Transit Asset Condition Reporting (2011)

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9The major effort in this project was the survey of industry practice in transit asset management. The nation’s 50 largest transit agencies in terms of operations size were polled using an Internet survey. The transit agencies surveyed are primar- ily multi-modal transit agencies that typically operate heavy, light, or commuter rail services and bus services. The survey focused on these agencies because it was expected that they would likely have the most advanced asset management sys- tems because of the complexity of their operations. The survey collected basic agency information and asked if the agency had and used a comprehensive asset database. The survey also covered a detailed set of 37 questions regard- ing current asset management systems practices. The ques- tions addressed the scope of the agency asset inventory, the agency human resources used, the determination of asset con- dition and its use, and details of the agency’s capital planning and programming. SURVEY RESPONSE The response rate for the initial survey was 82% or 41 agencies (Figure 1). Collectively, the respondents operate a variety of modes. More than two-thirds of the respondents (28 agencies) operate some form of rail service, heavy rail, light rail, or auto- mated guideway (Table 1). The remaining agencies typically operate bus and demand response services. Nearly all of the respondents (93%) provide bus service and most (86%) also provide demand response service. This illustrates the com- plexity of the multi-modal operations of the 50 largest U.S. transit agencies. The final question of the initial survey asked if the respon- dent was willing to participate in a much more detailed survey regarding the agency’s asset inventory database, its structure, and its use. A total of 37 respondents or 90% indicated their willingness to proceed with the second survey. SCOPE OF ASSET INVENTORY Virtually all respondents to the initial survey (98%) reported that they had a comprehensive asset inventory database. The same number of respondents noted that they maintained (updated) the database on a periodic basis. These responses are consistent with the grant requirements for agencies receiving federal funding regarding adequate control. Transit agencies must demonstrate knowledge of and control of transportation assets that are federally funded. The primary source of asset inventory data varies among the responding agencies (Figure 2). The most popular source was fixed asset ledger/counting data, which was cited by 40% of respondents. Often, these databases were created for finan- cial control purposes. Data collected for operational purposes, either as part of asset inspection or maintenance management systems, were cited by approximately one-third of the respondents. These databases were created to support the maintenance of good asset condition. The types of data systems used for asset inventory and condition monitoring varied across responding agencies. All respondents indicated that an electronic database was used to store the data (Figure 3). However, only one-half of the respondents reported using networked applications. Net- worked applications generally are considered to be the best way to enter and maintain data that must be entered by many departments in an agency because they reduce or eliminate the double-entry of data. The types of data storage also varied. More than one-half of the respondents reported that their agencies stored data in off-the-shelf, financial information, or asset management databases (Figure 4). Another 30% of the respondents indi- cated that their agencies use specially developed databases (internally or consultant). It is important that planning, as well as both near-term and long-term capital programming, be informed and guided by analysis based on asset inventory data. To make the most use of the asset inventory there needs to be a connection between (1) the update of the asset database (number of items) and (2) the planning and budgeting process. Approximately two-thirds of the responding agencies update the asset data in their databases every 1 to 2 years (Fig- ure 5). A 5-year update schedule is used for another 14% of the responding agencies. The remaining agencies do not have a fixed update sched- ule. For some responding agencies (8%), the frequency of updates occurs when changes are made to the asset inventory. For others (6%), the update frequency varies by asset type. CHAPTER THREE SURVEY RESULTS:TRANSIT CAPITAL PROGRAMMING AND ASSET TRACKING SYSTEMS

Designated in-house staff support and update the databases for most responding agencies. More than 80% of the respon- dents reported that their agencies use only in-house staff and do not use contractors to maintain and update their asset inven- tories (Figure 6). Almost 60% of the responding agencies use designated, but not dedicated, staff to maintain and update their asset inventories. These inventory responsibilities are one of several job responsibilities for the designated staff. USE OF INVENTORY DATA The use of the inventory data is reported to be high (greater than 75%) for most common applications (Figure 7). There is near unanimity reported in the use of the inventory data for capital planning purposes. For many agencies, the inventory also serves as the basis for condition assessment as well as reg- ulatory and financial reporting purposes. The capital program cycles vary by length and by whether the time interval is fixed (e.g., 2010 to 2014, then 2015 to 2019) or rolling (e.g., 2010 to 2014, then 2011 to 2015). About two-thirds of the responding agencies use programming cycles that are 5 years or less (Figure 8). Two of every three respon- dents indicated that their agencies used rolling programming cycles. Taken together, these two responses indicate that at least two-thirds of the transit agencies revise their capital programs every year; therefore, most of the large transit agencies need to make capital needs forecasts every year. The programming cycles are related to the planning cycles at most of the responding agencies. Twenty-five agencies (71%) reported that the renewal cycles of their capital pro- grams are linked to the duration of their planning cycles. The types of capital spending are often the subject of criti- cism from transit observers. Capital spending can be divided 10 into three general categories: (1) SGR, (2) service expansion, and (3) enhancements to existing assets. It is often claimed that SGR spending is low because it does not generate the public interest that is created by spending in the other two categories. However, the respondents reported that an average of 62% of 2009 capital funding was spent on SGR projects (Figure 9). This may reflect the national norm for a large transit agency seeking to balance growth and re-investment. The responses ranged from a low of 6% to a high of 100%. CONDITION ASSESSMENT Nearly 90% of responding agencies indicated that they assess the condition of some or all assets. This assessment may be tied to the reported high use of the data for capital program- ming and agency funding (see Figure 8). More than 80% of responding agencies determine asset condition through a com- bination of age and inspection results (Figure 10). This may imply that agencies assess the condition of selected asset cate- gories such as bridges based on inspections while relying on age for other asset categories. Almost two-thirds of the responding agencies update the condition data in their databases every 1 to 2 years (Figure 11). This is consistent with the responses to the question regarding the frequency of updates to the inventory data (see Figure 5). Another 17% of the responding agencies reported that the frequency of their updates varies by asset type. The collection of condition data on some asset types (e.g., vehicles) typically are part of routine maintenance activities. For other asset types (e.g., bridges), special efforts must be made to update the con- dition data. SUMMARY The survey revealed some key findings about the state of practice of asset tracking systems and capital programming at large transit agencies: • Virtually all large agencies have asset tracking databases that are frequently updated and include all assets. • The primary sources of the data vary among the transit agencies. Common sources include financial records (fixed asset ledgers), asset inspections, maintenance management systems, or some combination thereof. • Although all data are maintained electronically, there are variations in how the data are stored. The most common storage packages are off-the-shelf, financial information or asset management databases, and special databases developed internally or by outside consultants. • Designated in-house staff support and update the data- bases for most responding agencies. Most responding agencies do not use outside contractors for this support. FIGURE 1 Agency response to survey.

11 TABLE 1 RESPONDING TRANSIT AGENCIES AND MODES OPERATED Transit Agency Location Modes Operated AG MB CC CR DR FB HR IP LR TB VP Alameda Contra Costa Transit District (AC Transit) Oakland, CA X X Bay Area Rapid Transit District (BART) Oakland, CA X Bi-State Development Agency (METRO) St. Louis, MO X X X Broward County Transit (BCT) Pompano Beach, FL X X Capital Metropolitan Transportation Authority (CMTA) Austin, TX X X X Central Florida Regional Transportation Authority (LYNX) Orlando, FL X X X Chicago Transit Authority (CTA) Chicago, IL X X City of Detroit Department of Transportation (DDOT) Detroit, MI X X City of Los Angeles Department of Transportation (LADOT) Los Angeles, CA X X City of Phoenix Public Transit Department (Valley Metro) Phoenix. AZ X X Dallas Area Rapid Transit (DART) Dallas, TX X X X X X Greater Cleveland Regional Transit Authority (GCRTA) Cleveland, OH X X X X King County DOT — Metro Transit Division (King County Metro) Seattle, WA X X X X X Los Angeles County Metropolitan Transportation Authority (LACMTA) Los Angele, CA X X X X Maryland Transit Administration (MTA) Baltimore, MD X X X X X Massachusetts Bay Transportation Authority (MBTA) Boston, MA X X X X X X X Metro Transit Minneapolis, MN X X Metropolitan Transit Authority of Harris County, Texas (Houston METRO) Houston, TX X X X X Metropolitan Transit System of San Diego (MTS) San Diego, CA X X X Miami Dade Transit (MDT) Miami, FL X X X X Ride-On Montgomery County Transit Rockville, MD X X MTA Bus Company (MBT BUS) Brooklyn, NY X MTA Long Island Bus Garden City, NY X X MTA Long Island Rail Road (MTA LIRR) Jamaica, NY X MTA New York City Transit (NYCT) New York, NY X X X Niagara Frontier Transportation Authority (NFT METRO) Buffalo, NY X X X New Jersey Transit Corporation (NJ Transit) Newark, NJ X X X X X Orange County Transportation Authority (OCTA) Orange, CA X X X Pace Suburban Bus Corporation (PACE) Arlington Heights, IL X X X Port Authority of Allegheny County (Port Authority) Pittsburgh, PA X X X X Port Authority Trans-Hudson Corporation (PATH) Jersey City, NJ X X Regional Transportation District (RTD) Denver, CO X X X X Sacramento Regional Transit District (Sacramento RT) Sacramento, CA X X X San Francisco Municipal Transportation Agency (SFMTA) San Francisco, CA X X X X X Santa Clara Valley Transportation Authority (VTA) San Jose, CA X X X Southeastern Pennsylvania Transportation Authority (SEPTA) Philadelphia, PA X X X X Tri-County Metropolitan Transportation District of Oregon (TriMet) Portland, OR X X X Utah Transit Authority (UTA) Salt Lake City, UT X X X X X VIA Metropolitan Transit (VIA) San Antonio, TX X X X Washington Metropolitan Area Transit Authority (WMATA) Washington, DC X X X Westchester County Department of Transportation (The Bee-Line System) Mt Vernon, NY X X Mode Code Legend: AG: Automated Guideway MB: Bus CC: Cable Car CR: Commuter Rail DR: Demand Response FB: Ferryboat HR: Heavy Rail IP: Inclined Plane LR: Light Rail TB: Trolleybus VP: Vanpool

12 70% 60% 50% 40% 30% 66% 14% 8% 6% 6% 20% 10% 0% Every two years Every five years As changes made Varies by asset type Other FIGURE 2 Primary source of inventory data (n = 40). FIGURE 4 Data storage (n = 37). FIGURE 3 Data record and update system (n = 37). FIGURE 5 Frequency of inventory data updates (n = 36). FIGURE 6 In-house support.

13 FIGURE 9 Capital spending by investment type (n = 27). FIGURE 10 Condition assessment approach (n = 31). FIGURE 7 Use of asset inventory data (n = 40). FIGURE 8 Capital program type (n = 36).

14 • Two of every three respondents indicated that their agen- cies use rolling programming cycles. This means that most of the large transit agencies need to make capital needs forecasts every year. • The responding transit agencies spent an average of 62% of their 2009 capital funding on SGR projects. This may reflect the national norm for a large transit agency seek- ing to balance growth and re-investment. • Most responding agencies determine asset condition through a combination of age and inspection results. This may mean that agencies assess the condition of selected asset categories such as bridges based on inspections while relying on age for other asset categories. • Almost two-thirds of the responding agencies update the condition data in their databases every 1 to 2 years.FIGURE 11 Frequency of condition updates (n = 36).