Those whotake mass transitto work know the frustration of trying to make an important meeting only to discover the bus is not at the stop at its appointed time. The same goes for students who are trying to make that all-important class and get to the stop just as the bus is pulling away from the stop, earlier than expected.

Last week’s iSixSigma Live! Summit in Miamiexamined this problemduring anoff-site tour of the University of Miami in Coral Gables. Theschool, which has an advanced Lean Six Sigma system in its Business Services Division, recently completed a project to optimize its campus-wide shuttle busservice, which was experiencing problems with wait times that were beyond customer tolerances.

Dr. Howard Gitlow, Professor of Management Science, at the universitydescribed for the iSixSigma tour group someof the details of theroute optimization project, which was conducted by MBA students in the School of Business Administration and spearheaded by Master Black Belts Rick Melnyck and Scott Widener. After conducting more than 100 voice-of-the-customer surveys, the project found that nearly half of the customer complaints fell under the categories of long wait times for buses, great variability in wait times and “stacking” of buses at certain heavily used stops.

Whileone obvious solution would be to set up aschedule with timed stops, the VOC data showed that 81 percent of the students preferred toleave the current, unscheduled shuttle system in place, Widener said in his presentation.

One of the difficulties encounteredduring the project were the many variables that could create havoc in the system, such as time of day, rush-hour traffic, weather, bus breakdownsand heavy passenger loads caused by campus events. As Widener described it, the buses were “like links in a bicycle chain” running around theperimeter of the campus, only these links could also move independently and sometimes bump up against each other during their circuit.

Using the university’s state-of-the-art dashboard, the team analyzed data on the number of buses in service, the distance traveled between stops, the time duration at each stop, the particular dates and times under study, and the number of passengers embarking and disembarking. After cleaning up some “noise” in the data, such as GPS units that were not turned off at night, showing “huge stop durations,” the team began noticing patterns emerging, such as heavy passenger loads in the early morning and the very light use of some of the stops.

The team eventually came up with three recommendations to meet VOC demands and save money for the university:

  • Cut the express service, which would reduce the amount of buses and thus the incidencecs of stacking that occurs during peak periods. This change would also save the unversity $1,980 per day in expenses.
  • Eliminate certain stops, which also reduced the number of difficult and time-consuming left turns the drivers needed to make.
  • Add a timed schedule to only the night routebus, guaranting that buseswill be there at pre-determined times, which reduces wait time and increases safety.

One of the more intriguing findings in the data had to do with what Widener called the “sense of entitlement” many students held about their bus routes. Rather than walking to a stop that would take less than five minutes, they insisted on going to their usual stop and waiting longer for “their” bus to arrive. In some cases, he said, wait times could be significantly reduced if students crossed the street and took the bus in the opposite direction, say clockwise in the loop, which would get them to their destination faster than their usual counter-clockwise route. Yet, the students refused to change their habits, he said.

About the Author