I have been fascinated with two things my entire life—trucks and mathematics. More specifically, mathematical statistics, comparative analytics and benchmarking metrics. With the volume, variety and velocity of data now being produced in the trucking industry, I feel like a kid in a candy store. Data is the bedrock of productivity, performance, and cost reduction. However collecting the data is fruitless if you are not using the correct metrics to analyze it. The variety and relevance of data is opening our eyes to new connections and different factors that until recently were not even a blip on a fleet manager’s radar—or mine for that matter.
Take MPG for example. For years fleet managers used the metric of overall MPG to measure their fuel expense, a metric that is equally useful in calculating your total operating cost, forecasting your budgets and rating drivers in a leaderboard analysis. Often referred to as an activity metric, many fleet managers conclude their analysis here because historically that was all that they needed.
Not so with today’s volume and velocity of data. As equipment technology changes the fleet manager’s metrics also need to be revised. Consider the information that a fleet manager can garner when he uses impact metrics such as DRIVING MPG instead of overall MPG. Driving MPG eliminates many variables including idle time and traffic delays. It produces a true performance range of the vehicle and driver. It can disclose which OEM engine and transmission achieve higher MPG and help formulate a strategy for future equipment orders. It can also aid the fleet manager in developing programs that reward specific behaviors and correct those that have negative cost impacts.
This is not to suggest that idle and traffic time are not important. However, by altering the metric you can ‘isolate’ each variable with a sharper focus on separate issues that drive cost savings. For instance, idle time has a negative effect on maintenance and repair costs. A clear example of the impact of high idle time is increased DPF costs. Higher idle time leads to greater passive regeneration which increases maintenance costs and reduces DPF life. A replacement DPF can cost $3,000 plus labor, not to mention loss in overall MPG and down time. This is actionable intelligence that cannot be derived merely from overall MPG.
I came from an era where managing a fleet was often times like driving by the seat of your pants. The volume of today’s data can be very intimidating to even the most seasoned fleet managers. However, with the proper metric big data is the key to even greater success. One day he/she will have a moment of awe-inspiring insight and sudden realization that the data is their friend, the metrics tell the story that supports their decisions, and acts as a catalyst to re-think transportation and fleet management.
