Over the last few months I have heard more and more about analytics in workforce management. Coming from my former Division Manager and mentor, I heard countless times that “You get what you inspect, not what you expect.” The two are basically one in the same. Analytics inspect your operation for its follow through, execution and accuracy. From exception reporting to ratio analysis, analytics play a key role in any operation.
We live in a time where data is king. Data warehouses, data cubes, data clouds, you name it. More data is available to us faster than ever before. Smart operators are utilizing that data for many decisions and smart workforce management vendors are perfecting their offerings regarding analytics.
So, where does work measurement come in regarding analytics? At the baseline of all analysis of labor I would say. Remember, we need to inspect how people are performing to plan, not just expect them to adhere to our plans. We need to know how the forecasted labor need lines up with the scheduled hours. It is important to understand how the actual throughput of work stacked up with the actual need. It is advisable to always analyze the hours tracked and paid against the hours needed for the work generated.
In each of the three areas mentioned (forecasted labor, needed labor, and utilized labor), work measurement has a very important part. When looking at labor from a strict financial slant the metrics are less meaningful because business has changed. No longer can sales per labor hour and labor cost as a percent of sales give an operator something with which to accurately inspect the management of labor. There is too much volatility with mood swings of inflation and deflation in today’s economy.
A $20 shirt and a $60 shirt take the exact same time to unpack from a carton, place on a hanger, affix a size label to, and hang on a rack. An $8 bottle of wine and a $40 dollar bottle of wine take the same amount of time to unpack and place on a shelf. A $3 box and a $15 box take the same time to form and tape for packing. Therein lays the fallacy of reporting labor from a strictly financial point of view. Should the operator who sells $60 shirts get three times the labor to do their job? Should the store that sells a$40 bottle of wine this week get five times the labor to operate than last week when it sold $8 bottles? Should the plant schedule five times the labor if the same size box is being put together because the sales price of the box to the consumer is higher? I would hope we all agree that the answer is “No” to each of these questions.
A better method of productivity analysis and therefore labor analysis is to use work measurement to develop your benchmarks. Drop the concept of financial analysis only, and start inspecting your operation based on facts from measuring the actual time it takes to do work, not only the cost it takes to do work. I speak to executives around the world about labor and each and every one of them can tell you down to the penny how much labor they did use last week. Only a very select number of them can tell you how much labor they should have used last week.
So, getting back to the subject, how does work measurement fit in with analytics? It is a key ingredient. Every operation should be using work measurement against the huge number of data drivers available to track need versus schedule, actual versus forecast, and actual need versus actual hours used. These metrics give the operator a great insight into their workforce utilization. They give the operator a tool and template for rigorous inspection of performance.
Many things are being analyzed in this age of data availability. The technology to set up valuable analytics and reporting has never been more robust. Therefore, it is the perfect time to use work measurement to get a true gauge of your company productivity and to keep it in line for the foreseeable future. Remember, you get what you inspect, not what you expect.
