Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance (2015)

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42 The NCHRP Project 08-91 framework and tool prototype demonstrate that a cross-allocation approach to analyze and communicate the likely system performance impact of investment deci- sions across multiple types of transportation assets can be developed and applied. The project products were well received by agency decision makers and technical practitioners participating in the project as part of the research panel or tool workshops and testing. The tool prototype provides an implementable framework that can be used to directly link plan- ning, resource allocation, and programming to achieve agency performance goals. While example applications for the framework and tool prototype are documented in Chapter 4, it is important to note the following summary considerations, which link directly to the suggestions and next steps for implementing the NCHRP Project 08-91 research. The idea is that these considerations are challenges that must be addressed in a real-life deployment setting. • Data development and integration: The framework suggests a bottom-up approach to pro- gram development, where all possible projects are pooled and prioritized prior to capital budget- ing. The challenge for many agencies is the overall lack of a suitable list of candidate projects with adequate information on project details and anticipated performance impacts. More work is needed at the agency level to better understand how and where data must be aggregated to feed the tool. Additionally, identification is needed of how/where qualitative information (e.g., equity and quality-of-life considerations) can support the framework to better integrate priorities outside of those traditionally measured. • Integration with existing management and analysis systems: The use of siloed asset man- agement systems is widely applied in many state DOTs, and with MAP-21’s focus on asset con- dition and performance, most states will likely rely on management systems at some level in their decision-making processes in the near future. The NCHRP Project 08-91 frame- work shows that management systems can be applied to identify performance information for both the project-level (bottom-up) and the network-level (top-down) optimization approaches; however, the tool prototype would need to be expanded to directly integrate these data in an automated or agency-wide enterprise solution. This means that the man- agement systems would develop candidate project lists for incorporation directly into the tool prototype. Additionally, the integration of other models into the tool could be researched. This would include an assessment of how national models [e.g., HERS-ST, NBIAS, AASHTOWare Bridge (aka PONTIS)] can be used to feed the before-and-after performance information needed to run the tool. • Development of a more streamlined user interface: Suggested refinements to the tool pro- totype include making the mechanics of using the tool more user-friendly and providing a web-based solution. For example, changing the nine-point comparative scale to a sliding bar Conclusions and Next Steps C H A P T E R 5

Conclusions and Next Steps 43 or scale to compare measures as well as development of trend lines for performance measures. Additionally, allowing for each user to be assigned different weights within the weighting process could be integrated to allow for the relative importance of a group to influence performance weights (e.g., stakeholders, practitioners, technical experts). • Testing the framework and tool in planning and programming: Chapter 4 highlights the intended applications of the framework and tool for agency long-range, strategic, and TAMP planning; project prioritization and capital programming; and communications and public involvement. Clearly, the ability to apply the framework and tool prototype depends on an agency’s organizational structure and maturity with respect to performance-based planning, asset management, needs identification, and performance management. For example, many states expressed interest in using the top-down tool functionality as a first step toward its broader implementation. In addition, these or other agencies could use the framework and tool to analyze data to better understand the benefits of projects across performance types (e.g., pavement projects may have safety benefits that are not quantified in current data col- lection and analytical processes). • Establishing weighting and performance targets: The project testing workshops focused on applying the framework and tool functionality; thus it was assumed that the process of estab- lishing program area weightings and setting performance was linear. In reality, setting these parameters will likely require a significant and iterative policy development effort that will need to be integrated with an agency’s broader decision-making processes. • Scope of performance considerations: The tool testing workshops incorporated a fairly basic set of performance considerations—preservation, mobility, economic impacts, and safety. Many agencies use a broader set of metrics to drive decision making that include consider- ations such as environmental benefits and livability/sustainability. These could be incorpo- rated, as well as other modes or geographic subregions, to provide a more comprehensive and inclusive set of performance considerations. • Programmatic alignment: During testing of the framework and tool it was generally assumed that all agency funding was fungible (note that some testing scenarios did look at earmarking specific funding levels for certain program areas, but only as a sample project-specific exer- cise). In reality, agencies tend to have complex program funding structures, and effort will be required to translate the outputs of the tool and framework to an agency’s actual funding categories and associated requirements. The tool prototype has been developed to overcome these requirements but has not yet been tested in this way. While NCHRP Project 08-91 provides an implementable methodology that was tested for the research, it does not include a full deployment of cross-asset resource allocation approach within a transportation agency. A full test deployment would include: • An assessment of data and suggestions for data sets and tools that are available to sup- port comprehensive performance management: This includes the ability to predict future performance, whether based on objective or subjective information. Both quantitative and qualitative post-processing and predictive modeling of available information are suggested to support and validate predictive models. • Modifications to the framework and tool to accommodate an agency-wide enterprise solution: A full deployment would be used to implement the project research at an agency enterprise level, where the tool would accommodate data automation and updated interface considerations. • Real application to agency planning and programming: The framework could be applied to the development of an LRTP update, for example, or to the development of a capital program. The exact application would depend on the agency’s timing in the planning and programming process, but would largely follow the applications in the self-assessment in Section 4.3.

44 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance • Improved outputs and visualization: While the tool prototype provides dashboard indicators and other graphical inputs, development of better visualization capabilities and exploration of how the tool could be linked to other graphic and communication platforms could greatly enhance the benefit of the tool to agencies. The main contributions of the research have been in advancing data-driven techniques to support performance-based project prioritization, program development, scenario analysis, and target setting while still accommodating various opportunities for expert judgment. While the research team has accomplished the goal of delivering an implementable framework that decision makers may use to better understand the outcomes of investing across asset classes and investment types, a full pilot deployment was advised by participants at project workshops and testing to overcome the implementation challenges noted and to better understand how the framework and tool prototype could be applied in practice. This is also suggested by the research team, since many of the modifications needed to make the tool implementable at an enterprise scale are outside the scope of the current research project.