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Iterative Design and Implementation: A Model of Successful Scheduled Maintenance Technology Deployment

With significant budget reductions, many transit providers are finding that they must examine the way in which they maintain their fleets. As the use of outsourcing to stay within budget increases, those serious about maintaining their own fleets are looking more closely at totally new approaches that emphasize the efficient use of funds and labor resources with the goal of maintaining high fleet performance. Preventive maintenance has been accepted as a solution, and many transit industries are investigating computerized decision support systems (DSSs), often borrowing technologies developed for related industries (e.g., aviation) and tailoring them for transit purposes. Unfortunately, most implementations fall short of expectations. To be effective, DSSs require users with an in-depth understanding of their logic and detailed knowledge of the work being done. Mechanics and foremen have the work knowledge but are unlikely to possess an understanding of computerization and the abstract algorithms driving these technologies. One system adapted to the transit industry by New York City Transit—MIDAS—has been implemented successfully in the Department of Buses. The three-part top-down/bottom-up model for technology deployment is described, as is the evaluation used to measure its success: a relatively small design team of software developers, maintenance managers, shop-floor workers, and foremen; a powerful new training technique resulting in direct data entry from the shop floor; and feedback from the work floor to tailor the system. It is concluded that deployment must be organized around the concept that DSSs are tools appropriated by the users and that implementation efforts should facilitate that process. This is in striking contrast to “turnkey” approaches. Follow-up evaluation data are presented that show how this model leads to more innovative and effective system use over time.