Data Driven Instead of Complaint Driven SAFE, EFFICIENT, and TIMELY deliveries of transportation service are the three key pillars of the student transportation mission. These three areas make up what should become the measures of student transportation operation performance. If we want to have a successful student transportation operation, efforts should constantly be made to acquire data linked to these performance measures. Certainly we have accident and incident data to provide information on the SAFE part of our operation. Tracking it from year to year with intervention strategies would provide some interesting comparisons. Likewise, budget information is readily available on the cost of various aspects of the transportation operation which provides some information on efficiency. However, in most operations, there is no objective information available for TIMELY delivery of students. Typically, the measures for the TIMELY portion of the operation are subjective measures coming from a building administrator or a bus driver. Many drivers and principals choose not to report late arrivals or only report them when they become a nuisance. In some special education center programs, administrators only report if buses are late in taking students home, and do not report late morning arrivals. Objective systems need to be put into place to provide this important measure of student transportation performance. Every school transportation operation should have daily and weekly objective on-time arrival rates, but most do not. Fortunately, integrated AVL is the right tool to fill this data gap. Moreover, it is also the right tool to help determine EFFICIENCY. In other words, EFFICENCY and TIMELY are interwoven together. Comprehensive data sets to record vehicle positions and movements, and analysis tools to find optimal paths accommodating the movements are essential elements in providing this information. Such data sets include student enrollment data (SED), school programs and building data (SPBD), student home address data (SHAD), street network data (SND), bus stop data (BSD), and bus runs and route data (BRRD). The tools for optimizing transporting students include assigning stops, scheduling bus runs, optimizing bus routes, and data synchronizing among various data sources for conciliating changes and discrepancies. The solution for moving to a data driven student transportation management makes it imperative to construct an ISTMS.  Fig 1 Only when the two sets of data are integrated can GIS functions be used to optimize bus routes and to make bus schedules |