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Guide for Data Management II-37 Step 3--Identify which business functions are supported by which data programs. Step 4--Establish policies, standards, and procedures which mandate how data is to be collected and used within the agency. Step 5--Establish Data Action plans on both a data program and enterprise level, to address needs and gaps in data and information across the agency. Step 6--Establish a risk management plan for protecting data programs as valuable assets of the agency. Mn/DOT is an excellent example of an agency who conducted a thorough, detailed, and well thought out planning process. They began with the establishment of a BIC which serves as the leadership body for the development and implementation of the data business plan. Its charge was to do the following: Craft a vision and mission for managing data and information in the department; Develop and implement processes for identifying and prioritizing data and information gaps and needs; Identify new data governance principles and frameworks to effectively manage information; Develop a business plan that recommends strategies, actions, and resources required to achieve Mn/DOT's data and information vision and mission; and Share the data business plan with Division Directors and Commissioner's Staff and assist with the implementation of approved actions and strategies. The vision and mission was established as follows: Vision--All Mn/DOT business decisions are supported by reliable data. Mission--To provide reliable, timely data and information that is easily accessed and shared for analysis, and integrated into Mn/DOT's decision-making process. The BIC also identified a comprehensive list of issues to be addressed in their Data Business Plan listed. At the time of the writing of this Guide, the BIC was still working on the rest of these items. Once goals for the data management process are in place, the assessment of data programs can begin. 2.3 Assessing Current State of Data Programs The previous sections provided tools to assess an agency's state of readiness for developing and implementing data governance and laid the groundwork for beginning improvement. Once goals for the Data Management process have been established, an agency should work on clearly identifying and linking data programs to office and agency-wide goals. This section provides guidance related to assessing an agency's data programs, so an appropriate data management improvement strategy can be established. It will assist agencies in conducting surveys, work team meetings, focus groups, or other mechanisms for gathering information regarding customer needs for data programs, agency needs for the programs, and gaps that need to be addressed with a data management program. A Risk Assessment is a key component of assessing current state of data programs.

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II-38 Guide for Target-Setting and Data Management This section assists in achieving the following success factors: Performing a health assessment of data systems to determine where the most critical deficien- cies exist and to develop a strategy for addressing those deficiencies; and Performing a risk assessment of existing data programs to highlight the importance of mission critical programs to management and, thereby, gain continued support for those programs. Identifying Data Programs The first step in assessing an agency's data programs is to clearly identify which programs will be included in the assessment. Other components include identifying which data products are provided by the data programs and who the providers/users of the data products are. Most of the time an agency already has identified data systems, databases, data offices, or even data programs. These should be cross walked so all stakeholders can clearly understand how the data systems, processes, and programs interrelate. The identification of data programs also should include a connection to missions and business core services. An excellent exam- ple of the result of such a process is shown in Figure 2.1. Alaska DOT&PF linked the overall ADOT&PF mission to the core services, business programs, and primary and secondary data systems. This is an important step in assessing the value of the programs in terms of meeting high-level agency goals. The process of organizing data categories and relating them to other institutional frameworks within the department is important to the data business planning process for two reasons. First, it allows all stakeholders to clearly see how their data program(s) fit into the over- all existing structure of the agency. This ensures buy in for the plan and an understanding of how the data systems fit together and are essential to support the overall mission of the agency. Sec- ondly, an established list of data categories allows for the assignment of data governance roles as described later in this Guide. Alaska DOT&PF developed a more detailed framework shown in Figure 2.2. The framework links business objectives, programs, and processes to data systems, services, and products. It also starts to define how the data stewardship roles fit in. It is important to note how Alaska has carefully defined data systems, services, and products. Stakeholders, such as those responsible for collecting data, can quickly see how their institutional systems or reports fit into the overall structure. Another example, Figure 2.3, illustrates a similar framework used in Virginia. The Virginia framework clearly indicates the applications that are used to support the data products. The frameworks should be accompanied with reports defining the systems and relationships. In both of these state examples, reports were generated and distributed to a large number of stakeholders within and outside of the DOTs. Evaluating Data Programs To begin prioritizing needs for data programs, they must be carefully evaluated in terms of their ability to meet overall agency goals. For example, traffic and safety data programs must pro- duce quality data to support decision-making regarding safety and mobility projects. Criteria must be developed to assess the data programs. An example of the type of criteria that could be used were initially identified for use with the FHWA's Traffic Data Quality Management Report

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Guide for Data Management II-39 Figure 2.1. Alaska DOT&PF data development program. and are applicable, as well, for assessing quality of data used for performance measurement and target setting. These criteria include the following: Accuracy--The measure of degree of agreement between a data value or sets of values and a source assumed to be correct. Timeliness--The degree to which data values or a set of values are provided at the time required or specified. Completeness--The degree to which the data values are present in the attributes (data fields) that require them.

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II-40 Guide for Target-Setting and Data Management Business Objectives Provide Federally required highway data collection and analysis to state, federal, and local agencies Provide Geographic Information System (GIS) and Global Positioning (GPS) data collection and analysis, as well as cartographic and other technical services Develop and administer the State Highway Safety Program Oversee the web and phone 511 Traveler Information System and the Road Weather Information System Business Programs Business Processes Highway Safety Identify Needs and Solutions Traffic Budget & Manage Resources Road Weather Management Manage Real-Time Data Systems 511 Traveler Information Provide Data and Information GIS Services Monitor and Report Performance Business Data Data Custodian Assigns Owner Primary Data System Data Services HAS 1. Collection RWIS 2. Quality Assurance 511 3. Description/Documentation Enterprise GeoDB Metadata/Catalog TDP 4. Storage, Access and Security 5. Outreach/Sharing 6. Integration and Value Added Solutions Use Data Products Accident Reports Traffic Reports HPMS Communities of Travel Condition Reports Interest Roadway Inventory GIS Basemap Road Weather Information Seasonal Weight Restriction Decision Information Figure 2.2. ADOT&PF data business plan framework. Validity--The degree to which data values satisfy acceptance requirements of the validation criteria or fall within the respective domain of acceptable values. Coverage--The degree to which data values in a sample accurately represent the whole of that which is to be measured. Accessibility--The relative ease with which data can be retrieved and manipulated by data consumers to meet their needs. For example, these measures helped ADOT&PF identify which data programs were most crit- ical to agency operations and also where data was lacking to meet department needs. The crite- ria were tested through interviews with key stakeholder groups. The Virginia Department of Transportation (VDOT) used a survey approach to assess their data programs. Mn/DOT also used an agency-wide survey as a valuable tool to begin the assessment process and will provide

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Guide for Data Management II-41 SO Business Areas SO Business Processes Infrastructure/Maintenance Management SO Business Objectives Identification of Needs & Solutions Equipment Management Improve Safety Budgeting Land Development Improve Security Work Scheduling and Management Support Safety Management Achieve Improve Highway Real-Time System Management Congestion Management Operational Performance Providing Traveler Information Emergency Management Preserve the Infrastructure Monitoring and Reporting Performance Critical Infrastructure Management Data Products Roadway Inventory Asset Information - Pavement Enable - Structure & Bridge Data Services - Safety Business Case Applications Data - Drainage Design Designates RNS ADMS Architect - ITS Acquisition & Updating AMS LUPS - Roadside Quality Assurance Structures PMSS LandTrack Manage Data - Facilities Provide Description & Context VaTraffic TAMS & Consume Steward Work Tracking Storage & Access Coordinates TREDS MDSS Traffic & Travel Characteristics Security DACHS TMS Current Travel Conditions Outreach EMS RWIS Data Road Event History Catalog Designates Coordinator Safety Information Financial & Resource Management Ensure M&O Needs Planned Work Data Business Designate Custodians Owners Land Development Use Communities Provide Feedback of for Improvement Interest Figure 2.3. Virginia data business plan framework. the basis for further analysis of the data and information needs at Mn/DOT. Completing the assessment helped Mn/DOT do the following: Identify data and information priorities to meet user business needs; Determine the current ability of data and information to meet user business needs; Determine current and anticipated gaps in data and information; Identify methods to address current and anticipated gaps in data and information; and Enhance user access to information on available data sources and stewards. The success of the assessment process will depend upon the commitment of the participants to identify what is working well, so those methods can be repeated with other data programs in the DOT. Likewise, this assessment will highlight areas where improvements are needed, to develop a plan of action to address gaps in the data systems. Instruments for Gathering Feedback Assessing the current state of data management and data programs in a Transportation agency can be a challenging process, depending upon the size of the organization. However, this process can be expedited through the use of structured methods and instruments for gathering feedback from staff across the organization.

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II-42 Guide for Target-Setting and Data Management Develop criteria for evaluating programs and instruments for gathering feedback. This may include the use of: Surveys; Focus Groups; Workshops; and Research Studies. The best approach for the development and use of these instruments depends upon the size of the agency, and the resources and funding available to develop the instruments. The type of instruments that can be considered for use in the assessment process include: surveys, focus group meetings, data program workshops, and research studies. The intent of each of these instruments is to gain perspective on the quality of data programs within the organization from the viewpoint of the audience, whether the audience is enterprise- based (using surveys) or a more limited audience which includes participants in focus groups and workshops for specific data program areas, or research studies which may assess data pro- gram performance in a specific area such as traffic or pavement. Surveys Surveys can be used to assess how well the data programs and information needs of the agency are being met, to identify gaps in needs, and potential solutions for addressing gaps. Surveys pro- vide an opportunity to reach a wide audience with a quick assessment of how well data programs are performing within the agency. Particular attention should be given to developing a survey instrument which assesses data programs across the organization, if the intent is to develop a data business plan for the entire agency. A more limited survey should be used if the data busi- ness plan being developed is for a limited division or office of the agency. Focus Groups Focus groups offer the opportunity to assess data programs at a more detailed level than sur- veys. Agencies should include data providers and data users of the particular data program(s) in the focus group discussions. The following are some suggestions regarding Focus groups: Use in-depth discussions which focus on specific areas of data and information needs within the organization; Develop a list of intended outcomes which are known to all participants, such as a prioritiza- tion list and ranking of needs identified for data programs and action plan recommendations for addressing those needs; Design to allow for additional pertinent and valuable information to be provided by partici- pants that may not have been previously considered; and Reach a consensus on the top three to five data issues that can be addressed over a short time- frame by the agency and also identify those issues that may be addressed as part of a long-term data action plan or data business plan. Data Program Workshops Data program workshops can include staff from the Information Technology office of the agency, staff from the business offices who represent the business owners of the data, and other agency staff who represent the data providers and users of the data program(s). Data program workshops are structured to address particular needs identified for a limited group of data pro-

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Guide for Data Management II-43 grams or a single data program. The workshops occur after data program needs have been iden- tified and strategies need to be developed to address the data and information needs using a tech- nology solution. This may or may not include the development of new systems and applications or the enhancement of existing applications. Data program workshops can include the prelimi- nary design of new data applications, or data models, and design for integration of existing data and applications into an enterprise model, which better suits the needs of the agency on a wide- spread level. The outcome of data program workshops can include preliminary architecture and system design for new applications or integration of existing applications within a new frame- work, such as a GIS. Research Studies An agency should consider the use of independent research studies to assess data program per- formance within the agency, when resources are limited to conduct the analysis internally. Some advantages of research studies include the following: Research studies offer an unbiased assessment of the data programs at the agency; Research studies can include benchmarking used at other agencies to assess how well similar data programs meet the needs of those agencies; Research studies can present proposed methods for assessing data programs and addressing potential problems, based on best-practices across multiple agencies in the private and pub- lic sector; and Research studies can be sized in scope to focus on limited or enterprise solutions to address data and information needs of the organization. Compiling and Analyzing Results Regardless of the feedback instrument used, once the information is gathered on the state of data programs at an agency, the task begins of compiling and analyzing the results. The agency should perform a preliminary and detailed analysis of the results, in order to develop the best possible solution for addressing its most critical needs regarding data programs. Determine gaps in data program needs by analyzing results of data program eval- uation instruments. Preliminary Analysis Step 1--Compile the raw data from the instrument used. Step 2--Evaluate the raw data by identifying the data programs which are ranked most criti- cal in supporting business operations. Step 3--Evaluate whether those programs fully, partially, or do not meet the needs of the agency. Step 4--Evaluate the gaps in data and information needed as identified by the audience. Step 5--Evaluate the recommended solutions for addressing the gaps in data and information. Step 6--Prioritize the recommended solutions. Once the preliminary analysis is completed a more detailed analysis follows. Detailed Analysis Step 1--Evaluate the results according to: Needs within core business areas of the organization;