When it comes to providing the right level of customer service within their physical stores, retailers find themselves in a dilemma. Economic uncertainty, coupled with the changing retail landscape, have made it more difficult than ever to predict shopping trends, in-store traffic and subsequent sales revenues. As a result, retailers have become even more risk averse and are continually looking for ways to reduce costs within stores. Since most store expenses are beyond the typical store manager’s control (rent, cost of goods, etc.), the easiest outlay they can control is payroll – particularly the allocation of associate hours. But the price of overly tight controls is that fewer associates will be available when the customer does decide to shop.
Conflicting directives between finance and operations is nothing new
It’s an age-old game of tug-of-war: the retail operators call for payroll increases to take advantage of potential customer traffic opportunities and drive additional revenue, while the finance team demands tighter payroll controls to protect the bottom line. And store managers are caught in the middle – changing schedules during the week in an effort to satisfy both leadership groups and instead frustrating both their employees and their customers. The typical process works something like this:
- Store Managers receive their allocation of staff hours in advance of the week being scheduled.
- A schedule is created and distributed to the workforce prior to the beginning of the week.
- The week begins, and all levels of management sift through the daily results and attempt to determine if the week will come in as planned.
- At some point during the week (and sometimes even daily), a message goes out to the store management teams to modify the schedules as a reaction to what’s already occurred so far in the week.
The problem with this approach is that it makes two inaccurate assumptions:
- False assumption #1: What happens at the beginning of the week is exactly what happens at the end of the week
- False assumption #2: Impacting one week’s customer service level has no bearing on customer lifetime shopping habits
There is no such thing as a reliable mid-week re-forecast
Let’s start with false assumption #1. If there was a universal class in Retail 101, one of the first things store managers would be taught is to modify schedules based on how the week is “trending”. This is code language for “cut back your payroll hours” since such trending analysis is rarely positive (as those of us who have been responsible for corporate payroll planning and individually managing store schedules can attest to). Statistically speaking, this is simply not true. Taking the assumption to the extreme, if you believe that the first few days of the week are a good indicator for the rest of the week, then what happens in the first week of the month should predict what will happen during the rest of the month and the month should foretell the quarter and the year. That would mean that the first few days of the New Year should actually give you a sense of how the entire year will end. No one would accept those assumptions because there is too much volatility within the 12 months that make up the year.
In my retail career, I’ve had the experience of working for a very diverse group of specialty and department store brands that range from smaller boutiques to larger, “big box” stores. What happened on Sunday, Monday and Tuesday did not indicate what happened on Thursday, Friday or Saturday. If you do not believe me or think that your organization runs contrary to this analysis, you can perform your own analysis as one of my old colleagues, Ted Nugent (no, not that one), did. Ted is not only an expert on statistical analysis, but he has the engineering background to apply that theoretical knowledge to the practical application of running a retail business.
Ted did an extraordinary deep dive correlating daily sales and in-store traffic results on a store-by-store basis with more than three years of data. Since trending usually involves period-over-period analysis, he used daily comp sales and comp traffic as his guide. The idea was to see if the aggregate sales comps for Sunday through Tuesday correlated to the aggregate sales comps for Thursday through Saturday. He also applied the same logic with customer traffic comps. Assuming that there was a good correlation, then the idea that the trend from the beginning of the week could tell us something about where the week would end up makes sense. However, we found between a zero and low 20% correlation – meaning that what happened at the beginning of the week had little to no influence on the business for the end of the week. I’ve repeated this same analysis with other retailers’ data and found the same lack of correlation.
The best time to re-forecast was just prior to the start of a new week immediately after the most recent week closed. This gave us slightly more reliable data since it included an entire weeks’ worth of information and was closest to the week that was being predicted. If you do your own analysis and find a different answer, I’d love to hear from you!
If you think about it, this makes sense: consumers don’t shop based upon a reaction to what transpired earlier in the week with the possible exception of a significant weather incident or a major traffic detour. And even in these instances, customers may be just as likely to shop earlier in a week in reaction to late week incidents from the prior week.
The finance team is looking at the wrong math
Now on to false assumption #2. As discussed earlier, the finance team is always looking for opportunities to contain operating costs, especially if sales estimates are lower than anticipated. The direction appears to be pretty straightforward: keep the selling cost at a specified percentage (or the sales per hour at a consistent rate) at all times. But “all times” are not equal, especially at an hourly level and on a store-by-store basis. Too much volatility occurs. The math may work when the numbers are rolled up to a higher level on an aggregate basis, but that becomes purely a math exercise.
The true impact is that the store manager is forced to sacrifice service levels and the customer is underwhelmed with the result. Customers either don’t buy (lower conversion rate) or don’t maximize their shopping visit (average transaction size). In either case, they may be less likely to return at a later date to re-engage with the store, which puts their lifetime shopping value at risk for the brand. If this appears to be too dramatic, review your stores’ conversion and average transaction sizes at the end of a week as compared to the beginning and take a look at customer loyalty scores for the same periods. You may think that you are having better sales results at the end of the week, but if you separate out the traffic during those times from the productivity measurements of conversion and average transaction size, you will find that the higher sales result purely from higher traffic, not higher store productivity. And that lower productivity is directly related to the allocation of staff hours.
Striking an optimal balance by controlling what can be controlled
So why do retailers re-forecast trends for payroll purposes? Two answers come to mind. The first is the flawed math of taking the beginning of the week (Sunday through Tuesday) trend and comparing it to the TOTAL week trend (Sunday through Saturday). Since you already know half the week, those results play a significant role in the eventual outcome. When trending, each day should be considered on its own merits rather than compared to the full week. That is why it’s more optimal to wait until you have the necessary full weeks of data to trend and adjust payroll accordingly.
The second reason that retailers perform this exercise is to exert some control over the week’s outcome. We all want to feel that we can reverse declining performance or maximize improvements, so continuing to adjust hours by shifting associate schedules, sending someone home early or by asking someone else to be available for a last minute shift makes us feel like we have more control over sales outcomes. The problem is that we are addressing the wrong behaviors when we adjust in this manner. Changing already established schedules with very little notice accomplishes two detrimental actions: employee satisfaction and earnings are lowered and customer service declines. Some retailers recognize that the most critical shopping times occur during Fridays through Sundays, and have adjusted their scheduling weeks to begin on Friday so that mid-week adjustments happen after the weekend has ended. While this may help to protect the biggest shopping days of the week, it reduces necessary customer engagement time for the rest of the week because you would have fewer hours to distribute during those later times.
If you shouldn’t rearrange the schedule mid-week, what can you do to positively influence sales results?
Within the moment as within the week, the greatest influence managers can have is by staying on the sales floor. Observation, asking questions, interceding when necessary and taking advantage of in-the-moment training opportunities can make more of a difference in closing sales and is also more empowering and more fun for everyone involved!
The other strategy to employ, is to plan for a week realistically (as opposed to optimistically) in advance of the week to be scheduled. If the week is planned with unreasonably high sales, then the payroll allocation will also be too high. This leaves the manager with two risky options: either offer inadequate service or blow payroll hours. While overusing payroll is not cost-effective, poor customer service puts even more at risk if customers decide to shop elsewhere in the future.
Is there ever a good time to make schedule changes?
Given the dynamic nature of retail, there will always be the need to adjust schedules to respond to the needs of the business. Associates still call in sick or have unexpected personal needs and their shifts will need be filled so that customer service doesn’t erode. Weather or unusual events will persist and the store’s traffic pattern will be influenced accordingly. All of those decisions should be made in the moment and with strong corporate guidelines and perhaps even with the wise counsel of a field leader. Trying to address all of these scenarios through a re-forecast is time consuming and counterproductive. Remember that you are influencing customer behavior as well as associate behavior, which means that you are doing more harm than good in the long run!
So as far as re-trending mid-week goes, stay the course. Cutting back as a result of a misperceived trend just creates a self-fulfilling prophecy!
Teaching managers how to make good decisions in the moment and then holding them accountable to execute a realistic weekly payroll allocation with minimal inter-week adjustments will lead to both consistency and better customer service in both the short and the long run.
Prudent hours management starts with realistic weekly expectations, includes sound scheduling practices and a lot of patience, so that operators do not over-react to falsely perceived business trends.