Staffing | 6 min read
Overstaffed: Does Scheduling More Staff Always Mean Better Results?
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By The Nowsta Team,
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The Challenge
Managers have to strike a difficult balance when building the work schedule. You need to make sure you have enough staff on duty to meet customer demand, but not so many that you overshoot your labor budget or eat into margins. But generally speaking, most would assume that the more employees you have scheduled for a shift, the better the team will perform, since the workload can be spread out across a larger group.
But the research suggests that isn’t always true.
A 2014 University of Pennsylvania study on worker productivity in restaurants found that at certain customer volumes, staff actually perform better with a smaller team working. Their findings suggest many managers may be overstaffing their businesses. Below, we’re going to break down the study’s findings and explore a few possible takeaways for your scheduling strategy.
What’s the optimal ratio of workload to staff?
The key question when it comes to how many staff you need on duty is how much work each team member can take on at once while still maintaining high performance. This is especially important for customer-facing roles like waitstaff and retail sales, where staff need to maintain pleasant interactions, answer questions, and try to upsell while also completing the basic functions of their jobs.
That’s why the study we’re analyzing here is so helpful. Researchers monitored the performance of servers at five sit-down restaurant chain locations over eleven months, collecting data from over 190,000 transactions. The goal of the study was to uncover the optimal staffing level by seeing how workload affected waiters’ performance and service speed. Specifically, the researchers used data from the restaurants’ POS devices to calculate the following:
- Workload: Tables assigned to server at time of meal
- Performance: Bill amount, based on the premise that staff can increase check sizes by upselling customers
- Speed: Length of customer meal. The study assumes that staff can shorten meal length by spending less time talking to customers, timing the drop off of order tickets, and carrying more dishes per trip to the kitchen.
Most would assume that as workload goes up, speed and performance would both fall because staff’s attention is divided across more tables. Under this assumption, the only downside to scheduling more staff is the increase in labor costs — staff should always perform better and faster if their individual workload is lower with more teammates on duty.
However, that wasn’t the case. Marginal increases in workload affected staff differently depending on the size of the overall workload. Below the workload threshold of 2.59 tables per server, an additional table decreased a server’s speed as expected, but also triggered an increase in sales performance. Above that threshold though, both speed and performance decreased with each additional table. Because of this, researchers concluded that the restaurant chain was overstaffed, as servers’ average workload was 2.16 tables per server. If the chain scheduled fewer waitstaff and kept everyone’s workload at 2.59 tables per server, it could have increased overall sales by 3% while reducing labor costs by 17%.
It’s unclear why exactly a workload increase might sometimes help staff perform better. Goal-setting theory suggests that employees feel extra motivation when they face a challenge. Perhaps the challenge of a new table to wait on motivates servers to perform better when the overall workload is still low, but decreases their ability to perform when they hit the 2.59 table tipping point. Another theory comes from Parkinson’s Law: the age-old adage that work expands to fill time. Perhaps when servers’ overall workload is low, they spend more time on trivial tasks that don’t help increase bill size, but then shift their attention to upselling when they get more tables. But regardless of the reason, the data follows a clear pattern of increased speed and performance until staff hit the workload threshold of 2.59 tables per server.
What does this mean for you?
If you run a restaurant, you can try testing the study’s findings for yourself. Think about how demand changes throughout the week, and consider changing the number of staff you schedule to get closer to that magic number of 2.59 tables per server. You may be able to get a boost in sales while saving on labor. Or, better yet, if your POS device makes it possible, try looking at data from your own transactions to see if you can identify similar trends in your business or workload thresholds at which your team’s performance begins to suffer with each additional task.
You can also try and apply these lessons if you work in catering or events. In fact, you’re at an advantage because you know in advance how many guests and tables your team is responsible for heading into each event. It wouldn’t be hard to try scheduling more or fewer staff depending on the anticipated workload and seeing how it affects team performance.
But more generally, this study challenges the widely-accepted notion that scheduling more staff — and thereby lowering each team member’s individual workload — leads to better performance. If you’re a manager in charge of scheduling, you might want to test it for yourself. See if there’s a sweet spot at which you can schedule fewer staff, save on labor, and keep everyone’s workload just high enough to spark their best possible performance. The only way to know is to give it a try and see what the data reveals.