What Gets Measured Gets Improved

Its a priceless mantra that we’ve all used many times. However, knowing what you are going measure (and why), how are you going to measure it and how are you going to turn your new knowledge into an actionable and worthwhile result is the real challenge.

What I’m talking about is reducing driver turnover and using the real data that is right at your fingertips, if you chose to mine it and use it for better turnover results. When I ask most companies about their turnover rate, rarely do I get a response that is more than a guess. I find that surprising, to say the least. In today’s trucking environment it is all about the driver, hiring them and keeping them. Here is what I measured, how I measured it and how I used the results when I ran my company.

What

  • We had 6 dispatch boards with approximately 300 trucks. We measured short-term turnover, meaning those who had been with us for under 1 year. We grouped this by drivers, O/O’s and overall. We tracked companywide turnover, meaning the board fleet as a group, again segregating company drivers and O/O’s. We also measured turnover coming out of our training trucks on entry-level drivers. Total reports were 4-5 per board, depending on whether they had ELD or not, and overall total reports were 27 – 33.

How 

  • We used an old JJ Keller formula that I still use, it really doesn’t matter what you use if it is consistent, and it is a rolling 365 day a year tool. We used the following:
  • Short-Term Driver turnover ratio 12 Month = Drivers no longer with the company that were hired in the last 12 months divided by the number of drivers employed in the previous 12 months.
  • Long-Term Annual Turnover Formula    = Drivers no longer with the company (YTD) divided by elapsed days X 365 divided by total # of Drivers. By the way, an employed driver is one that has turned at least one mile of work in which revenue was generated. The fact that you have any no shows at orientation is an entirely different issue.

Action

  • We’re looking for variations in the numbers. Why are some boards results better than others? We’re not looking for bad guys here. The exercise will reveal two things are at play here that can help our results:
    • First, you will likely see where you are getting some stellar results – an individual or two that have turnover rates that are well below the rest of the gang. The obvious question is how are they getting these results? Are there things that they do that can be shared with the rest of the dispatchers? Do these individuals have behavioral traits that we can identify and possibly hire to those traits in the future? Can this person or persons mentor other dispatchers?
    • Secondly, are there things we’re doing or not doing that are creating poorer turnover results on those boards that have the higher turnover numbers? Take a second level deep dive into common root causes on these boards and let’s see what’s really going on.

Once the measurements process is set up and functioning, it is quite easy to generate these reports on a monthly basis. Give it a try and see what opportunities you might uncover. Measure and manage – here we come.

Safe Trucking,

RJH

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