Goldilocks and the Three Dispatchers: Quantifying the Impact of Dispatcher Management

Editor’s Note: The SCM thesis Goldilocks and the Three Dispatchers: Quantifying the Impact of Dispatcher Management on Truck Driver Performance was authored by Danielle Procter and Paulo Sousa Jr. and supervised by Dr. David Correll ([email protected]). For more information on the research, please contact the thesis supervisor.

The problem with trucking

There is a saying, “If you bought it, a truck brought it!” This captures the expanse and impact of the American trucking industry. In the United States, overland trucking accounts for the vast majority of all freight movements. Yet despite being so crucial to the U.S. economy, the freight industry faces several compounding challenges: driver shortages, low driver utilization, and high driver turnover. The driver shortage is exacerbated by the under-utilization of driver hour-of-service hours and the frequent driver employment turnover.

But are drivers really responsible for these issues, or is there a way for carriers to mitigate these impacts? These questions led us to investigate the impact of carrier dispatchers on driver performance metrics. Dispatchers manage drivers and serve as the direct link between a trucker on the road and their carrier organization. Considering this, what attributes of drivers and dispatchers are most impactful in improving driver performance? For this study, we measured performance in three key metrics: hour of service utilization (daily hours driven out of the 11 hours allowed by law), average miles driven per workday efficiency, and driver retention.

What does Goldilocks know?

The first step of the study was to cluster dispatchers across their performance in these key metrics as well as a number of other areas engineered from the raw data. This clustering revealed three distinct dispatcher classes with significant differences in performance. These classes are most easily understood in the context of the children’s story “Goldilocks and the Three Bears.” 

The Mama Bear class is perhaps a bit too soft, creating an environment where retention is high, but productivity is low. The Papa Bear class is the opposite: Drivers are worked to maximum output, but he is a little too rigid, and those drivers see low retention. Finally, the Baby Bear class is “just right”: These dispatchers achieve balanced performance in all three key metrics.

Creating the “just right” dispatcher

So, what does this mean for carriers? Through clustering and linear regression analysis, our study distilled three managerial areas that carriers can focus on to impact fleet performance. The first is the importance of weekday. Though carriers have long considered Monday driving to be key to fleet productivity, we found the opposite: Drivers who drive less frequently on Mondays show higher efficiency. It is likely that these drivers are not following a standard Monday–Friday workweek and have more flexible schedules, allowing them to accept more loads.

The second is the distribution of work within a team. Dispatchers who assign loads based on driver capability and interest show higher aggregate productivity. And the third area is team size, which is positively correlated to efficiency and utilization. Crucially, we also found that team size is highly correlated to unequal distribution of loads within a team. This indicates that larger teams provide dispatchers the flexibility to build schedules that best suit driver strengths and needs.

The most crucial takeaway from this project, however, is the trade-off seen in the three key metrics of utilization, efficiency, and retention. Carriers should reevaluate their business strategies in the context of this trade-off and decide where to place the fulcrum to balance the key metrics. Though retention has long been a focus of the freight industry to mitigate driver shortages, it may not be the most important consideration. If we define the driver shortage as not just a lack of actual drivers but instead a shortage of available driver hours, utilization actually becomes a more important metric.

By acknowledging this trade-off, Goldilocks may determine which dispatcher bear will be “just right” to best meet her strategic goals.

Every year, approximately 80 students in the MIT Center for Transportation & Logistics’s (MIT CTL) Master of Supply Chain Management (SCM) program complete approximately 45 one-year research projects.

These students are early-career business professionals from multiple countries, with two to 10 years of experience in the industry. Most of the research projects are chosen, sponsored by, and carried out in collaboration with multinational corporations. Joint teams that include MIT SCM students and MIT CTL faculty work on real-world problems. In this series, they summarize a selection of the lat

SC
MR