National Academies Press: OpenBook

Return on Investment in Transportation Asset Management Systems and Practices (2018)

Chapter: Chapter 5 - Using the ROI Calculator (ROI Tool)

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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Chapter 5 - Using the ROI Calculator (ROI Tool)." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

66 This chapter provides step-by-step instructions for using the spreadsheet-based ROI Calcula- tor (ROI Tool) that accompanies this report. The instructions detail data requirements of the tool, how to use the tool, and how to interpret the results of an analysis following the basic steps presented in Chapter 4. At the end of this chapter, two worked examples illustrate use of the tool. The ROI Tool is intended to support ROI analysis of a TAM system or business process improvement, such as new software system or improved data collection program. The tool sup- ports analysis of a variety of asset and improvement types. In the case of pavements and bridges, improvements that may impact a transportation agency’s capital investment strategy may be considered by importing into the tool results from a supplemental simulation performed in the FHWA’s HERS-ST or NBIAS, or in a third-party PMS. Additional guidance on the use of simulation results in the tool is provided in Appendix G. This tool estimates the benefits and costs of a potential investment by comparing a base case with an investment case. The base case is a business-as-usual scenario and reflects current prac- tices, conditions, and costs. The base case assumes that the current state of things will continue into the future. The investment case is a scenario in which the agency invests in a TAM improve- ment. This case reflects the costs of procuring, implementing, and operating the new system or process, as well as any benefits (cost savings) generated by the improvement. The ROI Tool displays results as a series of tables listing the undiscounted and present-value benefits and costs of the potential improvement. A series of corresponding charts also display the data in the tables. The results are summarized using four ROI measures: net present value (NPV); benefit-cost (B/C) ratio; internal rate of return (IRR); and payback period. The tool was tested in a pilot project that is summarized in Appendix F. System Requirements The spreadsheet-based ROI Tool is a Microsoft Excel workbook designed to run in Microsoft Excel 2010 or higher. The tool has been tested in Windows 7, Windows 10, and macOS 10.12 operating systems. Tool Components The ROI Tool consists of seven worksheets. It includes two input worksheets (Inputs and Additional Parameters), one results worksheet (Summary Results), and four calculation work- sheets (Cost Calcs, PMS Totals, PMS Base, and PMS Investment). Certain fields in the ROI Tool are hidden to streamline use of the tool; however, there are no locked fields or calculations, and the tool does not utilize plug-ins or macros. C H A P T E R 5 Using the ROI Calculator (ROI Tool)

Using the ROI Calculator (ROI Tool) 67 Mapping Framework Benefits and Costs to the ROI Tool In this guidebook, Chapter 2 presented information on the potential benefits and life cycle costs of TAM investments. Tables 5-1 and 5-2 list these potential benefits and costs, adding details that note where the related data can be entered in the ROI Tool. Using the ROI Tool Users of the ROI Tool will enter data in the Inputs and Additional Parameters worksheets, and then view the calculation details and results of the analysis by navigating between work- sheet tabs. The model includes various fixed, default parameters that users can override at their Direct and Indirect Agency Cost Savings (Benefits) ROI Tool Input Staff time savings from improved data collection and accessibility Staff time savings can be represented by the Agency Labor and Recurring Cost values. Cost savings from the optimization of investment strategies HERS-ST, PMS, or NBIAS results can be used to model the benefits of changing investment strategies. Lower costs from reductions in failure risks for critical assets (e.g., bridges) Agency benefits due to reductions in failure risks for critical assets are represented by Predicted Failure Incident values. Avoided outlays for legacy systems, including hardware maintenance and software updates The input values Hardware and Software Acquisition Costs, Recurring Costs, and Contractor Costs can all be used to show cost savings due to avoiding outlays. Enhanced reputation and level of public trust gained through information sharing This indirect benefit is not modeled in the tool because it is too difficult to quantify. Delayed capital expenditures due to increased asset life (residual value of assets) HERS-ST, PMS, or NBIAS results can be used to model the benefits of changing investment decisions. Worker safety (due to bundling of projects) Worker safety benefits are not broken out in their own category. However, these benefits could be modeled using Other Costs. Residual value (remaining asset value at end of analysis period) Residual value can be modeled using PMS or NBIAS results. User Cost Savings (Benefits) ROI Tool Input Vehicle operating cost savings (e.g., reduced wear and tear, and reduced fuel consumption) from smoother pavements or more direct routing (e.g., with bridge availability) Vehicle operating costs are entered using Operating Cost Model Parameters. Capacity Model Parameters are used to help estimate vehicle operating costs (when PMS results are used). Travel time savings Travel time savings are entered using Incident Cost Model Parameters. Accelerated improvements from timely asset management decisions or increased capacity to program maintenance and rehabilitation projects due to cost efficiency Benefits from accelerated improvements can be modeled using Predicted Failure Incidents. Reduced work zone delays Reduced work zone delays can be modeled using Incident Cost Model Parameters. Safety benefits User safety benefits can be modeled using Incident Cost Model Parameters. Benefits to the General Public (Social Benefits) ROI Tool Input Emission cost savings from smoother pavements or more direct routing Environmental user benefits can be modeled using Incident Cost Model Parameters. Reduced noise generation Benefits related to reduced noise generation are not modeled in the tool. Table 5-1. Benefits of potential TAM investments, mapped to the ROI Tool.

68 Return on Investment in Transportation Asset Management Systems and Practices discretion. Cells shaded in blue are input cells the user may edit. Unshaded cells should not be edited; they contain default values or formulas. The outputs of the tool are calculated automati- cally as the inputs are updated, and the results are presented in the Summary Results worksheet. To preserve the default values in the ROI Tool for future use, it is best to open the ROI Tool and immediately save the file to a unique filename specific to the current analysis. Inputs Worksheet The Inputs worksheet contains the necessary parameters for performing an ROI calculation, including general parameters, parameters for the base case, and parameters for the investment case. A partial view of the Inputs worksheet is shown in Figure 5-1. Not shown in this screenshot are the tables for entering results from HERS-ST, NBIAS, and/or an agency PMS. General Parameters This section of the Inputs worksheet describes the process of entering general parameters into the ROI Tool. The general parameters are used to define the time period, discount rate, and costs for the analysis. The ROI Tool contains default values for the general parameters that the user may choose to override. The fields for general parameters are shown in Figure 5-2. The following procedure is used to complete the inputs for the General Parameters section of the Inputs worksheet: 1. Define the Analysis Start Year. The default value is 2018, meaning that the analysis will start in 2018. The suggested value for the start year is the year during which the improvement scenario will begin. 2. Define the Analysis Period (years). The default value is 20 years, meaning that the tool will estimate benefits and costs over a 20-year period beginning at the Analysis Start Year. The Non-Recurring Costs ROI Tool Input Hardware and software acquisition Acquisition costs can be entered in Hardware & Software Acquisition. Installation Installation costs can be entered in Hardware & Software Acquisition and/or Contractor Costs. Training Training costs can be entered in Hardware & Software Acquisition, Contractor Costs, and/or Other Costs. Decommissioning Decommissioning costs can be entered in Hardware & Software Acquisition, Contractor Costs, and/or Other Costs. Shift in investments A shift in investments could be modeled in Other Costs. Recurring Costs ROI Tool Input Maintenance and repair Maintenance and repair costs can be entered in Recurring Costs. Operating expenses Operating costs can be entered in Recurring Costs. Software maintenance costs Software maintenance costs can be entered in Recurring Costs. Software updates Software update costs can be entered in Recurring Costs. Data collection and data analysis cost Data costs can be entered in Recurring Costs. Table 5-2. Costs of potential TAM investments, mapped to the ROI Tool.

Using the ROI Calculator (ROI Tool) 69 Figure 5-1. Inputs worksheet. Figure 5-2. General parameters.

70 Return on Investment in Transportation Asset Management Systems and Practices analysis period may vary according to the purpose of the analysis. It can be as short as 1 year, but analysts frequently select a period of 5 years, 10 years, or 20 years. 3. Define the Discount Rate. The discount rate is used to calculate the present value of future benefits and costs, reflecting the time value of money. The default value in the ROI Tool is 4%, meaning that future benefits and costs will be discounted by 4% annually to allow compari- sons across time. A 4% discount rate was selected in accordance with historic real discount rates between 3%–5% (see discussion in Chapter 2). A rate of 4% also avoids overstating potential benefits and is consistent with the rate used in the case studies. 4. Define the Annual Cost per Full Time Equivalent (FTE) ($). The annual cost per FTE is a unit measure of labor cost and is used to calculate annual agency labor costs. The default value is $75,000, meaning that each FTE costs the agency $75,000 per year including salary and benefits. A higher number can be input to allow for additional overhead costs if these costs have been quantified and are expected to change as a result of the investment. 5. Define the Personal Travel Value of Time ($/veh-hr). This parameter is used to measure the cost of delay to a non-business motorist. The default value is $12.30 per vehicle-hour, mean- ing that each vehicle-hour of delay results in a user cost of $12.30. 6. Define the Business Value of Time ($/veh-hr). This parameter is used to measure the cost of delay to a business motorist. The default value is $28.00 per vehicle-hour, meaning that each vehicle-hour of delay results in a user cost of $28.00. 7. Define the Multiplier for Updating User and Social Costs. This multiplier can amplify or reduce the user and social costs in the calculation. The default value is 1.00, meaning that the user and social costs are not modified. When modifying this input, care is needed to use a realistic value in order to avoid inadvertently exaggerating or underestimating the result. 8. Define the Agency Cost per Incident. This parameter is used to calculate agency cost incurred in the event an incident occurs. This cost is relevant if the investment is expected to reduce incidents. A typical incident might be an asset failure that requires immediate replacement, as well as road closure; however, the tool is structured to support flexible definition of what constitutes an incident. User costs parameters for incidents are defined on the Additional Parameters worksheet. The final three fields in the General Parameters section of the Inputs worksheet are “Yes/No” statements regarding additional analyses. If the agency using the ROI Tool has performed analy- ses using HERS-ST, an agency PMS, and/or NBIAS, and wishes to include additional data from those analyses in the ROI Tool, the analyst would indicate that choice here. Generally, results from one or more of these other tools would be included if the investment being evaluated may impact the agency’s capital investment strategy for pavement and/or bridges. Data from HERS-ST or a PMS may be used to capture impacts of changes to pavement investments. NBIAS may be used to capture impacts of changes in bridge investments. Selecting “Yes” for any or all of these fields enables access to other parts of the ROI Tool where the analyst can input data from the selected tools. Use of these tools is further detailed in Appendix G. The following procedure is used to complete the inputs for the final parameters in the General Parameters section of the Inputs worksheet: 1. Select whether or not to include data from HERS-ST Analysis. The default answer for this question is “No.” To override the default and answer “Yes,” click in the “Override” cell in the appropriate row and select “Yes” from the drop-down menu. Selecting “Yes” unlocks addi- tional data fields further down the Inputs worksheet. 2. Select whether or not to include data from Supplemental PMS Analysis. The default answer for this question is “No.” To override the default and answer “Yes,” click in the “Override” cell in the appropriate row and select “Yes” from the drop-down menu. Selecting “Yes” unlocks additional data fields further down the Inputs worksheet.

Using the ROI Calculator (ROI Tool) 71 3. Select whether or not to include data from NBIAS Analysis. The default answer for this ques- tion is “No.” To override the default and answer “Yes,” click in the “Override” cell in the appro- priate row and select “Yes” from the drop-down menu. Selecting “Yes” unlocks additional data fields further down the Inputs worksheet. Figure 5-3 shows the additional analysis cells overridden with “Yes” responses, along with the drop-down menu. Base Case Parameters The base case is the no-build scenario against which the investment case is compared. The base case scenario should be realistic, reflecting current processes, policies, and costs. The base case parameters define the scenario in which no system investment or process change is made (see Figure 5-4). The following procedure is used to complete the inputs for the Base Case Parameters in the Inputs worksheet: 1. Enter the number of Agency Labor (FTEs) per year for the analysis period. This parameter captures the level of agency effort required to continue existing practices. For example, if a legacy system requires one FTE to operate, the base case would assume one FTE for each year of the analysis. 2. Enter the Hardware & Software Acquisition ($) costs for each year in the analysis period. This parameter captures the costs of purchasing any hardware or software used in the base case (i.e., hardware costs, software costs, installation costs, training costs, and other Figure 5-3. Additional analysis drop-down selection. Figure 5-4. Base case parameters.

72 Return on Investment in Transportation Asset Management Systems and Practices non-recurring system costs, including any TAM system acquisition costs that are part of the base case). If the base case involves no hardware and software acquisition costs, the value of this parameter should be zero. 3. Enter the Recurring Costs ($) for each year in the analysis period. This parameter captures recurring costs that are part of maintaining the TAM hardware or software. Examples of recurring costs include data collection and analysis costs, operating expenses, maintenance and repair costs, and software update costs. This parameter does not include the recurring costs of the transportation assets being managed; this parameter focuses on the recurring costs of the management system. 4. Enter the Contractor Costs ($) for each year in the analysis period. This parameter is the annual contractor cost related to operating the TAM improvement in the base case. 5. Enter the Other Costs ($) for each year in the analysis period. This parameter includes any other costs related to operating the TAM system in the base case that are not captured by the previous parameters. 6. Enter the Predicted Failure Incidents for each year in the analysis period. This value is the number of predicted failure incidents. A definition of what constitutes a failure incident should be provided with each ROI calculation. For example, if an agency is evaluating the potential acquisition of a bridge management system and defines a failure incident as struc- tural bridge failure, the value of this parameter would be the number of predicted structural bridge failures. This parameter is used to calculate agency and user costs resulting from the predicted incidents. Investment Case Parameters The investment case is the build scenario in which an agency makes a TAM system invest- ment or process change. The investment case scenario should focus on the implementation of a TAM system. As seen in Figure 5-5, the investment case uses the same parameters as the base case, but with different input values that reflect the different benefits and costs of the investment scenario. The following procedure is used to complete the inputs for the Investment Case Parameters in the Inputs worksheet: 1. Enter the number of Agency Labor (FTEs) per year for the analysis period. This parameter captures the level of agency effort required in the investment case to implement the TAM improvements. For example, if a new asset management system requires three FTEs to oper- ate, the investment case would assume three FTEs for each year of the analysis. 2. Enter the Hardware & Software Acquisition ($) costs for each year in the analysis period. This parameter captures the cost of acquiring any TAM hardware or software used in the investment case. The acquisition costs include hardware and software purchase costs, instal- lation costs, training costs, and other non-recurring costs. Figure 5-5. Investment case parameters.

Using the ROI Calculator (ROI Tool) 73 3. Enter the Recurring Costs ($) for each year in the analysis period. This parameter captures recurring costs that are part of maintaining the TAM improvement. Examples of recurring costs include data collection and analysis costs, operating expenses, maintenance and repair costs, and costs for software updates. This parameter does not include the recurring costs of the transportation assets being managed; rather, it focuses on the recurring costs of the man- agement system/TAM investment. 4. Enter the Contractor Costs ($) for each year in the analysis period. This parameter is the annual contractor cost related to operating the TAM improvement. 5. Enter the Other Costs ($) for each year in the analysis period. This parameter includes any other costs related to operating the TAM improvement that are not captured by the previous parameters. 6. Enter the Predicted Failure Incidents for each year in the analysis period. This value is the number of predicted failure incidents that occur in the investment case, and it is used to cal- culate agency and user costs resulting from the predicted incidents. The investment case uses the same definition of a failure incident as the base case. For example, an agency evaluating the potential acquisition of a bridge management system that defined a failure incident as a structural bridge failure in the base case would define a failure incident as a structural bridge failure in the investment case. In the investment case, however, the value of this parameter would be the number of predicted structural bridge failures assuming the implementation of the proposed bridge management system (the investment). HERS-ST Results—Base Case If the user opts to include results from HERS-ST by selecting “Yes” in the general param- eters section, additional fields will be unlocked on the Inputs worksheet. The user will then be able to input data for the HERS-ST Results - Base Case (see Figure 5-6), and the HERS-ST Results - Investment Case (see Figure 5-7). Figure 5-6. HERS-ST results—base case. Figure 5-7. HERS-ST results—investment case.

74 Return on Investment in Transportation Asset Management Systems and Practices The following procedure is used to complete the inputs for the HERS-ST Results - Base Case in the Inputs worksheet: 1. Enter the Cost of Selected Improvements ($ 000) for each 5-year period in the analysis. The table defaults to four 5-year periods as each analysis period in HERS-ST is limited to 5 years. This value is the cost of highway pavement improvements, as modeled by HERS-ST, in the base case, represented in thousands of dollars. 2. Enter the VMT (M) for each 5-year period in the analysis. This value is the number of vehicle- miles traveled (VMT) on the highway system, as modeled by HERS-ST, in the base case, represented in millions of vehicle-miles. 3. Enter the User Cost ($/1000 VMT) for each 5-year period in the analysis. This value is the user cost, as modeled by HERS-ST, in the base case, represented in dollars per thousand VMT. 4. Enter the Maintenance Costs ($/mile of road) for each 5-year period in the analysis. This value is the unit cost of highway maintenance, as modeled by HERS-ST, in the base case, rep- resented in dollars per mile. Highway maintenance is a primary driver of agency cost; thus, any reduction in maintenance cost is an agency benefit. 5. Enter the Emissions Costs ($/1000 VMT) for each 5-year period in the analysis. This value is the unit cost of emissions, as modeled by HERS-ST, in the base case, represented in dollars per thousand VMT. This parameter captures the cost of air pollution generated by motor vehicle traffic. Emissions can vary based on traffic, vehicle mix, and speed. 6. Enter the Miles of Road (miles) for each 5-year period in the analysis. This value is the num- ber of miles of road in the agency’s highway system, as modeled by HERS-ST, in the base case. HERS-ST Results—Investment Case The HERS-ST results—investment case is the scenario in which an agency makes a TAM system investment or process change. The investment case uses the same parameters as the base case, but with different values that reflect the benefits and costs of the investment scenario (see Figure 5-7). The following procedure is used to complete the inputs for the HERS-ST Results - Investment Case in the Inputs worksheet: 1. Enter the Cost of Selected Improvements ($ 000) for each 5-year period in the analysis. This value is the cost of highway pavement improvements, as modeled by HERS-ST, in the invest- ment case, represented in thousands of dollars. 2. Enter the VMT (M) for each 5-year period in the analysis. This value is the number of VMT on the highway system, as modeled by HERS-ST, in the investment case, represented in millions of vehicle-miles. 3. Enter the User Cost ($/1000 VMT) for each 5-year period in the analysis. This value is the user cost, as modeled by HERS-ST, in the investment case, represented in dollars per thousand VMT. 4. Enter the Maintenance Costs ($/mile of road) for each 5-year period in the analysis. This value is the unit cost of highway maintenance, as modeled by HERS-ST, in the investment case, represented in dollars per mile. Highway maintenance is a primary driver of agency cost; thus, any reduction in maintenance cost is an agency benefit. 5. Enter the Emissions Costs ($/1000 VMT) for each 5-year period in the analysis. This value is the unit cost of emissions, as modeled by HERS-ST, in the investment case, represented in dollars per thousand VMT. This parameter captures the cost of air pollution generated by motor vehicle traffic. Emissions can vary based on traffic, vehicle mix, and speed. 6. Enter the Miles of Road (miles) for each 5-year period in the analysis. This value is the number of miles of road in the agency’s highway system, as modeled by HERS-ST, in the investment case.

Using the ROI Calculator (ROI Tool) 75 PMS Analysis Groups If the user opts to include results from a PMS by selecting “Yes” in the general parameters section, additional fields will be unlocked on the Inputs worksheet. To complete this section, the user will first need to fill in information defining the PMS Analysis Groups (see Figure 5-8). The fields in this table organize data for mileage, traffic, vehicle mix, and traffic growth rate by pave- ment group description. This breakdown is used to separate user costs and benefits by group description as shown on the tool’s Summary Results worksheet. Under the heading Group Description, Figure 5-8 shows three pavement groups—“Interstate,” “Non-Interstate NHS,” and “Non-NHS”—as an example. In actuality, the user may define these PMS analysis groups as desired, specifying as few as one and as many as 13 distinct groups (including “Other”). For each defined pavement group, the data input to the table may reflect a single representative road or average the data collected from a group of representative roads. The following procedure is used to complete the inputs that define the PMS Analysis Groups: 1. Enter the Group Description for each pavement group to be defined. The ROI Tool accepts up to 13 distinct group descriptions (including “Other”). The remaining steps are completed for each pavement group. 2. Enter the Base Year AADT (annual average daily traffic). This value is the average number of vehicles traveling over the pavement group (a road or representative group of roads) in a day. 3. Enter the Base Year Truck %. This value is the percentage of annual traffic composed of trucks. 4. Enter the Annual Growth Rate (%) for Autos. This value is the annual rate of traffic growth for cars, expressed as a percentage. 5. Enter the Annual Growth Rate (%) for Trucks. This value is the annual rate of traffic growth for trucks, expressed as a percentage. 6. Enter the Road Length (miles). This value is the length of road being analyzed in the PMS, expressed in number of miles. 7. Enter the Avg. Num. of Lanes. This value is the average number of lanes in the pavement group being analyzed. 8. Enter the Predom. Func. Class. The functional classification of a roadway identifies its role in the greater transportation network. This field allows the user to indicate the predominant functional classification of each pavement group being analyzed. Using a drop-down menu, the analyst can select from 13 options (including “Other”): 1-Rural Interstate 2-Rural Other Principal Arterial 6-Rural Minor Arterial Figure 5-8. PMS analysis groups.

76 Return on Investment in Transportation Asset Management Systems and Practices 7-Rural Major Collector 8-Rural Minor Collector 9-Rural Local 11-Urban Interstate 12-Urban Other Freeway/Expressway 14-Urban Other Principal Arterial 16-Urban Minor Arterial 17-Urban Collector 19-Urban Local Other [not numbered] The numbering of the options in the drop-down menu corresponds to the set of functional classification codes as listed in HERS-ST. PMS Results—Base Case PMS results entered into the ROI Tool for the base case will include expenditures, the backlog of needs, and the International Roughness Index (IRI) for each group. All of these are specified by year. As shown in Figures 5-9 and 5-10, agency expenditures and backlog are expressed in millions of dollars in the base case and the investment case. IRI values are used to predict travel time and operating costs utilizing cost models extracted from HERS-ST. The following procedure is used to complete the inputs for the PMS Results - Base Case in the Inputs worksheet: 1. Enter Agency Expenditures ($M) for each year in the analysis period. This value is the total expenditure on pavement, as modeled by the PMS, in each year in the base case, expressed in millions of dollars. 2. Enter the Backlog ($M) for each year in the analysis period. This value is the total pave- ment backlog, as modeled by the PMS, in each year in the base case, expressed in millions of dollars. 3. Enter the Average IRI by Group for each pavement group for each year in the analysis period in the base case. IRI is expressed in inches per mile. Notice that Figure 5-9 shows the three sample pavement groups—Interstate, Non-Interstate NHS, and Non-NHS—that were defined under PMS Analysis Groups. The tool automatically repopulates the necessary tables with the user-defined pavement groups. Figure 5-9. PMS results—base case.

Using the ROI Calculator (ROI Tool) 77 PMS Results—Investment Case Figure 5-10 shows the PMS results for the investment case. Inputs for this case are the same as for the base case, but the values are based on the investment case rather than the base case. The following procedure is used to complete the inputs for the PMS Results - Investment Case in the Inputs worksheet: 1. Enter Agency Expenditures ($M) for each year in the analysis period. This value is the total expenditure on pavement, as modeled by the PMS, in each year in the investment case, expressed in millions of dollars. 2. Enter the Backlog ($M) for each year in the analysis period. This value is the total pavement back- log, as modeled by the PMS, in each year in the investment case, expressed in millions of dollars. 3. Enter the Average IRI by Group for each pavement group for each year in the analysis period in the investment case. IRI is expressed in inches per mile. NBIAS Results—Base Case If the user has opted to include results from NBIAS by selecting “Yes” in the general param- eters section, additional fields will be unlocked on the Inputs worksheet. The user will be able to fill in the NBIAS Results - Base Case, shown in Figure 5-11, and the NBIAS Results - Investment Case, shown in Figure 5-12. The following procedure is used to complete the inputs for the NBIAS Results - Base Case in the Inputs worksheet: 1. Enter the Total Work Done ($M) for each year in the analysis period. This value is the cost of bridge work, as modeled by the NBIAS, performed in each year in the base case, expressed in millions of dollars. Figure 5-10. PMS results—investment case. Figure 5-11. NBIAS results—base case.

78 Return on Investment in Transportation Asset Management Systems and Practices 2. Enter the Backlog ($M) for each year in the analysis period. This value is the total bridge back- log, as modeled by the NBIAS, in each year in the base case, expressed in millions of dollars. 3. Enter the User Benefits Obtained ($M) for each year in the analysis period. This is the value of user benefits, as modeled by the NBIAS, in each year in the base case, expressed in millions of dollars. NBIAS Results—Investment Case Figure 5-12 shows the NBIAS results for the investment case, with inputs for total work done, project backlog, and user benefits in an improvement scenario in which the agency makes a TAM system investment. The investment case uses the same parameters as the base case, but with values that reflect the costs and benefits of the improvement scenario. The following procedure is used to complete the inputs for the NBIAS Results - Investment Case in the Inputs worksheet: 1. Enter the Total Work Done ($M) for each year in the analysis period. This value is the cost of bridge work performed, as modeled by the NBIAS, in each year in the investment case, expressed in millions of dollars. 2. Enter the Backlog ($M) for each year in the analysis period. This value is the total bridge backlog, as modeled by the NBIAS, in each year in the investment case, expressed in millions of dollars. 3. Enter the User Benefits Obtained ($M) for each year in the analysis period. This is the value of user benefits, as modeled by the NBIAS, in each year in the investment case, expressed in millions of dollars. Additional Parameters Worksheet The Additional Parameters worksheet contains incident cost model parameters, operating cost model parameters, and capacity model parameters. Cells shaded in blue are input cells the user can edit. Unshaded cells should not be edited; they contain default values or formulas. Notice that on this tab the default values are not retained separately; entering a value in a blue-shaded cell overrides a system default. The sections labeled Incident Cost Model Parameters for Autos and Trucks, Operating Cost Model Parameters Specified by Vehicle Class, Operating Cost Model Parameters Specified by Functional Class, and Capacity Model Parameters are popu- lated with default values. Unless otherwise noted, default parameters are based on values used by FHWA for national-level analyses in HERS and NBIAS as of 2016, specified in 2014 dollars. The first section in this worksheet, Incident Cost Model Parameters, has no default values; the user should complete the blue input cells. The section labeled Incident Cost Model Derived Values contains values that are automatically calculated from other input cells in this worksheet. The cells in this section should not be edited. Figure 5-13 shows a partial view of the Additional Parameters worksheet. The white cells are calculated based on the blue cells using basic formulas that automatically update. Figure 5-12. NBIAS results—investment case.

Using the ROI Calculator (ROI Tool) 79 Incident Cost Model Parameters Figure 5-14 shows incident cost model parameters that are used to estimate agency, user, and social costs due to incidents, along with the potential benefits of incident reduction as a result of TAM investment. The values chosen for these parameters will depend on the previously selected definition of an incident. Three parameters in this section are calculated based on other parameters and should not be edited: % ADT subject to incident, % ADT subject to stoppage, and Average stoppage time (min). The default values for Cost per fatality ($), Cost per injury ($), and Cost per property damage incident ($) are estimates based on values used by FHWA for national-level analyses in HERS and NBIAS as of 2016, specified in 2014 dollars. The remaining default values for inci- dent parameters are representative values derived from the case studies performed as part of the research effort. The following procedure is used to complete the inputs for the Incident Cost Model Parameters in the Additional Parameters worksheet: 1. Enter the Average incident duration (min). This value is the length of time that an incident is disrupting normal transportation flow, measured in minutes. For example, if an incident causes a lane closure for five hours, the value of this parameter would be 300 minutes. Figure 5-13. Additional Parameters worksheet.

80 Return on Investment in Transportation Asset Management Systems and Practices 2. Enter the Average initial stoppage time. This value is the length of time that traffic is stopped due to an incident, measured in minutes. For example, if an incident causes traffic to stop for 1 hour, the value of this parameter would be 60 minutes. 3. Enter the AADT. This value is the annual average daily traffic—the number of vehicles travel- ing over a road in a day. The AADT should be calculated for the pavement group being evalu- ated in the ROI calculation. 4. Enter the Average % trucks. This value is the percent of daily traffic composed of trucks. 5. Enter the Average detour length (miles). This value is the average detour length caused by an incident, measured in miles. 6. Enter the Average detour speed (mph). This value is the average vehicle speed on a detour caused by an incident, measured in miles per hour. For example, a detour from a highway onto a collector or local road will involve a lower speed limit. 7. Enter the % cars using detour. This value is the percentage of car traffic using the detour. For example, if every car must use the detour, this value would be 100%. 8. Enter the % trucks using detour. This value is the percentage of truck traffic using the detour. For example, if every truck must use the detour, this value would be 100%. 9. Enter the Cost per fatality ($). This value is the cost per fatality, expressed in dollars. Cost per fatality is used to help estimate incident user costs. 10. Enter the Cost per injury ($). This value is the cost per injury, expressed in dollars. Unit injury costs are estimated based on the willingness-to-pay concept used by HERS-ST. Cost per injury is used to help estimate incident user costs. 11. Enter the Cost per property damage event ($). This value is the cost per property damage event, expressed in dollars. These costs are used to help estimate incident user costs. 12. Enter the Fatalities/incident. This value is the rate of fatalities occurring per incident, expressed as a number. 13. Enter the Injuries/incident. This value is the rate of injuries occurring per incident, expressed as a number. 14. Enter the Property damage events/incident. This value is the rate of property damage events occurring per incident, expressed as a number. Figure 5-14. Incident cost model parameters.

Using the ROI Calculator (ROI Tool) 81 Incident Cost Model Parameters for Autos and Trucks The table for incident cost model parameters for autos and trucks, shown in Figure 5-15, collects parameters that help estimate user and social costs from incidents. All of the input cells in Figure 5-15 are shaded blue, indicating that the user may choose to override the default values. The following procedure is used to complete the inputs for the Incident Cost Model Parameters for Autos and Trucks in the Additional Parameters worksheet: 1. Enter a Vehicle cost per hour congested ($/vehicle hour). This value is a user cost of driving in traffic, measured in dollars per vehicle-hour. 2. Enter a Vehicle cost per mile free flow ($/mile). This value is a user cost of driving without traffic, measured in dollars per mile. 3. Enter an Environmental cost per hour congested ($/mile). This value is a social cost of driving in traffic, measured in dollars per mile. 4. Enter an Environmental cost per mile free flow ($/mile). This value is a social cost of driving without traffic, measured in dollars per mile. Incident Cost Model Derived Values The incident cost model derived values shown in Figure 5-16 are calculated from other input values. These cells should not be edited. Operating Cost Model Parameters Specified by Vehicle Class Figure 5-17 shows operating cost model parameters specified by vehicle class. The ROI Tool provides default values for most of these parameters, which are used to estimate vehicle operat- ing costs. Users may edit the default values in the cells that are shaded blue; however, the bottom six rows shown in Figure 5-17 are not shaded. These parameters are calculated from other inputs and should not be edited. The following procedure can be used to override the default values for the Operating Cost Model Parameters Specified by Vehicle Class in the Additional Parameters worksheet: 1. Enter the Personal - Average Occupancy (people/vehicle) for each vehicle class. This value is the number of people traveling in a personal vehicle on average, expressed as people per vehicle. 2. Enter the Personal - Percent of Travel for each vehicle class. This value is the percentage of vehicle travel that represents personal travel for each vehicle class. 3. Enter the Business - Multiplier on Value of Time for each vehicle class. This value is a num- ber used to increase or reduce the business value of time parameter used in the ROI Tool. Figure 5-15. Incident cost model parameters for autos and trucks.

82 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-16. Incident cost model derived values. Figure 5-17. Operating cost model parameters specified by vehicle class.

Using the ROI Calculator (ROI Tool) 83 4. Enter the Business - Average Occupancy (people/vehicle) for each vehicle class. This value is the number of people traveling in a business vehicle on average, expressed as people per vehicle. 5. Enter the Business - Vehicle Cost (2012 $/hr) for each vehicle class. This value is the average cost to operate a business vehicle, expressed as 2012 dollars per hour. 6. Enter the Business - Inventory Cost per Vehicle (2012 $/hr) for each vehicle class. This value is the average cost of business vehicle inventory, expressed as 2012 dollars per hour. 7. Enter the cost of Fuel ($/gallon) for each vehicle class. This value is the cost of fuel for each vehicle class, expressed in dollars per gallon. 8. Enter the cost of Oil ($/quart) for each vehicle class. This value is the cost of oil for each vehicle class, expressed in dollars per quart. 9. Enter the cost of Tires ($/tire) for each vehicle class. This value is the cost of tires for each vehicle class, expressed in dollars per tire. 10. Enter the cost of Maintenance and Repair ($/1000 miles) for each vehicle class. This value is the cost of maintenance and repair for each vehicle class, expressed in dollars per thousand miles. 11. Enter the Depreciable Value ($/vehicle) for each vehicle class. This value is the average depreciable value of a vehicle in each vehicle class, expressed in dollars per vehicle 12. Enter the Fuel Efficiency Adjustment for each vehicle class. This value is a multiplier (num- ber) used to increase or reduce the fuel efficiency parameter used in the PMS calculations. 13. Enter the Oil Consumption Adjustment for each vehicle class. This value is a multiplier (num- ber) used to increase or reduce the oil consumption parameter used in the PMS calculations. 14. Enter the Depreciation Rate Adjustment for each vehicle class. This value is a multiplier (number) used to increase or reduce the depreciation rate parameter used in the PMS calculations. Operating Cost Model Parameters Specified by Functional Class Figure 5-18 shows the operating cost model parameters specified by functional class. These parameters are used to help estimate vehicle operating costs. They are organized by functional class, as defined in HERS-ST. The values represent the percentage of vehicle types by vehicle class in each functional class. Values for Small Auto, Med. Auto, and 4-Tire Truck sum to 1 (rounded) for each functional class. The values for 6-Tire Truck, 3-4 Axle Truck, Bus, Figure 5-18. Operating cost model parameters specified by functional class.

84 Return on Investment in Transportation Asset Management Systems and Practices 4-Axle Comb., and 5-Axle Comb. also sum to 1 for each functional class. Additional param- eters also are provided under Other Parameters Specified by Functional Class. The ROI Tool provides default values for these parameters; however, the expert user may choose to override the default values. It is suggested that these values be overridden only by an expert user familiar with the details of the HERS models, which are documented in FHWA’s HERS-ST Version 2.0 Technical Report (2002). Capacity Model Parameters Capacity model parameters, shown in Figure 5-19, are used to help estimate vehicle operating costs (when PMS results are used). The ROI Tool provides default values for these parameters, which are used to populate user cost parameters in NBIAS. The expert user may choose to over- ride the default values. Summary Results Worksheet The Summary Results worksheet contains the summary outputs of the ROI Tool. The tables and charts on this worksheet present the estimated benefits and costs of a potential TAM invest- ment. The results displayed in this worksheet automatically update when the input worksheets are edited. All of the cells in this worksheet are calculated from other input cells and should not be edited. The Summary Results worksheet contains five tables that address: • Summary Measures; • Agency, User, and Social Benefits of Incident Reduction; • Agency, User, and Social Benefits Predicted Using HERS-ST; • Agency and User Benefits Predicted Using a Pavement Management System; and • Agency and User Benefits Predicted Using NBIAS. In addition, four charts graph the following results: • Summary Results; • Benefits of Incident Reduction; • Benefits of Pavement Investment Changes; and • Benefits of Bridge Investment Changes. Figure 5-20 provides a partial view of the Summary Results worksheet. Figures 5-20 through 5-29 show the tables and charts with illustrative data. Figure 5-19. Capacity model parameters.

Using the ROI Calculator (ROI Tool) 85 Figure 5-20. Summary Results worksheet. Summary Measures The Summary Measures table, shown in context at top left in Figure 5-20 and by itself in Figure 5-21, summarizes the total costs and benefits of the potential TAM improvement in discounted and undiscounted terms. Costs and benefits are calculated by subtracting base case costs from investment case costs. Total Benefits ($) are organized into three catego- ries: Agency Benefits, User Benefits, and Social (Emissions) Benefits. Total Costs ($) are organized into five categories: Agency Labor, Hardware & Software Acquisition, Recur- ring Costs, Contractor Costs, and Other Costs. Subtotals for these benefit and cost catego- ries are calculated by summing the benefits and costs estimated in the other sections of the ROI Tool. The table also shows the Net Present Value ($) of the subtotals. The NPV also is represented in the Summary Results chart, which appears at top right in the worksheet (see Figure 5-20). Figure 5-22 shows the Summary Results chart enlarged to show additional details. The ROI calculation results are summarized using four ROI measures. As described in Chapter 2, these measures compare the estimated costs and benefits over the TAM investment life cycle. Shown in Figure 5-21, the four measures are: • Net Present Value (NPV) ($). This measure shows what the TAM investment is worth in present-value terms. It is calculated as the present value of the benefits (i.e., the entire stream

86 Return on Investment in Transportation Asset Management Systems and Practices of benefits discounted to the present) minus the present value of the costs (including initial capital costs and ongoing maintenance and operating costs discounted to the present). NPV is not scaled to the size of the investment. A $5 million NPV is better than a $2 million NPV, even if the former required a $10 million TAM investment whereas the latter required only $1 million. • Benefit/Cost Ratio. This measure allows comparisons across investments of different costs. The ratio is calculated as the present value of the benefits divided by the present value of the costs. A B/C ratio above 1.0 means that the benefits of a TAM investment outweigh the costs whereas a B/C ratio below 1.0 means that the costs are greater than the benefits. The benefits and costs are exactly equal if the benefit-cost ratio equals 1.0. B/C ratios can be used to prioritize investments to achieve maximum benefit given a limited budget. • Internal Rate of Return. This measure is the discount rate at which benefits and costs are equal. IRR is expressed as a percentage. A project with an IRR greater than the discount rate used for the ROI analysis has benefits greater than costs and a positive economic value. IRR allows comparison of projects with different costs, different benefit flows, and different time periods. • Payback Period (years). This measure is the number of years it takes for the net benefits (benefits minus costs) to equal or pay back, the initial investment costs. If a TAM investment is expected to pay back costs in 22 years but the initial investment will last only 10 years, the costs are never paid back. The payback period varies inversely with the B/C ratio. That is, a shorter payback period yields a higher B/C ratio. Summary Results Figure 5-22 shows the Summary Results chart, which graphically displays the estimates from the Summary Measures table. In the chart, benefits are shown as a stacked column rising above the x-axis and costs are shown as a stacked column descending below the x-axis. The benefits Figure 5-21. Summary Measures table.

Using the ROI Calculator (ROI Tool) 87 and costs are broken down by subtotal and are color-coded and labeled. Hovering the mouse over the elements of a stacked column in the chart causes a pop-up window to appear contain- ing the specific value for that portion of the chart. This feature works for all of the charts in the Summary Results worksheet. Agency, User, and Social Benefits of Incident Reduction Figure 5-23 shows the estimated agency, user, and social benefits of incident reduction in both discounted and undiscounted terms. The Reduced Agency Expenditures are calculated from the reduced costs due to fewer incidents. The User Benefits are estimated from reductions in delay costs, operating costs, and accident costs. The social benefits (Emissions Benefits) are estimated from the reduction in emissions due to stoppages and detours. Benefits of Incident Reduction Figure 5-24 graphically displays the benefits of incident reduction. The present values of the benefits are presented as stacked columns; one column shows the Reduced Expenditures that benefit the agency and the other column stacks the User Benefits above the Social (Emissions) Benefits. Figure 5-23. Agency, user, and social benefits of incident reduction. Figure 5-22. Summary Results chart.

88 Return on Investment in Transportation Asset Management Systems and Practices Agency, User, and Social Benefits Predicted Using HERS-ST Figure 5-25 shows the agency, user, and social benefits predicted using HERS-ST in both dis- counted and undiscounted terms. Reduced Agency Expenditures are calculated from the reduced spending in the investment case. User Benefits are estimated from reductions in user costs in the investment case. Reduced Maintenance Expenditures are calculated from the reduced mainte- nance spending in the investment case. Emissions Benefits are estimated from the reduction in emissions in the investment case. Agency and User Benefits Predicted Using a PMS The table shown in Figure 5-26 summarizes the agency and user benefits predicted using a PMS, presented in discounted (Present Value) and undiscounted terms. The agency and user benefits are calculated by subtracting base case values from investment case values. The pave- ment groups defined on the Inputs worksheet are automatically included in this summary. Benefits of Pavement Investment Changes Figure 5-27 graphically summarizes the benefits of pavement investment changes. The present values of the benefits are displayed as stacked columns. One column displays Agency benefits and the other displays User/Social benefits. Within each column, subtotals are color-coded and labeled. Agency and User Benefits Predicted Using NBIAS The table shown in Figure 5-28 summarizes the agency and user benefits predicted using NBIAS in both discounted and undiscounted terms. The agency and user benefits are calculated Figure 5-24. Benefits of incident reduction. Figure 5-25. Agency, user, and social benefits predicted using HERS-ST.

Using the ROI Calculator (ROI Tool) 89 Figure 5-26. Agency and user benefits predicted using a PMS. Figure 5-27. Benefits of pavement investment changes. Figure 5-28. Agency and user benefits predicted using NBIAS.

90 Return on Investment in Transportation Asset Management Systems and Practices by subtracting base case costs from investment case costs. Dollar values are provided for three types of benefits: Reduced Agency Expenditures, Reduced Backlog, and User Benefits. Benefits of Bridge Investment Changes The chart in Figure 5-29 graphs the summarized benefits of bridge investment changes. The chart reflects the data from the agency and user benefits predicted using NBIAS that were shown in Figure 5-28. Agency and user costs appear as stacked, color-coded columns, with benefits rising vertically from the x-axis and costs dropping below the x-axis. Costs and/or benefits with a value of $0 do not appear in the chart but will be listed in the legend (e.g., Reduced Expenditures in Figure 5-29). Worked Examples This section of Chapter 5 presents two worked examples that illustrate the use of the ROI Tool. These examples use fictitious data. They are intended to help users understand the tool and how it might be applied to their agencies. The first worked example is for the fictitious Alfa State Department of Transportation (Alfa DOT). Alfa DOT is responsible for managing transportation assets across the state. This agency has well-established systems and processes for inspecting, tracking, and main- taining pavement and bridge assets. Management of drainage assets is less mature, however, leading to expensive emergency work when drainage assets fail. Alfa DOT is considering purchasing and implementing a data collection and inventory system for drainage assets. The intended outcome of the investment is a reduction in drainage asset failure incidents and associated costs. The second worked example is for Bravo State Department of Transportation (Bravo DOT). Bravo DOT is interested in investing in a suite of asset management systems. The agency currently uses a potpourri of legacy systems developed internally to support fed- eral reporting requirements. These systems help manage the inventory but provide limited support for investment decision making. Bravo DOT’s leadership team acknowledges there are potential benefits to be realized from improving asset preservation, but has expressed concern about undertaking such a large systems investment. The agency would like to use Figure 5-29. Benefits of bridge investment changes.

Using the ROI Calculator (ROI Tool) 91 the ROI Tool to help develop the business case for implementing new pavement and bridge management systems. Example 1: Alfa DOT Alfa DOT would like to improve its culvert and closed drainage system (hereafter referred to as culverts) asset inventory to support improved inspection and maintenance of culverts. This analysis focuses on the potential installation of a culvert data collection and inventory system. The TAM investment should reduce the number of failure incidents, resulting in agency, user, and social cost savings. Alfa DOT is particularly interested in two potential benefits of an investment in an inven- tory system for drainage assets (culverts, catch basins, pipes, and other related systems). First, Alfa DOT would like to have better data for articulating the need for drainage main- tenance funding. Currently, Alfa DOT cannot articulate the need for drainage maintenance work in the same way that the agency can for pavement and bridge work. Second, Alfa DOT would like to examine potential savings from bundling drainage projects and pavement projects. Currently, no system exists for drainage management. Drainage assets are not regularly or consistently inspected, and the inspections are not tracked. Ahead of the paving program, main- tenance personnel tend to scout the roads and identify culverts for needed work. The pavement work ends up driving much of the culvert work. Drainage issues typically are discovered in the field by maintenance or design staff. The initial discovery is followed by a more detailed inspec- tion. Depending on the results of the inspection, Alfa DOT will choose a plan of action for the asset. If the results show significant potential negative impact, the asset receives expedited treatment. Alfa DOT envisions using a single methodology to collect data, which will be structured using data governance and quality assurance (QA) best practices. The data will be available to the whole department and will eventually be moved to an enterprise service layer to support dashboards and reports. A separate operational element will be made available to help with work orders as well. Alfa DOT is using the ROI Tool to evaluate a potential investment in a drainage asset data col- lecting and inventory system. The ROI Tool contains a number of default values that can be used by Alfa DOT. Alfa DOT includes certain scenario-specific data points to fine-tune the analysis. The necessary data for calculating ROI for Alfa DOT’s potential TAM investment is presented in Tables 5-3 through 5-6. Defining the General Parameters To perform an evaluation using the ROI Tool, the general parameters of the analysis must be defined. In the case of Alfa DOT, the agency’s desired general parameters are listed in Table 5-3. General Parameters Analysis Period 10 years Annual Cost per FTE $119,993 Agency Cost per Incident $1,000,000 Table 5-3. General parameters for Alfa DOT.

92 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-30. Updated general parameters for Alfa DOT. Base Case Agency Labor (FTEs) 0 Hardware & Software Acquisition ($) $0 Recurring Costs ($) $0 Contractor Costs ($) $0 Other Costs ($) $0 Predicted Failure Incidents 1 (per year) Table 5-4. Base case for Alfa DOT. After opening the ROI Tool, the following procedure is used to define the general parameters for the Alfa DOT case: 1. Click the tab to open the Inputs worksheet, and then save the file to a unique filename. 2. Using the information in Table 5-3, adjust the following general parameters, entering the new values in the “Override” cells for the analysis period, annual cost per FTE, and agency cost per incident. 3. Confirm that the cells next to the HERS-ST, Supplemental PMS, and NBIAS analyses are set to the default value (“No”). For added security, the “Override” cells can be manually set to the “No” value. The updated general parameters in the worksheet for Alfa DOT appear as shown in Figure 5-30. Defining the Base Case Next, the base case is defined. For Alfa DOT, the base case is the current state of practice at Alfa DOT with regard to drainage management. Table 5-4 shows the base case parameters for Alfa DOT.

Using the ROI Calculator (ROI Tool) 93 The following procedure is used to define the Alfa DOT base case in the ROI Tool: 1. Using the information in Table 5-4, adjust the base case parameters. For each year, enter the new values for agency labor (FTEs), hardware and software acquisition, recurring costs, con- tractor costs, other costs, and predicted failure incidents. 2. Confirm that the updated base parameters have been entered correctly in the worksheet. For the Alfa DOT analysis, the correctly entered parameters appear as shown in Figure 5-31. Defining the Investment Case The next task in the analysis is to define the investment case. For Alfa DOT, this is the TAM investment scenario with regard to drainage management. The investment case reflects the poten- tial costs and benefits of purchasing, installing, and operating a drainage management system. Table 5-5 shows the investment case parameters for Alfa DOT. The following procedure is used to define the Alfa DOT investment case in the ROI Tool: 1. Using the information in Table 5-5, adjust the investment case parameters for each year, entering the new values for agency labor, hardware and software acquisition, recurring costs, contractor costs, other costs, and predicted failure incidents. 2. Confirm that the updated investment parameters have been entered correctly in the worksheet. For the Alfa DOT analysis, the correctly entered parameters appear as shown in Figure 5-32. Investment Case Agency Labor (FTEs) 1 FTE every fifth year, 0.5 FTE in all other years Hardware & Software Acquisition ($) $50,000 every 5 years Recurring Costs ($) $230,000 per year Contractor Costs ($) $7,500 per year Other Costs ($) $0 Predicted Failure Incidents 1.0 in the first year, declining 0.2 each subsequent year, and remaining at 0.0 after 5 years Table 5-5. Investment case parameters for Alfa DOT. Figure 5-31. Base case parameters for Alfa DOT.

94 Return on Investment in Transportation Asset Management Systems and Practices Defining the Additional Parameters Next, the additional parameters are defined. These parameters help estimate agency, user and social costs and benefits. Alfa DOT’s analysis will override the default values provided in the ROI Tool for only two parameters. Table 5-6 shows the values for these two parameters. The following procedure is used to adjust the additional parameters for Alfa DOT in the ROI Tool: 1. Click the tab to open the Additional Parameters worksheet. 2. Using the information in Table 5-6, adjust the two incident cost model parameters (average incident duration and AADT) by typing the new values over the existing (default) values in the ROI Tool. 3. Confirm that the overwritten values have been correctly entered and that the default values remain in place for all other cells. For the Alfa DOT analysis, the updated additional parameters appear as shown in Figure 5-33. This figure shows only a partial view of the Additional Parameters worksheet. The tables and cells not shown in the figure all retain their default values. Examining the Analysis Results Next, the results of the ROI analysis are examined. The ROI Tool displays the results as a series of charts and tables on the Summary Results worksheet, which is opened by clicking the appropriate tab in the ROI Tool. Figure 5-34 shows a partial view of the summary results for the Alfa DOT analysis. In this analysis, the table showing benefits predicted by HERS-ST is blank, reflecting the selection of “No” for that optional analysis on the Inputs worksheet. The tool summarizes the results using four measures of ROI: NPV, B/C ratio, IRR, and pay- back period. The chart in Figure 5-35 indicates that, for the Alfa DOT analysis, estimated ben- efits clearly outweigh estimated costs. The positive ROI measures shown in Figure 5-36 suggest that the investment would be a financially prudent decision. The NPV is over $3 million, the B/C ratio is over 2, the IRR is 52.4% and the payback period is only 4 years. Incident Cost Model Parameters Average Incident Duration (min) 540 AADT 14,260 Table 5-6. Incident cost model parameters for Alfa DOT. Figure 5-32. Investment case parameters for Alfa DOT.

Using the ROI Calculator (ROI Tool) 95 Figure 5-33. Incident cost model parameters for Alfa DOT. Figure 5-34. Summary Results worksheet.

96 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-36. Summary Measures for Alfa DOT. Figure 5-35. Summary Results chart for Alfa DOT.

Using the ROI Calculator (ROI Tool) 97 General Parameters HERS-ST Analysis Performed? No Supplemental PMS Analysis Performed? Yes NBIAS Analysis Performed? Yes Table 5-7. General parameters for Bravo DOT. Example 2: Bravo DOT Bravo DOT would like to evaluate a potential investment in a suite of asset management systems for bridge and pavement assets. Currently, pavement and bridge conditions in Bravo are relatively good; asset conditions are expected to worsen over time, however, and predicted spending is projected to be relatively flat once adjusted for inflation. In part because asset conditions have been good in the past, Bravo DOT has not fully explored the potential for improving its approach to asset preservation. For pavement, preventive maintenance treat- ments have been used only sporadically. For bridges, the focus of the capital program has historically been on replacing deficient bridges. Although implementing the new systems will require a substantial investment, Bravo DOT staff are confident that using asset management systems will help support an increased emphasis on asset preservation that will yield benefits over the long term. To support this effort, other Bravo DOT staff have already estimated the costs of imple- menting the new systems. Also, staff have simulated pavement and bridge conditions for a variety of scenarios. With permission from the system owner, a limited pavement analysis was performed using a PMS licensed to a neighboring state agency. The bridge analysis was performed using the FHWA’s NBIAS. In each system, Bravo DOT simulated future condi- tions given Bravo DOT’s best estimate of future funding for two cases: a base case in which Bravo DOT’s approach to asset investments is unchanged, and an investment case in which Bravo DOT focuses more on asset preservation. Tables 5-7 through 5-14 show the data used to populate the ROI Tool. Defining the General Parameters In the case of Bravo DOT, only two general parameters differ from the defaults in the ROI Tool. The agency’s desired general parameters are listed in Table 5-7. After opening the ROI Tool, the following procedure is used to define the general parameters for the Bravo DOT case: 1. Click the tab to open the Inputs worksheet, and then save the file to a unique filename. 2. Using the information in Table 5-7, enter the new values in the “Override” cells for the HERS-ST analysis (“No”), the supplemental PMS analysis (“Yes”), and the NBIAS analysis (“Yes”). (Even though “No” is the default, using the “Override” cell to enter “No” for the HERS-ST analysis helps ensure that the correct values are entered for all three parameters.) 3. Confirm that the updated values have been correctly entered. For the Bravo DOT analysis, the updated general parameters in the worksheet appear as shown in Figure 5-37. Defining the Base Case The base case for the Bravo DOT ROI analysis is the current state of practice at Bravo DOT with regards to pavement and bridge management systems. Table 5-8 shows the base case parameters for Bravo DOT.

98 Return on Investment in Transportation Asset Management Systems and Practices Having defined the general parameters, the following procedure is used to define the Bravo DOT base case in the ROI Tool: 1. Using the information in Table 5-8, adjust the base case parameters by entering the new val- ues, by year, for agency labor, hardware and software acquisition, recurring costs, contractor costs, other costs, and predicted failure incidents. 2. Confirm that the updated parameters have been entered correctly. The updated base parameters in the worksheet for Bravo DOT will appear as shown in Fig- ure 5-38. (The screenshot in Figure 5-38 shows a portion of the table. In the worksheet, the table extends to the year 2037, reflecting the default analysis period of 20 years.) Defining the Investment Case For Bravo DOT, the investment case is the TAM investment scenario with regard to pavement and bridge management systems. The investment case reflects the potential costs and benefits of purchasing, installing, and operating management systems for pavement and bridge assets. Table 5-9 shows the investment case parameters for Bravo DOT. Base Case Agency Labor (FTEs) 0 Hardware & Software Acquisition ($) $0 Recurring Costs ($) $0 Contractor Costs ($) $0 Other Costs ($) $0 Predicted Failure Incidents 0 Table 5-8. Base case for Bravo DOT. Figure 5-37. General parameters for Bravo DOT.

Using the ROI Calculator (ROI Tool) 99 Investment Case Agency Labor (FTEs) 5 FTEs every seventh year, 2 FTEs in all other years Hardware & Software Acquisition ($) $2,000,000 every 7 years Recurring Costs ($) Starting from year 1 of the analysis: 0; $31,595; $32,000; $40,000; $44,000; $49,000; $60,800; $0; $62,400; $61,900; $61,400; $60,900; $60,400; $59,900; $0; $59,600; $59,000; $60,000; $57,400; $59,600 Contractor Costs ($) $50,000 per year Other Costs ($) $0 Predicted Failure Incidents 0 Table 5-9. Investment case for Bravo DOT. Figure 5-38. Base case parameters for Bravo DOT. The following procedure is used to define the Bravo DOT investment case in the ROI Tool: 1. Using the information in Table 5-9, adjust the investment case parameters, entering the new values for each year for agency labor, hardware and software acquisition, recurring costs, contractor costs, other costs, and predicted failure incidents. 2. Confirm that the updated parameters have been entered correctly. Figure 5-39 shows a partial view of the updated investment parameters section of the work- sheet for Bravo DOT. Defining the PMS Analysis Groups In the case of Bravo DOT, the next step in performing the ROI analysis is to define the PMS analysis groups. These parameters are required when using PMS results to augment the ROI Tool. The analysis groups must be defined before the PMS data can be entered. Table 5-10 shows the PMS analysis groups for Bravo DOT. Note: In Table 5-10, the information listed under “Predom. Func. Class” (Predominant Functional Class) matches the available selections from the drop-down menus in the ROI Tool. When preparing the descriptions of the PMS analysis groups before entering the data, an agency (e.g., Bravo DOT) can consult the ROI Tool to note which of the 13 options available in the drop-down menu best matches each analysis group.

100 Return on Investment in Transportation Asset Management Systems and Practices Annual Growth Rate Group Description Base Year AADT Base Year Truck Autos Trucks Road Length Avg. Num. Lanes Predom. Func. Class Interstate 20,000 5% 2% 2% 100 miles 6 11-Urban Interstate Non- Interstate NHS 4,000 3% 1% 1% 2,500 miles 4 14-Urban Other Principal Arterial Non-NHS 1,000 1% 1% 1% 5,000 miles 2 17-Urban Collector Table 5-10. PMS analysis groups for Bravo DOT. After defining the investment case parameters, the following procedure is used to define the PMS analysis groups for the Bravo DOT analysis: 1. Still using the Inputs worksheet of the ROI Tool, scroll down to the table labeled “PMS Analy- sis Groups” and key in the three descriptions from Table 5-10. 2. Fill in the data for each of the three PMS analysis groups using the information from Table 5-10. 3. Confirm that the group descriptions and data have been entered correctly. The updated table showing the PMS analysis groups for the Bravo DOT analysis appears as shown in Figure 5-40. Defining the PMS Results—Base Case PMS results are required for both the base case and the investment case when using PMS results to augment the ROI Tool. The PMS data obtained by Bravo DOT is input to define a base case and investment case for pavement assets. Table 5-11 shows the PMS results for the Bravo DOT base case, arranged in an order convenient for keying into the ROI Tool. The following procedure is used to input this information into the ROI Tool: 1. Still using the Inputs worksheet of the ROI Tool, scroll down to the table labeled “PMS Results - Base Case.” Using the information in Table 5-11, adjust the following base case parameters, entering the new values, by year, in each cell for agency expenditures, backlog, and average IRI by group (Interstate, non-Interstate NHS, and non-NHS). 2. Confirm that all of the information has been entered accurately. Figure 5-41 shows a partial view of the updated PMS base case table in the worksheet. Figure 5-39. Investment case parameters for Bravo DOT.

Using the ROI Calculator (ROI Tool) 101 Value by Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 Agency Expenditures ($M) 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 Backlog ($M) 900 897 891 873 856 823 831 869 887 925 961 1055 1116 1160 1203 1241 1291 1333 1362 1390 Average IRI by Group Interstate 70 71 72 72 72 75 75 75 73 73 75 75 77 77 78 78 79 78 80 81 Non- Interstate NHS 102 103 103 104 104 106 105 106 106 107 108 109 109 111 111 109 112 110 112 113 Non-NHS 120 121 123 123 123 125 124 125 125 126 127 127 125 127 128 129 129 131 132 134 Table 5-11. PMS results—base case for Bravo DOT. Figure 5-40. PMS analysis groups for Bravo DOT. Figure 5-41. PMS results—updated base case for Bravo DOT.

102 Return on Investment in Transportation Asset Management Systems and Practices Value by Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 Agency Expenditures ($M) 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 Backlog ($M) 900 890 881 858 836 798 801 834 847 880 911 1000 1056 1095 1133 1166 1211 1265 1300 1325 Average IRI by Group Interstate 70 70 71 70 71 70 71 72 73 73 73 74 74 75 76 76 77 77 77 76 Non-Interstate NHS 102 102 102 103 103 101 100 100 101 102 103 104 105 106 107 107 109 109 109 108 Non-NHS 120 122 120 119 119 120 121 122 123 124 124 125 126 127 128 129 129 130 131 132 Table 5-12. PMS results—investment case for Bravo DOT. Figure 5-42. PMS results—investment case for Bravo DOT. Defining the PMS Results—Investment Case As was done for the base case, the PMS data obtained by Bravo DOT is then input to define the investment case for pavement assets. Table 5-12 shows the PMS results for the Bravo DOT investment case, again arranged as convenient for keying the information into the ROI Tool. After defining the PMS results for the base case, the following procedure is used to define the PMS results for the investment case in the ROI Tool: 1. Scrolling down to the investment case table in the Inputs worksheet and using the informa- tion in Table 5-12, adjust the investment case parameters by entering the new values, by year, in the cells for agency expenditures, backlog, and average IRI by group (Interstate, non- Interstate NHS, and non-NHS). 2. Confirm that all the information has been entered correctly. Figure 5-42 shows a partial view of the updated PMS investment case table in the worksheet. Defining the NBIAS Results—Base Case Bravo DOT’s analysis also includes NBIAS data, requiring additional data entry. NBIAS data can be used to define a base case and investment case for bridge assets. Both a base case and an investment case are required when using NBIAS results to augment the ROI Tool. Table 5-13 shows the parameters for the NBIAS results base case for Bravo DOT as arranged for convenient input into the ROI Tool.

Using the ROI Calculator (ROI Tool) 103 Value by Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 Total Work Done ($M) 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 Backlog ($M) 3000 2970 3005 2987 2345 2143 2576 2673 2751 2357 2919 2415 2020 1754 1554 1375 1396 1245 1132 1123 User Benefits Obtained ($M) 18 35 24 38 64.8 75.2 77.4 76.5 76.3 75.8 76 76.8 77 76.5 77.9 78.1 78.8 78.6 77.9 78.9 Table 5-13. NBIAS results—base case for Bravo DOT. Figure 5-43. NBIAS results—base case for Bravo DOT. The following procedure is used to define the NBIAS results for the Bravo DOT base case in the ROI Tool: 1. Still working in the Inputs worksheet, scroll down to the NBIAS Results - Base Case table and, using the information collected in Table 5-13, adjust the parameters by entering the new values, by year, in the cells for total work done, backlog, and user benefits obtained. 2. Confirm that all the information has been input correctly. Figure 5-43 shows a partial view of the updated NBIAS results table for the base case in the worksheet. Defining the NBIAS Results—Investment Case Table 5-14 shows the parameters for the NBIAS results investment case for Bravo DOT, arranged for convenient input into the ROI Tool. The following steps are used to define the NBIAS results for the investment case in the ROI Tool: 1. Using the information in Table 5-14, adjust the following parameters, entering the new values, by year, in the cells for total work done, backlog, and user benefits obtained. 2. Confirm that all the information has been entered correctly. Figure 5-44 shows a partial view of the updated NBIAS results table for the investment case in the worksheet. Defining the Additional Parameters Having defined the base and investment cases, the next step in performing the ROI analysis for Bravo DOT is to open the Additional Parameters worksheet. The parameters specified in this worksheet help estimate agency, user, and social costs and benefits, and the ROI Tool provides default values for each parameter specified (see Figure 5-45). Bravo DOT’s analysis uses all of the default values on the Additional Parameters worksheet; therefore, no values on this worksheet need to be modified for the analysis. Examining the Analysis Results The ROI Tool shows the results of Bravo DOT’s analysis as a series of charts and tables on the Summary Results worksheet (Figure 5-46). In the ROI Tool, this worksheet is opened by clicking on the Summary Results tab.

104 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-45. Additional Parameters for Bravo DOT (partial view). Value by Year 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 Total Work Done ($M) 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 250 Backlog ($M) 3000 2970 2673 2742 2684 2483 2338 2261 2144 2245 2600 2500 2400 2300 1950 1650 1350 1250 1100 900 User Benefits Obtained ($M) 18 33 23 37 66.8 75 77 76.5 77 76.8 78 78 78 76.5 77.9 78.1 78.8 78.6 77.9 78.9 Table 5-14. NBIAS results—investment case for Bravo DOT. Figure 5-44. NBIAS results—investment case for Bravo DOT.

Using the ROI Calculator (ROI Tool) 105 Figure 5-46. Summary Results worksheet.

106 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-47. Summary Results chart for Bravo DOT. In the Bravo DOT analysis the summary table showing benefits predicted by HERS-ST is blank because that optional analysis was not included. Also, no incident reduction was assumed in the analysis. The ROI Tool summarizes the analysis results using four measures of ROI: NPV, B/C ratio, IRR, and payback period. For the Bravo DOT analysis, the summary results chart (enlarged in Figure 5-47) shows that estimated benefits clearly outweigh estimated costs. Figure 5-47 also shows a pop-up window that appears when the mouse is positioned over a section in a stacked column in the chart. The pop-up window provides the specific value for that section of the column (in this case, $103,029,400 for the “User Benefits” portion of the “Benefits” column). The pop-up window feature works with all the charts in the Summary Results worksheet. The positive ROI measures shown in Figure 5-48 suggest that investing in asset management systems would be a financially prudent decision for Bravo DOT. The NPV is over $231 million, the B/C ratio is over 27, the IRR is 49.69% and the payback period is only 5 years. The results of the PMS and NBIAS analyses also are broken out on the Summary Results worksheet for Bravo DOT. Figures 5-49 and 5-50 show the benefits predicted using the PMS. The ROI Tool predicts a $30 million reduction in backlog and more than $100 million in user benefits. Figures 5-51 and 5-52 show the agency and user benefits predicted using the NBIAS data. The ROI Tool predicts a $105 million reduction in backlog, but also a slight user cost.

Using the ROI Calculator (ROI Tool) 107 Figure 5-48. Summary Measures for Bravo DOT. Figure 5-49. Benefits predicted using a PMS.

108 Return on Investment in Transportation Asset Management Systems and Practices Figure 5-52. Benefits of bridge investment changes. Figure 5-51. Benefits predicted using NBIAS. Figure 5-50. Benefits of pavement investment changes.

Next: Chapter 6 - Conclusions »
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TRB's National Cooperative Highway Research Program (NCHRP) Research Report 866: Return on Investment in Transportation Asset Management Systems and Practices explores how transportation agencies manage their transportation assets, and provides guidance for evaluating the return on investment for adopting or expanding transportation asset management systems in an agency.

As the term is most generally used, transportation asset management (TAM) entails the activities a transportation agency undertakes to develop and maintain the system of facilities and equipment—physical assets such as pavements, bridges, signs, signals, and the like—for which it is responsible. Based on the research team’s work and the experiences of these agencies and others, the researchers describe a methodology that an agency may use to assess their own experience and to plan their investments in TAM system development or acquisition.

A spreadsheet accompanies the research report helps agencies evaluate the return-on-investment of TAM systems.The tool allows users to summarize data from various simulation tools. The calculator also includes factors and procedures from the Highway Economic Requirements System State Version (HERS-ST) to estimate user benefits for pavement projects. It does not estimate user benefits for bridge projects.

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, Engineering, and Medicine 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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