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Champion(s)
EM - Synthesis: Multi-Objective Resource Allocation
Funding
Research Period
Description
As funding for resource allocation increase and decrease each year it is critical for agencies to ensure that they are spending the resources the best they can and meeting as many needs as possible. The challenge of meeting condition needs vs operational needs vs quality of life is increasing each year for agencies. Thus, as agencies work each year to make resource allocation decisions for multiple service areas, and analysis the impacts of these decisions are often difficult to captured with performance measures. For example, condition measures for physical asset classes (pavements, bridges, etc.); performance measures for system operations (snow and ice control, traffic operations, emergency response) and quality of life measures (safety, accessibility, equity) are used by agencies to evaluate these resource allocations. State agencies generally have flexibility to adjust the level of investment of these categories, yet evaluation of the tradeoffs or optimization of these decisions are often limited to similar measures (bridge condition vs pavement condition). Is there potential benefit in expanding the scope of these analyses to include performance measures and investment classes of less similar nature. What tools do agencies use for this cross-asset allocation; How are the tools used for asset resource allocations to include services and quality of life investments?
Literature Search Summary
Keyword searches in TRB’s TRID and RIP systems were performed for research related to:
• “Resource Allocation”
• “Cross Resource Allocation”
• “Cross Investment”
A search was also conducted on the Transportation Performance Management (TPM) Portal :
• Tools>Featured Tools>MODAT
The National Cooperative Highway Research Program (NCHRP) Report 806: Cross-Asset Resource Allocation and the Impact on Transportation System Performance developed a cross-asset resource allocation framework, a spreadsheet tool and guidance.
A subsequent project culminated in NCHRP Report 921:Case Studies in Cross-Asset, Multi-Objective Decision Analysis , which updated the NCHRP Report 806 spreadsheet tool and developed case studies illustrating multi-object decision analysis (MODA) applications. The Multi-Objective Decision Analysis Tool (MODAT) developed as part of this project helps prioritize candidate projects on a range of different objectives. MODAT can be accessed at: https://multiobjective.org/.
The American Association of State Highway and Transportation Officials (AASHTO) also developed a web-based training (WBT) training curriculum for performance-based prioritization using Multi-Objective Decision Analysis (MODA). This training is intended to educate and expose practitioners to the use of MODA.
Indiana DOT is scoring all of their projects based upon 7 categories including safety, congestion, environment, regional and state economic contribution, Intermodal connectivity, and total cost of ownership. This synthesis would be an extension of the research started here, specifically providing additional case studies of states implementing cross-investment allocation and considering investment categories other than physical assets.
1. American Association of State Highway and Transportation Officials. Transportation Performance Management (TPM) Portal. https://www.tpm-portal.com/. Accessed June 2022.
2. National Academies of Sciences, Engineering, and Medicine 2015. NCHRP Report 806: Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. https://doi.org/10.17226/22177.
3. National Academies of Sciences, Engineering, and Medicine 2019. NCHRP Report 921: Case Studies in Cross-Asset, Multi-Objective Resource Allocation. Washington, DC: The National Academies Press. https://doi.org/10.17226/25684
4. American Association of State Highway and Transportation Officials. MODAT Tool. https://multiobjective.org. Accessed June 2022
5. American Association of State Highway and Transportation Officials. “Performance-Based Prioritization Using Multi-Objective Decision Analysis (MODA). Web-Based Training. AASHTO Store. Washington DC. https://store.transportation.org/Item/TrainingDetail?ID=4506. Accessed June 2022
Objectives
Investigate, compile, and categorize examples of organizations’ efforts of using performance measures and data supported tools for cross resource allocation and goal-oriented decisions.
Urgency and Potential Benefits
As agencies make tough resourcing decisions every year, this synthesis would be useful to capture how the research products and tools described above are being used, along with any other methods state DOTs are using to make multi-objective resource allocation decisions. Research has shown that multi-objective resource allocation can be done. This synthesis could answer “Is it being done?” and if so, “How is it being done?”
Implementation Considerations
The product of this research would be a synthesis of the practice, facilitating knowledge transfer to performance management practitioners.
Champion(s)