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Fresh Encounter was able to cut its labor costs by between 8 percent and 12 percent -- without expensive, complex systems. The solution, in short, was vigilance on the part of the regional chain's s.v.p. and c.i.o., Todd Perry. The IT exec used nothing more than a watchful eye, a stopwatch, and a Microsoft Excel spreadsheet.
With Perry observing and timing them as they went about their day-to-day routines, store associates might at times have felt as if Big Brother were watching them. But the task benchmarks that Perry's surveillance rendered actually helped them excel at their jobs, and in some cases provided them with additional opportunities within the Findlay, Ohio-based organization.
Perry is no stranger to fine-tuning operations. "My background was in consulting -- primarily in operational efficiencies," he explains. "I dealt with everything from the retail space to manufacturing. And the interesting thing that you find as a consultant is that 80 percent of anything that actually occurs in a business isn't really unique to that business. All businesses have those same constraints, difficulties, and operational challenges."
During his years as a consultant, Perry formulated a model for achieving efficiencies, and he continues to refine that model at Fresh Encounter. Perry's model, which he first developed more than two years ago, focuses on four key operating areas: planning, including budgeting and forecasting; assigning work and understanding what that work means, follow-up; and reporting.
"To do these four things together means you'll be a lot more effective as an organization," says Perry. "This is pretty easy to accomplish once you set a standard and have something to train for. The difficult part is setting up those standards for making the observations."
With labor being the company's largest expense other than the cost of goods, Perry decided to put his model to work as soon as he joined Fresh Encounter. "When I got here, we didn't have much in the way of science behind our method of budgeting labor hours," he says.
"A lot of companies use sales per labor hour. That means if you're doing $100,000 in sales, you need x number of labor hours to support that volume." Perry is quick to point out, however, that this equation has some flaws, one of which is that it can't be applied across a chain of disparate stores and still produce effective results.
Lack of standards
Fresh Encounter is just such a chain. As the company has grown through acquisition, many of the stores it has collected were significantly different from each other, and still are. Some stores have just two departments, for example, while other stores might have four or five. Some are 8,000 square feet; others are 40,000 square feet. They tend to lack standard processes, as well. Also, each store differs in sales volume -- even in cases where they're similar in size and format. Add to this an ebb and flow to volume that's driven by promotions and seasonality, and the challenge becomes even more apparent.
To hit this moving target, Perry needed to assign some metrics to these variables. First, he categorized his stores by two measures, store size and sales volume.
"Once we defined it by those different sizes and footprints, we then took a look at the sales volume moving through those stores," he explains. "Is it an 8,000-square-foot unit where we're doing $40,000 a week, or is it doing $80,000 a week? That changes the way you look at the store, from a labor modeling perspective."
Next Perry surveyed each store's unique activities, which can differ drastically even between stores of similar size and volume.
"For example, because of the physical location of one of our larger stores, and the way the back room is configured, we probably have the equivalent of 200 additional steps that are needed to actually reach the back room to stock inventory," he notes. "We face a similar challenge with our service centers. Generally speaking, we all know that every store has a service center. Some of them take utility payments, but utility companies all take different amounts of time to process orders."
In other words, one size definitely does not fit all. "We wanted to make sure that if there was a particular activity happening in a particular department in a specific store, we counted labor for that particular activity," explains Perry. "We decided to visit each store, identify the activities that are taking place, and then observe these activities. And part of the observation is actually taking out a stopwatch and timing associates on how long it takes them to do a particular job, and recording the data into a spreadsheet."
With the goal of setting benchmarks for each task, Perry and his team -- which consisted of an operations manager, a director of operation, and front end specialists -- started at the front end and worked their way through every area of every store. They set both specific benchmarks targeted to individual stores and general benchmarks for the company.
"At the front end, we timed how long it took the cashier to greet a customer, scan the product, tender the customer, and then thank the customer," he says. "By doing this, we were able to determine how many items can be scanned in a certain period of time -- in this case we used items per minute. Once we were able to do that, we could begin looking at our front end operations and start to apply some of those metrics, not just at that location, but also across other locations, and then compare with other locations and find opportunities for efficiency."
The experience was an eye-opener for Perry's investigators: They realized that not every employee performed as he or she was trained, and that standards were sorely needed.
Theory vs. reality
Armed with activity benchmarks, Perry was able to develop another spreadsheet-based tool that would more accurately forecast labor hours. Called the Theoretical vs. Actual tool, it measures for each store how many labor hours are needed based on sales volume, the number of station fills (positions that must be filled regardless of sales volume), and the varieties of activities taking place.
How does Fresh Encounter put this data to use? "As we move through the week, if we're not hitting our sales targets, we're able to adjust our labor down scientifically, so that by the end of the week we meet our labor budget," says Perry. "The same is true on the converse: If the sales are forecasted to be over budget, the last thing you want to do is underserve your customer.
"By making managers accountable -- not to the budget, but to the theoretical vs. actual labor -- you're a lot more effective in the use of time and in actually adjusting during the week," he adds, "because if, for example, we budget $80,000, and we staff for $80,000, but we only do $75,000 in sales, we're going to miss our labor budget."
A business manager at corporate creates a weekly spreadsheet for each of the stores, instructing them what to do based on different scenarios. When hours are to be added or cut, the changes are made by specific department and activity, rather than across the board.
With benchmarks set and schedules running smoothly, Perry still needs something to keep track of the various skill sets among the company's resources. As a growing company, Fresh Encounter tries whenever possible to hire from within, so it's beneficial to know which functions each employee can fill. Plus there's the obvious issue of retail turnover, which speeds up the need for such information.
Perry uses a third spreadsheet tool to address this challenge. Probably the simplest item in Fresh Encounter's HR spreadsheet toolkit, the Skills Flexibility Matrix tracks the various skills of current employees as they progress through different roles in the course of their careers.
On one axis of the spreadsheet is the list of employee names, and along the other are the various job functions found throughout the enterprise, ranging from meat cutting to checkout. "Where they have a skill in a particular area, you indicate that skill by entering one of four options: Trained, Competent, Skilled, and Can Train," says Perry. "We grade each of our employees' skill levels using those criteria."
Perry has found that the matrix actually encourages retention by providing staff with an array of choices as to career development within Fresh Encounter.
Although the "stopwatch and spreadsheet" review is a tedious process, Perry still conducts such reviews annually. The industry changes so rapidly that if he doesn't, the benchmarks will lose their accuracy.
"Every time you get your standards set and move on to another area, you have to go back and revisit those areas," says Perry. "We typically do an audit about once a year to make sure either that we don't have too many activities included in the list which aren't actually being done because of changes in the business, or if the standards have changed because of some other circumstance, such as improved technology."
Perry cites a recent point-of-sale system upgrade as an example. New systems were installed at several locations, and because of these systems, checkout times increased. In turn, he expects to raise the benchmark for scans per minute for the cashiers in those stores. Plus once he finishes installing a wide area network (WAN), credit and debit processing time will significantly decrease, and that, too, will have to be accounted for.
While Fresh Encounter has seen tremendous results from the current system, Perry believes he can push the labor savings even higher.
"We've been able to do a lot of these observations and build models using Microsoft Excel to budget out labor," he says. "But we don't have all the technologies in place to automate these processes. When we get our WAN in place, we'll be able to monitor whether our cashiers are hitting their scan rates or not through the POS system, without having to physically be in the store. It will generate exception reports for our managers, which will speed up how we identify three cashiers as not being quick enough at the front end to service our customers."
It will also aid in his loss prevention efforts. Once the scanning standards are set, scams like sweethearting will immediately be identified and will generate exception reports.
The WAN will also enable Perry to automate much of the hiring procedure. "Right now there's a chain of six people that information has to flow through until you have everything in the system," he says. "The goal once we have that in the system will be to set our processes up so they trigger one after the other. That's about six months to a year down the road."
Probably the greatest benefit gained from the HR process is that it has moved corporate closer to the frontlines of the business. "A key takeaway from all this is, do the managers, the owners -- whoever is responsible for putting this type of practice in place -- understand the standards they've set and why they set them? We discussed this within our group, and what we realized is that all of us had a different feeling as to what the standards should be," recalls Perry. "No one really knew what it should be through a scientific observation process. It sounds basic, but it's probably one of the biggest areas that companies miss."