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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 FIGURE 1 Agency response to survey. 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 Designated in-house staff support and update the databases responding agencies determine asset condition through a com- for most responding agencies. More than 80% of the respon- bination of age and inspection results (Figure 10). This may dents reported that their agencies use only in-house staff and imply that agencies assess the condition of selected asset cate- do not use contractors to maintain and update their asset inven- gories such as bridges based on inspections while relying on tories (Figure 6). Almost 60% of the responding agencies use age for other asset categories. designated, but not dedicated, staff to maintain and update their asset inventories. These inventory responsibilities are one Almost two-thirds of the responding agencies update the of several job responsibilities for the designated staff. 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). USE OF INVENTORY DATA Another 17% of the responding agencies reported that the The use of the inventory data is reported to be high (greater frequency of their updates varies by asset type. The collection than 75%) for most common applications (Figure 7). There is of condition data on some asset types (e.g., vehicles) typically near unanimity reported in the use of the inventory data for are part of routine maintenance activities. For other asset types capital planning purposes. For many agencies, the inventory also serves as the basis for condition assessment as well as reg- (e.g., bridges), special efforts must be made to update the con- ulatory and financial reporting purposes. dition data. The capital program cycles vary by length and by whether SUMMARY 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 The survey revealed some key findings about the state of two-thirds of the responding agencies use programming cycles practice of asset tracking systems and capital programming at that are 5 years or less (Figure 8). Two of every three respon- large transit agencies: dents indicated that their agencies used rolling programming cycles. Virtually all large agencies have asset tracking databases that are frequently updated and include all assets. Taken together, these two responses indicate that at least The primary sources of the data vary among the transit two-thirds of the transit agencies revise their capital programs agencies. Common sources include financial records every year; therefore, most of the large transit agencies need to (fixed asset ledgers), asset inspections, maintenance make capital needs forecasts every year. management systems, or some combination thereof. Although all data are maintained electronically, there are The programming cycles are related to the planning cycles variations in how the data are stored. The most common at most of the responding agencies. Twenty-five agencies storage packages are off-the-shelf, financial information (71%) reported that the renewal cycles of their capital pro- or asset management databases, and special databases grams are linked to the duration of their planning cycles. developed internally or by outside consultants. Designated in-house staff support and update the data- The types of capital spending are often the subject of criti- bases for most responding agencies. Most responding cism from transit observers. Capital spending can be divided agencies do not use outside contractors for this support.

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11 TABLE 1 RESPONDING TRANSIT AGENCIES AND MODES OPERATED Modes Operated Transit Agency Location 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 Austin, TX X X X (CMTA) Central Florida Regional Transportation Authority Orlando, FL X X X (LYNX) Chicago Transit Authority (CTA) Chicago, IL X X City of Detroit Department of Transportation Detroit, MI X X (DDOT) City of Los Angeles Department of Transportation Los Angeles, CA X X (LADOT) City of Phoenix Public Transit Department (Valley Phoenix. AZ X X Metro) Dallas Area Rapid Transit (DART) Dallas, TX X X X X X Greater Cleveland Regional Transit Authority Cleveland, OH X X X X (GCRTA) King County DOT -- Metro Transit Division (King Seattle, WA X X X X X County Metro) Los Angeles County Metropolitan Transportation Los Angele, CA X X X X Authority (LACMTA) Maryland Transit Administration (MTA) Baltimore, MD X X X X X Massachusetts Bay Transportation Authority Boston, MA X X X X X X X (MBTA) Metro Transit Minneapolis, MN X X Metropolitan Transit Authority of Harris County, Houston, TX X X X X Texas (Houston METRO) 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 Buffalo, NY X X X METRO) 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 Sacramento, CA X X X RT) San Francisco Municipal Transportation Agency San Francisco, CA X X X X X (SFMTA) Santa Clara Valley Transportation Authority (VTA) San Jose, CA X X X Southeastern Pennsylvania Transportation Authority Philadelphia, PA X X X X (SEPTA) Tri-County Metropolitan Transportation District of Portland, OR X X X Oregon (TriMet) 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 Washington, DC X X X (WMATA) Westchester County Department of Transportation Mt Vernon, NY X X (The Bee-Line System) 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

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

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

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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 FIGURE 11 Frequency of condition updates (n = 36). condition data in their databases every 1 to 2 years.