The tl;dr
Your stores’ biggest asset is the team
They’re also one of the most expensive and complex investments to manage well. In some cases, they may even cost more than your rent!
The optimal labor model depends on what you’re prioritizing, each of which have their own pros and cons
Use a combination of operational views and simple math to determine whether your sales targets are reasonable given the operational limitations (eg budgeted labor hours and traffic counts)
Your stores’ biggest asset is the team
Whether you’re staffed with full time or part time associates, and whether you call them associates or some other title, they are the lifeblood of the channel. They’re what separate the channel from e-commerce, and the literal personality behind your brand in the physical world.
They’re also one of the most expensive and complex resources to manage well. In some cases, they may even cost more than your rent!
And while that’s not a bad thing, it’s also not necessarily a good thing.
So naturally, the question is: how do you staff a store to the optimal level?
The optimal labor model depends on what you’re prioritizing
I’ve seen quite a few ways to think about staffing, which are often driven by one or more of the following:
Budget: Unfortunately, some organizations take an overly simplified approach of setting a budget based on few or no assumptions — just a simple “we can’t afford more than X dollars or people. While this is not the optimal approach, it can be a harsh reality of an ill prepared business case.
Sales targets: While similar to the above, the driver here is based on a sales goal vs an operating expense budget. Particularly in heavily clienteled categories, some managers may back into the number of heads they need in order to drive a certain sales target. On a similar note, the Finance team may give a directive that payroll shouldn’t exceed X% of sales, in which case you’re back to the above (an operating expense budget).
Operating hours: This is my preferred driver. All other methods don’t really incorporate the realities of operating hours requirements. Unfortunately some malls and lifestyle centers require a set number of operating hours, which must be followed or you risk defaulting on your lease. A typical street location may operate just 58 hours per week (at your discretion based on neighboring tenants’ hours), but a mall in the same area may require 78 (or 34% more hours). This is a notable step up that requires more headcount, or fewer people working at any given hour.
Using operating hours gives you the ability to manage to a “coverage ratio”:
Coverage Ratio = Total Labor Hours Deployed / Total Store Operating Hours
This ratio can be your driver for determining how many hours you can budget:
Mall operating hours = 76 per week; targeting a 2.5x coverage ratio = 76 x 2.5 = 190 labor hours to deploy
190 labor hours / 40 hours per week = 4.75 Full Time Employee equivalents
The GM counts as 40 of those hours by default, or 1 FTE, so you’re left with the equivalent of 3.75 FTEs, which you can choose to hire as Full Time or Part Time (or some combination of both).
Anticipated traffic: The coverage model helps you think about averages, but that approach only gives you the number of labor hours you can deploy, and not necessarily how to deploy them across days or weeks. If the coverage model gave you 190 labor hours, for example, you still need to create a schedule to determine the days — and hours within those days — for each employee. While it’s obvious, it’s always great to see data validate what we already know: store traffic tends to be highest 9am - 5pm, and can vary between weekday vs weekend heavy. You can get a good sense of this by using mobility data technology prior to opening (see below), or using traffic counters post-opening to see how your store actually looks.
And, of course, the occasional holiday or promotional schedule should also influence how you allocate these hours.
As you think about coverage-based labor models, I also like to drill in a layer deeper with some other coverage metrics:An unconventional, but useful, way to think about staffing is to take this a step farther and look at the ratio of Traffic (Visitors) to Employees per Hour. A store that gets 100 visitors per week is very different than one that gets 500. So I also like to look at # of Visitors / Employee per Hour. This gives a good sense of how many visitors each of your associates is essentially expected to have to greet or serve. If your forecasted traffic levels, operating hours, labor hours, and headcount suggest that each employee will be greeting 100 visitors per hour, you can be sure that you’re not staffing enough.
Another similar lens is to look at the ratio of Orders to Employees per Hour. In some cases, it may be okay to have a high ratio of visitors to employees if (a) visitors come in groups (eg families) such that you’re greeting multiple people at the same time. But if they still need to process a crazy amount of orders, that might become problematic.
SQFT: Size matters. A 1,500 square feet store that’s open 76 hours per week will require a staffing level very different from a store that’s operating the same hours, but 10,000 square feet. One of the things I like to look at is Area Coverage. For example:
Area Coverage = Avg Daily FTEs / SQFT
So if you have 3 people working the store on average at any given time, and the store is 1,500 square feet, then: 3 Employees / 1,500 square feet = 500 square feet per employee.
I like to use this as a common sense check, and to compare across locations. Ideally, the square footage (or zones) that your employees are “managing” on a per person basis is not unreasonably large. A low ratio may result in less organized stores, higher shrink, or lost sales as customers are unsupported while there.
None are good.
A case study: bringing it all together
Here’s an example tying it all together to pressure test whether a certain sales target and operating model are feasible. Let’s set the stage:
Goals
Sales target = $20,000 per week
AOV: $100 (implying 200 orders per week)
Target conversion: 20%
Staffing constraints:
1 GM + payroll budget for 2 FTEs; 120 labor hours per week
76 operating hours / week required per lease
Store assumptions:
2,000 sqft
20% BOH = 1,600 front of house (aka “selling” square feet)
Mall location (hence the longer operating hours)
Here’s what that all means:
Weekly traffic estimate: 1,000 visitors
= $20,000 sales target / $100 AOV / 20% Conversion = 1,000
Depending on your location and category, this may be optimistic or pessimisticCoverage ratio: 1.6x
= 120 labor hours / 76 operating hours = 1.6x
This feels really tight. It means at most you probably have 2 people on staff, which might be tough if you have customers AND someone needs to go to the bathroom or on break.Customer coverage (traffic / employee / hour): 4.4
= 1,000 visitors / 3 FTEs / 76 operating hours = 4.4 visitors per employee per hour
This is roughly 1 visitor every 15 minutes. Doable on average, but may put you in a pinch if visitors tend to be concentrated during certain hours, or if each visitor requires a lot of support.Order support (orders / employee / hour): 0.9
= 200 orders / 3 FTEs / 76 operating hours = 0.9 orders per employee per hour
This doesn’t sound crazy initially — the employee needs to process ~1 order per hour. Unless you’re selling a product or service where the checkout process takes an extended period of time, this isn’t too crazy. However, keep in mind that on top of processing 1 order on average every hour, the associate also needs to greet and interact with 4 customers on average every hour too — and also take care of other duties like inventory management, cleaning, and even simply taking a break.SQFT Coverage / Employee: 533 sqft
= 1,600 sqft / 3 FTEs = 533 per employee
This is equivalent to ~23 ft x 23 feet, which is a manageable zone to keep an eye on and manage throughout the day.
None of these seem too crazy. In other words, the sales targets seem achievable with the operating constraints in place.
There’s a million different ways to look at this, but the point is that these metrics give you a few lenses to validate the feasibility of a goal with certain constraints, and/or to determine the resources you need in order to achieve those goals.
Staffing profitably — a key tactic for negotiating mall leases
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