeting Follow-Up Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Kickoff Meeting Follow-Up; <Process Focus> To: <Members of Assessment Team> Cc: <Project Sponsor> Thank you for attending the <Process Focus> kickoff meeting. In order to facilitate the completion of the upcoming self-assessment meetings, it is important for you to review the supplemental guidebook materials. These include the data life-cycle framework and the element-level response templates. It is also important to familiarize yourself with the digital tool. Please find attached the meeting minutes and supplemental guidebook materials for you to review before our next meeting. Here is a link to the digital tool: www.dataassessment.tam-portal.com. Thank you, <Assessment Facilitator>

III-102 Guidebook for Data and Information Systems for Transportation Asset Management Self-Assessment and Improvement Identification Self-Assessment Meeting Invitation Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Self-Assessment Meeting; <Target Area> within <Process Focus> To: <Members of Assessment Team> Cc: <Project Sponsor> You are invited to attend a self-assessment meeting for <Target Area> within <Process Focus> This meeting will give you the <Target Area> overview and context. You will help complete self- assessment activities for <Target Area> which includes establishing current state of practice, documenting the desired state of the practice, and identifying improvements to close the performance gap. We will be using the supporting digital tool to aid in this process. Attached are the previous meeting’s minutes and <Guidebook Materials> that should be reviewed prior to this meeting. Here is a link to the digital tool: www.dataassessment.tam-portal.com. The 90-minute meeting is scheduled for <Meeting Date and Time> at <Meeting Location>. Please reach out if you will not be able to attend or if you have any questions. Thank you, <Assessment Facilitator>

Facilitator Materials III-103 Self-Assessment and Improvement Identification Self-Assessment Meeting Agenda <Meeting Date> <Meeting Location> Objectives: Complete self-assessment activities, document current and desired state of targeted area, and identify potential improvements to close performance gap. Targeted Area: <Targeted area> 10 Minutes Process Status Review and Meeting Objectives Ÿ Previous meeting review & current meeting objectives 10 Minutes Area Overview and Context Ÿ General area overview 60 Minutes Self-Assessment and Improvement Identification • Establish current state • Document desired state • Identify improvements 10 Minutes Closing Discussion • Closing comments or questions • Action items • Next steps

III-104 Guidebook for Data and Information Systems for Transportation Asset Management Self-Assessment and Improvement Identification Follow Up Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Self-Assessment and Improvement Identification Meeting <Target Area> within <Process Focus> Follow-Up To: <Members of Assessment Team> Cc: <Project Sponsor> Thank you for attending the <Target Area> within <Process Focus> Self-Assessment and Improvement Identification meeting. The key conclusions discussed in the meeting were <Meeting Summary>. For our next step, we will be focusing on <Next Target Area>. In order to facilitate the completion of the upcoming self-assessment meeting, it is important for you to review the supplemental guidebook materials for <Next Target Area>. These include the data life-cycle framework and the element-level response templates. You may also review the assessment elements, benchmarks, and potential improvements here: www.dataassessment.tam-portal.com. Attached are the meeting’s minutes and <Guidebook Materials> that should be reviewed prior to the next meeting. Thank you, <Assessment Facilitator>

Facilitator Materials III-105 Improvement Evaluation Email to Gather Individual Responses From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Self-Assessment and Improvement Evaluation Meeting <Target Area> within <Process Focus> Follow-Up To: <Members of Assessment Team> Cc: <Project Sponsor> In preparation for the upcoming Improvement Evaluation meeting. The key conclusions discussed in the meeting were <Meeting Summary>. For our next step, we will be focusing on <Next Target Area>. In order to facilitate the completion of the upcoming self-assessment meeting, it is important for you to review the supplemental guidebook materials for <Next Target Area>. These include the data life-cycle framework and the element-level response templates. You may also review the selected improvements and evaluation criteria in the supporting digital tool: www.dataassessment.tam-portal.com. Attached are the meeting’s minutes and <Guidebook Materials> that should be reviewed prior to the next meeting. Thank you, <Assessment Facilitator>

III-106 Guidebook for Data and Information Systems for Transportation Asset Management Improvement Evaluation Improvement Evaluation Meeting Invitation Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Improvement Evaluation Meeting; <Process Focus> To: <Members of Assessment Team> Cc: <Project Sponsor> In preparation for the upcoming Improvement Evaluation meeting to evaluate the improvements selected in the previous Self-Assessment and Improvement selection meeting for <Process Focus>, please review the selected improvements and identify no more than five priorities for investment. Please pass along your prioritized improvements, along with your rational for selecting them, and some preliminary thoughts about their associated challenges to <Assessment Facilitator>. Attached is the Chapter 4 Improvement Evaluation Handout for you to review along with a list of the improvements selected in the previous Self-Assessment and Improvement Selection meeting. The upcoming 90-minute meeting is scheduled for <Meeting Date and Time> at <Meeting Location>. Please reach out if you will not be able to attend or if you have any questions. Thank you, <Assessment Facilitator>

Facilitator Materials III-107 Improvement Evaluation <Process Focus> Improvement Evaluation Meeting Agenda <Meeting Date> <Meeting Location> Objectives: Complete improvement evaluation activities, document potential implementation challenges and impacts, and prioritize improvements. 10 Minutes Process Status Review and Meeting Objectives Ÿ Previous meeting review & current meeting objectives 50 Minutes Improvement Evaluation Discussion • Review individual priorities • Improvement impact vs. effort • Implementation challenges 20 Minutes High-Level Prioritization Discussion • Review assessment summary material • Adjust improvement evaluation outcomes (based on broader context) 10 Minutes Questions and Feedback

Pre-Assessment Preparation 25 Improvement Evaluation Handout Impact is characterized by the extent to which new or existing practices will transform TAM-related business practices. Effort is characterized by the level of resources and staff time required and the extent to which those can be incorporated into the responsibilities and budgets of existing business units. Priority is established on the basis of when that improvement would be targeted for implementation, ranging from immediate action to being recognized for future, unplanned action. Challenges can be categorized into distinct categories of Time, Resource, Expertise, Coordination, Change, or Other. Impact Evaluation High Impact Transforms current business in a way that addresses major process pain points, is likely to extend to multiple business units, and adds value to multiple business processes. Medium Impact Makes existing business processes significantly more efficient and effective, however may be within a limited area of business (e.g., a specific business function or process area). Low Impact Contributes a minor adjustment to an existing business process, but will not significantly change the business. In general, these improvements may already be informally in place, but are simply being formalized or being made clearer in the context of the program at large. Effort Evaluation High Effort Requires a major commitment of resources and staff time, typically across multiple business units. Examples would include a major IT application, a statewide technology deployment, etc. Medium Effort May be incorporated within typical budgets and resources but would require planning and coordination, typically limited to a specific business function or process area. Low Effort Can be included within the routine responsibilities of a business unit or working group and typically able to be completed within a short timeframe. Priority Evaluation High Priority Targeted for immediate action. Medium Priority Desired to begin within the next several investment or planning cycles (e.g., 1-2 years). Low Priority Recognized, but not anticipated for action within the near future and unlikely to be incorporated into near term planning activities. Challenge Categorization Time Recommended when limited time is available for the given effort. Resources Recommended when level of resources or staff time would require executive approval. Expertise Recommended when the expertise required is not available to the DOT without specialized support. Coordination Recommended when engagement and agreement is required across many different areas of business within the DOT, particularly when many of the impacted business units do not typically work together as part of the routine business of the agency. Change Recommended when the improvement will significantly transform current business across multiple business units and processes, requiring extensive process reengineering and/or training to those impacted.

Facilitator Materials III-109 Improvement Evaluation Improvement Evaluation Follow up Email Template From: <Assessment Facilitator> Date: <Date> Subject: TAM Assessment Process Improvement Evaluation Meeting for <Process Focus> Follow-Up To: <Members of Assessment Team> Cc: <Project Sponsor> Thank you for attending the <Process Focus> Improvement Evaluation meeting. The key conclusions discussed in the meeting were <Meeting Summary>. For our next steps, we will be focusing on engaging with management and stakeholders and meeting with decision- makers. This will be aided by further summary materials, which will be developed and sent out in a later email. In order to facilitate implementation, it is important for you to engage your management and stakeholders. Please feel free to reach out if you have any questions or need any help. You may also review the assessment and evaluation results here: www.dataassessment.tam- portal.com. Attached are the meeting’s minutes. Thank you, <Assessment Facilitator>

III-110 A P P E N D I X I TAM Data Assistant Quick Reference Guide This appendix provides instructions and a brief explanation of the web-based, supporting digital tool developed for this guidebook.

TAM Data Assistant Quick Reference Guide III-111 Web-Based Tool Access The tool is available on the web to anyone who is interested. User credentials are required, but only a valid email is needed to register an account. The tool is hosted on the AASHTO TAM Portal website and directly accessible at the link provided to the right. Tool Organization The tool is organized around the formal use cases and process described in Chapter 2 of the Guide. This organization results in five main pages linked from the Home Page. 1 Create. This page allows the user to create new assessments. The user can createan unlimited number of individual assessments. 2 Assess and Select Improvements. This page allows the user to assess anddocument their current state of practice, desired state, and identify potential improvements against the 51 individual elements of the technical framework. 3 Evaluate Selected Improvements. This page allows the user to prioritize theirselected improvements, while also evaluating anticipated implementation impact and effort, as well as identifying potential challenges. 4 Assessment Results. This page provides summary results in a format useful forcommunication. 5 All Assessments. This page lists the assessments associated with the user’s account,and can be used to easily navigate to any assessment the user has created. TAM Data Assistant Overview The web-based TAM Data Assistant is designed to support a streamlined user experience through the self-assessment, improvement identification, improvement evaluation, and results summary and communication activities of the Guidebook process. TAM Data Assistant Access www.dataassessment.tam-portal.com Note: If the direct link is not available, please check the AASHTO TAM Portal to see if an updated link is referenced.

III-112 Guidebook for Data and Information Systems for Transportation Asset Management Assessment Login Page Functionality Login Page The login page prompts the user to enter their credentials in order to access the tool functionality. If a user has forgotten their login information, they are able to retrieve that information using the email address they associated with their account. New users are also able to create a new account from this page. Main Elements of the Login Page Username and Password Fields. The digital assessment tool requires a username and password to save assessments and keep them secure. Create Account. Allows a new user to create an account which they can use to create assessments. Forgot info. Allows the user to get their login information if they’ve forgotten it.

TAM Data Assistant Quick Reference Guide III-113 Assessment Landing Page Functionality Landing Page After logging in, the user finds a landing page. From this page, new assessments can be created or previous assessments viewed. A dashboard also provides information summarized from the “Most Recent Assessment” selected by the user. Navigation Menu. Easily navigate to any page of the tool. Create. Click to begin the creation of a new assessment. View All. Click for a summary view of all assessments associated with the user. Most Recent. Shows information about the user’s most recent assessment. Results. Clicking takes the user to the results summary page. Evaluate. Shows how many improvements have been evaluated. Clicking takes the user to the improvement evaluation page. Assess. Shows how much of the assessment is completed. Clicking takes the user to the most recently assessed element.

III-114 Guidebook for Data and Information Systems for Transportation Asset Management Assessment Menu Functionality Home Link. Returns the user to the page detailed in Figure 3 (page III-13). Current Assessment Dropdown. Current Assessment. Takes the user the assessment homepage Assess. Takes the user to the assessment. Evaluate. Takes the user to the improvement evaluation. Results. Takes the user to the results summary page. Create. Takes the user to the assessment creation page. See Figure 5 (page III-115). All Assessments Takes the user to a page showing all assessments associated with the user’s account. Log Out. Logs the user out of the assessment tool. Assessment Menu Each of the framework elements has its own landing page – color-coded to match its parent area’s color scheme.

TAM Data Assistant Quick Reference Guide III-115 Assessment Creation Page Functionality Creation Page This is where the user will create new assessments. Each assessment can be refined to a specific subset of the assessment areas within the Guidebook technical framework. Directions. A brief set of instructions for using this page. Assessment Area Selection. A description of each assessment area. The user can select a group of areas they’d like to assess. This group can’t be changed once the assessment is created. Assessment Information. The user can fill out information about the name, description, scope/focus, and group completing the assessment here.

III-116 Guidebook for Data and Information Systems for Transportation Asset Management Assessment Page Functionality Assessment Page Each element has its own page with its own assessment table. Self-assessment can be completed by rating current and desired practice levels and selecting potential improvement activities by click within their associated boxes. This functionality replaces the need for print response templates found in Appendices A-E. Navigation. Tabbed navigation for quick navigation about the assessment. There are also “Next” buttons for navigating to the next element. Element Description. Brief description of the element being assessed. Assessment Table. The user can set current and desired level of the element based on the description, and choose improvements related to the element. Notes Boxes. The user can take notes about their choices. Custom Improvements. The user can write their own improvements for consideration.

TAM Data Assistant Quick Reference Guide III-117 Improvement Evaluation Page This page collects and displays the improvements selected by the user. It features a number of tools to aid in navigating the improvement evaluation process. Improvement Evaluation Page Functionality Show All. Toggles displaying all improvements on one page. Improvement Panel. Display a description of the improvement, and the ability to evaluate it in the following ways: Impact/Effort. The user can characterize the improvement by the impact on the agency and the effort required. Challenge Type. The user can specify some challenges associated with the improvement. Priority. Users can choose Low, Medium, or High priority. Sort & Filter. Allows the user to customize the improvements that are displayed. They can sort the improvements, or filter the improvements so only certain improvements are shown.

III-118 Guidebook for Data and Information Systems for Transportation Asset Management Results Page Functionality Results Page This page provides a results summary useful for reviewing outcomes and summary and communication activities. Area Navigation. Show results from a certain area. Impact/Effort Grid. Shows the number of improvements in the area that fall in each box of the grid. Radar Chart. Shows the current and desired level for each Element in the Area. Improvement Detail. Clicking an Impact/Effort box shows panels summarizing the improvement and its evaluations. Reassessment. Users can reassess an improvement directly from the results page.

TAM Data Assistant Quick Reference Guide III-119 Excel Export The user can export their results from the Improvement Evaluation page, the Results page, and the Current Assessment page. The export is an Excel spreadsheet with three worksheets: 1) Assess, 2) Evaluate, and 3) All. The Assess sheet gives the element-by-element results of the current and desired practice assessment. The Evaluate sheet gives information about each improvement, including priority, impact, effort, and identified challenges. The All sheet joins the Assess and Evaluate results, giving all information about each improvement. Assess Sheet Content Element ID Label Area Name Section Name Element Name Description Current Level Desired Level Assessment Notes Improvement Notes Evaluate Sheet Content Improvement ID Time Challenge Description Resource Challenge Associated Element Expertise Challenge Impact Coordination Challenge Effort Change Challenge Priority Improvement Evaluation Note Custom (indicates if custom improvement) Status (indicates if selected improvement)

III-120 Guidebook for Data and Information Systems for Transportation Asset Management All Assessment Page Functionality All Assessments Page This page lists all the assessments that belong to the logged-in user. The page shows the completion percentage of the Assessment and Improvement Evaluation activities based on the defined scope of the individual assessment. The date and time each assessment was created and last accessed are also provided. Clicking a row will take the user to that assessment.

TAM Data Assistant Quick Reference Guide III-121 Current Assessment Page Functionality Current Assessment Page This page gives some information about the current active assessment and provides links to the various sections of the assessment tool. The user can edit information about the Assessment here.

III-122 A P P E N D I X J Detailed Literature Review J.1 Key Technologies Table J.1.1: Key Technologies Key Data Storage or Specification Tools and Technologies Technology Description Asset Management Systems DOTs are required by the FHWA to maintain certain key asset management systems, such as Pavement and Bridge Management Systems, and as such, these systems have been developed and implemented across the DOTs. These systems store and maintain asset inventory, condition, and performance information, and may support use of detailed engineering and asset management models to develop optimized investment strategies, provide functions to share and report information, and meet other requirements of DOT asset management programs. In a typical application, these systems operate in silos. However, in more mature applications, an enterprise system may be in place, supporting cross-asset functionality and improved integration with planning, project development, project delivery, and agency reporting tools and systems. Geographic Information Systems (GIS) Integrated into data collected throughout the asset life-cycle, GIS allows the establishment of a precise location for information useful from planning to construction and maintenance. Internally within the DOT, GIS enables data collection and review, and location-based integration of data independently from legacy location referencing systems. GIS also enables simple but powerful communication and sharing of information with external partners. As such, GIS is an integral part of a mature DOT asset management program. Global Positioning Systems (GPS) Built into field data collection and construction equipment to establish the precise location during design, maintenance, or construction activities, this technology allows for very accurate and efficient data collection. GPS tools streamline field review and analysis of existing GIS information, maps, or reports based on the current location information. In emerging Building Information Modeling (BIM) applications, GPS is integral to fully maximizing the value of 3D asset models, the update of detailed as-built information, as well as the automation of construction processes where detailed 3D models are provided in design plans.

Detailed Literature Review III-123 Key Data Collection Tools and Technologies Technology Description Vehicle Mounted Highway Data Collection Systems These systems represent the current industry standard for DOT network-level asset inventory and condition surveys. Comprised of vehicle mounted hardware and software, these systems enable collection of a wide range of information at highway speed. A typical data collection can include collection of roadway and pavement imagery, roadway geometry, pavement profiles, condition and structure information, roadside asset inventory and conditions, bridge clearance, and other critical asset inventory, condition, and performance information. Imagery collected during the primary survey can also be used to populate a video log for future, project-specific reference. Vehicle mounted LiDAR data collection has been adopted by a limited number of DOTs to provide near survey-grade accuracy in data collected during network-level assessment. Web-based Mapping Systems Tools for automated mapping of asset management and other information based on simple user input. Very useful throughout all phases of the data life-cycle, from initial specification and collection, through sharing and reporting. Mobile Devices and Applications Leveraging GIS and GPS information, these tools support field capture, log, and reference of asset inventory, condition, and project information in real time, replacing the need for hard copies of reference documents, project plans, and specifications with digital copies. Wireless data and camera functionality can be leveraged to transfer information, document construction progress or issues, process construction reports and directly access an electronic document management system, provide electronic signatures, and create other construction process efficiencies. These tools can also allow for field access to and update of asset management system inventories, condition, performance, or other information to both support construction and facilitate update of work accomplishments. Light Detection and Ranging (LiDAR) A data collection technology which allows for the capture of accurate spatial data in three dimensions during survey. Currently, this technique is primarily used in the delivery of complex construction projects; however, in mature asset management implementations, LiDAR enables the speedy creation and update of 3D asset models, which can be used to update asset inventory or as-built information to asset management systems for use in future project scoping, design, construction, and maintenance. With the rapidly advancing power of mobile tools, mobile LiDAR applications are an emerging technology which will offer field users more dynamic access to these large, complex, but powerful 3D asset models. Three- Dimensional Engineered Models These models include spatial relationships among various design elements of an asset or work activity. Detailed as-built 3D models can be provided through LiDAR (light detection and radar) surveying. These models allow for attachment of metadata, clash detection, and 4D/5D simulation (if enhanced with scheduling and estimation metadata). In examples found in the international transportation sectors, as well as at some U.S. airports, these models are the foundation of organization-wide BIM implementations, which fully integrate and leverage data across the entire asset life-cycle, from planning into operations and maintenance. Key Data Storage or Specification Tools and Technologies Technology Description

III-124 Guidebook for Data and Information Systems for Transportation Asset Management J.2 Supporting Tools Table J.2.1: Supporting Data Storage Tools Supporting Data Storage Tools Technology Description Video Log A commonly used data storage, sharing and reporting tool in DOT asset management programs, a video log provides location referenced roadway imagery, organized for ad- hoc review by internal and/or external DOT staff. Typically populated with imagery collected during network-level data collection completed by Vehicle Mounted Highway Data Collection Systems, these images can replace more time intensive, costly, and higher risk field surveys during project scoping and design, as well as maintenance delivery. Electronic Document Management Systems (EDMS) These systems enable more efficient internal and external collaboration by providing electronic filing, management, and use documentation. In mature applications, these systems can enable paperless job sites by providing managed access to project information to both DOT and construction or maintenance contractors. Cloud Data Storage Cloud storage can provide efficient access to information across various internal and external actors within DOT asset management processes. Use of these tools comes with information management and security implications, which can pose challenges to DOTs. Table J.2.2: Supporting Data Collection Tools Supporting Data Collection Tools Technology Description Crowdsourced Data An emerging technique for data collection, there are examples of data captured by the general public being useful to DOT asset management programs. These can include direct engagement of the public as well as partnerships with third party industry or data vendors that can provide real time information collected from the general public on network performance, asset conditions, or other information which can be used to enhance DOT decision-making processes. Unmanned Aerial Vehicles (UAV) An emerging technology, remotely piloted or automated drones offer value to DOT data collection and asset management programs by providing a lower cost for inspection of otherwise difficult to access assets, such as bridges, high mast lighting, or other structures. Additionally, UAVs can provide detailed aerial data collection to support project design and construction. Augmented Reality (AR) Tools An emerging technology, enabling the superimposition of computer-generated images on the user’s view of the real world. AR tools have potential application in asset data collection and review by field staff as well as support applications delivering more accurate project design and construction. Optical Character Recognition (OCR) Tools Tools used for the automated recognition of typed, handwritten, or printed text within scanned images, photos of documentation, or from other imagery. These tools are commonly used in business applications for data entry from printed records and have applications for DOT asset management programs that include the development and mining of data from legacy paper records, as well as the identification and classification of roadway sign and other asset information from right-of-way imagery.

Detailed Literature Review III-125 Table J.2.3: Supporting Project Delivery Tools Supporting Project Delivery Tools Technology Description Digital Signatures DOTs can deliver efficiencies and capture time and cost savings by use of digital signatures to enable completely paperless documentation of design, construction, or maintenance activities. Automated Machine Guidance (AMG) In BIM applications, AMG can be used to enhance the productivity and accuracy of construction by replacing use of field stakes and human operation with use of 3D models to guide machinery. Intelligent Compaction (IC) Systems The integration of real-time measurement of location and compaction data into construction equipment can yield increased productivity and quality in construction.

J.3 Information Management and Integration Practices Table J.3.1: Information Management Practices: Broadly Applicable Information Management Practices – Broadly Applicable to Multiple Stages Practice Description Data Life- Cycle Maturity Level Challenges AMS & MMS Integrations with Construction and Design Systems/Tools Design and Construction system integrations with Asset Management and Maintenance Management Systems to exchange asset inventory, design and as-built work plans, work accomplishments, priorities, etc. Small scale examples from U.S. DOTs are found: • Population of AMS analysis into work order/contract systems • Establishment of contract and work order templates allowing automatic population or update of AMS/MMS asset inventories and work history Multiple High Large scale integration information systems and business practices both address and generate challenges for DOTs. Addressed: • Lack of internal data standards • Limited formal documentation • Lack of system interoperability • Institutional silos Faced: • Greater system complexity • Lack of readiness to change • Lagging workforce AMS/MMS Integrations with GIS Process to integrate spatially referenced information into and across various asset management and maintenance management systems Multiple Medium BIM Adoption in Planning and Design Examples from U.S. airport management organizations show that initial adoption of BIM in planning and design may be most practical Multiple Medium High BIM Adoption in Construction Examples from U.S. airport management organizations show that initial adoption of BIM is most practical to construction after it has been incorporated into planning and design, where immediate value can be generated through project efficiency and quality improvements. Multiple High BIM Adoption in Maintenance and Operations Examples from U.S. airport management organizations show that incorporation of BIM into operations and maintenance is most difficult. The international transportation sector shows that the largest benefits to a DOT may be found in this most mature application of BIM practices. Multiple Very High Asset Tiers Used to break up large asset populations to assist in prioritization of resources, work activities, data collection, etc. Asset tiers often take the form of: • Prioritized networks/corridors, • Identification of critical infrastructure, or • Other measures of public use, value, or risk. Multiple Low

Table J.3.2: Information Management Practices: Specify Data Information Management Practices – Specify Data Practice Description Data Life- Cycle Maturity Level Challenges 3D/4D/5D Asset Information Models Asset information models providing spatial relationship of asset and design elements are critical for advanced practice. Metadata for schedule and cost should be attached, as well as for asset management information (inventory, condition, performance, etc.). Specify High Adoption of new data or information specifications can be a solution to many DOT challenges, but may generate friction due to resulting complexities associated with change. Addressed: • Lack of internal data standards • Lack of system interoperability • Difficulty integrating systems • Effective data governance Faced: • Greater system complexity • Lack of readiness to change • Lagging workforce • Industry or another stakeholder acceptance Information Exchange Specifications Efficient exchange of information between design, construction, maintenance, and operation systems and tools requires identification of what information will be captured and exchanged at each phase of a project. Various information standards have been developed to support these exchanges, such as COBie, IFC, and OmniClass. Specify Very High Location Referencing Methods Various approaches used to document the location of an asset, work accomplishment, or supporting data or information. Common methods include GIS, route mile point, link-node, route reference post, route street reference, multi-level LRS. With ongoing advancement in GIS and mobile device technologies, DOT reliance upon traditional route-based linear referencing methods is expected to reduce, particularly in field data collection applications. Specify Low Spatial Data Standards Common standards for geospatial referencing of data Specify Medium Temporal Data Standards Common standards for temporal referencing of data Specify Medium

Table J.3.3: Information Management Practices: Obtain or Store Data Information Management Practices – Obtain or Store Data Practice Description Data Life- Cycle Maturity Level Challenges Geofencing Use GPS information to automatically identify nearby assets to support asset management decisions or collection Obtain Medium High Use of GIS-based data collection tools can add efficiencies to the workforce and enable improved system integration, while generating challenges with system complexity and the workforce Addressed: • Resource limitations • Difficulty integrating systems Faced: • Greater system complexity • Lack of readiness to change • Lagging workforce GIS-based work tracking Real time tracking of work accomplishments based on location information Obtain Medium Operational Databases Support day-to-day operations of a particular application Store Low Routine practice Enterprise Data Sets Information or data which needs to be exchanged across multiple functional areas within an agency (e.g., financial data, roadway network and inventory) Store Medium High Establishment of enterprise data sets can extend the value of a given data set by allowing efficient use beyond the initial business areas Addressed: • Resource limitations • Difficulty integrating systems Faced: • Effective data governance

Table J.3.4: Information Management Practices: Manage or Share Data Information Management Practices – Manage or Share Data Practice Description Data Life- Cycle Maturity Level Challenges Data Warehouses Integrating data originating from multiple sources, typically pulling together information across various management systems or tools Share Medium High Creating locations where data can be integrated and exchanged to support analysis and reporting creates efficiency, while generating needs for effective data governance Common Data Environments Utilize common data environments to identify single source of truth for information Share Medium High Asset Tagging Use of radio-frequency identification, barcoding, stenciling or other technologies to support field identification of assets for look up in management systems or presentation in field data tools Manage Medium Routine practice that generates efficiencies and improves quality in data collection Data Transfer Protocols & Standards Development and utilization of standardized protocols for data transfer between DOT and external stakeholders, such as construction and maintenance contractors Manage Medium Routine practice that generates efficiencies in data exchange and information sharing Data Standard Operating Procedure Documentation Standardized documentation to identify procedures for data collection, update, load, backup, retention, archiving, access policies, and delivery platforms Manage Medium Documenting data and business practices is integral to effective governance, however, can be costly to develop and maintain Addressed: • Difficulty integrating systems • Privacy and security concerns • Effective data governance Faced: • Resource limitations Business Data Glossary, Catalogs, Dictionaries Standardized documentation to support proper understanding and use of data in asset management decision processes, typically containing information on data meanings, structures, values, naming, business rules, quality expectations, acceptable uses, etc. Manage Medium High Reference Data Management Ensuring of consistency of standard code lists across applications Manage Medium High

Information Management Practices – Manage or Share Data Practice Description Data Life- Cycle Maturity Level Challenges Master Data Management Ensuring the organization maintains a “single version of the truth” with respect to core data entities through central management of master data and use of synchronization or replication services Manage High Documenting data is integral to effective governance, however, can be costly to develop and maintain Addressed: • Difficulty integrating systems • Privacy and security concerns • Effective data governance Faced: • Resource limitations BIM Execution Plan A project-specific plan identifying BIM goals and uses throughout project delivery and operation and maintenance phases, including associated processes, deliverables, and responsibilities within the project team. Manage Very High Useful management tools are needed to meet BIM data and business process requirements Addressed: • Difficulty integrating systems • Effective data governance • Institutional silos Faced: • Resource limitations • Contracting and legal hurdles • Industry acceptance issues • Political challenges BIM Model Checking Software Tools have been developed to support effective review and visualization of BIM models. These can include automated reporting to identify compliance with BIM requirements. Manage Very High

Information Management Practices – Manage or Share Data Practice Description Data Life- Cycle Maturity Level Challenges Evidence-Based Design & Construction The establishment of formal programs for conducting research, and tracking and analyzing project outcomes (with respect to the asset owner’s or key stakeholder’s expectations) for the purpose of adjusting future design and construction practices to achieve more exacting operational requirements and demonstrating satisfaction with an asset in operation. A key benefit of organization-wide implementation of BIM is that it facilitates broad application of evidence- based design, construction, and maintenance practices. Manage Very High Changing DOT practices in design and construction to more directly address functional outcomes can improve outcomes, but comes with large institutional barriers Addressed: • Political challenges • Resource limitations Faced: • Institutional silos • Contracting and legal hurdles • Industry acceptance issues

Table J.3.5: Information Management Practices: Analyze Data Information Management Practices – Analyze Data Practice Description Data Life- Cycle Maturity Level Challenges Data Quality Measures Tools allowing for data stewards to understand where asset management or data collection practices may be resulting in unintended quality concerns, typically summarize data accuracy, consistency, reliability, timeliness, completeness, currency, integrity, and confidentiality Analyze Medium High Data quality measures allow a DOT to monitor and improve quality over time; however, workforce and political issues may be generated Geoprocessing Leverage GIS data to automatically integrate and compile data for planning or asset management analysis (such as population, traffic, weather, detour routes, flood plans). Package asset management work within geographic areas or corridors to maximize efficiencies and/or minimize impacts to customers Analyze Medium More advanced analytical tools can be used to identify and drive efficiencies; however, they require governance and workforce considerations Addressed: • Resource limitations Faced: • Lagging workforce • Lack of readiness to change • Lack of internal standards • Effective data governance Data/Text/ Process Mining Finding anomalies, patterns, and correlations within large data sets to predict outcomes Analyze Medium High Temporal Analysis Enable examination or modeling of a variable within a data set over time. Valuable in the examination of asset deterioration, performance trends, investment scenarios, work history, or other asset management data sets. Analyze Medium Trade-Off Analysis Compare priorities with fiscal constraints Analyze Medium Routinely used tools in a DOT, advanced and effective use hinges on workforce skill sets, data governance, and other considerations Prescriptive Analytics Use of business analytics to find the best course of action for a given situation Analyze Medium Predictive Modeling Use of historical asset inventory, investment, and/or condition data to develop models to predict future performance/needs or project impacts of planned work Analyze Medium

Information Management Practices – Analyze Data Practice Description Data Life- Cycle Maturity Level Challenges Online Analytical Processing Application Multidimensional data store used for reporting purposes, useful for allowing efficient slicing, dicing, pivoting, and aggregation of data by business users Analyze Medium High Emerging analytical tools in a DOT, effective use hinges on workforce skill sets, data governance, and other considerations Predictive Analytics Use of data mining, statistics, modeling, machine learning, artificial intelligence or other techniques to make predictions about unknown future events Analyze Medium High Decision Science Score projects and optimize selection for programming based on benefits, costs, and other measures that can be used to assign relative importance Analyze Medium High Table J.3.6: Information Management Practices: Report Data Information Management Practices – Report Data Practice Description Data Life- Cycle Maturity Level Challenges Straight Line Diagramming Tools that provide a simplified representation of the roadway in order to effectively visualize and provide location referencing context of multiple asset management and supporting data for decision-making. Advanced SLD tools may include integration with video log or mapping tools. Report Low Improved reporting tools will address many institutional hurdles by raising awareness and understanding of existing data Addressed: • Resource limitations • Political challenges • Industry acceptance • Contracting and legal hurdles • Lack of readiness to change • Institutional silos Faced: • Legacy system integration • Greater system complexity • Limited formal documentation • Lack of internal standards • Effective governance Performance Dashboards Reporting tool which allows for tracking of agency goals, objectives, and performance measures, useful in guiding daily asset management work activities and investment decisions Report Medium Interactive Reporting Deliver highly usable reporting tools to business users; such tools can be customized specifically to address critical issues based on simplified data entry or offer a wide range of ad hoc reporting functions Report Medium Data Marts Scaled down version of a data warehouse, meeting particular analytical, reporting, or decision-support needs Report Medium High

III-134 Guidebook for Data and Information Systems for Transportation Asset Management J.4 Organizational and Institutional Practices Table J.4.1: Organizational Practices Org Practice Description Management Area Cross-Functional Engagement As DOT systems, processes and practices evolve, cross-functional stakeholder engagement is key to successfully maximizing existing systems to meet new requirements, eliminating redundancy between data and information systems, establishing enterprise and master data sets, and providing data sharing and reporting tools that meet needs Change Management Workforce Capacity and Development As data and information systems grow increasingly complex, mature governance and management programs are required to manage these systems, and daily work activities will require new skill sets In the context of these requirements, DOTs must identify core skills needed for each position, establish training plans for acquiring needed skills and minimize loss of staff knowledge due to staff turnover Workforce Management Training As complex information systems are introduced into traditional technical programs and processes, formal training programs are needed to develop new workforce skill sets and train on new process requirements, data standards, and job expectations Knowledge Management Culture of Data Sharing Formal collaboration and data sharing across institutional silos as well as with external stakeholders are integral to BIM and other mature asset management processes Knowledge Management Supply Chain Integration Data and information are generated throughout the asset life-cycle, from initial strategy and planning through ongoing operation and maintenance of in-place assets To maximize efficiencies and value, DOTs must integrate data and information collection, management, and sharing across their supply chains in all stages of their asset life-cycle Performance Management Cross-Asset Resource Allocation Formalized, funding constrained investment optimization between various asset management activities and services allows DOTs to objectively distribute funding across traditional asset and institutional silos. Performance Management Target-Setting Formalizing agency goals, objectives and performance measures will allow a DOT to adopt performance targets to drive agency asset management decisions and investments Performance Management Risk Management Asset management program and project prioritizations should be made in the context of agency risks An agency with a formal risk management program can more effectively and transparently identify how asset management decisions are influenced by and mitigate agency risks Performance Management Performance- Based Planning Agency planning documents become the blueprint to achieve performance outcomes Performance Management

Detailed Literature Review III-135 Org Practice Description Management Area Performance- Based Programming Guide resource allocation across broadly defined assets and programs to achieve performance targets Performance Management Monitor and Adjust Strategies Track and evaluate actions to improve performance Performance Management Performance- Driven Decision- Making Institutionalize performance management within the agency, with staff at all levels evaluating daily work activities, decisions, and investments against agency performance targets Performance Management Data Governance Planning Documented vision for data governance within the agency, identifies goals, objectives, strategies, action plan for improvement Governance Data Governance Structures Formalized data stewardship roles, responsibilities, and escalation processes Typically organized in a pyramid-shaped organizational structure with an upper-level council or committee providing oversight, enterprise data stewards providing coordination across business units, and data stewards responsible for individual business technologies, applications, data, and/or processes Governance

III-136 Guidebook for Data and Information Systems for Transportation Asset Management J.5 Existing Maturity Models and Self-Assessment Tools Table J.5.1: Existing Maturity Models and Self-Assessment Tools Resources Description Data Value Assessments Templates and formats used to assess to what extent data users believe that existing data is providing value and meeting needs. These tools can be used to identify spot improvements to data. Data Management Maturity Assessments Templates and formats used to assess the current level of agency capabilities for managing data assets to maximize value. These tools can be used to identify improvements to data governance, architecture, integration, and quality management. TAM Self- Assessment Provides approach to self-assessment of DOT transportation asset management programs. TAM Maturity Scale Provides approach to establishing the maturity of DOT transportation asset management programs. IAM Self- Assessment Methodology The Institute of Asset Management has developed a tool that enables all organizations to measure their capabilities against international standards (PAS 55 and ISO 55001) as well as the 39 subjects in the IAM Conceptual Model. IIMM Gap Analysis Tools New Zealand has developed processes and tools to assess capabilities against the practices of the International Infrastructure Management Manual. Data Capability Maturity Models Various models have been developed by private sector partners to assess data capability and maturity. These are generally not specific to DOT applications and include models developed by Gartner, IBM, EWSolutions, DataFlux, Knowledge Logistics, MDM Institute, and Oracle Institute. Capability Maturity Models for GIS use in TAM Capability maturity models for three areas of use of GIS in transportation asset management have been developed – Information Integration, Analysis, and Communication. Implementation Steps for use of GIS in TAM Overall strategy recommendations are provided as well as implementation steps for improving use of GIS in transportation asset management. Business Case Template for GIS in TAM A template has been developed to organize the presentation of a business case for potential investments in GIS support for transportation asset management. TPM Capability Maturity Model Capability maturity models for transportation performance management have been developed. TPM Maturity Assessment Tools to assess transportation performance management maturity have been developed. BIM Maturity Model The UK has developed a maturity model for better information management.

Detailed Literature Review III-137 J.6 Annotated Bibliography Table J.6.1: List of Resources Title Year NCHRP Report 814: Data to Support Transportation Agency Business Needs: A Self- Assessment Guide 2015 AASHTO Asset Management Gap Analysis Tool 2014 NCHRP 08-36, Task 100, “Transportation Data Self-Assessment Guide” 2011 NCHRP Synthesis 508: Data Management and Governance Practices 2017 NCHRP Project 03-128, “Business Intelligence Techniques for Transportation Agency Decision Making” <Active Project> NCHRP Report 800: Successful Practices in GIS-Based Asset Management 2015 NCHRP Research Report 920: Management and Use of Data for Transportation Performance Management: Guide for Practitioners 2019 FHWA Transportation Performance Management Technical Assistance Program Guidebook 2018 NCHRP Report 666: Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies 2010 NCHRP Report 706: Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies 2011 NCHRP Report 806: Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance 2015 NCHRP Project 20-68A, Scan 13-02, “Advances in Civil Integrated Management” 2015 NCHRP Report 831: Civil Integrated Management (CIM) for Departments of Transportation, Volume 1: Guidebook, and Volume 2: Research Report 2016 Guide to Asset Management Processes Part 9: Asset Information Management Systems and Data 2018 Guide to Asset Management Processes Part 10: Asset Management Implementation and Improvement 2018 Harmonization of Location Referencing for Related Data Collection 2011 ACRP Synthesis 70: Building Information Modeling for Airports 2016 “BIM for Airports, ACRP – A Synthesis of Airport Practice” (PowerPoint Presentation) 2015 BS8536 Briefing for Design and Construction – Part 1: Code of Practice for Facilities Management (Buildings Infrastructure) 2015 BS8536 Briefing for Design and Construction – Part 2: Code of Practice for Asset Management (Linear and Geographic Infrastructure) 2016 Integrating 3D Digital Models into Asset Management 2018 Identifying Data Frameworks and Governance for Establishing CIM Standards 2018 Identifying Data Frameworks and Governance for Establishing Future CIM Standards 2018 Infrastructure Asset Managers BIM Requirements - TR 1010: Delivering the information ‘Asset Managers’ need and can trust using openBIM™ 2018

III-138 Guidebook for Data and Information Systems for Transportation Asset Management NCHRP Report 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide Year of Publication: 2015 Link: http://www.trb.org/Main/Blurbs/173470.aspx Overview The guide provides a framework that can be used to operationalize the AASHTO data principles and strengthen management of data assets to realize greater value. Two types of assessment tools are used to examine the current needs and practices of transportation agencies: Data Value Assessments – assess to what extent data users believe that existing data is providing value and meeting needs, identifying spot improvements to data Data Management Maturity Assessments – assess the current level of agency capabilities for managing data assets to maximize values, identifying systemic improvements to data governance, architecture, integration, quality management The guidance includes: A step-by-step guide for implementing the self-assessment tool A Data Improvement Catalog describing what agencies can do to move up the maturity scale Brief case studies TAM Motivations Align data with business needs – help DOTs answer the question: Do we have the right data? Provide reliable data to support scoping, design, resource allocation decisions – help DOTs answer the question: Is our current data good enough? Enable re-use of data to meet multiple needs – help DOTs answer the question: Are we getting full value from our data and making the best of our data collection and management resources? Information Management and Integration Practices Data Life-Cycle Management Standard Operating Procedures for collection, updates, loading, backups, archiving Data change management Data catalogs and dictionaries Data curation profiles (standard methods for documentation of data sets) Data management plans Data retention schedules and archiving Data access policies Data delivery platforms (query and reporting tools, APIs, clearinghouses, etc.) • • • • • • • • • • • Data Architecture and Integration Common geospatial referencing Standardized approach to temporal referencing

Detailed Literature Review III-139 Reference data management Master data management Enterprise information/data architecture Business glossaries Data integration tools (ETL, etc.) Data Quality Management Data quality metrics Data validation rules Data cleansing Organizational and Institutional Practices Data Management Maturity Assessment Data Value Assessment Data Strategy & Governance Data governance bodies Data governance and stewardship policies Data business plans Data management roles and responsibilities Data value mapping Data communities of interest Data Collaboration Multipurpose data collection Data partnerships Data sharing agreements Data outsourcing Information and Data System Challenges and Opportunities Identifies benefits of moving up maturity scale by various Data Management areas Examples or Case Studies Alaska DOT Data Business Planning Caltrans Data Governance Colorado DOT Knowledge Management Governance Oversight Committee Michigan DOT Data Governance Council Minnesota DOT Data Catalog NYSDOT Data Warehouse Ohio DOT Enterprise Architecture Emerging Technology or Techniques • • • • • • • • • • • • • • N/A

III-140 Guidebook for Data and Information Systems for Transportation Asset Management AASHTO Transportation Asset Management Gap Analysis Tool Year of Publication: 2014 Link: http://www.tam-portal.com/resource/aashto-transportation-asset-management-gap-analysis-tool-users- guide/ Overview This tool provides users a methodology to evaluate current and desired capabilities and establish a plan for making necessary enhancements. The tool provides 8 TAM-related assessment areas, with related assessment areas and criteria that can be used to establish current maturity on a 5-point scale. The tool allows for various functions, including: • Establishing a weighting of each criteria to establish an overall weighted average for an area • Set target performance for each criterion • Survey groups can be used to combine results for various groups (e.g., Executive vs. Asset Managers) • Results can be displayed in standardized tabular and graphical reports TAM Motivations The tool provides outputs that are useful in improving: • Asset management plan preparation • TAM processes, systems and data by providing organized, reliable information for prioritizing and aligning investments with agency needs and objectives • Alignment and organization by providing data to help identify programs that are not well understood across an agency The tool produces this by recognizing the following areas of motivation for TAM: • Aligning TAM investment with agency goals and objectives • Risk-based decision-making • Reduce life-cycle costs • Meet customer demands • Transparency and communication • Compliance Information Management and Integration Practices • Asset Management Practices Asset Management Plan Development Life-Cycle Management • Planning, Programming, and Project Delivery Planning and Programming Processes Performance-Based Management Resource Allocation Project Delivery

Detailed Literature Review III-141 • Data Management Asset Inventory Asset Condition and Performance • Information Systems System Technology and Integration Decision-Support Tools System Features • Results Data-Driven Targets Organizational and Institutional Practices • TAM Self-Assessment and Maturity Scale (adopted from 2011 AASHTO TAM Guide) • TAM Organization Policy and Goals Framework Leadership Support • Data Management Data Governance • Transparency and Outreach Accountability Benchmarking Communication and Outreach • Results Compliance Program and Plan Alignment • Workforce Workforce Capacity Workforce Development Information and Data System Challenges and Opportunities Table 4-5 provides suggestions for advancing in maturity • Policy, Goals, Objectives Evaluate measures vs. objectives Quantitative and measurable criteria Costs over the whole life of the asset, quantifying risk and benefits Reliability of information on asset condition and public perceptions Drive resource allocation by performance against objectives AMS provides meaningful info on policy choices and consequences Political pressure is met with objective information on performance • Asset Management Practices Strategies for accounting for maintenance trade-offs associated with capital investments

III-142 Guidebook for Data and Information Systems for Transportation Asset Management Asset management applied across agency, not just high value assets Processes for risk, long-term investment, trade-off considerations in prioritization of investment strategies Reporting changes in asset value based on planned investment strategies Documented asset management processes linked to financial plan Meet federal minimum Trends in road usage and state demographics reflected in objectives and strategies Project information available in planning (and vice versa) Risks identified, recorded, assessed at appropriate level of detail Life-cycle costs Account for maintenance issues • Planning, Programming, Project Delivery o Identify data to improve these functions Realistic projections of future revenue Include modal alternatives Resources required to maintain existing assets at targeted performance and to lower life-cycle costs Capital, maintenance, and operational considerations on statewide and corridor basis Data-driven priorities Performance-based budgeting – relate project costs to expected LOS Historical trends, current conditions, stakeholder expectations Progress toward targets is measured using documented methodology Program trade-off analysis (e.g., preserve vs. rehab) uses benefits and costs and related to expected LOS Realistically quantify project costs, benefits, and impacts on system performance Statewide competition among projects for incorporation into plan Identify agency resources, partnering agreements, outsourcing, other mechanisms Data on cost, risks, quality of procurement options Capture project change orders, costs/schedule, scope adjustments, etc. Accomplishment tracking and reporting • Data Management o Asset Inventory Pavement, bridge, other asset inventory is complete, accurate, current Key data elements identified based on maintenance needs and risks Asset tiers established to asset with prioritization Location-based data collection supports integration Appropriate mix of data collection technology to ensure high-quality inventory and condition is available, providing level of coverage and confidence to ensure quality Right level of detail for identifying and categorizing assets has been established based on costs, accuracy, and criticality to safety, risk, etc. Inventory updated at least annually to reflect system changes

Detailed Literature Review III-143 Asset Condition and Performance Condition/performance updated periodically based on regulatory or agency requirements Survey methodologies are accurate, repeatable, and documented Survey completed by knowledgeable, trained staff Performance monitored such that confidence exists that the asset will perform when needed Track focus groups, customer surveys, complaints, or other feedback to gauge public perception of asset conditions and performance Governance Enterprise data governance plan Enterprise data sets identified Single authoritative sources for shared data identified Data stewardship roles and responsibilities formalized Data meanings, structures, values, naming, and metadata standardized Business rules on data addition, update, or delete New data elements or applications minimize or eliminate redundancy Data quality expectations established Prioritize data needs based on risk and other key factors Develop a quality plan to improve quality of available data Establish a data governance plan • Information Systems Current capabilities of existing management system and prioritize enhancements Improve performance models Incorporate a range of treatments into existing management systems Integration/consistency of information systems with regard to shared data sets Information systems meet needs at multiple organization levels Systems build upon common geographic referencing and common map-based interfaces for analysis, display and reporting Procedure to manage changes in referencing systems GIS integration of agency data and system functionality Tools support trade-off analysis between asset classes and identify gaps in desired performance AM recommendations based on optimization Actual costs, accomplishments are tracked by project, asset, work type, location and allow improvement of models Predict future demand reflecting specific network conditions • Transparency and Outreach Include representative of public information office on asset management committee • Results Review existing performance measures and targets to determine suitability Data-driven targets consider progress toward safety, infrastructure condition, congestion, reliability, economy, freight movement, environmental sustainability, project delivery

III-144 Guidebook for Data and Information Systems for Transportation Asset Management • Workforce Capacity and Development Skills needed in each position Training plans for acquiring needed skills Minimize loss of key staff knowledge Examples or Case Studies • FHWA Transportation Performance Management Case Study: NCDOT Emerging Technology or Techniques • N/A

Detailed Literature Review III-145 NCHRP 08-36, Task 100, “Transportation Data Self-Assessment Guide” (Final Report) Year of Publication: 2011 Link: http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP08-36(100)_FR.pdf Overview The project set out to propose a framework and conceptual design to aid in the development of tools and resources to help DOTs perform self-assessment of their data programs’ adequacy, direction, and management. The tool addresses three objectives: 1. Identify/define current practices applicable to development of a data program self-assessment tool 2. Understand agency needs and challenges associated with data program management 3. Provide a conceptual design and roadmap for a future self-assessment tool TAM Motivations • Identify/define practices applicable to developing a data program self-assessment tool • Understand agency needs and challenges associated with data management • Provide a Conceptual Design and Roadmap for Future Development of a Self-Assessment Tool • Improved Risk Management • Increased Cost Effectiveness • Better Data Quality • Better Informed Decisions • Increased Cost Effectiveness • Better Understanding of Needs • Added institutional capacity • Identifies strategic initiatives Preservation, economic impacts, mobility, safety, sustainability Information Management and Integration Practices • Data Quality Accuracy Consistency Reliability Timeliness Completeness Currency Integrity Confidentiality

III-146 Guidebook for Data and Information Systems for Transportation Asset Management Organizational and Institutional Practices • Summary of various Data Capability Maturity Models Gartner, IBM, EWSolutions, DataFlux, Knowledge Logistics, MDM Institute, Oracle Institute • Strategic Alignment Organizational Roles User Needs Identification of data sources, uses, users Data Utilization Data Visualization • Data Program Management Clear Definitions Ability to Segregate, Aggregate, Analyze Audits Validation Reduce Cost Security Privacy Ethics Data Collaboration Management Continuity • Data Programs Travel, Financial, System Condition, System Inventory, Operational, Safety, Customer Relations • Evolutionary/cyclical approach to data management program improvement Information and Data System Challenges and Opportunities • Challenges Strategic Alignment Lack of Institutional Capacity Organizational Structures and Institutional Relationships Limited Budgets Institutional Momentum Absence of Leadership Continuity Management Indifference Weak Vision Management Turnover Short Management Horizon Poor Implementation Consensus Building Cultural Barriers, Organizational Resistance Task Magnitude

Detailed Literature Review III-147 Solid Intra-Organization Partnerships Communication Published Definitions and Standards Data Champions Examples or Case Studies • Assessment/Accountability Comprehensive Center Data Needs Assessment • International Health Care Example: Global Fund to Fight Aids, Tuberculosis, and Malaria - Routine Data Quality Assessment Tool • Transportation Example: Alaska Department of Transportation & Public Facilities Data Business Plan Emerging Technology or Techniques • N/A • Opportunities Strong Executive Leadership

III-148 Guidebook for Data and Information Systems for Transportation Asset Management NCHRP Synthesis 508: Data Management and Governance Practices Year of Publication: 2017 Link: http://www.trb.org/NCHRP/Blurbs/176005.aspx Overview This paper was a synthesis of research on data management and governance practices as they pertain to DOTs. Information was also gathered using a survey sent out to all U.S. DOTs. The paper addresses: 1. Review of Literature on Transportation Data and Data Management and Governance 2. State DOT Practices and Experiences 3. Local Practices and Experiences 4. Conclusions & Future Research TAM Motivations • Improved Accountability to produce reliable, high-quality data • Ensuring data are accessible and integrated using a common linear referencing system • Engaging business areas about data rather than viewing it as a strictly IT issue Information Management and Integration Practices • Nationally Mandated Transportation Data HPMS – system inventory, asset condition, operating characteristics NBI – bridge inventory and inspection information (bridges and culverts 20’+) Real-Time System Management Information – traffic and travel conditions • Data Integration and Warehousing Data Warehouses – integrate data originating from multiple sources Data Marts – scaled down version of a data warehouse, meeting particular analytical, reporting, or decision-support need Operational Databases – support day-to-day operations of particular application Processes for data extraction, cleaning, transformation, loading, refreshing GIS capabilities for visualization and spatial analysis Commercial cloud computing services Location referencing methods (LRM) – GIS, route mile point, link-node, route reference post, route street reference, multi-level LRS • Data Quality Accuracy (most common) Completeness Timeliness (most common) Relevancy Consistency Accessibility Access security (most common)

Detailed Literature Review III-149 Organizational and Institutional Practices • Categories of Data and Transportation Life-Cycle Planning and Programming Environmental Design Construction Operations and Safety Maintenance Monitoring • Pyramid-Shaped Data Governance Structure An upper-level council or committee providing oversight and strategic direction Enterprise data stewards providing coordination across business units Stewards accountable for the quality and use of individual information technology Information and Data System Challenges and Opportunities • Challenges Lack of Staffing Other mission-related issues are more pressing Lack of resources Lack of a Data Governance Council or Board Examples or Case Studies Governance • FDOT ROADS Initiative for Enterprise Information Management and Data Governance • MnDOT Infrastructure Data Domains • USDOT Data Business Plan Data Integration and Warehousing • Utah DOT - UGATE/UPlan - AGOL platform to access, share, map transportation data Approach emulated by other DOTs (Arizona, Florida, Kansas, Idaho, Montana, Pennsylvania) Emerging Technology or Techniques • Areas of future research Including development of a data management and governance guidebook and training materials Identifying the benefits, costs, and risks (e.g., security risks) of adopting cloud computing services for transportation agencies [future technology] Development of methods and metrics for evaluating data quality considering multiple quality dimensions Development of guidance and framework for integrating data within transportation agencies Case studies to assess the magnitude and complexity of data managed by transportation agencies Development of methods and case studies for mining archived data at these agencies

III-150 Guidebook for Data and Information Systems for Transportation Asset Management NCHRP Project 03-128, “Business Intelligence Techniques for Transportation Agency Decision Making” (Research is Ongoing) Year of Publication: <Active Project> Link: https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4352 Overview • Catalog techniques to extract actionable information from data sources that DOTs can use in making decisions TAM Motivations • Making data-based, actionable recommendations • Identifying promising business intelligence/analytics practices Information Management and Integration Practices • Reporting • Online analytical processing • Predictive/prescriptive analytics • Data/process/text mining • Complex event processing • Business performance management • Benchmarking Organizational and Institutional Practices • Agency decision-making processes • Knowledge of Agency Goals Asset Conditions Traffic Performance Safety Performance Finance/Budget Constraints Information and Data System Challenges and Opportunities • N/A Examples or Case Studies • N/A Emerging Technology or Techniques • N/A

Detailed Literature Review III-151 NCHRP Report 800: Successful Practices in GIS-Based Asset Management Year of Publication: 2015 Link: http://www.trb.org/Publications/Blurbs/172204.aspx Overview Identifies opportunities for agencies to operate better by implementing GIS systems into TAM practices, providing guidance on: 1. Assessing current agency capabilities for using GIS to enhance TAM 2. Identifying initiatives for advancing GIS implementation for TAM based on priorities and business cases for specific improvements 3. Moving forward with implementing initiatives, building on strategies to overcome common barriers to progress The approach is organized around five core TAM motivations and the maturity in GIS support of these areas TAM Motivations • Understand State of Assets • Assess and Manage Risks • Identify Needs and Work Candidates • Develop Programs • Manage Work • Efficiency Information Management and Integration Practices • Data Collection Video and sensing technologies for inventory capture (LiDAR, video log) GPS mobile devices for field data collection Location aware smart phones for crowd-sourcing Geotag photos • Automated Data Compilation for Analysis Consistent standards for measuring and referencing allow for automated integration of data • Automated Mapping Automated, web-based mapping tools • Work Scheduling Package work within geographic areas or corridors to deploy crews efficiently, minimize traffic disruption, etc. • Risk Management Integrate flood plans, fault zones, detour rates, historical weather with traditional asset management information Integrate population, traffic, other factors Track emergency/extreme weather response in real time

III-152 Guidebook for Data and Information Systems for Transportation Asset Management Integrate data for needs assessment Review and assign treatment Review geospatial patterns/trends in asset failure, deterioration, etc. • Developing Programs View integrated information across multiple asset classes and programs Public-facing web applications for asset conditions and planned projects Mobile GIS apps for executive “road shows” • Tracking and Management Work Review planned work by location to consolidate contracts, avoid conflicts, avoid adverse customer impacts • Ingredients for Success of GIS/TAM Initiatives identified, including: GIS Tools Foundation Geospatial data Consistent Data Standards for Integration Management Systems Linked with GIS Coordinated Data Collection Programs Organizational and Institutional Practices • Ingredients for Success of GIS/TAM Initiatives identified, including: Leadership and Alignment GIS Expertise Data Management and Stewardship Coordinated Data Collection Programs • Capability Maturity Models for each TAM Motivation Area Breaking down maturity in three areas - Information Integration, Analysis, Communication • At-a-Glance Assessment Matrix Simple chart to record maturity in five motivations, across three areas • GIS Foundation Assessment Checklist Agency-Level GIS Function Geospatial Data and Standards Tools and Technologies GIS Expertise, Training, and User Support • Various Implementation Approaches (Comprehensive, Pilot, Incremental, Targeted - Internal, Targeted - External) Information and Data System Challenges and Opportunities Benefits and Return-on-Investment in GIS Implementations • Data Collection Efficiency Staff time savings, reduced risk from field time • Maintenance and Project Management Efficiency Streamlined, integrated business process Optimized deployment of staff and equipment Lower likelihood of overruns due to improved access to information • Identifying Needs and Work Candidates

Detailed Literature Review III-153 • Decision-Support Efficiency Automation of data integration, mapping, and analysis tasks Reduced need for on-site review time • Project and Program Development Effectiveness Improved understanding of multiple complex factors Improve project scoping Ability to package work efficiently • Improved Program Development Improved ability to analyze implications of program changes • Risk Avoidance Reduced failure risks for critical assets (possibly lower insurance costs) • Disaster Recovery Greater likelihood of full FEMA reimbursement based on availability/accuracy of asset inventory records • Accountability and Credibility Enhanced reputation and level of public trust gained through information sharing Barriers and Success Factors • Sustained Executive Support Critical for major investments and multi-year initiatives to fill gaps in foundational GIS tools • Business Unit Management Engagement Business managers must recognize opportunities for GIS and serve as champions • GIS Expertise and Tools Asset management staff must have access to GIS tools, expertise in use of tools, access to the data they need to use the tools • Accurate Foundational Geospatial Data Accurate base map with road centerlines and jurisdiction boundaries Centrally managed LRS to provide foundation for data collection, storage, analysis, and display • Data Sets that can be Geospatially Integrated and Shared Consistent location referencing Standards for accuracy and precision • Management System Integration with GIS Processes to integrate spatially referenced information across various systems • Coordinated Approaches to Field Data Collection Coordinated, consistent approach across multiple business units Implementation • Overall Strategy Recommendations (by strength of GIS Foundation) • Implementation Steps for using GIS for TAM in Each Motivation Area Understanding State of Assets Assess and Manage Risk • GIS TAM Initiatives and Support Elements List Organized by Motivations and Maturity Levels

III-154 Guidebook for Data and Information Systems for Transportation Asset Management • Template for Business Case for GIS/TAM • Summary of Value Added by GIS TAM Capabilities Efficiency (Doing Things Right) and Effectiveness (Doing Right Thing) Presents Challenges, Strategies for Success and Case Studies by • Management and Organization • GIS Tools and Expertise • Data Stewardship • Foundational Geospatial Data • Data Standards Enabling Spatial Integration • Management Systems Linked with GIS Examples or Case Studies • Iowa DOT Pilot: Pavement Performance Demonstrate value of GIS for understanding pavement deterioration and maximizing ROI from non-destructive testing • Colorado DOT Pilot: Risk-Based TAM Program Demonstrate role of GIS for risk-based TAM Life-cycle forecasting Temporal Analysis and Budget/Scenario Planning Interactive Reporting • West Virginia Pilot: Multi-Agency ERP Integration across multiple business processes (maintenance, fleet, traffic, and safety) New LRS Straight Line Diagramming with integrated mapping and video log Performance measure dashboards Field Data Collection Work Order Management LRS and TAM Integration • GIS in Maryland: Power of Leadership • Ohio DOT: Benefits from Common Spatial Referencing • West Virginia DOT: Integrating Leveraging ERP Implementation for Advances in Asset Management and GIS • Washington State DOT: Strong GIS Foundation for Decision Support • Utah DOT: GIS as a Transformative Technology for Asset Management • MDSHA: Enterprise GIS for Better Decision-making and Communication • Illinois DOT: Building GIS Foundation with an Outsourced Approach • Applications Catalog • Data Collection Standards and Geospatial Data Policies NC, KTC, NYSDOT, ODOT, WVDOT, MD Emerging Technology or Techniques • N/A

Detailed Literature Review III-155 NCHRP Report 920: Management and Use of Data for Transportation Performance Management: Guide for Practitioners (NCHRP Project 08-108, “Developing National Performance Management Data Strategies to Address Data Gaps, Standards, and Quality”) Year of Publication: 2019 Links: • Project: http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4184 • Contractor’s Final Report: http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_920NPM.pdf • Published Guidebook: http://www.trb.org/Main/Blurbs/179095.aspx Overview • Prepare guidance to improve data utilization in DOTs’ transportation performance management (TPM). The guidance will include an examination of leading practices, contributing factors, strategies for overcoming shortcomings. TAM Motivations • Improving data utilization Information Management and Integration Practices • Data Specification Definition Obtaining Storage Management Analysis Use Organizational and Institutional Practices • Data Presentation Communication Sharing Management Information and Data System Challenges and Opportunities • Technical challenges Producing data and information suitable for use within TPM Availability Accuracy

III-156 Guidebook for Data and Information Systems for Transportation Asset Management Gaps in data Difficulty integrating data from disparate sources Difficulty aggregating data across districts Lack of/aging technology infrastructure Sharing data across districts Data storage and purging practices Lack of skills and expertise • Cultural and Institutional Challenges Limited resources focused on meeting external reporting mandates Tendency to make do with what is available rather than seeking better data Lack of integration between agency TPM and broader agency management and governance activities Leadership not prioritizing data improvement Decentralized decision-making about data system development Lack of collaboration across business units Lack of trust in externally collected data Discomfort in outsourcing data functions historically managed internally Unwillingness to share data when it may not be 100% accurate Overly restrictive data use agreements with public and private partners Difficulty attracting and retaining staff with relevant skills Inability to keep up with data improvements Examples or Case Studies • Asset Management Data Collection for Supporting Decision Processes (2006) Link: http://www.fhwa.dot.gov/asset/dataintegration/if08018/assetmgmt_web.pdf • NCHRP Project 20-24(37)D, “Recommendations for Improving the use of Traffic Incident Management Performance Measures when Comparing Operations Performance Between State DOTs” Link: http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP20-24(37)D_FR.pdf • Traffic Monitoring Guide (2013) Link: http://fhwa.dot.gov/policyinformation/tmguide/tmg_2013 • Benefit-Cost Analysis of Investing in Data Systems and Processes for Data-Driven Safety Programs (2012) Link: http://safety.fhwa.dot.gov/rsdp/downloads/bcareport.pdf Emerging Technology or Techniques • 3D laser scanning • LiDAR • Unmanned aerial vehicles • Traffic sensors • Video • Crowdfunding

Detailed Literature Review III-157 FHWA TPM Implementation Guidebook (the Transportation Performance Management Technical Assistance Program Guidebook) Year of Publication: 2018 Link: https://www.tpmtools.org/guidebook/ Overview A guidebook designed to help in the implementation of Transportation Performance Management by using information from past performance levels and forecasted conditions to guide investments, measuring progress toward strategic goals, and making adjustments to improve performance. TPM is grounded in sound data management, usability and analysis as well as effective communication and collaboration with both internal and external stakeholders. The key, however, to successful implementation of TPM practices lies in the organizational support and agency embrace of data-driven decision-making. TAM Motivations • Unified Focus for Agency • Prioritization of Investments Based on Performance Needs • Feedback between Decisions and Results • Connect Individuals to Agency Goals • Transparency • Linking Funding and Performance • Communication of Benefits of Investments • Fulfillment of Legislative Requirements • Improved Performance • Using System Information to Make Investment and Policy Decisions to Achieve Performance Goals • Fulfillment of Legislative Requirements Information Management and Integration Practices • Target-Setting - use data to collaboratively establish level of performance • Performance-Based Planning - plan documents become the blueprint to achieve outcomes • Performance-Based Programming - guide resource allocation to achieve targets • Monitor and Adjust - track and evaluate actions to improve performance • Reporting and Communication Organizational and Institutional Practices • TPM Capability Maturity Model • TPM Maturity Assessment • Organization and Culture - institutionalization of TPM • External Collaboration and Coordination - leverage partners resources • Data Management - coordination of data activities • Data Usability and Analysis - organization of data for use

III-158 Guidebook for Data and Information Systems for Transportation Asset Management Information and Data System Challenges and Opportunities • All of the above organizational practices Examples or Case Studies • Link: https://www.tpmtools.org/wp-content/uploads/2016/09/guidebook-final-appendix-b.pdf • Link: https://fhwaapps.fhwa.dot.gov/planworks/Reference/CaseStudy/Show/23 Emerging Technology or Techniques • N/A

Detailed Literature Review III-159 NCHRP Report 666: Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies: Volume I: Research Report, and Volume II: Guide for Target-Setting and Data Management Year of Publication: 2010 Links: http://www.trb.org/Publications/Blurbs/164178.aspx Overview The study was designed to help DOTs develop and improve performance management practices through pursuing the following objectives: • To provide an overall description of Performance-Based Resource Allocation (PBRA) • To provide a comprehensive description of the process and methods by which targets are set for use in PBRA • To provide a comprehensive description of the data, information systems, and institutional arrangements needed to support PBRA decision-making. TAM Motivations • Link organization goals and objectives to resources and results Information Management and Integration Practices • Systems - ERPs, data warehouses, data marts and ETL tools • Analysis - Program specific data analysis • Quality - Regular quality evaluation and documented data standards • Reporting - Accessible formats with integrated GIS, public dashboards, BI tools Organizational and Institutional Practices • Data management model matrix Tech/Tools People/Awareness Institutional/Governance • Data governance/Stewardship Charter a data governance board Establish data stewards and data work groups Document a data business plan • Knowledge Management systems • Data management Planning Goals Assessment Governance Linking to Business, Target-Setting

III-160 Guidebook for Data and Information Systems for Transportation Asset Management Information and Data System Challenges and Opportunities Challenges • Political influence • Customer and stakeholder perspective • Agency experience • Communication and reporting • Financial resources • Timeframe Opportunities • Use external data sources, such as environmental, historic, and other planning agencies for GIS data layers Examples or Case Studies • NCHRP Web-Only Document 154: Target-Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies – Volume III: Case Studies Link: http://www.trb.org/Publications/Blurbs/164179.aspx Emerging Technology or Techniques • N/A

Detailed Literature Review III-161 NCHRP Report 706: Uses of Risk Management and Data Management to Support Target-Setting for Performance-Based Resource Allocation by Transportation Agencies Year of Publication: 2011 Link: http://www.trb.org/Publications/Blurbs/166250.aspx Overview Describes how risk management and data management may be used by transportation agencies to support management target-setting for performance-based resource allocation. Specifically, this report intends to: 1. Describe a framework and set of methods to analyze/improve multi-objective performance of transportation systems and set specific targets to guide agencies 2. Detail factors influencing target-setting and the success of performance-based allocation systems, and explain how to successfully design and implement the systems 3. Analyze data and information needs, data acquisition and management systems, and institutional relationships to support success Case studies and other illustrating examples are provided. TAM Motivations • Using performance-based resource allocation • Risk management • Data management Information Management and Integration Practices • Performance-Based Resource Allocation (PBRA) • Data Sharing and Access Data Collection Right data for right use at appropriate detail Integration of real time and traditional data Collection and integration of state and local data Outsourcing data collection Data Storing Costs associated with archiving and large data files In-house vs. external storage Data Processing Replacing manual with automated processes Conversion of legacy data and information systems Data Analysis Automated analysis tools and procedures Documenting data accuracy, timeliness, completeness, validity, coverage, accessibility, currency

III-162 Guidebook for Data and Information Systems for Transportation Asset Management Data Reporting Documenting reporting frequency Appropriateness of tools (spreadsheet-based tools, web links, presentations, dashboards) Data Dissemination Define timely dissemination Appropriateness of tools Data Sharing Data sharing standards and cooperative agreements Integration of publicly produced vs. privately purchased data Data Access Data Security and Privacy Organizational and Institutional Practices • Performance Management Framework Establish goals and objectives Select performance measures Identify targets Allocate resources Measure and record results • Risk Management Establish Risk Tolerance Identify Threats/Hazards Assess Impacts or Consequences Identify Mitigation Strategies/Countermeasures Prioritize Strategies and Develop Plan Measure and Monitor Effectiveness • Data Sharing and Access Governance Data Business Plans Data Maturity Modeling Information and Data System Challenges and Opportunities • Benefits, Challenges, Solutions (Examples for the following Data Sharing and Integration Issues) Collection Archiving and Storage Processing Analysis Reporting Dissemination Sharing Access

Detailed Literature Review III-163 Institutional Governance Data Business Plans Maturity Models Risk Management Business Intelligence Knowledge Management XML for Sharing and Storage Wireless Technology Automatic Vehicle Location GPS CCTV Non-Intrusive Technology for Traffic Data Examples or Case Studies • GDOT Pavement and Bridge Preservation Risk Assessment o Move away from “worst first” and toward “most at risk” • TxDOT’s Statewide Freight Resiliency Plan o Key infrastructure corridors and strategies to ensure a resilient freight network • Mn/DOT’s Bridge Programming Risk Assessment o Communication tool to help explain factors in programing bridge projects • Washington State’s Bridge Retrofit Risk Assessment o Identify network of lifeline routes that are critical during major disasters • Caltrans’ Bridge Seismic Safety Retrofit Program o Prioritization process for bringing bridges to current seismic safety standards • Georgia DOT Pavement and Bridge Preservation Risk Assessment • Minnesota DOT Bridge Programming Risk Assessment • Texas DOT Statewide Freight Resiliency Plan • Washington State DOT Enterprise Risk Management Office • MinnDOT Risk Management Program • California DOT Seismic Safety Retrofit Program Emerging Technology or Techniques • BI Tools (dashboards, score cards) • Knowledge Management Systems • XML for Sharing and Storage • Wireless Technology • Automatic Vehicle Location • GPS • CCTV • Non-Intrusive Technology for Traffic Data (infrared, magnetic, radar, microwave, ultrasonic, passive, video) • Dynamic routing

III-164 Guidebook for Data and Information Systems for Transportation Asset Management NCHRP Report 806: Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Year of Publication: 2015 Link: http://www.trb.org/Publications/Blurbs/172356.aspx Overview The project aimed to provide guidance to DOTs on how to better analyze and communicate the likely impacts of system performance across multiple investment types to make better performance targets. In order to help agencies decide investment priorities, the paper provided an analytical data-driven performance-based framework and tool prototype for cross-asset resource allocation. Helps managers consider: 1. Multiple dimensions of system performance important to stakeholders 2. Multiple measures to describe condition and level of service (across various assets) 3. Targets that may be set for various dimensions of performance TAM Motivations • Align investment decisions with performance targets • Maximize impact • Achieve goals and performance targets across multiple assets Information Management and Integration Practices • Predictive models - forecast likely project impacts on system performance • Decision science - score projects and optimize their selection for programming based on benefits, costs, and relative importance • Trade-off analysis - compare priorities with fiscal constraints Organizational and Institutional Practices • Resource Allocation Approach Maturity Model Legacy-Driven, Fix It First, Soft Optimization, Performance-Based • Resource Allocation Self-Assessment Questions, Issues, and Considerations Intended Application Time Horizon Strategic Frameworks Program Structure Performance Targets Candidate Projects Stakeholder Roles Clear Institutional Constraints Resource Allocation Parameters • Goals and objectives that serve as an expression of agency priorities and vision • Performance measures that demonstrate progress toward agency goals and objectives

Detailed Literature Review III-165 Information and Data System Challenges and Opportunities • Institutional Barriers Weak Strategic Direction Tools and Data - particularly for Performance Forecasting Institutional Constraints Organizational Considerations Public/Stakeholder Issues Political Resistance Siloed mentality • Technical Challenges Setting a planning horizon Identifying “Must-Do” projects Providing the ability to analyze user-specified performance measures (including qualitative metrics) Identifying performance measures by functional class Handling alternative funding structures Integrating data from existing management systems Allowing geographic constraints Clear reporting • Opportunities Linking planning and programming process to ensure optimal allocation of limited resources Satisfying performance-based planning requirements Assisting in developing TAMPs Directly linking planning and project prioritization and programming Examples or Case Studies • General Example Applications or Use Cases: Overarching project prioritization Program level analysis Project level analysis Performance analysis and target-setting Scenario analysis Establishing relative priorities Risk analysis • Examples: Legacy-Driven: Louisiana, Kansas, Mississippi Fix It First: Georgia, Colorado, Virginia, South Carolina Soft Optimization: Arizona, Ohio, North Carolina, Michigan Performance-Based: Washington, Utah, Virginia, Florida, Oregon • Case studies: New Jersey, North Carolina, South Carolina, Utah, and Virginia Emerging Technology or Techniques • Cross-Asset Resource Allocation

III-166 Guidebook for Data and Information Systems for Transportation Asset Management Advances in Civil Integrated Management (Final Scan Team Report) (NCHRP Project 20-68A, Scan 13-02, “Advances in Civil Integrated Management,” Final Scan Team Report) Year of Publication: 2015 Link: http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP20-68A_13-02.pdf Overview The purpose of this publication is to examine projects that utilize CIM technologies and partnering efforts between state DOTs, consultants, contractors, and materials suppliers. Agencies will benefit from this by gaining knowledge of the use of CIM practices and tools in highway construction projects utilizing emerging intelligent construction technologies and partnering for the fast, efficient, and safe delivery of projects. The document provides: • Identified proven intelligent construction technologies • Construction project performance measures being used • Successful partnering techniques, including virtual meetings, wireless data sharing, and paperless communication, as applicable TAM Motivations • This publication was focused mainly on the emerging technologies being implemented at state DOTs currently. There was little current uptake in life-cycle asset management and construct-to-maintenance. The motivations for the study were to understand current best practice, and these were focused primarily on design and construction. Information Management and Integration Practices • Document highlighted the integration of digital information into public information activities. New forms of digital content creation allow us to connect the public to ongoing designs and construction activities • Common data, information and knowledge pools • Process of transforming “data to information and information to knowledge” • Data transfer protocols/standards • Long-term data storage standards • Alternative contracting and partnering practices Organizational and Institutional Practices • Culture of open communication should be promoted • Organizational focus on innovation and data standards to be embraced by upper management • Personnel training and upskilling plans should be implemented

Detailed Literature Review III-167 Information and Data System Challenges and Opportunities • Developing agency standards with regards to data types and formats • Ensuring data accessibility is managed through project via authorization level assignments • Developing agency standards with regards to data governance and environments • Overcoming legal hurdles surrounding digital document suitability certification (signing) Examples or Case Studies • Publication is based on survey and visits to: Iowa DOT – Statewide 3D model implementation Michigan DOT – 3D models and EDMS for Construction Admin New York State DOT – 3D Models and EDMS Texas DOT – Use of CIM in large Design Build projects Utah DOT – CIM bulk imported into GIS database Virginia DOT – use of CIM in large PPP projects Wisconsin DOT – Use of CIM with emphasis on 3D models Emerging Technology or Techniques • Geographic Information Systems (GIS) integrations into design data and data collection Data accessibility is large when standards and cloud storage used UDOT’s UPLAN: The development of a spatial database that located threatened plants so that construction avoid them and UDOT could coordinate easily with stakeholders outside the agency to make decisions regarding the extent of protection The efficient location of utilities so coordination could be accomplished early in the design and construction of projects Tools to manage renewal of leases for materials pits Tools to manage right-of-way, including right-of-way documented on legacy plan sets, and right-of-way markers and section corners • Global Positioning Systems (GPS) integrations into data collection and construction equipment GPS creates survey improvements GPS is fundamental technology behind intelligent construction systems (AMG) • 3D Engineered Models that include spatial relationships among various design elements both during design and during survey through the use of LiDAR Models allow for attachment of metadata Models allow for clash detection Models allow for 4D and 5D simulations Models allow for rendering and public engagement Models allow for enhanced quantity takeoff procedures • 4D/5D Models for enhancing 3D information with cost and schedule simulations Connection of models to scheduling software (P6) Connection of models to estimation software

III-168 Guidebook for Data and Information Systems for Transportation Asset Management • Light Detection and Ranging (LiDAR) to capture accurate spatial data in three dimensions during survey Simple creation of digital terrain models Existing asset documentation and surveying data collection Large data collection done quickly • Automated Machine Guidance (AMG) using 3D models to guide machines during construction (rather than field stakes and human operation) Enhanced productivity/speed and accuracy in construction • Mobile Devices to capture, log and reference project information in real time Almost all reference documents and project plans and specifications that used to be carried as hard copy in vehicles are now digitized and available to mobile users Wireless data is transferred using cell phone signals; thus, mobile email and web browsing are supported Still and video cameras are used to document construction progress and issues All construction reports are processed on mobile devices. Users have full access to the electronic document management system Video conferencing is supported, allowing field personnel a wide range of office support Electronic signatures are supported so that approvals can be made if personnel are in the field • Intelligent Compaction systems that integrate real-time measurement of location and compaction data into the construction compaction equipment Increased productivity and quality in construction • Electronic Document Management Systems Better collaboration and increased productivity Increased quality gains • Digital Signatures to enable complete digital delivery of projects Enables the transfer of electronic documents in a completely paperless way

Detailed Literature Review III-169 NCHRP Report 831: Civil Integrated Management (CIM) for Departments of Transportation, Volume 1: Guidebook, and Volume 2: Research Report Year of Publication: 2016 Links: • Volume 1: http://www.trb.org/Main/Blurbs/174318.aspx • Volume 2: http://www.trb.org/Main/Blurbs/174321.aspx Overview The research objectives were to assess the current state of CIM practices, document the observed trends across the agencies (benefits, costs, opportunities, risks), and develop a guidebook that can be used by DOTs to enhance their level of CIM. TAM Motivations • Document focuses on the benefits of CIM for project delivery (time, cost, savings) • Costs and Benefits of BIM (Business Case) • Technical Issues: Contracts, System, Resources, and Maintenance • Operations Issues: Moving to Facility Life-Cycle Management Information Management and Integration Practices • Deliverables are data and model centric • All information is digitally signed and georeferenced • Common Data Environments utilized for single source of truth • All disciplines follow same industry data standards Organizational and Institutional Practices • Adoption of required standards and governance • Implement training and upskilling programs • Engaging O&M during early project phases • Alternate contracting methods to integrate design through construction and beyond Information and Data System Challenges and Opportunities • Lack of organizational readiness to change • Lack of expertise • Greater system complexity • Lack of system interoperability • Lack of industry standards

III-170 Guidebook for Data and Information Systems for Transportation Asset Management Examples or Case Studies • Rotary upgrade to modern roundabout (CTDOT) • Relocation of KY7 in Elliott County (KYTC) • Fore River bridge replacement project (MassDOT) • Kiewit case study on I-70 project (CDOT) • Parksville Bypass bridge project (NYSDOT) • I-96 Livonia construction project (MDOT) • Crossrail Ltd. (UK) • WisDOT’s SE Freeway project • TxDOT’s Dallas-Fort Worth Connector Project • AASHTO’s UPlan • Michigan DOT’s “e-construction” initiative. Emerging Technology or Techniques • GIS-Based Asset Information Management • FDOT’s PEDDS (Professional Electronic Data Delivery System) • WisDOT’s Project Modeling Matrix for LOD documentation • Automated Machine Guidance • Digital point cloud – Mobile LiDAR

Detailed Literature Review III-171 Guide to Asset Management Processes Part 9: Asset Information Management Systems and Data Year of Publication: 2018 Link: https://austroads.com.au/publications/asset-management/agam09 Overview This guide was developed to support road agencies with the selection and implementation of an appropriate asset management information system (AMIS) for their organization. The guide is based on ISO 55000 and therefore retains a strong customer and strategic focus. The guide is part of a larger 15-part series that covers management overview, asset management processes, and technical information. TAM Motivations • N/A Information Management and Integration Practices • Selection of an appropriate AMIS needs to extend beyond software requirements and features to include vendor’s functional delivery ability, agency’s knowledge base, and training • AMIS Requirements Enterprise capability Role-based customization Data storage functionality Customizable workflow Scalability Asset definition Asset hierarchy/relationships • Once common, in-house or tailor-made systems are now unable to keep up with changing technology, and most agencies are ill equipped to maintain complex enterprise software, so commercial systems are slowly but surely replacing custom systems • Avoid over-specifying requirements to provide flexibility to combine the best of software offerings as increasing industry trends toward interoperability mean that everything doesn’t need to come in one piece of software • The importance of recognizing difference between data and information is a key aspect of successfully implementing AMIS (reference Section 4.4.1 of IPWEA [2015]) • AMIS process and procedures must address different users, levels of interaction and range of skills/capabilities • Pavement Management System (PMS) common functional elements: Asset inventory Asset condition Condition and performance prediction Treatment selection Budget allocation Works management and finalization

III-172 Guidebook for Data and Information Systems for Transportation Asset Management • Clear understanding of the range and scope of assets to be managed has direct impact on system choice • An asset register should be able to address cross-department reporting functions as well as integration with other corporate systems • Ensuring end users are part of any data transfer process is key for validation with setting up and configuring an AMIS • Field trials are critical to the successful implementation of an AMIS to ensure no additional errors are introduced Organizational and Institutional Practices • Involve all key staff that will be engaged with installing and using the AMIS from the beginning of the selection process • Ensure well-documented data management procedures and standards to address staff mobility • Plan for substantial organizational resources to be committed to operating the AMIS • A change-management plan is critical to support the implementation of an AMIS • Ensure that an experienced project manager with a track record of similar work is assigned to oversee the AMIS implementation • Complete an assessment of the project team’s capability and team dynamics prior to implementation to ensure the right composition and balance Information and Data System Challenges and Opportunities • Challenge – Lack of adequate planning and definition of high level business needs decreases optimal AMIS benefits for both organization and staff • Challenge – Justifying the cost and long-term benefits of implementing an AMIS is usually the largest barrier • Opportunity – Benefits of a partnered approach (agency and supplier) are highest on larger AMIS projects where collaboration can help fast-track delivery and address delivery barriers proactively Examples or Case Studies • Asset Management Systems Review Report (www.arrb.com.au/amsr) – Profiles the systems used across the country in each state • Categorization of anticipated resources associated with an AMIS implementation (Page 15, Table 2.1) – Lists the category and items involved in AMIS implementation with high level description of duties • Defined areas of resistance and outcomes if unmanaged (Page 18, Table 3.1) – Lists areas of resistance and outcomes underscoring criticality of change-management program • Referenced Case Study 4.19 in IPWEA (2015) provides example of supplier solution assessment with different functional requirements and relative weightings to determine an overall score Emerging Technology or Techniques • Advancements in computing power and hardware provision have made previously unattainable functions or features accessible to more customers • The spread of cloud-based solutions and increasing internet speeds continue to remove barriers to accessing higher end hardware

Detailed Literature Review III-173 Guide to Asset Management Processes Part 10: Asset Management Implementation and Improvement Year of Publication: 2018 Link: https://austroads.com.au/publications/asset-management/agam10 Overview This guide was developed to support road agencies with defining roles and responsibilities; developing asset management plans; delivering asset management activities; providing guidance and techniques for asset management status assessment; and continuous improvement planning and monitoring for all activities. The guide is part of a larger 15-part series that covers management overview, asset management processes, and technical information. TAM Motivations • N/A Information Management and Integration Practices • The network information function should be a clearly identified role in the asset management team Organizational and Institutional Practices • Asset management should be seen as agency-wide process of continuous improvement and not as activities undertaken by a small set of specialists • Five key areas of asset management implementation Roles and responsibilities SAMPs and AMPs Delivering asset management activities Asset management status assessment Continuous improvement • Managing assets requires a team effort which often does not involve adding new functions but coordination and integration of existing functions • Key organizational roles include: Asset ownership Managing the asset Service provision • Centralized and decentralized asset management functions’ advantages and disadvantages are analyzed and presented • The individual responsible for driving asset management in the organization should be prominently identified and not buried in the organizational structure • Regardless of size, an agency can benefit from a cross-organizational asset management approach

III-174 Guidebook for Data and Information Systems for Transportation Asset Management • Job descriptions should cover asset management competencies that cover technical, process and interpersonal skills • Commitment should be driven from the top with communication of organizational value and benefits • SAMPs should always link higher level goals and objectives for the more detailed AMPs • Per ISO 55001:2014, SAMPs should include: Asset management objectives Have asset management objectives aligned with organizational objectives Scope of asset management system aligned with SAMP and AMP Document how the asset management system will support delivery of the SAMP • Key road agency asset management maturity models include: IAM Self-Assessment Methodology Plus Gap analysis processes and tools based on IIMM (IPWEA 2015) from New Zealand AASHTO Transportation Asset Management: Volume 1 (TAM 1) focused on high level self- assessment, and Transportation Asset Management: Volume 2 (TAM 2) focused on more detailed gap analysis process (both AASHTO 2011) • Gaps, once identified, should be prioritized (mandatory, quick wins, medium- to long-term) • An improvement plan should include: Activity and area where improvement is required Reference to AMP Action name and priority Status and comments Date action identified and target end date Person responsible Measure of effectiveness identified Management and monitoring process • Asset management systems should take consideration of other systems which may require integration Quality (ISO 9001:2015) Environmental (ISO 14001:2015) Health and safety (IAS/NZS 4801:2001) Risk management (ISO 31000:2009) Information and Data System Challenges and Opportunities • Challenge/Opportunity – Staff turnover generates capability gaps which should be proactively addressed through succession planning • Challenge – Considering the variation of methods and tools for gap and maturity assessment, care should be taken before subjecting any agency to benchmarking to ensure like comparisons Examples or Case Studies • Sections 4.1, 4.2, 4.5 and 4.6 of the Institute of Public Works Engineering Australasia Infrastructure Management Manual (IIMM) (IPWEA 2015) provides examples of how asset management can be implemented satisfactorily

Detailed Literature Review III-175 • Table 2.3, Page 12 provides an example of a competency matrix that highlights skill areas with target and current ratings to reveal skill gaps • Case Study of New Zealand Transport Agency presented on Page 13 provides an example of a capability assessment and use of leading and lagging indicators to illustrate overall agency capability • Case Study of Department of Planning Transport and Infrastructure South Australia presented on Page 18 provides an example of SAMP and AMP alignment • Case Study of NZTA on Page 22 provides an example of how asset management practices and requirements are transferred into procurement strategies • Section 5.1, Pages 24-30, provide examples of application of various gap and maturity assessment methods and tools with illustration • Case Study of Queensland Department of Transport and Main Roads presented on Pages 33-34 provides an example of gap analysis and improvement plan with illustration of results • Case Study of benchmarking asset management maturity in the water market is presented on Page 36 • Case Study of DPTI from 2016 presented on Pages 40-41 provides an example of a prioritized improvement plan • An example asset management capability improvement approach is presented in Section 7 Emerging Technology or Techniques • N/A

III-176 Guidebook for Data and Information Systems for Transportation Asset Management Harmonization of Location Referencing for Related Data Collection Year of Publication: 2011 Link: https://austroads.com.au/publications/asset-management/ap-t190-11 Overview This report presents and reviews common linear and spatial location referencing systems used by road authorities in Australia and discusses the various benefits and limitations of each. The report examines the challenges resulting from the inconsistencies both in terms of data exchange, accuracy and maintenance. Highlighted in the report are methods and systems of several Australian road agencies and the fact that adoption of any new methods or systems would have to be in parallel to current systems to avoid business disruption. The report also highlights efficiencies that could be gained from adoption of common methods and systems as well as notes emerging technologies at the time of the report and new advancements that might make the shift to common systems easier for the road agencies. TAM Motivations • Promote improved transport outcomes and consistency in road agency operations • Adopt common methods and systems to generate operational and supply chain efficiencies • Linear referencing systems support business operations and corporate reporting Information Management and Integration Practices • Focus on creation of a common location referencing method for data collection at traffic speeds with understanding that any method could be then adapted for slower and stationary collection • Spatial referencing systems were recognized as holding the best potential for a universal method of data collection • Technical understanding and careful use of GPS tools is required to ensure positional accuracy • Drive toward common methods should provide a means for agencies to maintain legacy referencing systems while enabling them to adopt new methods. Spatial referencing can serve as the means to address this if approaches are used to integrate data with legacy linear referencing systems via post- processing routines Organizational and Institutional Practices • N/A Information and Data System Challenges and Opportunities • Challenge – Lack of consistent linear referencing systems across authorities creates significant challenges in trying to transfer or consolidate data for national applications

Detailed Literature Review III-177 • Challenge – Inconsistent linear referencing systems add time and cost to service providers when conducting data collection and post-processing efforts as they must continuously adapt to different standards • Opportunity – Harmonization of linear referencing methods and systems would allow for comparison of network data over time • Common linear referencing approaches use kilometer posts or reference posts, whereas aid drivers and field personnel are costly to maintain, not unique, and are subject to degrees of inaccuracy due to limitations for precise installation and/or movement from road works or other alterations • Challenge – The practice of “rubber banding” to force data collection to fit a linear referencing system results in inaccuracies and inability to track changes over time • Opportunity – Use of GPS significantly decreases the level of location variation and is a more objective, repeatable technology often with built-in tool or software features that correct • Challenge – Large investments have been made by road agencies in certain methods or technologies and moving toward a common, standardized approach can be costly and have reputational damage with respect to perception of wasted funds • Challenge – Adoption of new methods and systems must acknowledge supply chain resource limitations and constraints Examples or Case Studies • Department of Infrastructure, Energy and Resources (DIER), Tasmania – Use of GPS technology to survey and provide digital road centerline to absolute accuracy of within 10 m Emerging Technology or Techniques • GPS technology continues to advance and it is assumed that any non-spatial linear referencing will become redundant in the near future

III-178 Guidebook for Data and Information Systems for Transportation Asset Management ACRP Synthesis 70: Building Information Modeling for Airports Year of Publication: 2016 Link: http://www.trb.org/main/blurbs/174386.aspx Overview Document sets out “state of the art and practice” in BIM applications and implementations and then provides a snapshot of existing airport implementations based on airport and consultant survey. TAM Motivations • Results noted airports using BIM for planning and design heavily, Construction moderately, and O&M rarely – report motivated by desire to shift from project level BIM to organizational use (beyond design and construction and into O&M) • Costs and Benefits of BIM (Business Case) • BIM Purpose, Processes, and Tools • BIM Adoption and Implementation • Technical Issues: Contracts, System, Resources, and Maintenance • Facility Life-Cycle Management Information Management and Integration Practices • Requirements for BIM Execution Plan at planning/design stage should be created • Use of Omniclass data assignments to model information • Model to be formatted by COBie standards and commissioning to utilize this • LOD to be agreed and object metadata requirements to be determined • BIM Model to include cost and schedule metadata Organizational and Institutional Practices • Report focuses on shift from project level BIM usage to organization-level implementation (shifting from design to O&M) • Adoption of a required CAD/BIM Standard by organization (see info management practices) • Adopt a BIM Optimization for Facilities Management workflow (use for strategic planning, GIS, Retrofits, etc.) • Adopt an Enterprise Asset Management system to track assets and enable integrated workplace management facility decisions (e.g., Building automations, inventories, energy efficiencies, maintenance schedules) to be made based on digital asset models Information and Data System Challenges and Opportunities • Lack of organizational readiness to change • Lack of expertise • Greater system complexity

Detailed Literature Review III-179 • Lack of system interoperability • Lack of industry standards Examples or Case Studies • McCuen & Pittenger 2015 Survey of airports and consultants Denver International Airport: Realizing Benefits of Full BIM Implementation San Francisco Airport Commission: Undertaking a New Full BIM Implementation Los Angeles World Airports: Realizing Benefits of Project-Level BIM Ted Stevens Anchorage International Airport: Realizing Benefits of Organization-Level BIM Massachusetts Port Authority: Road mapping BIM Implementation Iron Horse Architects: BIM for Airports—A Designer’s Perspective Balfour Beatty Construction: BIM for Airports—A Contractor’s Perspective • BIM usage at Frankfurt Airport - Shoolestani et al. 2015 • BIM usage at Heathrow – buildingSMART UK 2010 • BIM usage at Gatwick – Neath et al. 2014 • BIM usage at Denver International – Ball 2015 • Facilities Management and Geographic Information Systems capabilities - FAA 2015b Emerging Technology or Techniques • COBie, IFC, OmniClass integrations to Maximo Asset Mgmt Software • Solibri Software for model checking • Building Automation Systems integrations • Integrated Work Management System integrations

III-180 Guidebook for Data and Information Systems for Transportation Asset Management “BIM for Airports: ACRP – A Synthesis of Airport Practice” (PowerPoint Presentation) Year of Publication: 2015 Link: http://onlinepubs.trb.org/Onlinepubs/acrp/acrp_syn_070.pptx Overview A presentation file presenting the results of a national survey of 10 airports and 4 AEC firms on the use of BIM, the maturity of the usage, and benefits realized from the use: • Current state of the art/practice in BIM • “Snapshot of existing experience” with BIM in North American Airports • Available opportunities, benefits and value TAM Motivations • Improved visualization • Better cost control • Collaboration among project team using a single source of information • Increased O&M efficiency • Enhanced asset (facilities) management Information Management and Integration Practices • N/A Organizational and Institutional Practices • N/A Information and Data System Challenges and Opportunities • Results noted airports using BIM for planning and design heavily, construction moderately, and O&M rarely • BIM benefits realized long term • Important to quantify benefits • No full integration of BIM yet • No full-facility-life-cycle benefits • Shift from project level to organization level • Custom implementation strategy Examples or Case Studies • McCuen, T. L., and D. M. Pittenger (2016). ACRP Synthesis 70: Building Information Modeling for Airports. Transportation Research Board, Washington, D.C. Available at: http://www.trb.org/ main/blurbs/174386.aspx. Emerging Technology or Techniques • Report noted importance of realizing BIM is not 3D modeling, but instead the integration of data into life-cycle

Detailed Literature Review III-181 BS8536 Brie�ing for Design and Construction – Part 1: Code of Practice for Facilities Management (Buildings Infrastructure) Year of Publication: 2015 Link: https://shop.bsigroup.com/ProductDetail/?pid=000000000030315621 (note: requires purchase) Overview BS8536 Part 1 focuses on briefing for design and construction to ensure that the design takes account of the expected performance of the asset/facility in use over its planned operational life. The document focuses on aspects of design, construction, testing and commissioning, and handover and start-up of operations that are concerned with achieving the required operational performance of a new or refurbished asset/facility. These include, but are not limited to: • Overall concept • Context • Uses • Access • Visual form • Environmental impact • Space • Internal environment • Durability • Adaptability • Usability • Engineering performance The aim is threefold: 1. Improve the focus of the supply chain on performance in use; 2. Extend supply chain involvement to operations and defined periods of aftercare; and 3. Involve the operator, operations team or facility manager, as appropriate, from the outset. BS8536 Parts 1 and 2 were a part of the BIM Level 2 suite of documents as defined by the UK Government’s BIM Task Group – and will continue to be a part of the suite supporting implementation of BIM Level 2 based on the ISO19650 series, the first two parts of which were due for publication early in 2019. TAM Motivations An asset/facility is likely to hold its value or benefit for the owner if it is efficient, trouble-free and represents best value in terms of operation.

III-182 Guidebook for Data and Information Systems for Transportation Asset Management • Evidence-based design and construction can be expected to result in improvements to the project’s outcomes and the achievement of more exacting operational requirements with respect to environmental, social, security and economic performance, including demonstration of the owner’s, operator’s and end users’ satisfaction with the asset/facility in operation. • Performance outcomes should be set at the “Strategy” work stage as the basis for measuring operational performance: (a) Environmental, (b) Social, (c) Security, and (d) Economic. Information Management and Integration Practices The standard sets out the methodology for establishing information management integrated with soft landings, for each stage of a design and construction project, and providing example templates: • Existing performance measurement standards and examples Design – Design Quality Indicator (DQI) A five-stage method for evaluating the design over the project life-cycle against three quality principles: functionality, build quality and impact. User Satisfaction – BUS methodology quantifies occupant satisfaction reveals features of value or concern in the asset/facility provides feedback Operational and environmental performance (existing assets/facilities) – BREEAM In-Use reduce the operational costs improve the environmental performance • Process measurement using key performance indicators (KPIs) to determine effectiveness Design and construction – Design and deliver asset/facility against operational requirements developed based on performance expectations over planned life Commissioning, training and handover – Should be supported by training to meet the needs of the operator, end users and other key stakeholders Asset/facilities management – Efficient, cost-effective strategy that is quantifiable Information and security management – Efficient and effective in terms that are quantifiable Deploying KPIs (suggests use of BS EN 15221-1) measure progress toward achieving objectives or other factors that are critical to success allow the owner to act quickly and decisively upon any deviation in performance • Follow a plan of work – UK digital standard for plan of work recommended is provided Detail approach provided

Detailed Literature Review III-183 Organizational and Institutional Practices • Identifies organizational practices required to enable information management which can comprehensively support soft landings • Soft landings – Assist in getting the best out of their new or refurbished asset/facility • Soft landings provide: A unified approach for addressing outcomes from an integrated process of briefing, design and delivery of the asset/facility Alignment with energy performance criteria, building logbooks, building manuals, green leases and social responsibility Greater involvement of the design and construction team with the operations team (or with the facility manager) during and after completion of construction Improve operational readiness Meet expectations for flawless start-up Support sustained operational performance in use • Soft landings should require information already collected in normal project delivery • Owner would be expected to nominate a soft landings champion Ensure suitability to the project throughout design and construction and into operation • An approach to specification of Organizational, Asset and Project Information Requirements (OIR, AIR, PIR) is described in detail in relation to the recommended Plan of Work Information and Data System Challenges and Opportunities Opportunities and challenges • Use of Building Information Modeling (BIM) in general • Creation and management of a project-specific building information model in particular is set within the wider context of the owner’s information management system – but is rarely done in practice Opportunity • Ensure that there is sufficient information technology in place to support “Level 2 BIM” Common data environment (CDE) to be used Details of information required from the project delivery team to support optimal operational performance of the asset/facility Format and means for information exchange Trend is to shift to method of open standard information exchange (IFC or equivalent) away from proprietary standards (e.g., COBie) Provides a common structure for the exchange of information Ensures that information can be reviewed and validated for compliance, continuity and completeness Establishes the structure and format of the asset information model (AIM) that will receive the content from the project information model (PIM)

III-184 Guidebook for Data and Information Systems for Transportation Asset Management Details the transfer of content from the project information model (PIM into the owner’s asset information model [AIM]) Establishes requirements, policy, processes and procedures for the security of information and data, including the management of access both physically and digitally Identifies software to be used to meet operational and security requirements such as the owner’s defined enterprise system, a computer-aided facilities management (CAFM) system or other means Examples or Case Studies Examples are illustrative of the approach and are likely to vary from project to project. • Checklists are provided as follows: Design and construction brief - typical considerations from a largely design and construction perspective in regard to the work activities involved in briefing Operational brief - typical considerations from a largely operational (i.e., facilities management) perspective • Approaches to be adopted and typical measures to be taken by an owner: Environmental performance evaluation Social (i.e., functionality and effectiveness) performance evaluation Economic (cost) performance evaluation • Responsibility assignment matrices using a RASCI chart • Design responsibility matrix incorporating information exchanges • Risk and opportunity assessment recording the risks and opportunities of an example project A new university hall of residence (500 single-study bedrooms off campus) • “Plain language” questions that might be asked by the design and construction team based on original questions developed by the UK Government Cabinet Office • Stakeholder impact analysis approach using an impact/probability matrix Individual stakeholders and groups of stakeholders are positioned in the matrix according to the level and probability of impact they have on the design and construction of the asset/facility and its subsequent operations Emerging Technology or Techniques • N/A

Detailed Literature Review III-185 BS8536 Brie�ing for Design and Construction – Part 2: Code of Practice for Asset Management (Linear and Geographic Infrastructure) Year of Publication: 2016 Link: https://shop.bsigroup.com/ProductDetail?pid=000000000030333121 Overview The standard observes that while constructability is widely applied in design, operability has not historically been considered to the same extent. The document describes how briefing for design and construction should focus on those aspects of design, construction, testing and commissioning, handover and start-up of operations that are concerned with achieving the required operational performance of a new or upgraded asset. The aim is to: 1. Improve the focus of the supply chain on the performance of the asset in use; 2. Extend supply chain involvement through to operations and defined periods of aftercare; 3. Involve the operator, operations team or asset manager from the outset of the project; and 4. Account for the need to maximize the value of the asset. The standard complements and strengthens briefing practices and procedures by • Promoting the early involvement of the operator, operations team or asset manager • Extending the commitment on the part of the delivery team Aftercare post-handover Safe, secure, efficient and cost-effective operation in line with environmental, social, security and economic performance outcomes and targets BS8536 Part Two assumes use of “BIM Level 2” for projects – adoption of soft landings is not precluded where “BIM Level 2” cannot be achieved in the project. TAM Motivations Operational performance improvements • Energy use and greenhouse gas emissions • Water abstraction and consumption • Waste prevention, reclamation, recycling, treatment and disposal • Noise and vibrations • Asset availability, access, inclusiveness, utilization, safety, security, capability, capacity, resilience, serviceability/maintainability, adaptability, quality, cost, value and comfort

III-186 Guidebook for Data and Information Systems for Transportation Asset Management • Operational considerations in design • Value or benefit increased through trouble-free, efficient and cost-effective operation Evidence-based design and construction • Improve outcomes • Support more exacting operational requirements with respect to environmental, social, security and economic performance • Demonstrate satisfaction with outcomes Asset Value – depends on many factors • Striking the desired balance between cost, risk and performance • Depends on owner and other key stakeholders • Can be tangible or intangible, financial or non-financial, and changes over the life of the asset (see BS ISO 55000) • Benefit and utility are synonymous with value and all three are linked to cost Information Management and Integration Practices Whole-life view of an asset • Need to realize value from entire life; not solely its design and construction or upgrading • Vast amount of information and data is generated and exchanged during asset lifetime • Security-minded approach to the handling of information and data is needed Evidence-based approach to design and construction—decisions based on the best available information from multiple sources • Owner’s business objectives • Current operations • Lessons learned from previous projects • Design modeling and simulation • Performance evaluations • Include the provision of evidence to support proposals and recommendations prepared by the delivery team • Information and data for these purposes should be handled, stored and protected in accordance with the owner’s security requirements Meet operational needs of the owner, operator, end users and other key stakeholders.

Detailed Literature Review III-187 Plan of work—outlines the work stages and digital plan of work, establishing • Level of model detail • Level of model information that needs to be delivered by each originator during each work stage for a specific project and in operation • Progression criteria at decision points (or gates) that include requirements relating to environmental, social, security and economic performance • Iterative nature of some work activities, where the need to reassess assumptions is a normal and necessary feature (e.g., design process is not linear and involves iteration to converge on an acceptable solution) Asset Information Model (AIM) • At each stage, and for each role, the relation between the asset and project information models is discussed • Used to process project information throughout project, not just at handoff • Facilitates preparation of operational and asset management staff for start of operations Organizational and Institutional Practices Align with soft landings framework (identified by UK Government) • Smooth transition from design and construction into operation and use of an asset • Maintain focus on the required outcomes Close collaboration during briefing, design, construction and handover between the delivery team and operations team or asset manager in matters affecting operations and end users Set up projects for success from the outset, otherwise unlikely to achieve expectations, objectives or performance requirements • Emphasize the front end of the project, where the ability to influence changes in design is relatively high and the cost of making those changes is relatively low • Develop sufficient strategic definition through which the owner can articulate requirements and address uncertainty and risks • Commit resources to the project in a controlled manner • Consider program interdependencies holistically Performance outcomes set at the “Strategy” work stage and monitored during each subsequent work stage up to and including Operation and End of Life • Post-implementation review at prescribed intervals during extended aftercare recommended for measuring operational performance Environmental Social

III-188 Guidebook for Data and Information Systems for Transportation Asset Management Security Economic • Quantitative approach taken to measuring performance and value (recommends PD ISO/TS 21929-2) Provides environmental, social and economic performance indicators Includes a framework for developing indicators of economic, environmental and social impacts Establishes a core set of aspects and impacts to be considered when developing systems of indicators Roles, main activities and responsibilities for facilitating information management and soft landings in the context of asset management • Discussion between the owner and delivery team on the alignment of decisions and information exchanges • Project decision points should be determined by the owner’s internal policy and decision-making, not the delivery team Information and Data System Challenges and Opportunities Opportunity: • Creating the Asset Information Model (AIM) at the start of the project so that it can be operated alongside the Project Information Model (PIM) Examples or Case Studies The following examples are provided: • Brief checklist – specifically for a highway • Environmental performance evaluation • Social performance evaluation • Economic (cost) performance evaluation • Responsibility assignment matrices • Risk (threat and opportunity) assessment • Plain language questions • Stakeholder identification • Stakeholder impact analysis • Activity checklist Emerging Technology or Techniques • N/A

Detailed Literature Review III-189 Integrating 3D Digital Models into Asset Management Year of Publication: 2018 Link: N/A Overview The goal of the document is to guide practitioners at transportation agencies in the United States in the incorporation of as-built 3D project information models created during the design and construction phase of projects into asset management systems. These models contain information about the assets addressed. In addition to analyzing the content of these and identifying what data needs to be transferred to meet asset management data needs, the document also investigates other information needs (e.g., asset quality information generated during construction) and the information management framework that must be established to ensure a data transaction can happen. TAM Motivations • Align data with business need • Payoffs to investment in data • Improve access to decision data • Provide guidelines on strategies to enable integration of new technologies Information Management and Integration Practices • BIM maturity models • BIM framework • BIM use for enabling data migration • BIM data models Project and asset information models • BIM data processes Information management strategies Information delivery process • BIM data interoperability and exchange program Platforms Open standards Organizational and Institutional Practices • Asset management goals Identifying what assets are needed Identifying funding requirements Acquiring or creating assets Establishing an asset operation and maintenance plan Adopting optimal renewal, decommission, and disposal strategies

III-190 Guidebook for Data and Information Systems for Transportation Asset Management • Maintaining an inventory of assets and information about their condition/performance • Achieving target level of service/performance requirements within budget constraints • Preserving the assets in good condition, while improving return on investments • Trading off between improvement alternatives and investments to find optimal solutions • Connecting customer expectations with agency policies, practices and investment decisions relating to system performance, condition and availability • Optimizing allocation of monetary, human and physical resources to provide greater value to the asset system and users • Conformance with legal, statutory and regulatory requirements • Maximizing the value of asset portfolios through careful consideration of trade-offs between performance, cost and risk over all stages of the assets’ life-cycles • Continual improvements to asset preservation related policies, practices and procedures to achieve agency goals • Strategically aligning agency policies with long-term financial health and asset needs Information and Data System Challenges and Opportunities • Challenges/Pitfalls Interoperability between diverse BIM and asset management platforms Data collection (field) Narrow definition of BIM Data redundancy Data quality Data Integration Consistency of data use Open standards for data interoperability and integration Developing processes to build and implement a BIM-integrated asset management system Robust data linkage Configuration management process Streamlined data flow Standardization Data interdependency Data access Data security Perception of BIM. BIM is still a new topic and its potential is not fully understood. Still there is no evidence to convince asset managers to adopt this technology. Lack of benefits, real world projects; lack of proof of positive return of investment; and lack of standards and guidelines. Fundamental difference between project and life-cycle management Different methodology between BIM and asset management BIM implementation for running existing projects/buildings.

Detailed Literature Review III-191 Contractual and legal framework Model contents and required data for asset management Model ownership and protection of data Model exchange format Model design liability Intellectual property ownership Standards and policy There is need for a unique BIM international standard Education and skills The construction industry is in the middle of the BIM learning curve Training not only provides new skills for new technicians but also helps to understand what can be achieved Unclear roles and responsibilities and lack of collaboration between project stakeholders Risk and uncertainty Resistance to change of stakeholders Cost Cost of software and hardware Cost of training and BIM consultant Cost of hiring new employees Interoperability Diversity between BIM and FM tools and platforms Open standard limitations Lack of common interest between the software vendors Information management and technology It is necessary to decide what information of BIM is useful for AM How integrated are the different software programs and applications Who will be in charge of information changes during the life-cycle • Opportunities Improved deployment and utilization of integrated data management systems Track changes in inventory data during the design and construction phase Leverage digital models to efficiently hand over as-built information Improve information capture Improve information management Improve information usage Expand open standards Knowledge capture. Share information and knowledge. Increased asset value capturing asset management know-how. Contracting More accurate cost estimates Long-term savings

III-192 Guidebook for Data and Information Systems for Transportation Asset Management Assist business journey BIM can be used as a tool to increase flexibility and adaptability, improving the quality of the work environment and therefore having positive effects on productivity Asset management early engagement Opportunity for asset management to be involved and influence the design process Feedback loop for continuous improvement and less rework Calculation of total expenditure during whole life Data strategy Identifying data needed by asset management during predesign stage providing single source data Allow asset management and owners to test the outcomes in the O&M phase Facilitate the handover Support soft/hard services and strategic asset management Informed decisions Improve maintenance strategy Cultural behaviors Facilitate data location Examples or Case Studies • Utah DOT • Michigan DOT • New York State DOT • Iowa DOT • Connecticut DOT • A556 Knutsford to Bowdon Road Improvement • Crossrail • High Speed Two • ORBIS • Netherlands • General vendor perspectives and technology trends Emerging Technology or Techniques • 3D digital project information models

Detailed Literature Review III-193 Identifying Data Frameworks and Governance for Establishing CIM Standards Year of Publication: 2018 Link: N/A Overview The presentation aims to identify existing and applicable digital transportation life-cycle data standards. Additionally, it aimed to develop a conceptual data standard, data governance approach, and implementation plan for Civil Integrated Management (CIM). It focused on three main areas: conceptual data standards, data governance, and business processes. TAM Motivations • See examples here: https://docs.google.com/spreadsheets/d/1WsInbgjsyD8tkJLo6vfWB_WAa8pU9_0tFW2O_NkKb fI/edit?usp=sharingApplication of better data governance tactics • Improving data standards, consistency, and quality Information Management and Integration Practices • Develop data governance requirements Ex. conceptual data standards • Data governance • Data architecture • Data modeling, design, and metadata • Data storage and operations • Data management Master data Content Quality • Data integration • Data interoperability • Data use Analytics Reporting Open data • Data warehousing

III-194 Guidebook for Data and Information Systems for Transportation Asset Management Organizational and Institutional Practices • Business intelligence • Gap analysis of CIM processes Information and Data System Challenges and Opportunities • Adoption and consolidation of standards Examples or Case Studies • Netherlands (completed, rest in progress) • Minnesota DOT • Kentucky DOT • Iowa DOT • Michigan DOT • Colorado DOT Emerging Technology or Techniques • UAV (e.g., drones) • 3D LiDAR • Video Data

Detailed Literature Review III-195 Identifying Data Frameworks and Governance for Establishing Future CIM Standards Year of Publication: 2018 Link: N/A Overview The objective of this research effort is to identify existing, applicable, digital transportation life-cycle data standards, and data governance approaches, as well as to develop a scalable implementation plan for agencies to achieve a BIM/CIM data governance approach. The goal of this project is to serve as a basis and starting point for future efforts toward data standards and governance. TAM Motivations • Improve data governance practices • Improve data standards Information Management and Integration Practices • Develop data governance requirements Ex. conceptual data standards • Data governance • Data architecture • Data modeling, design, and metadata • Data storage and operations • Data management Master data Content Quality • Data integration • Data interoperability • Data use Analytics Reporting Open data • Data warehousing • Hybrid of enterprise and functional data governance • Information value chain analysis

III-196 Guidebook for Data and Information Systems for Transportation Asset Management Organizational and Institutional Practices • Civil integrated management • Business intelligence • Mission focus • Focus areas • Decision rights • Accountables • Data stakeholders • Data governance office • Data stewards • Modeling standards • Web data standards Information and Data System Challenges and Opportunities • Challenges Lack of data interoperability Inaccurate data Data redundancy Untimely data Data access Absence of data standards Unavailable data integration • Benefits Cost-saving Innovations Manage risk Harness data Manage quality of data Manage consistency of data Manage usability of data Manage security of data Manage availability of data Examples or Case Studies • Netherlands • Minnesota DOT • Kentucky DOT

Detailed Literature Review III-197 • Iowa DOT • Michigan DOT • Colorado DOT • Connecticut DOT • Florida DOT • Rawlins (2016) • PricewaterhouseCoopers LLP (2016) • Minnesota DOT • Arkansas DOT • New Zealand • Virginia DOT • Ohio DOT • USDOT • U.S. Office of Management and Budget • Georgia Technology Authority • Georgia DOT • Tennessee DOT Emerging Technology or Techniques • E-Construction • nD Modeling • LiDAR • Unmanned aircraft

III-198 Guidebook for Data and Information Systems for Transportation Asset Management Infrastructure Asset Managers BIM Requirements - TR 1010: Delivering the information ‘Asset Managers’ need and can trust using openBIM™ Year of Publication: 2018 Link: https://buildingsmart-1xbd3ajdayi.netdna-ssl.com/wp-content/uploads/2018/01/18-01-09-AM- TR1010.pdf Overview This report outlines the infrastructure asset managers’ requirements for Building Information Modeling • Makes a distinction between requirements of asset managers and of designers and constructors • Reports on interviews and private conversations with asset owners across the infrastructure field Roads Railways Airports Water Environment • Highlights the trend of taking a holistic organizational and whole-life view of assets Findings presented as: • Information requirement principles that span across the life-cycle of infrastructure assets • Recommendations on the process of collection and content required • Principles for types and content of information captured • Techniques for collecting and managing information stage by stage NOT at detailed asset level • Follows an ‘Open’ approach to information Demonstrating how the standards of buildingSMART can be used and adapted to create value and quality in the data life-cycle • Highlights benefits of BIM, has it matured Significant savings in cost and effort Improved content quality and relevance if information can be acquired as an integration of BIM and Asset Information Management disciplines TAM Motivations Savings in cost, effort and improved content quality and relevance if information can be acquired as an integration of BIM and Asset Information Management disciplines

Detailed Literature Review III-199 Information Management and Integration Practices Successful asset management requires considering information requirements as an integral part of carrying out the overall asset management tasks Needs for information are more than a list of products or components with their immediate attributes • encompass the function of the complete asset set • describes performance, capacity, function, risk and interdependency, spanning: Strategic planning for whole asset portfolios Asset management decision-making Operational management Service delivery and use management Maintenance Risk management • Details high level information requirements • Highlights implications for buildingSMART standards Organizational and Institutional Practices Emerging best practices recognize: • Asset life and recording information starts at conception and not when constructed • Information requirements – driven delivery process is essential • Systems engineering approach to delivering information is desirable • Verification and validation of information against requirements at each asset life-cycle stage • Progressive delivery of information at appropriate stages of an asset’s life-cycle • Asset centric view of information delivery is paramount • Design and construction information model must meet design, cost and construction needs and be able to be rolled up to an asset model • Asset and asset information is the core delivery of a BIM process not components and manufactured products • A service and risk driven asset management process necessitating information that supports this • Recording of functional requirements against an asset as it is designed Why it’s there What it is supposed to do • Recording of technical specification against an asset as it is designed What technical performance is required of the asset Verified against functional requirement • Recording of as-built installation of assets

III-200 Guidebook for Data and Information Systems for Transportation Asset Management • Recording of the commissioning information against each asset Verifying it against functional and technical requirements Verifying the condition of the asset at handover Information and Data System Challenges and Opportunities • Describes some of the information and data system challenges, and walks through how these can be addressed using: BuildingSMART standards BS/PAS1192 suite of documents (BIM Level 2) - with reference to the emerging ISO19650 series. Examples or Case Studies • The report was based on interviews with a wide range of infrastructure owners around the world. A table in the document details these. Emerging Technology or Techniques • A roadmap is provided of future work guidelines recommended to facilitate asset information managers’ requirements implementation in openBIM Implications for Improvement Roadmap and Guidance Development • Guidance developed in the international transportation sector shows promising examples for organization and effective communication of data and information system uses within asset management. • These provide valuable organizational insights for the guidance to be developed, yielding powerful communication and organizational aids in areas such as: Asset Information Modeling Information Life-Cycles and Data Flows Asset Life-Cycle, Data Requirements, and Progressive Maturity Systems Approaches to Information Delivery Asset Information Hierarchies

III-201 Research Implementation A P P E N D I X K K.1 Introduction State Departments of Transportation (DOTs) have made steady progress in the use of data and information systems to inform transportation asset management (TAM) decision-making. Advances in data acquisition, management, and reporting tools and technologies are enabling more automated, efficient, and integrated flows of data across systems and more agile and effective ways of delivering information needs to end users. The objective of NCHRP Project 08-115 was to develop guidance to assist DOTs in advancing their use of data and information systems in transportation asset management (TAM) practices. This guidance provides a means for DOTs to benchmark their current practices and select and prioritize recommended improvements in order to advance to an identified desired state. The final products include: • Guidebook (Part I of NCHRP Research Report 956). The guide is organized into five chapters, (1) Introduction, (2) Pre-Assessment Preparation, (3) Self-Assessment and Improvement Identification, (4) Evaluation and Summary, and (5) Implementation Support. It allows users to assess current practice and establish a desired state; enables users to identify and evaluate data- and information system-related improvements; and offers implementation support and strategy development guidance and tools. • Digital Support Tool (the TAM Data Assistant). A web tool supporting the assessment, improvement selection, and implementation process. The tool greatly streamlines the process, allowing users to more easily review their selections and make changes to their assessment. The tool also includes canned reports and data exports for presentation and reporting. • Final Research Report (Part II of NCHRP Research Report 956). The research report summarizes the research project activities. The report outlines the research tasks, reviews the guide’s development process, synthesizes key findings related to the current state of the practice and key challenges in using data for TAM, and presents detailed results of a literature review and stakeholder survey. This appendix presents a research implementation plan. It defines the target users of the research products, suggests criteria for successful implementation, and identifies activities for disseminating the research results, extending the research to add value, and engaging with target users to implement the research products. Ballpark funding needs for research continuation and implementation activities are provided.

III-202 Guidebook for Data and Information Systems for Transportation Asset Management programs, and can be extended for use by any agency or organization that has Transportation Asset Management policies or responsibilities. To fully realize the benefits, other business, technical, and supporting functions should be involved in benchmarking current practice, identifying improvements and planning implementation strategies. Additional participants may include: • Field asset management staff, • Information technology managers, • Business intelligence and GIS managers, and • Workforce, human resource, and organizational change-management leads. Beyond DOTs, other transportation asset owners (such as metropolitan planning organizations or localities) and TAM practitioners will find significant value in the guidance materials and process of their use. Criteria for Success This project can be judged to be successful if: • The guidance produced is used by multiple DOTs to plan and implement improvements to better collect, analyze, and/or integrate data into asset management decision processes; and • The framework that is developed for this project is used for future research and allows for easy connectivity of recent research and applied knowledge. Research Dissemination Activities The following implementation activities are recommended to build awareness of the research products: • Introduce the guidebook and tools at the June 2020 Asset Management Conference. At time of writing, options are being pursued for a presentation at the TRB Statewide Data committee meeting, a workshop, and demonstration of the tool at a standing table (where other AASHTO tools are being shared). • Conduct a TRB-sponsored webinar that can be live or “straight to recording.” The webinar would include a presentation on the guidebook content from the research team as well as 1-2 speakers representing the agencies covered in the pilots or case studies. • Include one of the NCHRP 08-115 pilot states in the FHWA/AASHTO TAM Webinar series. • Publicize availability of the products via email newsletters and email communications, such as: – Transportation Research E-Newsletter, available at: http://www.trb.org/Publications/ PubsTRBENewsletter.aspx; – AASHTO Daily Update email newsletter, available at: https://news.transportation.org/ Pages/DailyUpdate.aspx; K.2 Research Implementation Target Users of Research Products The guidebook is targeted at DOT asset managers, business leads, system owners, and stewards interested in evaluating and improving how data and information systems are used within their TAM

Research Implementation III-203 • Post a description and link to the products on: – The AASHTO TAM Portal website: https://www.tam-portal.com/; and – The AASHTO TPM Portal website: https://www.tpm-portal.com/. • Work with TRB Committee Chairs and AASHTO Committee Chairs to publicize the products to their members and friends through email blasts, electronic mailing lists (ListServs), and social media postings. • Brief the FHWA program leads for TAM and TPM on the research products and discuss opportunities for leveraging them within ongoing technical assistance activities including webinars, peer exchanges and workshops. Target Organizations and Groups for Research Dissemination • AASHTO Committee on Data Management and Analytics • AASHTO Committee on Performance-Based Management (CPBM) • AASHTO CPBM Subcommittee on Asset Management • TRB Asset Management Committee • TRB Statewide Transportation Data and Information Systems Committee • TRB Information Systems and Technology Committee • The FHWA Asset Management Team Research Continuation Activities The following activities can be considered to enhance the existing research products. Videos Create video content building on the case studies – produce a series of 5-minute videos for some or all of the case studies. Enlist target agency staff to speak about what they did and highlight success factors and lessons learned. Post the videos on the web. Estimated funding: $20K–30K (for video scripting and coordination – assumes state DOT or AASHTO video production, no travel included) Integration with the Online AASHTO TAM Guide Integrate the guidebook content from NCHRP Project 08-115 and the online tool with the new online AASHTO Transportation Asset Management Guide. Key points of integration to be considered are as follows: • Chapter 7 of the TAM Guide covers Information and Systems for TAM, with subsections for Information Integration; Asset Data Collection; Asset Data Sharing, Reporting and Visualization; and Data Governance and Management. This chapter includes practice examples, checklists and how-to guides. This material is directly related to many of the improvement recommendations that are built into the assessment. Links could be added to the digital tool to provide access to this guidance from a selected improvement. In addition, contextual material from Chapter 3 of the 08-115 guidebook could be linked to or integrated with the TAM Guide Chapter 7 content. – FHWA TPM Digest, available at: https://www.fhwa.dot.gov/tpm/resources/digest/ current.cfm; and – AASHTO Subcommittee on Asset Management email communication.

III-204 Guidebook for Data and Information Systems for Transportation Asset Management • Both the NCHRP Project 08-115 guidebook and the TAM Guide include case studies. These case studies could be made available from within the TAM portal in a consistent, integrated fashion and linked to appropriate guidance content. Creating a digital, web-based version of the NCHRP Project 08-115 guidebook and integrating it with the TAM Guide would allow for regular updates to the curated resources and links to new case examples as they are produced through other research efforts. Estimated funding: $75K Online Tool Enhancements Implement improvements to the online tool. There were several improvements identified at the NCHRP 08-115 panel meeting that could not be addressed within the scope of the project. Other enhancements may be identified in the state DOT pilots. These improvements may include: • Functionality to allow individuals from an agency to complete an assessment, and then aggregate the assessment results in a format suitable for a group process to arrive at a consensus assessment. • Functionality to allow agencies to compare their assessment levels to their peers – in order to initiate conversations with more advanced agencies in areas of interest. • Functionality to link case study examples to improvements being considered. • Functionality to enable users to contribute content such as practice examples or implementation tips. • Improved standard reporting functionality. Estimated funding: $50K–100K, depending on the scope Research Implementation Activities The following activities can be considered to facilitate implementation of the research products. State DOT Workshop Conduct a 2-day workshop involving 10-15 DOTs. This event could include presentations on the guide’s content, interactive exercises based on the assessments, presentations from the agencies represented in the pilots and case studies, and peer-to-peer discussion of key challenges and strategies to implement TAM data and information system improvements. One option is to attach this workshop to an existing event, such as the planned TPM conference in April 2021 in Rhode Island. Estimated funding: $50K–75K, depending on the number of participants requiring travel and the selected venue State DOT Pilots Enlist participation from 2-3 state DOTs, and facilitate a process of applying the guidance – including use of the online tool. This support would be provided through a series of telephone/video conferences. Based on the pilots, identify usability and functional improvements to the online tool, which could be used to scope online tool enhancements. Estimated funding: $100K • Section 2.3 of the TAM Guide covers assessment and improvement and presents examples of assessment tools. Information on the 08-115 tool could be integrated within this section.

Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FAST Fixing America’s Surface Transportation Act (2015) FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TDC Transit Development Corporation TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S. DOT United States Department of Transportation

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