Getting In-Store Labor Just Right: What Retailers and Goldilocks Have in Common
Let's face it: If you lead store operations for a brick-and-mortar retailer, you have something in common with Goldilocks, the fairy tale character made famous by author Robert Southey. For starters, just like Goldilocks, you typically demand that things around you are done just right. This is especially true when it comes to the all-important issue of scheduling labor in retail stores.
When store labor is heavy, payroll expenses go up and operations run hot. When store labor is light, conversions go down and operations run cold. However, when store labor is perfectly aligned with defined plans, then operations run just right. And when operations run just right, consumers receive the right amount of help from store associates, conversions go up, important tasks are completed on time, margins improve and everyone wins.
Unfortunately, if you're anything like most specialty retailers, your store managers are probably spending too much time in the back room fighting with unwieldy spreadsheets in an attempt to schedule the right people at the right times — and trying to do so in a manner that (hopefully) matches their allotment of labor hours for the week.
This, of course, is a problem because store managers are your best employees. They don't belong in the back room; they belong on the sales floor where they can answer consumers’ questions, provide coaching to store associates and attend to important tasks — all of which increase revenue and improve retail profits.
So what's the best way for modern retailers (and Goldilocks herself) to ensure that store labor is just right?
First, if one doesn't already exist, retailers should invest in some form of labor forecasting engine. Fortunately, a wide variety of models exist at different price points, including custom solutions from specialized consultants and "off the shelf" solutions from software vendors such as Kronos, Workplace Staffing, Workbrain, Empower and others. In all cases, such tools help retailers by integrating and interpreting various data to predict as accurately as possible the ideal amount of labor needed in a specific store to satisfy customer demands, maximize conversions and improve profit.