RSR Research: Death to Payroll as Percent of Sales
Commentary by Nikki Baird, Managing PartnerÂ
Through a special arrangement,
presented here for discussion is a summary of an article from Retail Paradox,
Retail Systems Research’s weekly analysis on emerging issues facing retailers.
Assigning
labor budgets based on payroll as a percent of sales is bad and should be reconsidered.
One of RedPrairie’s innovative customers (who shall remain nameless) presented
their pilot at RedShift and their move away from the rationale and they made
a believer out of me.
The first issue with payroll as a percent of sales is that
of a self-fulfilling prophecy. Have you ever been in an airport early in the
morning to find a coffee stand that is staffed by one poor employee, hounded
by mobs of angry people anxious to buy coffee before getting on a plane? In
this case, sales have been ‘okay’ at the stand in the morning hour, but not
because of demand – it’s because the employee simply can’t serve any more customers!
How much greater would sales be during that morning rush if there were two
employees? Or three? That retailer may never know.
Now the reverse issue is a store firing on all thrusters,
but using labor it didn’t need. The example given during the session was selling
one $1 million item vs. selling one million $1 items. Which requires more labor?
So
what should you use instead? This retailer, together with a partner, developed
a method for budgeting labor based on minutes per traffic, or MPT. It’s dependent
in part on measuring foot traffic and subsequently, conversion. Measurement of
these two metrics can be controversial but it shouldn’t stop you – it’s the trend
that’s important, not the absolute numbers. Once you know how many customers,
and how often you convert per labor minute investment, you can figure out the
optimal number of minutes per traffic that should be invested in order to convert
a sale.
I have a strong feeling that this number is going to differ significantly
depending on the retailer and the category of goods sold. But the analysis
is pretty straightforward. Just look at your stores’ history of traffic, sales,
and labor hours. Plot minutes per traffic (how long an employee spends on average
with a shopper, based on labor hours divided by traffic) against conversion
rate and you get a good idea of which stores are good at making sales – good
investors of payroll – and which ones are not. You can also see a trend line
that will let you know what you should be expecting in terms of optimal minutes
per traffic to get optimal conversion.
So, as consumer spending returns, I know there are a lot of
retailers out there that suspect they are under-investing in labor and that
it might be hurting sales. Try this. Your payroll as a percent
of sales may increase in the short term, but the visibility and control that
you will have over stores’ effective use of their labor will pay you back in
spades.
Discussion Question: What do you see as the pros and cons of basing labor
budgets on traffic counts rather than sales?
I worry that delinking labor from financial gain would lead to all sorts of bad incentives, and therefore bad actions. For one, where is the incentive to convert?
The very best way to set labor levels is to examine the _marginal_ return on labor investment, rather than the standard _average_ labor productivity. It isn’t simple, but large retailers who are analytical in their view of operations run tests of increasing labor above/below the norm and measure the effect on sales. Then, they see how the effect varies by store characteristics (often store size, demographics, and competition are big drivers). With that knowledge, they understand marginal labor productivity, by store, not just to sales but to flow-through profit.
We used this with a coffeehouse client quite successfully and I profile it in my new book. Nikki is right on to suggest abandonment of the labor as a percent of sales. Fewer people on the floor due to fewer customers on the floor leads is a direct result of giving up. Number of transactions per hour over a period of a few months often can predict when the business most needs the help.
There are a number of metrics that can be used to measure labor. As a percent of sales has been around a long time and perhaps works in some industries. In restaurants, and now c-stores, labor is often looked as a percent of gross margin dollars (forecasted and post). Anytime you are using percents in this manner you are looking at a short hand method of measurement.
We have used a variety of ways to schedule labor over the years and have learned that two stores with exactly the same sales can have very different labor needs. One has larger market baskets purchased by fewer customers and the other has just the opposite. Some locations have control issues and require more labor to control shrink. One may have a larger mix of foodservice versus another, etc.
The article didn’t indicate how foot traffic was being measured. We all know that the number of people in a retail environment will be larger than the number of transactions. Transactions are easy to track, but I am not sure how you accurately track foot traffic. In some environments even if could track foot traffic there is a difference between those that can to buy possibly something and those that just came with. I look forward to learning more about what environment this labor scheduling model was used in.
I agree strongly that wages as a percentage of sales is a counterproductive means of staffing and to the author’s point, often a self-fulfilling prophecy for poor results.
I don’t disagree with looking at traffic and scaling manpower to appropriately meet it but I think there’s something important that has to happen before a retailer comes to that point.
Retailers have to very clearly design the architecture of the experience that they intend to deliver. What service level is required? How many staff per customer are required to meet these expectations? What components of service are essential to maintaining the stores unique image or position? To what degree is the environment self-service oriented?
All of these elements will have a very direct influence on the number and caliber of staff required.
Once this benchmark is established, it provides a sense of the minimum threshold for staffing–regardless of traffic, sales or anything else–to deliver the brand experience. If you slip below the minimum, you can be sure that you are falling short of delivering the intended experience to customers.
Depends upon the nature of the retail business that you are in…anyone who has stood in front of an impatient line of customers seeking small ticket items, like a QSR (I have), knows the value of proper staffing. So, too, do each of us who have walked into peak periods or low volume periods in other types of retail establishments. The customer wants to be taken care of, when they are ready to be taken care of–SERVICE is one of the highest priorities of the consumer.
I’ve walked into a big box home improvement retail store in Naples, Florida prior to Mother’s Day weekend, and seen 30 associates in the store at 9:30 on a Saturday morning. Perfect, perhaps, for the customer base in Atlanta, Raleigh, Chicago, or numerous other markets. In Naples, in early May, the ‘Snowbirds’ have flown North. I was one of perhaps 5 customers.
Staffing plans have to be driven by local market conditions, not an all-encompassing blueprint from the home office. The sales data and traffic counts are available from register tapes. Paying attention to the details of the labor costs, and having it in relationship to total sales is important…is vital.
I like using a combination of traffic, sales, and conversion rate to set payroll hours. I think the biggest mistake is setting payroll hours on the same week’s metrics. I recently spoke to a store manager who feels that if she’s short of goal three or four days into the week she has to cut payroll and then has no chance of achieving her sales goal. It’s better to set the payroll budget based on a four or six week trend than on the same week’s actuals. While this might lead to higher payroll in some weeks, it also gives the store the best chance to maximize their customer opportunities and exceed goal.
A friend of mine says it’s a lot easier to work on growing sales than cutting costs in a way that doesn’t hurt your sales. So true.
I agree completely with Nikki that blindly staffing a retail location based on a percentage of some smoothed-out sales number ignores the reality of retail. In grocery, we see a pattern we like to call the “grocery heartbeat,” which is the regular, weekly spike of volume on Saturday and Sunday (with a mini-peak on Thursday), and lower sales other days. If a grocer had the same number of registers open Tuesday at 11:00 AM as Saturday at 3:00 PM, they would lose money on Tuesdays and lose customers on Saturdays.
Any modern retail POS system tracks the date and time of each transaction, so you can very easily put together a chart showing the “heartbeat” of each location of your particular retail establishment, down to the day of week, hour, or even minute if you so desire (although, given the “lumpiness” of labor hours–you can’t really ask someone to come in from 8:00 – 9:15, 11:45 – 1:20, and 5:00 – 7:45–analyzing down to the minute has limited value). So, once you know your Minutes Per Traffic (MPT), then in theory, you could do the math and figure out the appropriate staffing levels for each hour of each day.
The question I have here is with one of the assumptions of the Minutes Per Traffic (MPT) measure. It seems that there is an assumed constant number of staff-minutes that it takes to handle a transaction. I wonder whether that number is truly constant. Labor is fungible, and the nature of employee activity can change depending on customer volume. Someone who is answering questions and running the register when the store is full of shoppers can be stocking shelves and sweeping floors when it’s empty. In fact, you *want* to, on average, over-staff the down time (so that you can catch up from the peaks) and under-staff the peak time (as long as you have enough bodies to handled the traffic).
So, I think the MPT number has to be different for peak vs. valley times. At peaks, your MPT should be lower, and your employees should stop doing everything except serving customers. During valleys your MPT should be higher so that part of the workforce can handle the customers while the rest of them ready the store for the next rush.
Payroll as a percent to sales is indeed a self-fulfilling and specious approach to determining store payroll levels. It is typically set by people who have neither worked in nor understand the reality of store operations. The result, ironically, is that sales suffer and, as a result, the percent to total actually goes up. This phenomena goes far beyond the selling staff and customer service as there is a lot more to running a store than just customer service.
Here’s a classic example. Black Friday to the second week of January is typically the highest sales period for most retailers. October and November typically produce much less volume. Just as typically, most retailers cut back on store hours in October and November and add hours in December. This completely ignores the reality that store receipts, floor sets, and a host of other transactions are highest in October and November. The result is stores having their payroll cut just as their task load peaks. Many bad things happen, not least of which is very poor associate morale and customer service.
The retailers that have done the best at this planning process are those that take a holistic view of all the transactions and tasks by time frame and then schedule hours accordingly. Doing this better optimizes the payroll costs and, when taken over an annual basis, actually helps to lower payroll costs as a percent to total.
There is an “invisible ceiling” on sales that is only partially effected by staffing, although that is the first issue that should be solved because inadequate staffing is a direct cause of a poor shopping experience and sets off a death spiral with bad word of mouth.
Simply adjusting store hours to traffic or sales volume is better than ignoring them but still only a shot in the dark. Charting sales to identify the invisible ceiling reveals the problem that detailed analysis and in-store observation can lead to the specific causes. Other factors that this analysis may identify include parking, cash register effectiveness, availability of shopping carts, in-stock position, etc.
The title of the RSR article is a little dramatic. But there is a great deal of truth in the article. The most important metric in planning labor is traffic. The second most is conversion rate. The third is planned non-selling activities. The fourth is minimum coverage. The fifth is the margin after selling costs per hour. The sixth is anticipated promotional uplift. The seventh is weather. The eighth is mall traffic. The ninth is recent trend of traffic conversion rates for day of week or hour of the day.
Way down on the bottom of the list is store associates costs as a percentage of sales.
The trouble of course is that point solutions like labor forecasting tools are very limited in what they can model. A better approach is to load as many of these metrics into a data warehouse and to model store labor based on the complete picture.
The one best way for scheduling labor is the one that works the best for a particular area given the season. All the above have a right place and right time. Nonetheless, Mr. Marek, direction the marginal return on incremental tends to reveal the most accurate information. Test your assumptions in the microcosm of the deli at a grocery store. A few items require little to no labor and others require substantial labor. Think you got it right? Wait until the seasons change. If your model doesn’t automatically change with the season, you are in trouble.
I agree 100% with Nikki. I think basing staffing on historic sales data is shortsighted and results in a self-fulfilling prophecy of continued downward spiral not only of total sales, but UPT and ADS as well. When traffic counters hit the scene a couple of decades ago I thought the technology would make a burn through the retail marketplace because they tell the story of conversion and opportunity that sales and transactions simply do not.
Retailers that pay attention to traffic patterns and staff accordingly convert higher. If they also ensure that their associates are properly trained and give them technology that enhances their ability to provide a consistent on brand experience to each customer, they will see UPT and ADS lift as well.
For the apparel retailer the traffic versus sales debate takes a further step into the fitting room which is the highest conversion area in their store. Knowing what percent of their total store traffic use the fitting rooms and how long they stay per visit is a great indicator of the efficacy of their service strategy. The apparel retail associate’s number one job should be to connect with the customer on the sales floor and drive as many customers as possible to the fitting room where they are more than 70% likely to buy. Staffing the fitting rooms based on fitting room traffic patterns is essential to capitalize on the opportunities that the committed fitting room customer offers.
Full disclosure: My company manufacturers fitting room tech that counts fitting room customers and provides insight into the opportunities the fitting room offers.
It’s about time the payroll as a percent of sales metric is abandoned! I’ve seen it used as the whipping tool for so long, yet it more often than not doesn’t begin to tell the much needed story. With the advent of cost effective traffic counting/conversion rate measuring solutions retailers now have the ability to properly and more effectively manage labour productivity, not with just an eye to cost containment but instead, with a more global approach to providing a great customer experience.
Most of the discussion points above (in particular, the author’s) are very valid. Keeping this discussion front and centre with retailers, regardless of the new model they choose, will pay huge dividends for customers and the bottom line!
It’s refreshing, if not in fact quaint, to think that any thinking at all goes into staffing decisions; to judge from the comments most frequently offered (both on this board and others) one would think that most companies have made the ultimate simplification: sales > 0, optimal staffing level = 0.
Let me be a bit of a contrarian here. I would never recommend using payroll as a percent of sales as a tool for scheduling labor. I concur completely with the techniques that have been described by others above. But at the end of the day, payroll as a percent of sales cannot be ignored if you want to hit bottom line cash flow requirements.
Perhaps the best way to think of it is this. The techniques being described above are all pretty much bottom-up methods at arriving at optimal staffing levels for any particular block of time. When you roll that up, however, you may find that it exceeds levels that the revenue base and margin structure can profitably sustain. So payroll to sales ratios serve as an essential top-down check on the bottom-up analysis.
Labor as a percent of revenue has been utilized since the dawn of time, however, we shouldn’t be too swift to throw it away. I believe this can be a key metric that is used in combination with other metrics, such as revenue per employee, operational expense per employee, etc. There are myriad ways to measure effectiveness, and keeping payroll dollars as a percent of sales sustains the ability to measure apples to apples versus industry peers.