Return on Investment in Transportation Asset Management Systems and Practices (2018) / Chapter Skim
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Pages 111-122
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111 A P P E N D I X A Literature Review This appendix details findings of a literature review conducted in 2015 to review literature related to calculating ROI of TAM investments. Appendix B includes an annotated bibliography detailing the materials that were reviewed.
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112 Return on Investment in Transportation Asset Management Systems and Practices While these references provide extensive information on the benefits of TAM in qualitative terms, there is relatively little information on how to quantify the benefits of TAM systems and procedures and measure the return on investments in them. Thus, the research team performed a literature review focused on documents published during the last decade on estimating the return on investments in systems and procedures supporting TAM.
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Appendix A 113 the recent literature on the quantification of transportation asset management is summarized according to: Quantitative Measures Used o Agency Data Collection, Processing, and Analysis Cost Savings o Reduced Expenditures for Asset Maintenance, Rehabilitation, and Replacement o Asset Condition o User Benefits Basis for Quantitative Analysis o Time Series o Controlled Field Experiments o Simulation o Breakeven Analysis The emphasis of this summary is on methods and measures, so most studies are mentioned multiple times depending on the approaches used in the studies. QUANTITATIVE MEASURES USED Agency Data Collection, Processing, and Analysis Cost Savings Demonstrating that the cost of a proposed TAM action will be more than offset by future savings in agency costs for data collection, processing, and analysis provides a strong basis for advocating the action.
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114 Return on Investment in Transportation Asset Management Systems and Practices person-hours required for physical inventory collection, acquisition cost for hardware and software, and annual maintenance expense. In a study for Michigan DOT, Dye (10)
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Appendix A 115 comments received by FHWA on the proposed rule, including those from AASHTO, questioned the cost and benefit assumptions in the RIA. Commonly cited issues in the comment are that the costs assumed by FHWA appear low, and that many agencies have already implemented an asset management approach, and thus have already gained the benefits projected by FHWA.
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116 Return on Investment in Transportation Asset Management Systems and Practices each investigated as potential methods in Phase 1 of this research. In Phase 2, the authors developed simulation and optimization tools for TxDOT right-of-way sections and budget decision makers.
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Appendix A 117 All of the above examples involve changes in pavement condition. Similar quantitative approaches could in theory be applied to changes in bridge condition, though in practice no such examples were identified in the review.
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118 Return on Investment in Transportation Asset Management Systems and Practices depending on whether the asset management action being evaluated has already been implemented or is a prospective implementation. The quantitative methods found in the literature review included the use of: Time series data on system-wide conditions before and after implementation of the actions Controlled field experiments to measure cost savings and differences in asset conditions with and without the actions Simulation of conditions with and without the actions Breakeven analysis in which benefits required to offset the cost of the actions are related to the scale of the system affected by the actions.
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Appendix A 119 Nokes (29) presents a quantitative analysis of the benefits from Heavy Vehicle Simulator (HVS)
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120 Return on Investment in Transportation Asset Management Systems and Practices prioritization procedures are significantly flawed, the tools will score better than current practice because the flawed elements are used to keep score. This is not a problem if using prediction models that have been independently verified, but this caution should be kept in mind in using unverified simulation models to assess their own usefulness.
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Appendix A 121 REFERENCES 1.
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122 Return on Investment in Transportation Asset Management Systems and Practices Operations: Final Report," prepared for the Wisconsin Department of Transportation and the Clear Roads Program, November 2010.
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