Managing a service department by looking only at your monthly financial reports can be like driving a car with your eyes closed. You don’t see the real numbers that determine profitably. Even worse, those vital numbers, presently hidden to you, could clearly show you the leverage points in your operation, the things you can change with a small effort to produce bigger results in the long run.
What You Don’t Know Can Hurt You
Here’s one example of hidden metrics. When asked to list their technicians in order from most profitable to least, most managers would simply produce a history of billable hours by tech. Going further, they might give you productivity metrics too, like billable hours compared to clock time and the like. So, what’s missing from that type of analysis?
Data Scientists Do Microscopic Surgery on Your Records
Suppose a data scientist, a skilled one who had studied your records in depth, proved that some of your highest earning techs are also your least profitable? How could he or she possibly say that? How would he arrive at those alarming numbers?
Easy. Suppose the scientist showed that the techs in question have the worst customer retention rate among all your techs. That means that they are losing you service customers faster than anybody else is. Every tech has service customers who were not pleased, and who never come back without ever lodging a service complaint. But some techs loose more customers than others. It would be profitable to identify those techs and reverse their negative trend with some focused training and counseling.
Trends in Your Customer Retention Data Show What’s Really Happening in the Service Bays
To uncover those trends, the data scientist did a longitudinal study of customer retention by technicians over time. Then he or she ranked the techs in order from the best at retaining your customers (the customers who come back repeatedly for repairs and service), to the worst, the techs who had the most customers who never returned, ever again.
Typically, you would want to see this data presented by the number of repeat sales versus the length of time (the number of years) since the customer’s very last service visit. See the point?
Yes, you do have to distill the data to account for things like customers who moved away, bought another brand of car and the like. But we know that the majority of customers who are unhappy with a business won’t complain. They will just stop doing business with you. In those cases, what you don’t know does hurt you in the long run, because you can’t fix the cause(s).
Repeat Customers Are Your Most Profitable Customers
Does your shop measure that metric, customer retention? Do you have the numbers readily at hand to counsel techs, to see what they are doing wrong, to train them, or to coach them on best practices?
SAs Have Their Own Customer Retention Trends as Well
While you are analyzing data, look at how well each SA does at keeping their customers coming back. Only by seeing actual numbers on things like that can you take corrective action.
Support Your Service Manager
A service manager who asks the IT people for this data would normally meet resistance. The CRM system does not capture these numbers automatically, but the data that will yield those numbers is buried in there none-the-less. That’s why the process of uncovering valuable info like this is called data mining.