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

Chapter: Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops

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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
×
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Suggested Citation:"Attachment - Technical Memorandum: Cross-Asset Resource Allocation Workshops." National Academies of Sciences, Engineering, and Medicine. 2015. Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22177.
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47 Contents Section 1. Overview ..................................................................................................................... 48 Section 2. Workshop and On-Site Testing Participants ............................................................. 49 Section 3. Pre-workshop Surveys ................................................................................................ 52 Section 4. Workshop Objectives and Structure .......................................................................... 53 Section 5. Findings ....................................................................................................................... 53 Appendix A: Survey Results .......................................................................................................... 57 Appendix B: Workshop Materials ................................................................................................ 67 Appendix C: Scenario Handouts .................................................................................................. 88 Appendix D: Workshop Discussions .......................................................................................... 104 A T T A C H M E N T Technical Memorandum: Cross-Asset Resource Allocation Workshops

48 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Figure 1.1. States where the framework and tool were presented for testing. Section 1. Overview NCHRP Project 08-91, “Cross-Asset Resource Allocation and the Impact on System Performance,” sought to address a common performance-based planning challenge for transportation agencies. While there is considerable interest in assessing the anticipated performance outcomes from differ- ent ways of allocating resources across asset classes and investment types, a lack of tools and methods exists to enable agencies to conduct these analyses through optimization-based approaches. As a result, current agency processes for defining performance measures and setting targets are often sep- arated from efforts to select projects or optimize the allocation of limited transportation resources. The research team conducted research to develop an implementable framework and tool proto type that advances the state of the practice in cross-asset resource allocation and program optimization. From April through July of 2014, the team conducted multiple workshops and presentations to present the proposed framework and test the tool prototype. Workshops were held in Miami (FL), Scottsdale (AZ), Albuquerque (NM), and Indianapolis (IN) in conjunction with TRB and AASHTO conferences. These workshops provided and allowed for the opportunity to test the tool with a broad cross-section of state DOTs and other transportation professionals and enabled participants to comment on the framework. Tests were also conducted for several state DOTs, including those of New Jersey, Utah, North Dakota, Illinois, California, Kansas, and Missouri, through state-specific, on-site workshops (see Figures 1.1 and 1.2). Top Takeaways from the Workshops Key issues, considerations, and observations that emerged from the various testing workshops included the following: Participants representing a range of agencies: The FHWA, state DOTs, and MPOs generally expressed a strong interest in and curiosity about the concept of cross-asset

Technical Memorandum: Cross-Asset Resource Allocation Workshops 49 allocation and the development of an associated analytical framework tool to sup- port its application/implementation. Users had mixed reactions to the AHP approach to developing goal weighting; some found the approach uncomfortable (e.g., I can’t provide a relative preference for pres- ervation versus safety), while others felt the weighting exercise provided a meaningful starting point for determining an agency’s relative priority for competing goals. Through the workshop exercises, participants appeared to gain a strong apprecia- tion for the framework’s/tool’s capacity to support decision-maker and stakeholder discussions regarding goal weighting, performance targets, investment strategies, and impacts of one-off decisions. Participants expressed concern about their agencies’ abilities to gather enough proj- ect data across asset classes to run the tool prototype analysis. Although researchers pointed out that an expert panel approach could be used to estimate project benefits or other needed tool inputs, participants expressed reservations about the amount or resources that would be required to do so. The prototype is seen as a powerful scenario analysis tool that could help agencies evaluate alternative futures based on different assumptions about available revenues. Section 2. Workshop and On-Site Testing Participants Workshop and on-site tool prototype testing participants included NCHRP Project 08-91 Panel members, senior leaders and practitioners from DOTs, FHWA staff, representatives from MPOs, and consultants and other private-sector representatives. Table 2.1 summarizes partici- pants’ roles and expertise from the various workshops. Figure 1.2. Conducted conferences in a variety of states.

50 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Table 2.1. Tool workshops and testing attendees. Locaon Date Parcipants Experse Esmated No. of Parcipants Workshop at 10th Annual Asset Management Conference Miami, FL April 28, 2014 NCHRP Project 08-91 Panel Agency decision makers Data analysts Programmers External communicaons professionals Consultants State DOTs, MPOs, and transit agencies were represented. Analycs Asset management Bridge Construcon Finance ITS Mobility Modes Non-pavement assets Operaons Pavement Programming Safety System-level cross-asset allocaon 20 registrants Utah DOT Tool Tesng Salt Lake City, UT June 16, 2014 Bridge directors Consultants Contract administrators Directors Engineers Engineers Asset Advisory Commi ee Execuve leadership including the Utah DOT execuve director Finance directors Regional directors Technical staff Asset management Bridge design Bridge modeling Bridge planning Central preconstrucon Operaons Pavement management Pavement modeling Program development Program finance Project development Traffic and safety Traffic management Traffic operaons Transportaon 25 Workshop at AASHTO SCOP/SCOPM Conference Sco€sdale, AZ June 20, 2014 Agency decision makers Data analysts FHWA staff also a ended to provide a naonal perspecve with regard to MAP-21. Bridge Construcon Mobility Modes Operaons Pavement Programming Safety Transit 21 New Jersey Tool Tesng Trenton, NJ June 25, 2014 Assistant commissioner for Capital Investment Planning and Grant Administraon Directors Engineers Capital investment planning and development Pavement and drainage management Project management Project planning Statewide planning          Statewide strategies 7

Technical Memorandum: Cross-Asset Resource Allocation Workshops 51 Table 2.1. (Continued). (continued on next page) Locaon Date Parcipants Experse Esmated No. of Parcipants WASHTO Conference Albuquerque, NM July 15, 2014 Agency decision makers Data analysts FHWA staff also a ended to provide a naonal perspecve with regard to TAMP development, where a refocus on starng with bridges and pavements first was recommended. Bridge Construcon Mobility Modes Operaons Pavement Programming Safety Transit Meeng at MAASTO Conference Indianapolis, IN July 30, 2014 Agency decision makers Data analysts Bridge Financial planning Opera ons and maintenance Pavement Programming North Dakota DOT Tool Tesng Bismarck, ND August 18, 2014 Division directors Engineers Planning specialists Bridge specialists Business support execu ves Asset management Bridge Construc on Design Opera ons Pavement Planning Programming Transporta on programs 10 – – Illinois DOT Tool Tesng Springfield, IL August 26, 2014 Engineers Sec on chiefs Program development managers Bureau chiefs Directors Planning specialists Unit chiefs Squad leaders Planning analysts Bridges and structures Cost and es mates Highways Land acquisi on Loca on studies Opera ons Pavement management Planning Performance and cost support Programming Project and environmental 34 studies Structural services Systems planning and services Transporta on planning ˆ Urban planning

52 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Section 3. Pre-workshop Surveys Prior to the Asset Management Conference and the AASHTO SCOP/SCOPM Conference workshops, the research team conducted a short electronic survey of planned attendees to help understand participants’ experience with, and interest in, cross-asset allocation analysis. Survey questions included: • What role do you play in asset allocation/programming? • In what areas do you have specific knowledge or expertise? • Within your agency or client base, to what extent is there demand for cross-asset allocation? • If there is little to no demand for cross-asset allocation, why do you think that is the case? • What challenges or hurdles has your agency faced (or do you imagine it might face) when it comes to cross-asset allocation? In the case of the Asset Management Conference held in Miami, results from respondents indicated that while transportation officials have considerable interest in cross-asset allocation analysis, workshop attendees have little experience in the field. No respondents indicated a high level of comfort with their agencies’ current allocation process. Moreover, respondents expressed concern with the industry’s current ability to develop meaningful performance measures, com- pare measurement results/projections, and quantify the trade-offs between different resource allocation strategies. At the AASHTO SCOP/SCOPM Conference in Scottsdale, Arizona, seven respondents indi- cated that there is definite interest in cross-asset allocation analysis. However, all respondents answered that the agency is technically challenged when it comes to cross-asset allocation. In addition, more than half of the people surveyed said that a lack of industry-accepted tools, funding mandates, and stove-piped decision making have been challenges faced when it comes to cross-asset allocation. Appendix A contains survey results. Table 2.1. (Continued). Locaon Date Parcipants Experse Esmated No. of Parcipants Kansas DOT Tool Tesng Topeka, KS September 8, 2014 Assistant directors Program managers Chiefs Engineers Bridge Budget Construc on and materials Management engineering Pavement Performance measures Planning Program and project management Transporta on safety and technology 12 Missouri DOT Tool Tesng Jefferson City, MO September 9, 2014 Specialists Engineers Directors Administrators Organiza on performance Planning Transportaon system analysis 6

Technical Memorandum: Cross-Asset Resource Allocation Workshops 53 Section 4. Workshop Objectives and Structure The research team identified four key objectives for the workshops and on-site tests: 1. Focus on the decision-making framework developed as a part of the project research; 2. Introduce the tool prototype to aid implementation and understanding of the framework, and guide participants through performance measure selection, weighting, budgeting, and scenario planning case studies to simulate real-world decision-making needs and challenges; 3. Demonstrate tool functionality to support both top-down analysis where a recommended program of projects is developed based on pre-established investment budgets, and bottom- up analysis where program budgets are driven by project prioritization based on project- specific performance; and 4. Keep participants engaged through an interactive workshop that enables them to test drive the tool prototype. Based on these objectives, highly interactive workshops were developed by the research team. The workshop format and materials were prepared for each workshop based on the number of participants and whether the workshop was conducted as part of a national conference or for a state department of transportation with specific concerns. Representative materials, including a workshop agenda, presentation, and scenario handouts, are provided in Appendix C. Key components of each workshop included: • An overview presentation to introduce participants to the cross-asset resource allocation framework and prototype tool, including the methodology (and math) behind the tool. • One or more activities that were conducted with breakout groups (and in some cases, a single group) so that participants could experience firsthand how the tool works and identify ways in which the tool might be improved. Generally, participants decided on the weights for each performance measure, the desired target(s) for each performance measure, and the amount of funding required to meet some or all of the performance targets. Funding was constrained to simulate real-life situations. • A discussion, at the conclusion of the workshop, of the functionality and practicality of the tool, refinements that could be made, and the best use of the tool in practice. Section 5. Findings Both the cross-asset resource allocation framework and the tool prototype were well received by workshop and testing participants. Workshop attendees were active in their breakout group exercises, and the discussion helped identify several potential refinements for follow-on initia- tives. To review specific suggestions for refinement, opportunities to use the prototype tool, and additional observations or concerns from each workshop and state department of transporta- tion meeting, please see Appendix D. Overall, participants indicated that there was significant value in the technical analysis capa- bilities of the tool prototype as well as the ability to apply it toward supporting and inform- ing decision-maker and stakeholder discussions regarding performance targets, measures, and investment strategies. Following are highlights of the suggested or possible uses of the tool prototype based on com- ments received from the participants. • Identifying appropriate performance measures: Most participants focused on the perfor- mance metrics established by MAP-21 as the baseline for all measures nationwide. However, Throughout the work- shops, groups were reminded of their sce- nario and were asked to make decisions based upon that scenario.

54 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance individual states may want to layer on their own set of metrics. With multiple metrics lay- ered on top of one another, finding a common system for evaluation poses many challenges. Participants had concerns that such a common set of standards could realistically be agreed upon, giving several examples of metrics that could be at odds across states and systems. For instance, some technical experts struggled with the use of overall condition indices since these ratings could mask the true nature of disaggregated condition metrics. The tool prototype can help frame these discussions by building a consensus among stakeholders. • Establishing investment program areas: Participants indicated that it may be helpful to cat- egorize investment programs in subclasses. Programs that focused on asset management were identified as different when compared to those that focused on operations or capital projects. Additionally, specific regional differences in investment programs were acknowledged. Topog- raphy, population, and primary road types can differ by region, and participants suggested that investment programs may need to be aligned in regional categories. • Evaluating data availability and management systems: Workshop participants noted several practical concerns related to data collection. The ability to generate, gather, store, and analyze data varied greatly across jurisdictions and agencies. While most currently collect some data metrics, the format of each differed, making both intra-agency and inter-agency cross-asset comparisons difficult. A paradigm shift toward collecting post-implementation performance data, not nor- mally collected, is additionally important so as to improve future impact assessments. There were practical technical issues identified as barriers to linking such data systems. Interest was high in a system to automate linkages among management systems and the tool prototype. • Facilitating values discussions through weighting: While deriving weights, participants noted that agency goals and objectives are sufficiently publicized and instilled across all levels of the organization, yet there is still wide latitude when it comes to interpreting how those values translate to a program. By sitting down together and talking through the importance of one measure over another, revealing conversations were had on more closely defining perfor- mance preferences (e.g., what is more important, the structural health of the pavement or the ride quality that the users experience? Are pavements more important than bridges because of the sheer magnitude of investment, or does the larger risk with bridges dominate?). Some participants feared that these conversations could favor larger personalities getting their way but still appreciated the opportunity to think beyond their silo and make a case for their per- formance areas. In practice, such weighting discussions could be incorporated via a Delphi method to protect against internal biases. • Prioritizing projects from a system perspective: Many workshop participants noted that their agency does have siloed asset management systems in place, particularly for pavements and bridges. They pointed out that these systems could be integrated by using the tool pro- totype and decision making could likely be improved through a more holistic approach. Additionally, because various groups within the agency would be required to participate in broader prioritization processes, it is likely that a better organizational understanding would be developed. In this way, agency management systems would generate lists of projects, and the tool prototype would be used to select the best projects across all management systems, which could then be integrated into the STIP or midterm capital program (for example, a 10-year program). Having both top-down and bottom-up approaches was encouraging to participants so as to more directly link common management system outputs. • Analyzing investment trade-offs: Participants suggested that this tool is not so much a “cross- asset” tool as a “cross-investment” tool. The tool could be expanded to look across modes and has the ability to consider performance with regard to operations (e.g., congestion) instead of just physical infrastructure. The ability to quickly evaluate the trade-offs among investment areas was found to be powerful in supporting decision makers in finding the right mix of investments.

Technical Memorandum: Cross-Asset Resource Allocation Workshops 55 • Making a case for increased flexibility: By reflecting real-world constraints, participants appreciated having the ability to run the tool prototype with and without different policies so as to make a case for additional discretion in decision making (e.g., if the governor says I must do Project X, what are the impacts on system performance? If we could reallocate dedicated funds, what performance benefits could be realized?). While many saw the usefulness, there was also genuine concern about implementation. Now that the tool prototype has been developed and tested with audiences across the country, the following are possible refinements, based on participant feedback, that could help ensure that the tool prototype best meets agency needs. It is important to note that the tool prototype as developed cannot accommodate all of these refinements but that any add-on or future deploy- ment might have the following: • Simplified interface: A few refinements were suggested regarding making the mechanics of using the tool prototype more user-friendly. For example, the user currently weights perfor- mance measures against each other using a numerical, nine-point comparative scale. Attend- ees suggested that a sliding bar or scale between measures might be easier to use for this task to avoid confusion about how to value relative priorities. Participants mentioned this refinement several times. • Performance measures/outcomes: The tool prototype’s output currently provides the value of performance measures as a result of implementing certain projects or portfolios of projects. Some attendees expressed a desire to show trend lines, not just points in time, commenting that it would be useful to see if asset conditions are improving or worsening. It was also noted that the tool should be able to adapt to varying performance targets by functional class. This has been incorporated into the framework but is not reflected in the sample data set provided in the tool. • Scenario comparison: Participants noted a desire to save each scenario/run within the tool so that subsequent runs can be compared. This accommodation has been built in to the tool prototype. Additional discussions at the workshop meetings focused on risk-based planning, the ability to incorporate economic impacts, longer-term analyses, and data needs. One participant asked what capacity the tool prototype would have to support risk and sensitivity analysis, particu- larly since MAP-21 includes requirements for agencies to factor uncertainty into planning and decision-making processes on the NHS. Risk has been incorporated into the tool by including standard deviations around the budget and performance impacts, which allows users to make decisions with confidence given the likelihood of various outcomes. After the tool prototype was demonstrated with a preloaded measure for number of jobs cre- ated, participants pointed out that economic models (e.g., IMPLAN and REMI) already exist that could supplement traditional silo analysis. Related to economic value was a discussion point a participant raised on how the tool prototype could be used to show the impact of the delay of a project (i.e., missing the window of opportunity) with regard to both cost and performance. This can be accommodated in the tool by defining lagging performance measures such as a life-cycle cost metric. If fully integrated with a management system, the tool prototype could be linked to compare the diminishing value between project alternatives (e.g., rehabilitation vs. patch-fix) at any point in time. Sensitivity testing could then be conducted by iterating the project timing or activity type and evaluating the corresponding impacts on performance. In anticipation of the framework being implemented with long-range transportation plans, several participants asked how the tool prototype could be adapted to predict performance over time. While this was outside the scope of the project, the tool can be analyzed from the top down or repeatedly run on a year-by-year basis with manual updating based on what projects were selected each year. To automate this process, a linkage to management systems is suggested. With

56 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance access to deterioration predictions, life-cycle cost evaluations, and project alternatives, the tool could be enhanced to support long-range optimization, including the ability to set minimum performance levels throughout the planning horizon. Discussion at workshops and testing also included questions on what performance measures/ allocation areas should be included in the tool prototype and on the availability of data to sup- port these measures. The sample data set used in the workshops included safety data, for exam- ple, which not all DOTs consider to be a stand-alone allocation area. The flexibility of the tool allows for customization so that states/agencies can use whichever areas/performance measures work best for their unique circumstances and decision-making support needs. It was also noted that the prototype tool depends on data being entered for each project, including the impact of the project on various performance measures. Concern was expressed that this type of information does not exist at many agencies, and the tool is only as good as the data that are entered into it. The research team acknowledged that executive leadership will have to be convinced of the value of such data collection and of its reliability and further noted that, as states/MPOs continue to expand their data sets, many mandated by MAP-21, information will be more readily available for use within the tool. Of course, the application of the framework and tool prototype depends on the agency’s orga- nizational structure and performance management maturity. New Jersey, for example, is unique in that it has more flexibility with state and toll dollars, so agency leadership is supportive of the concept of allocating funds that are not pre-dedicated to a specific silo. Utah has expressed interest in an enterprise solution that can accommodate strategic planning, long-range planning, and STIP development. Many states expressed interest in using the top-down tool functionality as a first step toward implementation while they work to understand the benefits of a project across performance types; for example, pavement projects may have safety benefits that are not captured in current data collection processes.

57 A P P E N D I X A Survey Results

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88 A P P E N D I X C These materials were used at the April 28, 2014, workshop in Miami, Florida, as part of the TRB 10th National Conference on Transportation Asset Management. All subsequent workshops used a variation of these materials. Scenario Handouts

Scenario Handouts 89 Scenario #1: Preservation Mode Your job – Develop a $400 M program to get to a state of good repair without getting stuck in traffic Workshop: 017 Cross Asset Allocaon (NCHRP Project 08 91) Monday, April 28, 2014, 8:30 a.m. – Noon Hello and welcome. You are here today to bring the NCHRP Project 08 91 cross asset resource allocaon framework to life. You have been assigned to a team that will operate as a transportaon agency. You will navigate through a case study that is designed to simulate a real world decision environment and arrive at a recommended allocaon strategy given the priories of your agency and the demands placed upon it. Your acve and thoughtful participation is requested to make this experience both fun and worthwhile. Let’s get to work! Inspired to improve her city within your agency’s district—and hopefully for the benefit of others as well—Mayor Florida contacted your transportaon secretary and convinced her to make system preservation the number one transportaon priority for the state and your district. Following this discussion and the seing of a strategic preservation goal for the state, the transportaon secretary is requesting your agency’s help to determine how best to allocate your district’s $400 M budget to achieve a state of good repair for highway and bridge assets while addressing performance requirements across the remaining transportaon priories.

90 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Scenario #1: An Agency in PreservaonMode Inspired to improve her city within your agency’s district—and hopefully for the benefit of others as well—Mayor Florida contacted your transportaon secretary and convinced her to make system preservation the number one transportaon priority for the state and your district. Following this discussion and the seing of a strategic preservation goal for the state, the transportaon secretary is requesting your agency’s help to determine how best to allocate your district’s $400 M budget to achieve a state of good repair for highway and bridge assets while addressing performance requirements across the remaining transportaon priories. Acvity 1 –PerformanceMeasures andWeighng 1a. Weighting • (Parcipants). Review the pair wise comparison exercise in the supplemental worksheet to understand the weighng process. Record preferred weights on individual worksheets. • (Parcipants). As a group, complete the weighng exercise for each performance measure. Measures have been provided based on a sample data set obtained from the Utah DOT. These are examples of common measures only and do not reflect all the measures that the tool can incorporate. 1b. Weighting Override After you presented your weights to your transportaon secretary, she has provided the following guidance for your weights (Table 1). Your district must use these weights to complete the exercise [Expert Override]. The weights of the group can be further explored in Acvity 4. Table 1. Required performance measures and weights. Performance Measure Weight Pavement IRI 15% Pavement OCI 15% Number of Jobs Created 5% Bridge OCI 45% Number of Crashes 15% Level of Service 5% TOTAL 100% Note: IRI = interna onal roughness index; OCI = overall condi on index.

Scenario Handouts 91 Acvity 2 – Target Seng/UnconstrainedNeeds 2a. Set Targets – TF4 The agency must address preservation as its priority. What targets are optimal? • (Parcipants). Discuss and record targets for each performance measure in Table 2 Table 2. Proposed targets. Performance Measure Target Average IRI % Pavements in “Good” or Be‹er Condition Total Jobs Created % Bridges in “Good” or Be‹er Condition Total Number of Crashes % of Congested Roads Note: IRI of 80 and 85% for pavement/bridge percentages are “good” for this data set. Additionally, for the data set provided, 15,000 jobs, 2,200 crashes, and 10% congested roads represent near opmal conditions. 2b. Develop Unconstrained Needs – TF4 • How much would it cost to achieve your targets listed in Table 2? • Would it be valuable to know the total costs required to achieve LOWER targets? Record reduced targets in Table 3. • Use TF4 to input lower target values from Table 3 and record total cost: Table 3. Reduced targets. Performance Measure REDUCEDTarget Average IRI % Pavements in “Good” or Be‹er Condition Total Jobs Created % Bridges in “Good” or Be‹er Condition Total Number of Crashes % of Congested Roads

92 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance The mayor and secretary are on the same page; however, the legislature has also established performance targets (Table 4) for use in priorizing projects. These have been mandated. • Determine and record the unconstrained cost of meeng these mandated targets across all performance areas: • Use these targets for the remainder of the exercise Table 4. Mandated performance targets. Performance Measure Target Average IRI 80 % Pavements in “Good” or Be‹er Condition 85% Total Jobs Created 15000 % Bridges in “Good” or Be‹er Condition 85% Total Number of Crashes 2200 % of Congested Roads 10% Acvity 3 – Constrained ProgramOpmizaon In this exercise, the group will develop an optimal program based on the mandated performance targets. Addional targets can be tested in Acvity 4. Given the mandated performance targets, answer the following quesons and record your results: • Can 85% good or be‹er condion be achieved for pavement and bridge assets with a total budget of $400 M? • Is the $400 M budget sufficient to achieve 85% good or be‹er condion for bridge and pavement assets and ensure that total crashes do not exceed 2,200? • Is the $400 M budget sufficient to achieve 85% good or be‹er condion for bridge and pavement assets and ensure that the percentage of congested roadways does not exceed 20% after removing the crash constraint? • As a gesture of good will, your agency decides to perhaps endorse implementaon of the governor’s signature expansion project. If the $400 M budget is maintained, can a pavement average of 80 IRI and 85% of bridge assets in good or be‹er condition be achieved if a poron of the budget is earmarked for the $32 M expansion project (#280)? (You might want to try both with and without the 20% congeson constraint.)

Scenario Handouts 93 Given your analysis, what would your agency’s recommended budget and outcomes look like and/or what total budget would you request? (Choose your preferred allocaon and performance outcomes to share with the group during report out.) Outputs Allocated Budget Program Areas Pavement Bridge Safety Mobility Total Allocated Budget ($M) Outputs Performance Measures Performance Measures Average IRI (inches/mile) % of Pavements in "Good" or Beer Condition Total Jobs Created % of Bridges in "Good" or Beer Condition Total Number of Crashes % of Congested Roads Values Acvity 4 – Your Budget Now that you know how the tool works, take some me to evaluate a larger or smaller budget ($350–$500 M). Acvies may include determining the following (example of $500 M budget is provided): 1. The optimal allocaon for your budget using your original weights in exercise 1a (Remove the expert override) 2. The outcomes of different targets using these weights You can also use Trade offs 4, 5, and 6 to conduct addional analyses: • Targets (TF4) – Lower targets unl a minimum budget less than $500 M is achieved • Budget Allocaons (TF5) – Run opmizaon at $500 M with previous preferences and choose other budget allocaons (all totaling to $500 M) • Weights (TF6) – Use weights from Acvity 1 and re priorize for $500 M

94 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Workshop: 017 Cross Asset Allocaon (NCHRP Project 08 91) Monday, April 28, 2014, 8:30 a.m. – Noon Hello and welcome. You are here today to bring the NCHRP Project 08 91 cross asset resource allocaon framework to life. You have been assigned to a team that will operate as a transportaon agency. You will navigate through a case study that is designed to simulate a real world decision environment and arrive at a recommended allocaon strategy given the priories of your agency and the demands placed upon it. Your acve and thoughtful participation is requested to make this experience both fun and worthwhile. Let’s get to work! How did your state governor become the most liked/ tweeted/ followed figure in the state? “It’s simple,” he says, “give the people what they want.” As the former director of your agency, the governor has decided to run for a reelecon on a plaorm of transportaon system expansion and job creaon. Immediately following his successful campaign speech, the governor contacted the director of your agency to discuss how to bring his vision to life. “I promised congeson reduction because I know that’s what resonates with my voters,” he said, “and it will create 15,000 new jobs in your district. But I know from being in your shoes not long ago that we must also take care of what we have, especially our bridges.” Your DOT director is enlisng your help to evaluate whether it is truly possible to achieve an acceptable level of service on roadways in your district while also addressing other transportaon priories—all for a total budget of $400 M.

Scenario Handouts 95 Scenario #2: Economic Development and Mobility How did your state governor become the most liked/ tweeted/ followed figure in the state? “It’s simple,” he says, “give the people what they want.” As the former director of your state DOT, the governor has decided to run for a reelecon on a platform of transportaon system expansion and job creaon. Immediately following his successful campaign speech, the governor contacted the director of your agency to discuss how to bring his vision to life. “I promised congeson reduction because I know that’s what resonates with my voters,” he said, “and it will create 15,000 new jobs in your district. But I know from being in your shoes not long ago that we must also take care of what we have, especially our bridges.” Your DOT director is enlisng your help to evaluate whether it is truly possible to achieve an acceptable level of service on roadways in your district while also addressing all other transportaon priories—for a total budget of $400 M. Acvity 1 –Performance Measures and Weighng 1a. Weighting • (Parcipants). Review the pair wise comparison exercise in the supplemental worksheet to understand the weighng process. Record preferred weights on individual worksheets. • (Parcipants). As a group, complete the weighng exercise for each performance measure. Measures have been provided based on a sample data set obtained from the Utah DOT. These are examples of common measures only and do not reflect all the measures that the tool can incorporate. 1b. Weighting Override With a strategic vision of system expansion and job creaon in mind, the governor and state DOT director weighed various transportaon priories against each other to assign relative importance (Table 1). Your district must use these weights to complete the exercise [Expert Override]. The weights of the group can be further explored in Acvity 4. Table 1. Required performance measures and weights. Performance Measure Weight Pavement IRI 10% Pavement OCI 10% Number of Jobs Created 20% Bridge OCI 20% Number of Crashes 10% Level of Service 30% TOTAL 100%

96 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Acvity 2 – Target Seng/ UnconstrainedNeeds 2a. Set Targets – TF4 • The agency must show the governor that it is addressing his priories in the district’s capital program. What targets are optimal to meet his desires? • (Parcipants). Discuss and record targets for each performance measure in Table 2. Table 2. Proposed targets. Performance Measure Target Average IRI % Pavements in “Good” or BeŽer Condition Total Jobs Created % Bridges in “Good” or BeŽer Condition Total Number of Crashes % of Congested Roads Note: IRI of 80 and 85% for pavement/bridge percentages are “good” for this data set. Additionally, for the data set provided, 15,000 jobs, 2,200 crashes, and 10% congested roads represent near opmal conditions. 2b. Develop Unconstrained Needs – TF4 • How much would it cost to achieve your targets listed in Table 2? • Would it be valuable to know the total costs required to achieve LOWER targets? Record reduced targets in Table 3. • Use TF4 to input lower target values from Table 3 and record total cost: Table 3. Reduced targets. Performance Measure REDUCEDTarget Average IRI % Pavements in “Good” or BeŽer Condition Total Jobs Created % Bridges in “Good” or BeŽer Condition Total Number of Crashes % of Congested Roads

Scenario Handouts 97 • The legislature has also established performance targets (Table 4) for use in priorizing projects. These have been mandated. • Determine and record the unconstrained cost of meeng these mandated targets across all performance areas: • Use these targets for the remainder of the exercise Table 4. Mandated performance targets. Performance Measure Target Average IRI 80 % Pavements in “Good” or Be‡er Condition 85% Total Jobs Created 15000 % Bridges in “Good” or Be‡er Condition 85% Total Number of Crashes 2200 % of Congested Roads 10% Acvity 3 – Constrained ProgramOpmizaon In this exercise, the group will develop an optimal program based on the mandated performance targets. Addional targets can be tested in Acvity 4. Given the mandated performance targets, answer the following quesons: • If 15,000 total jobs created be achieved with a total budget of $400 M, how do the programmed outcomes compare with the mandated targets/what happens to congeson? Does it seem like 15,000 jobs will allow for no more than 10% congested roads? • Is the $400 M budget sufficient to achieve 85% good or be‡er condion for bridge assets if you must also ensure that there are no more than 2,200 crashes? What happens to congeson? • Is the $400 M budget sufficient to achieve 85% good or be‡er condion for bridge and pavement assets and ensure that the percentage of congested roadways does not exceed 20% after removing the crash constraint? To increase his popularity with voters who are concerned about congeson, the governor has asked your agency to implement a major expansion project. If the $400 M budget constraint is maintained, can the targets of 15,000 jobs created and no more than 15% congested roadways be achieved if a portion of the budget is earmarked for a $32 M expansion project (#280)?

98 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Given your analysis, what would your agency’s recommended budget and outcomes look like and/or what total budget would you request? (Choose your preferred allocaon and performance outcomes to share with the group during report out.) Outputs Allocated Budget Program Areas Pavement Bridge Safety Mobility Total Allocated Budget ($M) Outputs Performance Measures Performance Measures Average IRI (inches/mile) % of Pavements in "Good" or Beer Condition Total Jobs Created % of Bridges in "Good" or Beer Condition Total Number of Crashes % of Congested Roads Values Acvity 4 – Your Budget Now that you know how the tool works, take some me to evaluate a larger or smaller budget ($350–$500 M). Acvies may include determining the following (example of $500 M budget is provided): 1. The optimal allocaon for your budget using your original weights in exercise 1a (Remove the expert override) 2. The outcomes of different targets using these weights You can also use Trade offs 4, 5, and 6 to conduct addional analyses: • Targets (TF4) – Lower targets unl a minimum budget less than $500 M is achieved • Budget Allocaons (TF5) – Run opmizaon at $500 M with previous preferences and choose other budget allocaons (all totaling to $500 M) • Weights (TF6) – Use weights from Acvity 1 and re priorize for $500 M

Scenario Handouts 99 Workshop: 017 Cross Asset Allocaon (NCHRP Project 08 91) Monday, April 28, 2014, 8:30 a.m. – Noon Hello and welcome. You are here today to bring the NCHRP Project 08 91 cross asset resource allocaon framework to life. You have been assigned to a team that will operate as a transportaon agency. You will navigate through a case study that is designed to simulate a real world decision environment and arrive at a recommended allocaon strategy given the priories of your agency and the demands placed upon it. Your acve and thoughtful participation is requested to make this experience both fun and worthwhile. Let’s get to work! Scenario #3: Confused Legislature For the last 10 years, to satisfy the desires of your state’s constuents, your state legislature has set aside $250 M in funding for major system expansion projects, leaving less money for system preservation (total budget of $400 M). When a small bridge in a remote area of the state collapsed last month— fortunately resulting in no fatalities or injuries—the legislature quickly blamed your agency for not beer preserving its highways and bridges. However, it failed to reexamine its historical set aside for mobility projects. Faced with the recent catastrophe, your agency must show the legislature that you are addressing (or trying to address) pavement and bridge condition as part of your current priorized program while complying with the legislative mandate to priorize mobility projects. The legislature still requires a 30% priority weighng for mobility projects in the priorizaon program.

100 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Scenario #3: Confused Legislature For the last 10 years, to satisfy the desires of your state’s constuents, your state legislature has set aside $250 M in funding for major system expansion projects, leaving less money for system preservaon (total budget of $400 M). When a small bridge in a remote area of the state collapsed last month—fortunately resulting in no fatalities or injuries—the legislature quickly blamed your agency for not beer preserving its highways and bridges. However, it failed to reexamine its historical set aside for mobility projects. Faced with the recent catastrophe, your agency must show the legislature that you are addressing (or trying to address) pavement and bridge condion as part of your agency’s current priorized program, while complying with the legislative mandate to priorize mobility projects. The legislature still requires a 30% priority weighng for mobility projects in the priorizaon program. Acvity 1 –Performance Measures and Weighng 1a. Weighting • (Parcipants). Review the pair wise comparison exercise in the supplemental worksheet to understand the weighng process. Record preferred weights on individual worksheets. • (Parcipants). As a group, complete the weighng exercise for each performance measure. Measures have been provided based on a sample data set obtained from the Utah DOT. These are examples of common measures only and do not reflect all the measures that the tool can incorporate. 1b. Weighting Override In Senate Bill 5000, the legislature has required the following weights for transportaon priories (Table 1). Your agency must use these weights to complete the exercise [Expert Override]. The weights of the group can be further explored in Acvity 4. Table 1. Required performance measures and weights. Performance Measure Weight Pavement IRI 15% Pavement OCI 15% Number of Jobs Created 10% Bridge OCI 20% Number of Crashes 10% Level of Service 30% TOTAL 100%

Scenario Handouts 101 Acvity 2 – Target Seng/ Unconstrained Needs 2a. Set Targets – TF4 Your agency wants to address preservation as its priority; however, the legislature is concerned about increasing congeson levels in the state. What targets are optimal? • (Parcipants). Discuss and record targets for each performance measure in Table 2. Table 2. Proposed targets. Performance Measure Target Average IRI % Pavements in “Good” or Be’er Condition Total Jobs Created % Bridges in “Good” or Be’er Condition Total Number of Crashes % of Congested Roads Note: IRI of 80 and 85% for pavement/bridge percentages are “good” for this data set. Additionally, for the data set provided, 15,000 jobs, 2,200 crashes, and 10% congested roads represent near opmal conditions. 2b. Develop Unconstrained Needs – TF4 • How much would it cost to achieve your targets listed in Table 2? • Would it be valuable to know the total costs required to achieve LOWER targets? Record reduced targets in Table 3. • Use TF4 to input lower target values from Table 3 and record total cost: Table 3. Reduced targets. Performance Measure REDUCEDTarget Average IRI % Pavements in “Good” or Be’er Condition Total Jobs Created % Bridges in “Good” or Be’er Condition Total Number of Crashes % of Congested Roads

102 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Immediately following the catastrophe, your legislature established performance based planning requirements to increase accountability and transparency in transportaon decision making. As part of this exercise, the legislature set performance targets to define state of good repair thresholds across performance categories (Table 4). • Determine and record the unconstrained cost of meeng these mandated targets across all performance areas: • Use these targets for the remainder of the exercise Table 4. Mandated performance targets. Performance Measure Target Average IRI 80 % Pavements in “Good” or Beer Condition 85% Total Jobs Created 15000 % Bridges in “Good” or Beer Condition 85% Total Number of Crashes 2200 % of Congested Roads 10% Acvity 3 – Constrained Program Opmizaon In this exercise, the group will develop an optimal program based on the Table 4 mandated performance targets. Addional targets can be tested in Acvity 4. Given the mandated performance targets, answer the following quesons: • Can 85% good or beer condion can be achieved for pavement and bridge assets when $250 M of the total $400 M budget is set aside for mobility projects? • Can 80% be achieved for pavement and bridge when $250 M of the total $400 M budget is set aside for mobility projects? What happens to congeson performance? • Can 85% good or beer condion be achieved for pavement and bridge assets if the total budget is increased to $450 M and the $250 M set aside for mobility is maintained? What if the number of crashes cannot exceed 2,200? • At a total budget of $400 M, your legislature will lower the bridge and pavement state of good repair threshold to 80% good or beer, but will also earmark your agency’s critical $29 M pavement improvement project (#114) in the same budget. Is it possible to implement the $29 M project and achieve 80% good or beer condion for pavement and bridge assets when $250 M of the $400 M budge is reserved for mobility projects? With the same budget constraint and set aside, is it possible to implement the $29 M project and achieve the original target of 85% good or beer condition for pavement and bridge assets?

Scenario Handouts 103 • Is it possible to implement the $29 M project and achieve 85% good or beer condition for pavement and bridge assets if the total budget is increased to $450 M and the set aside is maintained? Given your analysis, what would your agency’s recommended budget and outcomes look like and/or what total budget would you request? (Choose your preferred alloca†on and performance outcomes to share with the group during report out.) Outputs Allocated Budget Program Areas Pavement Bridge Safety Mobility Total Allocated Budget ($M) Outputs Performance Measures Performance Measures Average IRI (inches/mile) % of Pavements in "Good" or Beer Condition Total Jobs Created % of Bridges in "Good" or Beer Condition Total Number of Crashes % of Congested Roads Values Acvity 4 – Your Budget Now that you know how the tool works, take some me to evaluate a larger or smaller budget ($350– $500 M). Acvities may include determining the following (example of $500 M budget is provided): 1. The optimal allocaon for your budget using your original weights in exercise 1a (Remove the expert override) 2. The outcomes of different targets using these weights You can also use Trade offs 4, 5, and 6 to conduct addional analyses: • Targets (TF4) – Lower targets unl a minimum budget less than $500 M is achieved • Budget Allocaons (TF5) – Run opmizaon at $500 M with previous preferences and choose other budget allocaons (all totaling to $500 M) • Weights (TF6) – Use weights from Acvity 1 and re priorize for $500 M

104 A P P E N D I X D Asset Management Conference Workshop On April 28, 2014, 20 people registered for the TRB 10th Annual Asset Management Con- ference in Miami, Florida, for a workshop where participants used role playing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool’s usability/value and the need for refinements. The areas of expertise of the attendees included asset management, bridge design, bridge modeling, bridge planning, central precon- struction, operations, pavement management, pavement modeling, program development, pro- gram finance, project development, traffic and safety, traffic management, traffic operations, and transportation. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • A few refinements were suggested regarding making the mechanics of using the tool more user-friendly. For example, the user currently weights performance measures against each other using a numerical, nine-point comparative scale. Attendees suggested that a sliding bar between measures might be easier to use for this task to avoid confusion about how to value relative priorities. • There was a desire to save each scenario/run within the tool so that subsequent runs could be compared. • A participant asked what capacity the tool would have to support risk and sensitivity analysis, particularly since MAP-21 includes requirements for agencies to incorporate them into their planning and decision-making processes. Risk will be incorporated into the tool by including standard deviations around the budget and performance measures, which will then enable the development of confidence factors. It was also pointed out that economic models already exist and may be useful to agencies in accommodating these MAP-21 provisions. Opportunities for Tool • Currently, the tool’s output gives the value of performance measures as a result of implement- ing certain projects or portfolios of projects. Some attendees expressed a desire to show trend lines, not just points in time, commenting that it would be useful to see if asset conditions are improving or worsening. • Participants expressed a desire to have the tool show the impact of the delay of a project, with respect to both project cost and system performance. Workshop Discussions

Workshop Discussions 105 • Participants expressed a desire for the tool to reflect the entire network of a state/agency and not just one data set of projects. Integrating the tool with existing network data sets (such as pavement condition indices) would be useful. The research team pointed out that further work and refinement would allow for different classifications of roadways and their value on the network to be addressed within the tool. Additional Discussion/Observations/Concerns • There was discussion on what performance measures/allocation areas should be included in the tool. The sample data set used for the Miami workshop included safety, which not all DOTs consider to be a stand-alone allocation area. The flexibility of the tool allows for customiza- tion so that states/agencies can use whichever areas/performance measures work best for their unique circumstances and decision-making support needs. • It was noted that the prototype tool depends on data being entered for each project, including the impact of the project on various performance measures. Concern was expressed that this type of information does not exist in many states/agencies, and the tool is only as good as the data that are entered into it. The research team acknowledged that executive leadership will have to be convinced of the value of such data collection and its reliability and further noted that as states/MPOs continue to expand their data sets, many mandated by MAP-21, informa- tion will be more readily available for use within the tool. Conclusions Both the cross-asset resource allocation framework and the tool prototype were well received by the participants. Workshop attendees were active in their breakout group exercises, and the discussion was both lively and informative. Overall, participants indicated that there was value in the technical analysis capabilities of the tool as well as the ability to use the tool to support and inform decision-maker and stakeholder discussions regarding performance targets, measures, and investment strategies. The pre-workshop surveys indicated skepticism that a tool like the cross-asset allocation tool could be developed. While many saw the usefulness, there was genuine concern about imple- mentation. With the tool prototype now developed and tested with audiences across the country, questions about how the tool can be used have replaced those of if the tool can be developed. Utah Department of Transportation Workshop On June 16, 2014, in Salt Lake City, Utah, 25 workshop participants used role playing and real- life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included asset management, bridge design, bridge modeling, bridge planning, central preconstruction, operations, pavement management, pavement modeling, program development, program finance, project development, traffic and safety, traffic management, traffic operations, and transportation. Following are suggested or possible uses of the tool listed based on comments received from the participants. Opportunities for Tool • Optimize projects. Use existing management system to generate lists of project and then use this tool to optimize. At that point, the optimized projects can be used to feed STIP.

106 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance • Identify investment programs. Programs could be defined in a variety of ways, including: – Asset/operational classes, and – Regions. • Identify performance measures. Measures could be identified based on: – MAP-21 rulemaking, – State metrics, or – Differences in systems/measures (seemed to be some disagreement on OCI measure, for example). • Evaluate data availability and management systems, including: – Gap assessments of measures and predictive abilities, – Organize data for cross-asset before/after, and – Identify ability to automate linkage of systems to cross-asset tool. • Analyze investments. Participants suggested that this tool is not so much a “cross-asset” tool as a “cross-investment” tool. The tool could be expanded to look across modes and has the ability to consider performance with regard to operations (e.g., congestion) instead of just physical infrastructure. AASHTO SCOP/SCOPM Conference Workshop On June 20, 2014, in Scottsdale, Arizona, a combined AASHTO SCOP/SCOPM workshop was held with 21 participants using role playing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included bridges, construction, mobility, modes, operations, pavement, programming, safety, and transit. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • Develop a simple, understandable user guide. • To aid and help simplify the weighting process, develop a sliding-scale graphic approach (as opposed to the current 9/1 to 1/9 structure). • Focus on making the tool as user friendly as possible, specifically in terms of changing perfor- mance measures or program areas. • Additional consideration might be given to how agencies can generate candidate project lists. Research in this area might need to be conducted. • Tool guidelines should identify minimum data requirements and optional data. Opportunities for Tool • Could qualitative assessments (e.g., “high,” medium,” and “low” scores for a given perfor- mance area) be substituted for quantitative numbers if adequate data are not available? • How could the tool provide better outputs on job creation? Perhaps it could be linked to one of the SHRP 2 products to improve job creation forecasting. • Improve awareness of the tool by conducting a webinar, or apply some of the implementation lessons learned from SHRP 2. • NCHRP might consider an implementation/pilot program as follow-on research. • Include discussion of the tool in the quarterly FHWA roundtable—people could be put on the program to discuss the tool.

Workshop Discussions 107 Additional Discussion/Observations/Concerns • Would be interesting to look at how well the tool can work with an existing (unscrubbed) data set. • Concern that there are not predictive data at the project level. New Jersey Department of Transportation Workshop On June 25, 2014, in Trenton, New Jersey, seven workshop participants used role playing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included capital investment planning and development, pavement and drainage management, project management, project planning, statewide planning, and statewide strategies. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • Participants thought that it would be beneficial to add in funding splits to more accurately match sources of funding with eligible projects. • Participants thought that a sliding scale would help when it comes to setting weights. • Intrigued how to incorporate smart-growth policies into the tool. • Highlighted local system integration as locals actually maintain part of NHS, so would like tool to show their responsibility with and without local input. • Biggest concerns were how to incorporate program line items—for instance, bridge deck overlay budget is one line item, not a project-by-project data set. Opportunities for Tool • Not so much a “cross-asset” tool as a “cross-investment” tool; attendees liked that the process could be expanded to look across modes and has the ability to consider performance with regard to operations (e.g., congestion) instead of just physical infrastructure. • Participants liked having ability to compare scenarios and project sets against one another. • Liked looking at projects across metrics, recognizing linkage between drainage and roadway deterioration for example, or large-scale projects that affect several areas. • Liked that the process is data-driven—that is the direction they are going. Additional Discussion/Observations/Concerns • New Jersey is unique in having more flexibility with state and toll dollars, so appreciated concept of allocating funds that are not pre-dedicated to a specific silo. • There is a need for good data; wondered how accurate/reflective what they currently have is. • Participants were more likely to use top-down approach and were surprised to see bottom-up approach. • Concerned that the tool’s optimization could give different answer than management system optimization. • Lots of discussion around safety being important but not the driver of projects, usually tacked on in ancillary projects. • Said scale of project is important to identify when determining impacts like mobility. • Said that “everything works if you don’t measure it.”

108 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance North Dakota Department of Transportation Workshop On August 18, 2014, in Bismarck, North Dakota, 10 workshop participants used role playing and real-life planning scenarios to work with the tool prototype and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included bridges, construction, design, operations, pavement, planning, program- ming, and transportation programs. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • Does not tell when to build project just to build in x time frame. • Show stakeholders in real time. • Can maintenance be added? Opportunities for Tool • Is not linked to safety counter measures yet. • Values different than those of taxpayers out west. • Helpful to municipalities; move assets. • Optimize timing of project construction. • Get from pavement management to here. Additional Discussion/Observations/Concerns • In North Dakota, there were questions about how the tool fits into the current programming system. The agency is overwhelmed by the need to expand the system and is shifting from a perspective of “what’s best for pavement?” to “what’s best for the system?” • Concern about the subjective nature of some of the data examples was expressed. Partici- pants also noted that while this tool has subjective elements, it allows more objective analysis than the North Dakota Department of Transportation currently employs across asset classes. • The group noted that more data per measure would be beneficial to analysis and recognized some benefit to using the tool with external stakeholders. Illinois Department of Transportation Workshop On August 26, 2014, in Springfield, Illinois, 34 workshop participants used role playing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included bridges and structures, cost and estimate, highways, land acquisition, location studies, operations, pavement management, planning, performance and cost support, programming, project and environmental studies, structural services, systems planning and services, transpor- tation planning, and urban planning. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants.

Workshop Discussions 109 Suggestions for Refinement • Participant mentioned that weightings and targets should be set at the state rather than dis- trict level to direct investments made at all levels of the state. • In terms of implementing the tool for programming purposes, a participant suggested making a gradual transition and comparing outcomes from this approach to what would have been programmed using past processes. • Illinois has a highly centralized programming process, and a potential tool enhancement could be to provide recommended allocations by district given optimization programs. • There was a question concerning whether different phases of projects can be incorporated into the tool (e.g., preconstruction) even if they do not yet have tangible performance benefits so the district, and broadly Illinois DOT, can get credit for implementing this work. Opportunities for Tool • It was suggested that the tool would be most useful for capital programming. • The tool could be useful in informing target setting, which is required to be done by states under MAP-21. • It was noted that the tool could be used to better coordinate and communicate between adjoining districts. • There is value to the proposition of approach and the tool: – Compliance with federal requirements established under MAP-21. – Accountability, transparency (internally and externally with stakeholders and public), and transferability of knowledge and processes (e.g., for succession planning). – States are increasing adopting performance-based planning and programming as well as supporting tools and processes to improve decision-making capabilities and the abil- ity to communicate the rationale behind the consequences resulting from investment decisions. – The tool documents the decision process to support transparency and accountability. Additional Discussion/Observations/Concerns • The tool does not handle selecting scope of projects; projects are determined in individual management systems (e.g., using life-cycle–based activity selection) and then provided as inputs to the tool. • The tool has no predictive capabilities; the performance impacts with and without project implementation are inputs derived from individual data management systems with perfor- mance forecasting capabilities. • There were questions regarding whether the tool can handle set asides (e.g., for safety programs). • Current processes and tools constrain staff ’s abilities to effectively prioritize projects for fast- track capital program and to quickly respond to questions regarding project prioritization and programming. • Illinois has a centralized programming process. The central office distributes funding to dis- tricts, which are in most cases “spoon fed” prioritized projects. • There was limited acceptance of the suggested performance-based cross-asset allocation approach at the staff level (those in attendance). • In the past, federal funding has been primarily applied for expansion, while state resources have been primarily applied toward maintenance and preservation.

110 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance • There was interest from this group in knowing and reporting on where federal funding is going and what is being delivered as a result. • There was a question regarding how the tool can be applied at different levels of statewide planning, including by regional and local agencies. California Department of Transportation Workshop On August 27, 2014, in Sacramento, California, workshop participants used role playing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • Suggestion from the discussion of using climate change resiliency as a potential measure. • Discussion about using proxy measures where appropriate (e.g., percent trucks for goods moved). • It would be a good idea to develop a public outreach tool. This improved data visualization would allow the public to see if the system’s health is going up or down. • For Caltrans, worker safety in addition to roadway safety is an important department initiative. • Accessibility and community considerations (e.g., historical bridge) are not incorporated in current analysis. • A suggested enhancement—have the tool automatically diagnose inconsistent AHP choices; summarize projects programmed by district. • There are limitations of the framework and tool—primarily data requirement. It is not an easy process to define the framework, which is a significant policy process. Transparency/black-box issue (still exists to some extent). Opportunities for Tool • It was noted during the discussion that this tool enables comparison of benefits of dissimilar projects (e.g., culverts, pavement, and mobility). • Perceived value of tool: preprocessing effort at planning level as the original allocation among silos dictates what can be done within individual silos. • Tool is useful for communications (stakeholders, public, legislators). Additional Discussion/Observations/Concerns • There was discussion noting that there are not too many measures for multi-objective opti- mization and this will dilute their importance. • There was a desire for a repeatable, consistent method for rating projects. • Caltrans is looking at software or freeware options to support prioritization once criteria are determined. • Caltrans has concept and idea for multi-objective decision-making process but has not determined the selection criteria. • Caltrans’ budget has some funds that are committed and some (~$1 billion) that are discre- tionary. Caltrans is looking at how to spend discretionary funds. • Caltrans is investigating a road user charge because tax base is insufficient.

Workshop Discussions 111 • It was noted that the AHP in the tool is confusing. • At the asset management executive follow-up meeting: Caltrans has been talking about this cross-asset optimization process and is looking to implement. Kansas Department of Transportation Workshop On September 8, 2014, in Topeka, Kansas, 12 workshop participants used role playing and real- life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The areas of expertise of the attendees included bridges, budget, construction and materials, management engineering, pavement, performance measures, planning, program and project management, and transportation safety and technology. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • There was a question about how long the evaluation period is. Because it is 1 year and does not look out to impacts that might occur over 3 to 5 more years, there was an observation that DOTs seem to want a tool that would look at project impacts for more than just 1 year since impacts accrue over time. • Programming by goal area is difficult; the number of alternatives can become unmanageable if scopes keep changing. • There was concern from the participants about how much time is needed to build out the data to run the tool. During the discussion, the consultant noted that it can be quite an effort to build out the data depending on the quality and range of existing data. It was also noted that the DOT needs to get several bureaus together representing several areas in order to get a bal- anced view for the value weighting exercise. Kansas DOT noted that this tool would be helpful when putting together a long-range plan or an asset management plan. Opportunities for Tool • Kansas DOT commented that the tool could be helpful in giving stakeholders choices and trade-offs, but only if they understand the context of the decision. For example, allocating 5% of the overall construction budget to transit might not seem like a large percentage, but it is an enormous amount of funding relatively speaking to previous allocations. • There was significant discussion about how the tool might be used to gauge trade-offs when performance matters—if targets cannot be hit because you are losing funds. Additional Discussion/Observations/Concerns • Overall, Kansas DOT is very familiar with scoring and prioritizing projects, having used a pri- ority formula approach for well over 20 years. However, the optimization across asset classes during scoring and prioritization of projects is a new concept to Kansas DOT. • There was a conversation about total jobs and concern that it is subjective. They asked if the tool would work without that input. The answer is yes, and states can measure whatever they want. • There was discussion about the sorts of projects/asset classes that would be best considered by the tool. Specifically, a participant asked about including lighting projects, to which the consultant responded that for those smaller parts of projects, those probably should not be included as a class of project.

112 Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance Missouri Department of Transportation Workshop On September 9, 2014, in Jefferson City, Missouri, six workshop participants used role play- ing and real-life planning scenarios to work with the tool and provided the research team with feedback on the tool usability/value and the need for refinements. The expertise of the attendees included organizational performance, planning, and transportation system analysis. Following are possible refinements, based on participant feedback, that could help ensure that the tool best meets the participants’ agencies’ needs. In addition, there are suggested or possible uses of the tool listed based on comments received from the participants. Suggestions for Refinement • There was a question during the workshop about whether the tool can take a longer-term view. The response is that this is something that can be done, but Missouri DOT (or any other DOT) would have to have a measure that reflects length of time of measuring performance. For example, you would have to have remaining service life as a data set. • Missouri DOT notes that it has scored and evaluated trade-offs for pavement but has not opti- mized pavement. It asked if this tool is helpful for optimizing within a class. The consultant pointed out that this tool could be used at the district level to discuss and compare ports to highways and other modes. • There was a question about whether the tool would be able to help in knowing if goals can be achieved with a particular set of projects. • There was another comment that it would be helpful to compare benefits per mode rather than project by project. • There was a good discussion around the idea of using an expert panel to assign outcomes of projects and that it is okay if scores are not calculated with extreme correctness. Working through the exercise of assigning outcomes and the values of weighting exercise is a good place to start the discussion and builds on many assumptions that currently are not considered in a systematic way. • Currently, the tool’s output gives the value of performance measures as a result of implement- ing certain projects or portfolios of projects. Some attendees expressed a desire to show trend lines, not just points in time, commenting that it would be useful to see if asset conditions are improving or worsening. • Participants expressed a desire to have the tool show the impact of the delay of a project with respect to both project cost and system performance. • Participants expressed a desire for the tool to reflect the entire network of a state/agency and not just one data set of projects. Integrating the tool with existing network data sets (such as pavement condition indices) would be useful. The research team pointed out that further work and refinement would allow for different classifications of roadways and their value on the network to be addressed within the tool. • Need to make sure changing performance measures or program areas are user friendly. A friend- lier user interface is desired. Opportunities for Tool • The tool seems valuable within the MAP-21 context so a state can see how money is spent to achieve targets. • The tool is helpful in optimizing investment in maintenance. This way, a state can see if it invests significant amounts of additional funds in maintenance and does not use these amounts, then perhaps those funds can be used for other purposes.

Workshop Discussions 113 Additional Discussion/Observations/Concerns • This tool would help for consistency across some districts—meaning that some districts would embrace the tool more and some less. • There is a strong need to clearly document what types of data need to be loaded into the tool for it to work effectively. • Evolve the tool to include disinvestment; an evolving and solid approach to the current economic and financial challenges of transportation. • Types of data input will be critical to the usability of the tool for many DOTs. • Missouri DOT noted that districts try to reach statewide goals for pavement, bridges, and other areas, and that some districts are closer to achieving these goals than others. The consultant team commented that the tool can be used at the district level.

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 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 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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TRB’s National Cooperative Highway Research Program (NCHRP) Report 806: Guide to Cross-Asset Resource Allocation and the Impact on Transportation System Performance provides guidance and a spreadsheet tool to help managers with applying data-driven techniques to project prioritization, program development, scenario analysis, and target setting. The tool and guidebook are intended to assist managers with analyzing and communicating performance impacts of investment decisions.

The software is available online only and can be download from TRB’s website as an ISO image. Links to the ISO image and instructions for burning an ISO image are provided below.

Help on Burning an .ISO CD-ROM Image

Download the .ISO CD-ROM Image

(Warning: This is a large file and may take some time to download using a high-speed connection.)

Software Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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