Maintenance Staffing Levels for Light Rail Transit (2005)

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29 Each light rail transit (LRT) agency operates in a unique environment. For this reason, it is difficult to guide a light rail agency to an optimal maintenance staff. However, it is nat- ural for managers to be curious as to how they are doing; to compare themselves with industry norms. This synthesis of industry practice offers some information in this area. It does not appear that the number of vehicle maintenance staff has any direct relationship to vehicle type, average vehi- cle age, or rate of revenue service failures. Nor does climate or even age of system infrastructure allow for any firm con- clusions on the optimal maintenance of way (MOW) staff lev- els. There are too many factors involved to be able to isolate any one as causal, and too few LRT systems to perform a meaningful regression analysis. There are also nonquantifi- able factors involved, including budget constraints, collective bargaining agreements, worker morale, and/or management philosophies. It is not possible to extract from published sys- tem statistics clear guidance on maintenance staffing. Certain indicators are used by most agencies as bench- marks. The most widely used is the “number of revenue sys- tem failures” for light rail vehicle maintenance. However, accurate information on this indicator is lacking owing to the varied definitions in use. National Transit Database statistics show reported annual revenue system mechanical failures ranging from zero to several thousand. This range appears to be large. Because of its importance to maintenance man- agers, the industry could benefit from a consistent definition of “revenue system failures.” For MOW maintenance the benchmark most used is “cost per track-mile.” Comparing the cost to maintain a track-mile among U.S. cities, however, is difficult, because each system is in a different cost-of-living area. Spare parts, on the other hand, are often purchased on the national or even global market. Some useful non-cost indicator of MOW maintenance performance could be selected by the industry as its standard benchmark. The need for and efficient use of common spare parts was noted by many transit systems. Although this is difficult to achieve given the number of railcar vendors in the market, the industry might want to select and standardize key com- ponents with high failure/replacement rates. The industry does not use part-time employees: only 4 of the LRT industry’s approximately 3,400 maintenance work- ers are designated as such. Moreover, there is universal agree- ment that it is less expensive to implement overtime than to hire additional staff. The case studies were helpful in providing information on maintenance staff levels. The four systems chosen for review were organized somewhat differently and had differ- ent numbers of maintenance positions. Overall productivity as measured by total maintenance employees per unit of common measure (track-mile, peak vehicle, or car-mile) appears to be better with simpler organizations and fewer job classifications. There also seems to be a fairly consistent range of maintainers-to-manager ratios across the industry. These vary somewhat by the technical nature of the maintenance function. For example, most agencies reviewed had more managers to maintainers in the signal and communications functional area than in any other. This makes sense given the critical nature of this subsystem. The study results could be used to confirm whether a staffing plan has a reasonable blend of managers and maintainers. The staff productivity indicators—employees per unit of measure—vary as well among the agencies surveyed. It was nevertheless possible to recognize a possible common range. Light rail transit systems can use these common staffing ranges (summarized in chapter four) as a check on reasonableness. CHAPTER FIVE CONCLUSIONS