National Academies Press: OpenBook

Proceedings of the 12th National Conference on Transportation Asset Management (2019)

Chapter: Track 2: Data Systems to Improve Decisions

« Previous: Track 1: Analyzing and Optimizing Investment Decisions
Page 22
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 22
Page 23
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 23
Page 24
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 24
Page 25
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 25
Page 26
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 26
Page 27
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 27
Page 28
Suggested Citation:"Track 2: Data Systems to Improve Decisions." National Academies of Sciences, Engineering, and Medicine. 2019. Proceedings of the 12th National Conference on Transportation Asset Management. Washington, DC: The National Academies Press. doi: 10.17226/25431.
×
Page 28

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

22 Track 2: Data Systems to Improve Decisions Data Collection to Support TAM Decisions This session featured presentations describing data collection activities that were being used to support TAM decisions. The presentations represented different approaches to data collection from high-level data collection and analysis by transit agencies across the nation to state data collection efforts on nontraditional assets. The moderator, John Puente (Ohio DOT), opened the session with a short summary of practices at the Ohio DOT regarding TAM audits, policies, and workflows. DATA GOVERNANCE FOR ASSET MANAGEMENT AND SAFETY: AN INTEGRATED APPROACH AT THE CONNECTICUT DOT Karen Riemer (Connecticut DOT) opened her presentation with a timeline that the DOT is using to ensure that asset management and safety requirements are being met. Frances Harrison (Spy Pond Partners, LLC) then introduced TAM readiness assessments that had been conducted, including a description of the process, the elements evaluated, and the lessons learned. Riemer followed this with a discussion of data governance at the Connecticut DOT from several perspectives, including basics, structure, owners, stewards, metadata, and guidance for the Transportation Enterprise Database. She also shared challenges, as well as a successful data governance approach that included making decisions together as a group, establishing authoritative data sources, and setting up metadata standards. The presenters also recognized the continuing challenge to maintain data quality. MANAGEMENT AND PRACTICAL USES OF TRANSIT CONDITION DATA Rick Laver (CH2M Hill) shared lessons learned from data collection activities supporting compliance with the FTA’s Final Rule on Transit Asset Management, which requires condition assessments of all facilities for transit modes. In this study, they collected high-level measures from 30 agencies of all sizes and transit models. The results were presented to show average conditions, condition distributions, and comparisons of condition to performance. In addition, Laver shared methods of storing and using the condition information. SELECTING DATA TO BEST SUPPORT ASSET INVESTMENT DECISIONS Prashant Ram (Applied Pavement Technology, Inc.) presented the reliability-centered maintenance (RCM) approach for determining the most effective maintenance strategy for various types of transportation assets. Ram shared two case studies using the RCM approach, including one from the Indiana DOT (a condition-based approach) and another

23 from the Nevada DOT (an interval-based approach). He stressed several keys to successfully using this approach, including (1) using performance measures to define and improve agency goals; (2) recognizing risk, changes, and gaps; (3) including all business units in determining what data to collect; and (4) establishing a realistic understanding of the asset’s function and the consequences associated with failure. KEY TAKEAWAYS • It is important to take steps to plan for data collection, maintenance, and governance before data collection efforts begin. • Not all assets are best managed by using a condition-based approach. The RCM approach can be used to help agencies determine the best management strategy for any asset. The Business of Business Intelligence in TAM This session, moderated by Ian Kidner (Ohio DOT), highlighted some best practices for using management systems to analyze information to support decision-making. The presentations included discussion of business intelligence concepts and the advancement of big data to support agency needs. THE I-70 RISK AND RESILIENCY PILOT: PROACTIVE MANAGEMENT OF THREATS, OPTIMIZING INVESTMENTS FOR IMPROVED RESILIENCY OF COLORADO HIGHWAYS Toby Manthey (Colorado DOT) introduced a risk and resiliency pilot conducted by the Colorado DOT and explained the motivation for the project. The agency used the Risk Analysis and Management for Critical Asset Prediction (RAMCAP) Plus process to prioritize its critical infrastructure. Manthey’s presentation stressed the importance of planning ahead for emergency events and having the tools and resources available to support the collection of data that will be used to inform decisions. The Colorado DOT is currently incorporating the risk analysis into its multiobjective decision analysis to further integrate risk and resilience into agency decisions. UTILIZATION OF AASHTOWARE BRM TO MEET AGENCY POLICIES AND OBJECTIVES FOR BRIDGE MANAGEMENT Joshua Johnson (Bentley Systems) and Harjit Bal (New Jersey DOT) discussed the implementation of the AASHTOWare Bridge Management (BrM) software at the New Jersey DOT. They discussed the challenges they faced during the implementation and how each of the major BrM components was addressed. Their work helped the DOT realize the importance of data sharing and data transfer across agencies and DOTs. The agency also recognized the need for data-driven methodologies that take into consideration LCP and preservation.

24 FILLING THE TANK: HOW BETTER ASSET INFORMATION FUELS BETTER ASSET MANAGEMENT Simon Smith (AMCL) discussed the importance of data to asset management and suggested that agencies often find they do not have the information needed. Smith suggested a three-step process for improving the potential of the data agencies are collecting: (1) understand what asset information means to your agency and how it is used; (2) identify your asset information needs, challenges, and decisions; and (3) improve your asset information. He stressed that asset information is vital to getting asset management in a position that can truly inform business practices, agency decisions, and how stakeholders interact with assets. KEY TAKEAWAYS • Business intelligence is powerful when used with data-driven information that can inform how stakeholders interact with assets. • Business processes and decisions that are made by executives need to demand data from operators and staff in other parts of the agency that are information rich. Data Visualization to Communicate TAM Results This session had more than 100 participants representing a cross section of agency types. It included two presentations, a panel, and a demonstration on the uses of data visualization. The moderator, Frances Harrison (Spy Pond Partners, LLC), opened the session with two quotes: The greatest value of a picture is when it forces us to notice what we never expected to see. —John Tukey Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space. —Edward Tufte SYSTEM OF ENGAGEMENT (STRATEGIC DATA INTEGRATION) Stan Burns (Integrated Inventory, LLC) explained that data are often stored in multiple systems within one organization. These systems can be complex and may require experts to extract the data. The New York State DOT is creating a single, shared, authoritative destination for data and information. The agency has map-based apps that combine data sets and make the information accessible to anyone. TOSTADA—IT IS NOT JUST FOR DINNER ANYMORE, IT IS MORE, IT IS DATA INTEGRATION David Schrank (Texas A&M Transportation Institute) stated that many agencies store data in multiple systems that do not talk to each other; however, comparing different sets of

25 information is valuable. The Texas A&M Transportation Institute is layering asset data and performance data in one location so that systematic problems can be realized and benefits can be communicated across multiple asset and performance categories. To compare unique data sets, Schrank showed an example of how to normalize separate indices to create a combined index. PANEL DISCUSSION Panel members included William Johnson (Colorado DOT), Anne-Marie McDonnell (Connecticut DOT), and Mathias Burton (Socrata). The questions posed to McDonnell and Johnson included the following: • What story have you told through visualization? • Do you have dedicated staff for data visualization? • What advice do you have for other agencies practicing data visualization? McDonnell provided the following responses: • The Connecticut DOT uses fact sheets about its assets as a tool to convey information quickly. • Visualization is about illumination and discovery. It can be used to learn things that would not be seen otherwise. • Agencies should not analyze one variable at a time. They should look at many factors for true success. • It is important to cultivate a role in transportation organization for creative, agile employees because data visualization will be a tool to help answer some of the complex transportation issues of the future. Johnson’s responses to the same questions are as follows: • The Colorado DOT created a publication that ranked its DOT against other state DOTs, highlighting all the good things the Colorado DOT is doing with its money. • Maps are an effective way to visualize data, so they should be used whenever possible. • Agencies do not always need GIS staff or data visualization experts to create effective graphics. Agencies can use existing resources. • Agencies can learn from what other state DOTs are doing. The session concluded with an overview of data visualization best practices by Mathias Burton. He recommended attendees understand their data, define their audiences, and identify the questions they are asking before beginning to visualize their data. He also suggested attendees make their displays minimal, that they be aware of connotations associated with certain colors, and that they include metadata with public-facing data displays. Burton showed several visualizations displaying the Seattle DOT’s bridge data that could be used in front of different audiences.

26 KEY TAKEAWAYS • Agencies can discover complex, systematic problems by analyzing multiple data sets at one location. This method improves transparency and consistency in decision-making. • Freeing data from systems that only experts can use creates a new way of thinking about data. • About 20% of the data are used 80% of the time. It is important to prioritize making the important data available first. • Administrators come and go, but systems, policy, and strategy leave a long-lasting effect. • Data visualization with systems such as Tableau, Socrata, and Excel can illuminate discoveries that would not have been realized otherwise. • Sharing data visually can help to quickly and clearly communicate with multiple audiences. • Visualizations should be created with the target audience in mind, which will dictate the story that is being told. Discussion Session: The Data Governance Road Less Traveled: What Did Your Agency Learn Along the Way? This discussion session began with opening presentations by the two moderators, Margaret Poteat (KPMG LLP) and Anita Vandervalk-Ostrander (Iteris). Poteat described data governance and a strategy executed through a set of processes that ensures accurate data enabled by technology. She suggested that data governance practices will enable agencies to more easily obtain a cohesive, coherent, timely view of asset information so data can be more readily turned into insights. Poteat introduced a governance framework designed to address structure, components, and roles and responsibilities. She stressed that data governance is a long-term, strategic view that is repeatable, flexible, adaptable, and scalable to allow for continual growth and sustainment of data integrity for the long term. Vandervalk-Ostrander discussed the importance of business planning to optimize asset management decisions. Following her presentation, the participants addressed a series of questions that had been selected for this session and shared their experiences with data governance. Is the Sky Really Falling? Communicating TAM Results This session included a mix of transit, city, and state agency speakers representing a range of experiences. Their presentations focused on the use of GIS for asset data determinations, the process of improving decisions with better data, and the use of sidewalk data to inform maintenance prioritization. The presentations illustrated how in-house, home-grown tools

27 have enabled agencies to solve problems associated with data collection and reporting to improve decisions. SMART USE OF GIS DATA TO DETERMINE ASSET AGE Royce Greaves (WSP ∣ Opus Canada) discussed the challenges many agencies face regarding the quality of asset age and cost data. He introduced a process that uses records, such as utility installation dates, building permit data, and subdivision consents/permits, as a way to obtain this type of information with the use of GIS. Agencies that have used this approach have seen a significant increase in data quality at a minimal cost. The process highlights the importance of GIS analysts in transportation agencies and the importance of sharing data with other agencies, such as utilities. Greaves encouraged participants to think about data that other agencies might have to help validate data or to build a more complete asset database. TRANSLINK’S CAPITAL INVESTMENT DECISION SUPPORT JOURNEY Vikki Kwan (TransLink) discussed the agency’s enterprise asset management program, which was established to enable proactive asset management and cross-enterprise partnerships. The program is used to answer two key questions: Are we funding what is needed? How do we prioritize capital investment projects? TransLink established scoring criteria for evaluating capital project requests that are not constrained financially. Rather, the process looks at how well the project addresses agency strategy and policy initiatives, the impact on the customer experience, business effectiveness, added safety and security, and other factors. The process has helped drive discussion about what TransLink’s corporate priorities should be. Through the development of this process, the agency has recognized strong alignment of corporate goals, buy-in among agency personnel, justification for changes to prior processes, and the importance of increasingly engaged stakeholders. SEATTLE’S SIDEWALK ASSESSMENT AND PRIORITIZING REPAIRS In a joint presentation, Colleen Fegley and Emily Burns (Seattle DOT) introduced the sidewalk assessment project implemented by the City of Seattle. Data collected for the project were recorded with a Collector App on iPad minis. The tool development and testing began in January 2017, and data collection conducted by interns on more than 34,000 blocks took place between May and September 2017. The data were processed, summarized, and presented to the City Council in spring 2018 with map displays. In addition to being used in presentations to City Council, the information has been used to communicate with other stakeholders, including citizens, agency partners, engineers, planners, and city crews. Several formats were used to present the information, including media and blogs, presentations to pedestrian advisory boards, a website, and information cards distributed to citizens during the data collection process. The process has enabled the city to allocate its limited budget to provide the best value for the community, it has

28 enabled city maintenance crews to feel more invested in repairs, and the public has more confidence in the way sidewalk investments are being made. KEY TAKEAWAYS • Other agencies (e.g., utility companies) often have data that might be able to be used to validate transportation agency data or to build a more complete picture of the assets. • Decision support tools that prioritize capital projects and support decision-making can be used to drive the discussion about corporate priorities. • The success of decision support tools is advanced through strong sponsorship, change management, and stakeholder engagement. • Agencies should look for partners to deliver improvements such as sidewalk repairs. • Open-source data collection and in-house tool development can be an effective first step in asset management.

Next: Track 3: Implementation »
Proceedings of the 12th National Conference on Transportation Asset Management Get This Book
×
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

TRB’s Conference Proceedings on the Web 25: Proceedings of the 12th National Conference on Transportation Asset Management is a compilation of the presentations and summary of the ensuing discussions at a July 14–15, 2018, meeting held in San Diego, California.

During the meeting, attendees explored the development of integrated investment decisions within an uncertain financial planning environment; and the development and implementation of data systems, best practices in data collection, methods used to estimate the expected return on investment, and strategies for communicating results.

The meeting also addressed best practices and lessons learned from Transit Asset Management (TAM) implementation efforts; offered a forum for the sharing of organizational transformations and key strategies for building an effective TAM workforce; and explored the development and maturation of agency transportation asset management plans (TAMPs).

The structure of the program also ensured that transit and risk and resilience were included in the areas of exploration during the meeting.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!