Staffing Optimization: Re-Evaluating Labor Needs in a Post-COVID World

by Susan Dekker, VP, Integrated Insight

COVID-19 has impacted workforce economics drastically, particularly for service-based businesses. Reports from the Bureau of Labor Statistics are showing that the real hourly wage rate for leisure and hospitality was up 9% in December compared to the pre-pandemic level. This drastic increase in wage pressure puts emphasis on the importance of operational efficiency and staffing optimization measures in the industry.

Hourly Wage Change by Industry
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Analytically assessing staffing levels is crucial to achieving a good customer experience while minimizing labor costs, particularly amidst heightened customer demand for post-COVID activities.

Developing workload models based on customer demand profiles allow businesses to staff and schedule locations efficiently.
These models will be most effective in operational, transaction-based roles, and include the following steps:

Let's take a look.

1. Identify customer demand.

How many customers do you expect? How does this vary by time of day, day of week, or time of year?

As with any operational business problem, always start with the customer and their needs.

Understand the volume of customers demanding the product or service at any particular time of day. For example, a restaurant may see sixty groups dining per hour during the busy lunch period, with less than ten groups mid-afternoon between meal periods.

There’s likely historical data that’s already available which can indicate demand such as historic point of sale transactions, wait times, customer entries into a venue, etc. Analyze how this demand changes based on different seasonal offerings or customer demographics.

While COVID has affected customer demand, comparing data from the past couple months with historical data from 2019 and earlier can provide useful context for the transition back to “normal.”

hospitality staff chef and server
2. Measure capacity required.

How long does it take to process each customer?

Next, calculate how many resources are needed to meet customer demand. This is accomplished by understanding the amount of time it takes to process each customer or party, known as the transaction time. Be sure to analyze both the distribution of transaction times as well as the average. Understanding what creates a long transaction could be an opportunity for process refinement.

Ideally, transaction time would be tracked systematically – for example, recording the time the first item was scanned at a POS and the time payment was completely finished to represent the start and finish of the transaction time. However, in-person observations can be used if this information is not available, and also used to validate the system-based transaction times (e.g., bagging items may not be captured in the system transaction time but does require the employee’s time).

Apply these expected transaction times to the respective customer volumes to translate this to workload. Also be sure to capture any additional non-transaction-based workload, such as restocking or time pre-opening/post-closing.

labor optimization
3. Understand business nuances.

What business rules must be met? What service levels are desired?

There are typically external or business constraints that may affect staffing levels. This may include the minimum or maximum number of hours an employee can work, requirements on certain certifications, or minimum staffing levels. These nuances will vary by line of business, so ensure you seek counsel from operational leaders.

Service levels will also inform how much capacity is needed. What is an acceptable wait time for your customers? What is the maximum wait time customers will accept? Be sure the capacity noted can accommodate natural fluctuations in demand to avoid excessive wait times.

4. Staff and schedule appropriately.

Do the scheduled labor resources match the workload need?

After understanding the customer demand, required capacity, and business nuances, create a staffing plan and schedule.

Ideally, the staffing levels throughout the day should match the forecasted calculated workload. This may require a mix of part-time and full-time shifts to meet the peaks and valleys of the customer demand.

5. Maximize operational efficiency.

What pain points in the process can you reduce or eliminate?

Take the staffing model to the next level by optimizing the process. This could include opportunities like:

- Adjusting/shifting demand: Influencing customer demand can spread customers more evenly across resources or throughout the day.
- Reducing transaction time: Increase the number of customers that can be processed by a single employee by reducing the time it takes.
- Eliminate delays: Identify times where customers or employees are waiting for a process, and brainstorm ways to reduce or eliminate these delays.
- Modify facility layouts: Often, slight changes to a facility layout can make a process more intuitive for a customer, and then can result in a lower transaction time.
- Optimize communication: Add signage or increase communication to reduce frustration and ease decision making, creating a better experience for customers.

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Ultimately, customer demand, expectations, and behavior will continue to evolve over the next year or so. As additional data becomes available and as customer volumes begin to stabilize to previous numbers, continually revisit staffing models so they reflect the most recent operation.

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