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A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan (2023)

Chapter: Chapter 3 - Data to Support Integrating Maintenance into a TAMP

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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
×
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Suggested Citation:"Chapter 3 - Data to Support Integrating Maintenance into a TAMP." National Academies of Sciences, Engineering, and Medicine. 2023. A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan. Washington, DC: The National Academies Press. doi: 10.17226/27291.
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16 Data to Support Integrating Maintenance into a TAMP Maintenance Data to Support TAMP Development There are several maintenance data elements necessary to support TAMP development, and they are not limited to costs. For cost data to be useful in a TAMP analysis, it needs to be associated with the asset inventory, activities, accomplishments, and performance improvement. A key source of this data is accurate work history. This work history data may come from work orders or contracts and should include labor, equipment, and materials costs as well as work units accomplished. This type of work order data is necessary to develop unit costs for maintenance activities. Modern maintenance management systems (MMS) enable an agency to better record and track maintenance work order history, including mobile functionality to gather the data in the field. Each of the case study agencies described herein has robust MMS cost and accomplishment data for in-house forces. To successfully integrate maintenance needs, activities, and costs into a TAMP, agencies must understand the type of maintenance work performed and link it to specific assets. Many agencies develop an asset and activity matrix that clearly defines the types of maintenance work expected to be performed when an activity is planned. This allows an agency to ensure that the necessary labor, materials, and equipment are available. Agencies may also define the deficiencies each activity is meant to address. For example, a culvert may have several associated maintenance activities over its life. A maintenance crew may repair, replace, or extend a culvert’s structural components if they are broken or deterio- rated. A maintenance crew may also clean that culvert to remove sediment and debris. These are separate maintenance activities intended to address separate issues with the same culvert asset. These activities have different labor, equipment, and material requirements and thereby costs. They may also have different units of accomplishment reporting and different impacts on asset performance. Each of these data items is important for a maintenance division to differentiate for developing the unit costs necessary for performance-based budgeting. Clearly defining this type of information is important for incorporating maintenance into a TAMP. Table 3-1 pro- vides an example of an asset-to-activity matrix for drainage features. How Much Data Is Enough Data? While current legislation requires state DOTs to include only pavement and bridge assets in their TAMPs, many agencies are expanding their TAM programs to include additional C H A P T E R 3 This chapter describes the process of gathering the necessary data to integrate maintenance costs into a TAMP. It includes guidelines on the connection between maintenance needs, activities, costs, and accomplishments, along with the necessary data to establish that connection. Case studies from agencies using data to support maintenance work planning provide real-life examples of these processes.

Data to Support Integrating Maintenance into a TAMP 17   ancillary assets. This is due to the reduction in life-cycle costs to operate and maintain these assets and increases in the ability to effectively manage risks. However, data is potentially expensive to collect and maintain. Therefore, the FHWA developed guidelines to help agencies prioritize the order in which ancillary assets are added to an asset management program. The Handbook for Including Ancillary Assets in Transportation Asset Management Programs (Allen et al. 2019) introduces the asset prioritization process shown in Figure 3-1. The first step is for agencies to prioritize their assets in a tiered system based on a review of the input from the various stakeholders. This step involves selecting a maintenance approach that could be condition-based, interval-based, risk-based, or reactive as discussed in this Guide in Chapter 2. The selected management strategy influences the data types and quantities necessary for each asset category. Tools such as GIS, dashboards, and analytics can be used to support financial planning and investment decisions using this data. Determining the right amount of data to collect is a challenge. It is important to strike a balance between the cost of collecting the data and the benefits expected. Agencies should also consider the frequency with which data needs to be collected and the necessary degree of accuracy needed to make decisions. A mature data management system can be beneficial for storing and analyzing the data available to support TAM activities. When collecting asset data, it is important to consider and establish clear data requirements for inventory, condition, and performance data models. Required and recommended fields should be feasible to collect and maintain; optional fields may only be collected under specific circumstances. Data that cannot be reliably collected or maintained should be excluded from the data model. Figure 3-2 shows examples of required, recommended, and optional inventory, condition, and performance data attributes. Minnesota DOT (MnDOT) and Maricopa County DOT (MCDOT) are examples of two agencies that evaluated their data collection needs to optimize the expenditure of resources. Data elements that are typically needed to support the TAM and the Transportation Performance Management (TPM) activities are shown in Table 3-2. The data elements that serve as input and output to support each activity are also defined. The relationship between the different activities and the data elements can serve as a framework for incorporating maintenance costs in various TAMP processes and the associated data needs. This would also allow for better maintenance workflows and better coordination between the TAMP and the MMS. Asset Feature Activity Description Category Culverts/Drop Inlets Closed drainage cleaning Routine maintenance Closed drainage repairs Repair Cut/Fill Slopes Brush removal Routine maintenance Erosion repair Repair Detention/Retention Ponds Detention pond maintenance Routine maintenance Ditches Ditch cleaning Routine maintenance Pipes/Culverts Special drainage (hydro-vacuum) Routine maintenance Culvert repairs Repair Table 3-1. Asset-to-activity matrix example.

18 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan SOURCE: Adapted from Allen et al. 2019. Figure 3-1. Process for prioritizing assets for inclusion in an asset management program.

Data to Support Integrating Maintenance into a TAMP 19   SOURCE: Adapted from Allen et al. 2019. Inventory Input Input Input Input — — Input Condition Input Input Input Input Input Input Available Funding Input Input — Input Output Input Input Investment (historical and planned) Input Input — Output Input — — Accomplishments Input Input Input — — — — Vulnerabilities — Input Input Input — Input — Historical Emergency Response — Input — — — — — Life-Cycle Strategies — Input — Input — Input — NOTE: — = not applicable SOURCE: Allen et al. 2019. Data Target Setting Consistency Review Managing Risk LCP Financial Plan Investment Strategy Gap Analysis Figure 3-2. Data collection attributes. Table 3-2. Data needs for different TAM and TPM processes.

20 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Example: MnDOT Asset Management Strategic Implementation Plan To further implement TAM in the agency, MnDOT developed an Asset Management Strategic Implementation Plan (AMSIP) (MnDOT 2021). The AMSIP evaluated 73 different asset classes following the process established in Allen et al. 2019 to determine the data needed to manage each asset class in support of MnDOT’s priorities. Following this approach, MnDOT established a multiyear plan for expanding its data collection and management efforts. As shown in Table 3-3, MnDOT defined six life- cycle maintenance approaches for infrastructure assets. These approaches ranged in terms of the sophistication of data needs. Table 3-4 shows MnDOT’s summary of the data needed for each asset class based on the selected maintenance approach. The information summarized in these tables, along with estimates of data collection costs, allowed MnDOT to prioritize the 73 assets into four prioritized tiers for inclusion in the asset management program. Table 3-3. MnDOT maintenance approaches (MnDOT 2021). Maintenance Approach Definition Minimal Maintenance No inventory or condition data is collected or maintained. Maintenance is performed when assets are identified as having an unacceptable defect. Reactive An inventory is maintained, but there is no regular condition data collection, and no maintenance is performed to slow or address damage or deterioration until an asset is reported as having an unacceptable defect. Annual work is planned at the aggregate level, without concern for the specific locations of potential future defects. Cycle-Driven The asset is maintained on a cyclical basis. Condition data may be collected on these assets to meet other business needs, but the inspection cycle is managed separately from the maintenance cycle. Condition data not required. Cycle-Driven Plus The asset is inspected and maintained on a cyclical basis; the inspection and maintenance activities are performed simultaneously or in concert and condition data is collected and maintained for analysis that could lead to additional condition-based decisions. Condition data is required. Condition-Driven The condition of the asset is routinely monitored and actions are taken to manage the long-term performance of the asset or the asset's impact on system performance. Condition-Driven Plus The condition of the asset is routinely monitored and modeled. Actions are taken proactively and reactively to optimize the asset’s life cycle through minimum life-cycle cost, maximum benefit, maximum life-cycle length, or some similar approach. Table 3-4. Required data by maintenance approach (MnDOT 2021). Maintenance Approach Inventory? Maintenance Cycle? Asset Condition? Performance Models? Optimized Life-Cycle Strategies? Minimal Maintenance No No No No No Reactive Yes No No No No Cycle-Driven Yes Yes No No No Cycle-Driven Plus Yes Yes Yes No No Condition-Driven Yes Yes Yes Yes No Condition-Driven Plus Yes Yes Yes Yes Yes

Data to Support Integrating Maintenance into a TAMP 21   Assessing Data Readiness To help agencies assess the availability of data to support the selected maintenance approach, a self-assessment is suggested. NCHRP Report 814: Data to Support Transportation Agency Business Needs: A Self-Assessment Guide (Spy Pond Partners and Iteris 2015) serves as a useful resource for performing this type of evaluation. The data effectiveness self-assessment described in NCHRP Report 814 can help agencies determine the data needed for meeting expected business needs and also the costs, benefits, and priorities of obtaining the data. Figure 3-4 shows the data self- assessment framework. The Data Value in the Assessment section of Figure 3-4 includes the following elements (Spy Pond Partners and Iteris 2015). • Data Availability: Is the right kind of data in place, at the right detail, and with sufficient coverage? • Data Quality: Is the data sufficiently accurate, credible, complete, and current to support decision-making? Example: MCDOT Priority Asset Collection and Evaluation Process MCDOT has developed an approach for its priority assets that involves collecting data to ensure a statistically significant sample size is evaluated for each priority asset class. The majority of MCDOT’s samples originate at an intersection to ensure that adequate asset-counts for signals, signs, crosswalks, sidewalks, and pavement markings are achieved. They have also created a field manual that includes evaluation criteria developed by subject-matter experts detailing a consistent approach that those conducting the assessments must follow. MCDOT is also able to view its condition states via map views, as shown in Figure 3-3. Figure 3-3. MCDOT pipe condition map. MCDOT’s asset and maintenance management system allows users to identify on the work order if the work is for an emergency event and flag it as a specific event type, such as “Federal Emergency Management Agency (FEMA)” or “COVID-related.” This enables analyses to quantify the impact of emergency events and/or COVID-related work on productivity or LOS. In response to the COVID pandemic, MCDOT has adopted protocols in its operations including the use of staggered start and end times for shifts and splitting shifts to Monday through Thursday and Tuesday through Friday to assist with social distancing. Maintenance and operations tasks to support COVID testing and vaccination sites include but are not limited to setting up signs and barricades, delivering lights, and other traffic control activities.

22 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Source: Adapted from Spy Pond Partners 2022. Figure 3-4. Implementing data self-assessment for transportation agencies.

Data to Support Integrating Maintenance into a TAMP 23   • Data Usability: Can data be easily accessed, integrated, analyzed, and presented as needed to support decision-making? Using the responses to the self-assessment elements, a data maturity level can be assigned. This is done through a Data Management Maturity Assessment, which includes the following elements (Spy Pond Partners and Iteris 2015). • Data Strategy and Governance: How are decisions made on what to collect? What are the costs? What are the benefits? How is data managed and delivered? • Data Life-Cycle Management: How are data maintained, preserved, protected, documented, and delivered? • Data Architecture and Integration: How are data standardized and integrated to minimize duplication and inconsistencies? • Data Collaboration: How is collection and management coordinated with internal and external users? • Data Quality Management: How is data quality defined, validated, measured, and reported? A second method, the “pass/fail approach,” is utilized by several state DOTs. However, there are limitations to this approach as it applies to performance-based budgeting. Pass/fail gener- ally results in replacement rates that are higher than actual deficiency rates. For example, if the threshold for a guardrail is 10 percent deficiency, and 12 percent of the guardrail is deficient, then according to the standard, the entire length of the guardrail in the survey segment is consid- ered deficient instead of simply the 12 percent deficient portion. This does not provide accurate measures for performance-based budget development as these results cannot reliably be used for maintenance planning and budgeting. In this example, there is no indication of the quantity of guardrail work that may be needed to address deficiencies and achieve the target LOS. It is only known that the amount of deficiency is greater than 10 percent. These deficiency thresholds and measures, as well as evaluation and reporting approaches and processes, can be documented in a Maintenance Quality Assurance (MQA) manual to ensure consistent processes. These manuals can be used to train data collection teams, either in-house or contracted. In the past, agencies used paper forms to report data collection. As mobile applications and modern MMS become more widespread, agencies are moving to electronic collection and data reporting. After data collection teams perform condition assessments, the agency should identify approximately 10 percent of the roadway samples for quality assurance/ quality control checks. LOS results can then be conveyed in a scorecard or “report card” format as a convenient way to express LOS in terms useful to planning and budgeting program managers and readily understood by nontechnical stakeholders and the public. Historical work order data provides inputs for estimating the LOS as well as required resources and funding to achieve performance targets. By tracking accomplishments and costs by activity and location, a transportation agency can build a work history. This allows agencies to establish a connection between cost, accomplishment, and performance. A work history typically includes labor, equipment, and material costs as well as the work accomplished in units. This data could be tied to asset performance. For example, a history of work orders can be used to develop unit costs for delivering maintenance, which can be used to forecast the future cost of delivering maintenance work for financial planning and developing investment strategies. The work-order history can also be used to connect the costs with the work accomplished and the resulting improvement in asset performance. This can help in evaluating LOS, performance gaps, and the funding required to achieve performance targets. It can also be used for setting statewide LOS targets based on agency priorities and goals from customer surveys.

24 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Example: Alabama DOT Maintenance Quality Assurance The Alabama DOT (ALDOT) has a well-established MQA program that it uses to establish maintenance budgets. ALDOT builds its budgets using a combination of performance-based budgeting and a bottom- up/top-down approach based on need and historical spending. ALDOT developed its MQA program several years ago and has enhanced it over time. The agency currently collects asset-condition data using in-house forces but has also utilized contractors over the program’s history. The steps in their condition assessment process are shown in Figure 3-5. Figure 3-5. ALDOT condition assessment process (ALDOT). ALDOT samples between 5 and 8 percent of its system, with a confidence level of 95 percent on Interstate roadways and 90 percent on the remainder of its system. ALDOT utilizes a Microsoft Access random sample-generating tool to identify survey segments. ALDOT also developed a data collection application using GIS applications. ALDOT performs quality assurance/quality control processes on the data collection procedure. This process, together with the results, is used to develop an LOS report card, including trend analysis, as shown in Table 3-5. Using a consistent scorecard format enables the comparison of the performance of asset condition over time and across organizational units. ALDOT uses a combination of performance- based budgeting and a bottom-up/top-down approach. Budgeting is a multistep process in which districts submit budget requests based on the level of effort to achieve agency performance targets. Requests are then reviewed and amended at higher levels of the organization based on need and historical spending, and the final budget allocations are allocated back to the districts.

Data to Support Integrating Maintenance into a TAMP 25   Table 3-5. Sample condition assessment scorecard: 5-year trend (ALDOT). Group Feature Asphalt Pavement Asphalt—potholes Raveling Shoving Concrete Pavement Spalling Faulting Joint Sealing Punchouts Pumping Paved Shoulders Potholes Edge Raveling Sweeping High Shoulder Drainage Side Drains Cross Drains Unpaved Ditches Paved Ditches Drop Inlets Curb and Gutter Roadside Erosion Control—Front Slopes Erosion Control—Back Slopes Undesirable Vegetation Brush/Tree Control ALDOT Fence Litter Control Traffic Services Pavement Markings and Legends Pavement Striping Raised Pavement Markers Delineators—Guardrail/Cable/Barrier/Wall Delineators—Other Object Markers Signals Signs—Regulatory and Warning Signs—Other Guardrail 2016 2017 2018 2019 2020 A A- B+ A+ A+ B- B- B+ B+ B+ C F D- F D- A- A A A A+ A- A A A A+ A- A A A A+ A- A A A A+ A A A+ A+ A+ A+ A+ A+ A+ A+ B+ B- A A B B- A A+ A+ D- D D- C D- F B B- B- C C B B- B- C C B B+ B+ B+ B C C F F D B- B- B- C+ F F C- C C+ C A+ C B+ A B+ A- C B- A- A A+ A+ A A B- C C D+ D F C+ C+ B+ A+ C D+ C C C C D B- B+ B C+ B+ A- A+ A C+ B- C- C- D+ C C B- B- B B- C A- C+ B+ B- D- D- F F F A+ A+ A A+ A+ B- B+ B C+ A- B A- A- C+ A- C B- C C D

26 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Collecting Maintenance Cost Data Accurate maintenance cost data is the foundation of any performance-based maintenance program. In the past, many maintenance organizations relied on average crew-day costs based on performance standards or guidelines for each maintenance activity. These standards or guidelines were typically based on statewide averages for costs and accomplishments. Establishing a unit cost for each maintenance activity accommodates variations between organizational units (e.g., districts, areas) and allows each organizational unit to develop more refined performance-based budgets. By collecting labor, equipment, and materials costs for each work activity or asset, and combining them with the quantity of work performed, an agency can develop a unit cost for each asset/activity combination. Below are key maintenance cost reporting data types that should be collected. In-House Costs Several DOTs effectively utilize MMS applications to capture in-house maintenance cost and accomplishment data. Typical data captured for maintenance work includes labor, equipment, material, and accomplishment units. The utilization of mobile applications can work to reduce data entry errors and enhance data quality overall. These applications allow maintenance crews to select specific assets in the field and report maintenance activity data in real time. Additionally, many agencies are working to expand the utilization of automated reporting technologies such as automatic vehicle location and other applications to further reduce data entry errors, improve data quality, and minimize the level of effort for maintenance crews to report activities. The continued proliferation of comprehensive MMS applications will enhance these processes at agencies across the country. Labor Costs Leveraging MMS applications enables an agency to track the in-house labor costs to perform maintenance activities. It is important that these labor rates are tied to the appropriate mainte- nance activity and/or asset. These rates should be “fully loaded” and include all associated over- head costs for employee labor. The rates within the MMS should be interfaced with the necessary financial or enterprise resource planning (ERP) modules to ensure consistent labor reporting across the agency. Equipment Costs Agencies must also account for the full cost to operate and maintain the equipment utilized for roadway maintenance. As with labor, the equipment rates charged to maintenance work must be fully loaded and include initial capital costs, depreciation, operating and maintenance costs, shop overhead (including mechanic rates), tools, software, facilities used to maintain equipment, etc. Several agencies utilize an equipment revolving fund that charges their maintenance office rates that include the previously mentioned costs as well as those to replace equipment at the end of its life cycle. It is also recommended that agencies account for the time the equipment is utilized to perform work as well as the time it is assigned to the maintenance activity. This is preferred as there is an opportunity cost to assign equipment to the activity even if it is not used. Material Costs Material costs to perform roadway maintenance are often significant. As such, it is important that all maintenance work orders include the quantity and costs of required materials. Agencies vary in the methods used to account for material costs. For example, an agency may utilize

Data to Support Integrating Maintenance into a TAMP 27   average material cost; rst in, rst out (FIFO); or last in, rst out (LIFO). ese processes are oen established in conjunction with agency accounting departments, thereby making it dicult to standardize an approach. Contract Costs All agencies deliver some maintenance activities through contracts. Capturing costs from contracts requires accessing data sets that are commonly formatted dierently from the in-house maintenance cost data. As a result, there is a need to correlate contract cost data to the activity or task denitions used to track in-house costs. is process is critical to being able to account for all maintenance costs in a similar way. e Texas DOT (TxDOT) and Maryland DOT State Highway Administration (MDOT SHA) case studies present dierent examples of how agencies have approached the challenge of aligning in-house and contract maintenance cost data. e decision to contract out maintenance activities may involve consideration of the following types of questions. • Is the equipment purchased or leased? • Are sta well trained with experience in safe handling and proper installation? • Are sta available to deliver the work safely, e.g., with proper trac control installed? • What materials are available? • What is the availability of qualied contractors for installation? • How competitive are contract costs per work unit? Example: TxDOT’s Approach to Tracking Contract Maintenance Costs TxDOT provides an example of effective contract maintenance cost data collection processes. TxDOT contracts approximately 52 percent ($620 million) of its $1.2 billion maintenance budget for routine maintenance. Contracted work interfaces with TxDOT’s MMS in two ways: with its enterprise resource planning (ERP) software and with its construction contract management software. TxDOT typically uses work orders (WO) for contracts valued at less than $25,000. The process for capturing and reporting contract maintenance costs is shown in Figure 3-6. Figure 3-6. TxDOT contract purchase order data collection process (TxDOT). For larger projects, TxDOT utilizes AASHTOWare Site Manager, including the Routine Maintenance Contract Administration module. Daily work reports allow inspectors to capture work performed at the job site such as personnel, equipment, work items, quantities, descriptions, etc. Over 3,700 pay items are used on routine maintenance contracts, and the Maintenance Distribution Window, a custom upgrade to the AASHTOWare Site Manager, ties the pay item cost to the MMS function code (i.e., what work is being performed) and the amount of work performed. The MMS then provides reports by function code for both in-house and contracted work, and TxDOT actively monitors data quality to ensure accurate reporting and analysis.

28 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Accomplishment Reporting Agencies must also report the amount of work performed or accomplishment by maintenance activity or asset. is is necessary to develop the unit costs to perform maintenance work. ese unit costs are key inputs for developing performance-based budgets. Accomplishment units vary by activity. For example, linear feet of guardrail repair, number of sign faces replaced, acres mowed or vegetation control, cubic feet of sediment removed, or square yards of asphalt repaired are all considered accomplishment units. Tying Maintenance Cost Data to Asset Performance Data Once costs are captured, determining the relationship between cost and performance allows for the use of cost data in asset management analyses. Chapter 5 provides additional details on how unit costs can be used to develop life-cycle strategies and support for LCP. ALDOT and MnDOT provide examples of dierent approaches to determining the relationship between Example: MDOT SHA’s Approach to Tracking Contract Maintenance Costs The MDOT SHA reports labor, equipment, and materials costs for its state-forces’ work into an electronic team activity cards (eTAC) system. These costs are captured by asset or unit. MDOT SHA enters contract data into the FHWA Financial Management Information System (FMIS) and other contract management software. The contract systems and eTAC assign a project cost activity (PCA) code for each expense. The PCA codes allow costs from similar work, delivered by different means, to be aggregated. The PCA codes are linked to the 21 Maryland Condition Assessment Reporting System (MCARS) elements to align costs with asset performance. MDOT SHA uses QlikView, an analytics software, to aggregate the work output, cost data, and MCARS data and associates each to the appropriate PCA code for the work activity accomplished (see Figure 3-7, a screenshot of QlikView provided by MDOT SHA). Data aggregation with QlikView works well if the data is accurate within the PCA codes, costs, and accomplishments. Figure 3-7. Screenshot of QlikView (MDOT SHA). This approach enables MDOT SHA to perform an analysis to determine whether in-house or contracted maintenance provides a more cost-efficient result for the activity or asset. This is an important analysis to consider when developing maintenance work programs as it allows an agency to be strategic with limited resources.

Data to Support Integrating Maintenance into a TAMP 29   Example: ALDOT’s Approach to Linking Maintenance Costs with Performance ALDOT ties maintenance cost data to asset performance data via the process detailed in Figure 3-8. The elements in the row headings (Inventory, Condition, Accomplishment, Performance, and Budgeting) categorize the types of data utilized for the analysis. The unit costs for maintenance activities (e.g., cost per linear foot of guardrail repair) are derived from maintenance costs and accomplishment reporting from its MMS. Inventory is summarized from actual data, or in some cases, estimates derived from the statistically significant condition survey process. The current LOS is calculated using the process described in the ALDOT MQA example provided previously in this chapter. By using established LOS targets, ALDOT can calculate the gap between current and targeted LOS in terms of percent deficient of the total inventory. The gap between current and targeted LOS can then be defined as a level of effort with associated unit costs. An MMS should provide the ability to change LOS targets and automatically calculate the associated costs to achieve them. For example, what would the cost be in the scenario if an agency selected an LOS target of 2 percent deficient rather than an LOS target of 5 percent deficient? Figure 3-8. ALDOT MQA process diagram (adapted from ALDOT).

30 A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan Example: MnDOT’s Approach to Relating Pavement Condition to Maintenance Costs MnDOT has developed separate processes for capturing pavement maintenance cost data for contract and state-forces’ work. For contract work, MnDOT has an estimating section that determines statewide costs per lane-mile based on contract costs detailed in the project lettings. For state-forces’ maintenance work, MnDOT uses data from work orders and day cards incorporated into the Transportation Asset Management System (TAMS). In both cases, the cost data includes location information. Using this combination of cost and location data, MnDOT develops models describing the relationship between pothole patching costs and the condition of pavements. Figure 3-9 displays pavement performance based on various investment scenarios: PL0, PL1, PL2, PL-1, and PL-2. Each scenario represents a different level of investment in pavement resurfacing and displays the resulting pavement pothole patching budget as seen in Figure 3-9. MnDOT demonstrates strong asset management practices as they relate to connecting maintenance costs and treatments in ancillary assets. MnDOT’s TAMS is an integrated system that enables MnDOT to develop maintenance cost data for roadway assets due to varying levels of data availability, and MnDOT has adopted different approaches for each asset. TAMS is MnDOT's primary work management system for the Office of Maintenance and is used to track all work performed by MnDOT maintenance field staff. Although the current MnDOT TAMP includes 10 ancillary assets, MnDOT manages several other assets in TAMS. MnDOT's maintenance cost models have been calibrated to conditions. MnDOT has used these models to develop pavement management system (PMS) runs based on costs, predicted conditions, and funding. During an interview for this project, MnDOT presented an example of the cost models for pavement patching that could support the framework being developed under this study. The models could potentially support the justification for pavement funding needs and enhance pavement target-setting efforts. MnDOT's practices show how incorporating powerful tools and software, coupled with well-defined procedures, can result in effective maintenance management practices. SOURCE: MnDOT. Figure 3-9. MnDOT pavement patching models output graphic. maintenance costs and asset performance. In the ALDOT example, maintenance cost data is used to determine the level of investment needed to improve asset conditions. MnDOT demonstrates how asset conditions can be used to estimate future maintenance costs. System Integration Integrating asset condition and life-cycle cost information into an asset management system enables a thorough life functionality. DOTs are required by the FHWA to maintain certain key asset management systems, such as pavement and bridge management systems, and as such, these systems have been developed and implemented across the DOTs. e systems store and

Data to Support Integrating Maintenance into a TAMP 31   maintain asset inventory, condition, and performance information. In more mature applications, an enterprise system may be in place, supporting cross-asset functionality and improved inte- gration with planning, project development, project delivery, and agency reporting tools. Data Management Both maintenance and asset management are data- and analysis-intensive. NCHRP Research Report 956: Guidebook for Data and Information Systems for Transportation Asset Management provides a framework for advancing TAM systems and data management through benchmarking, improvement identification, and improvement evaluation (Spy Pond Partners and Atkins 2021). Both maintenance and asset management require data input and sharing by multiple parties and likely from multiple organizations, both within and separate from the asset-owner agency. Due to the number of individuals and systems responsible for inputting, managing, and accessing the data, data security is a major concern. Data Security Data access and security are most easily managed early on during system development (e.g., when the system and associated data models can be structured to support the assignment and enforcement of data access or security levels). With proper consideration, data access and security can be controlled at the system level, the application level, or even the database level (Spy Pond Partners and Atkins 2021).

Next: Chapter 4 - Incorporating Maintenance into Life-Cycle Planning »
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Since 2018, State departments of transportation (DOTs) have been required to develop risk-based transportation asset management plans (TAMPs) and to update processes for developing these plans every four years. To date, several DOTs have described challenges in showing clear connections between maintenance investments and asset condition.

NCHRP Research Report 1076: A Guide to Incorporating Maintenance Costs into a Transportation Asset Management Plan, from TRB's National Cooperative Highway Research Program, leads practitioners through a six-part framework designed to tackle the biggest challenges agencies face in projecting future maintenance costs in TAMP activities. Supplemental to the report is a pocket guide.

Supplemental to the report are NCHRP Web-Only Document 372: Incorporating Maintenance Costs into a Transportation Asset Management Plan, an Executive Summary, an Implementation Memorandum, an Overview Presentation, and a Publication Announcement.

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