One of TransPro’s key values is to present fact-based recommendations when engaging with our clients and teammates, and make it clear when we are only expressing our opinion. As a way of reflecting on and reinforcing this value, we ask each team member at our quarterly meetings to share a time when the facts brought them to a different answer than they expected.
Here are a few examples of cases where our data-driven diagnostic approach surfaced unexpected results:
- Nationwide On-Demand Mobility Provider – We recently engaged in a comparative study of traditional models of paratransit to an on-demand, TNC-style model. Using detailed data from participating transit agencies as well as the on-demand provider, our analysis validated some of our assumptions, but also provided some surprises. One of the counterintuitive findings was that despite single-loading of vehicles in the on-demand model, its productivity was over 50% higher in customers per hour. This finding reminds us the importance of questioning what may seem intuitive at the surface.
- County Government in Central New York – When we started this transformation project, which aimed to align resources with County priorities and identify cost savings, many expected that the largest opportunities would come from the Public and Mental Health Departments. When our team dug into the budget data and operating statistics in comparison to peers, we actually found that when taking into account revenues, these Departments were significantly outperforming peers. In fact, our analysis revealed that some of the biggest opportunities could be found in the Probation Department, which hadn’t been on anyone’s radar before the project began. This case reminds us to approach projects with an open mind and comprehensive diagnostic before designing solutions.
- Transit Agency in the Midwest – One of our favorite examples is an agency that was struggling to put service on the street. The prevailing view had been that the agency lacked enough buses to make pull out, and that they needed to lay off a significant number of bus operators due to the financial crisis they found themselves in. After careful analysis and documentation, our team found that the exact opposite was true. Maintaining an oversized fleet and inefficiencies in maintenance were causing excessive overtime. Additionally, due to absenteeism rates, the agency would need to hire more drivers in order to make pull out. Within weeks of parking extra buses and hiring additional drivers, the agency went from delivering 65% of scheduled service to over 90%, while still being able to realize significant cost savings overall. Similar to the examples above, this case reminds us that conducting data analysis with an open mind is critical for getting to solutions that will actually produce results.
We hope these examples inspire you to pay closer attention to what the data is telling you the next time you are addressing a challenge or designing a solution.
