Do Your Retail Staffing Profiles Match Your POS Patterns?

There are a myriad of components to an exemplary retail customer experience. For retail stores, the customer experience begins at the first awareness of any advertising and price promotion. Experiences progress into location cleanliness, store appearance (attractiveness), lobby organization, store cleanliness and organization, signage effectiveness, merchandise recovery (straightening merchandise that was heavily shopped), price marking, price accuracy, approach and acknowledgement by sales associates…and the list goes on.

To optimize the customer experience your stores offer, your store associate staff needs to be properly trained, sufficiently available to properly serve your customers and their presence needs to be aligned with customer shopping patterns (when customers are present). These components have always challenged retailers and they can quickly go awry if not monitored regularly.

In analyzing various retail staffing situations, I have repeatedly encountered misalignment between customer shopping patterns and staff availability patterns. The initial graphic (above) is a real client example of what is discovered all too often. Note the lack of alignment between hours and POS transactions on Friday, Saturday and Sunday, the busiest shopping days of the week. The amount of deviation from calculated “required hours” (derived from the labor standards by key task) indicates that both the scheduled and actual hours were fewer than required for adequate sales floor coverage. Customers notice this.

Contemporary staffing algorithms are intended to match historical POS patterns (by date, day of week and time of day (hour) with staffing availability and protect against potential misalignment as is shown in the initial graphic example. These algorithms, however, are not perfect. The organization depicted above had been utilizing their own home-grown staffing algorithm. Its lack of effectiveness is quite obvious.

If a (capable) staffing system is properly configured and able to accurately access store POS data (number of transactions), then it should be able to predict (with reasonable certainty) what future POS patterns should be. There is always an error factor to be dealt with when estimating customer traffic, due to unforeseen factors such as serious weather occurrences or even serious social issues. The POS pattern projections are just that, projections. Although they are based upon historical patterns (see sample graphic below), they do tend to repeat by date (time of year), day and hour and present a reasonable expectation to which associate staffing should be matched. Note that different days of the week have unique patterns (below).

Associate staffing presents a world of unknowns to the retailer. Scheduled associates can exhibit early and/or late arrivals / departures, sick or injury calls, jury duty, etc. even if they are properly scheduled. Alert store management creates contingency plans to deal with associate schedule non-compliance and can, should they choose, come remarkably close to matching POS pattern projections despite call-outs, but it requires pre-planning.

If you are not utilizing one of the contemporary store scheduling algorithms available to retailers today, I suggest that your operations team consider analyzing your scheduling patterns to discover if your stores are in alignment, or not. This process literally needs to be done to the hour level by day by store like the graphic below. Retailers who average coverage patterns over an entire day risk having any over and under scheduled periods cancel themselves out, appearing acceptable, when on an hourly basis they may not be.

Once your staffing coverage analysis is complete, should you feel you need to consider the installation of a more capable staffing program I recommend you consider the following suggestions:

• Seek knowledgeable assistance before you start spending time or money on a new scheduling system (or your application of existing software) and purchase a current, well developed package. These packages are expensive, so do your homework. Perhaps the best place to begin this process may be at a major retail trade show like the NRF Annual Show, typically held in January in NYC, where you can speak to various scheduling software providers and compare their capabilities. You would learn a lot about scheduling by attending that show.
• Carefully, develop updated labor standards for each of your key store tasks and keep in mind that you are mathematically modeling the tasks performed in your stores. Any inefficiencies that currently exist in your store practices will be reflected in your standards for all stores to follow. Logically, the best time to re-engineer your operational practices is while you are setting new task standards so that you can reflect “best practices” in your new schedules and drive labor cost lower throughout the chain.
•  Invest in a home-office operations team to oversee the use of the software and make sure they are well trained so that they can insure all of the variables that the system employs are accurate. If they are inaccurate you run a serious rick of under-staffing (potentially negatively impacting customer service) or over-staffing which could be painfully expensive.
• Ensure your store level associate lifestyle files are kept current to reflect accurate associate “schedule availability” and make an effort to ensure that the stores team “owns” any scheduling tool. Your IT team should support them, not the reverse, which is too often the case.

 Normally a significant training effort is required at the store level to help the store staff properly understand and utilize the staffing algorithm. One user “error” that seems to repeat itself is store management making too many schedule edits. If the scheduling software suggests a questionable staffing profile for an area and the staffing level seems inappropriate, the store staff should explore why before they adjust the schedule. System variables should be adjusted if required rather than store management deciding they do not wish to follow the system generated schedules and changing them without guidance. Schedule edits by store management should be limited.

After installing a new scheduling system, it is recommended that the stores take their time adapting to the new software. They should initially post newly created schedules along with copies of the “old version” schedules, to point out changes the system may be suggesting. Do this before you fully adopt new schedules created by the algorithm. Hold a discussion of scheduling pattern differences with the associates at (each) store and explain why the new schedules are suggesting staffing changes that your old manual schedules may not have considered.