Data Plus Observation:
The Keys to Effective Labor Management

By Dan Kaus

There is a quote that often appears on the desks of accountants and others who work with statistics: “In God we trust; all others bring data.” Accurate data is so valuable because indeed it can be trusted. But is data on its own to be relied upon at the exclusion of other relevant information? For fast lube operators, utilizing the data they have collected over the previous weeks, months and years is undoubtedly an important source that is helpful in making current day management decisions. But when it comes to decisions about labor management for example, some of the most meaningful choices operators make when it comes to the overall health of their business, combine the use of data with another important element — observation. So, because decisions about labor influence so many aspects of the business, it’s timely to spend a few minutes considering the wisdom of combining data and observation.

The Role of Data

The process of effectively managing employee labor consists of a variety of elements, one of which is the use of historical volume records.

There’s no doubt that the ability to track historical volumes is extremely simple with the wide variety of computer programs designed to do just that. Computer systems across the fast lube industry are doing their jobs collecting and categorizing the data into as many different analysis models as you may care to list. But do managers often times schedule out of habit or according to the available data?

To illustrate the importance of this question, in one instance an operator of multiple units had his managers write, from memory, a weekly employee schedule based on the volume patterns that they had come to expect for each hour of the day and each day of the week. After the managers had written their schedules, the operator asked these questions, “You’re sure these are the schedules you want to go with? You’re certain that you know your operation well enough that these schedules fit the customer patterns in your center?” Every manager in the room answered in the affirmative, and each was confident that he knew his center and that the schedule he had written was appropriate.

As you might have guessed, when the operator compared the schedules the managers had written to the schedules that actual historical data would dictate, every schedule written by the managers needed major adjustments. The point is that managers may often come to believe they know volume patterns well enough without checking actual data. That can be a costly mistake either in terms of too much labor at given hours or not being staffed to handle peak volume periods.

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