Optimizing Your Retail Labor Model

By Tom Hill and Donncha Carroll

Retailers were already under formidable pressure to improve store profitability before the American consumer market largely shut down in mid-March. Some big-box retailers quickly adapted by turning stores into distribution centers focused on maintaining sales through online orders with curb-side pickup and other services. Most retailers not large enough to employ this strategy are doing their best to stay afloat by reducing labor costs, delaying lease or mortgage payments to ride out one of the worst disruptions to consumer buying in living memory.

Interestingly the shutdown will likely further expedite eCommerce growth and has the potential to create a step change in consumer buying patterns but safe to say retail isn’t really going away – rather it’s changing to serve different consumer needs that are still evolving in an omni-channel world. Certain goods may even see a significant dip in demand as social distancing pushes buyers to focus on the essentials, but fundamentally we should expect to see a return to old patterns. Even Amazon sees the value of brick-and-mortar as evidenced by the Whole Foods acquisition, Amazon Books, and Amazon Go and we’ll likely see more of the same in the years to come.

Whenever we do return to the ‘new normal’ – whatever that is, retailers will need to be ever more vigilant and hyper-focused on managed store P/L which more than anything means managing labor costs even as commercial real estate costs trend lower. Some of this will likely come in the form of automation but just as importantly it will require building a better understanding of the buyer and how best to serve their needs across the journey.

3 Ways to Maximize ROI on Labor Investment

The most successful and most profitable retailers continuously monitor and manage store operations and retail execution to better align staffing with demand. From our experience and the key to maximizing return on labor investment is to:

1. Classify and manage stores based on operationally relevant attributes. Each segment is organized based on these characteristics allowing the operations team to determine the optimal full-time/part-time staffing model for each one
2. Within each segment define and deploy roles and people based on store characteristics to ensure optimal coverage and improve efficiency to deliver higher in-store margins. Consider blending roles and tasks to enable greater flexibility in future staffing plans
3. Design compensation and incentive programs that support and encourage the behaviors that drive consumer purchases regardless of whether those buying decisions are made in-store or online

Aligning Staffing Models

Once you have a working model in place, layer in other more detailed data elements that are helpful in determining location-specific tactics to inform management actions including individual sales, CRM data, customer transactions, etc. These more operationally-focused measures should be used to answer key questions such as, “What is the relationship between conversion and employee coverage?” and “Should we concentrate outbound calls between 11 and 1 pm on Tuesdays and Thursdays?”

It’s important to consider selling and stock resource capacity. We find that oftentimes, retailers have the total hours budget reasonably close but the mix and assignment of work is imbalanced particularly when the reality of store traffic patterns come into the picture. Another interesting analysis is to examine how supervisory support on the floor compares against certain KPIs like ADS or conversion often highlighting how those resources can be more effectively used during different times.

Benefits of  Data-Driven Decision Making

Besides the obvious need to balance store labor with foot traffic, you can use the integrated data asset and new analytical capability to suggest and support key decisions:

1. Change the mix of responsibilities by role to increase selling time (e.g., removing non-selling tasks from the Sales Associate’s role)
2. Realign pricing by understanding shifts in demand and average time to sell certain products (i.e. custom item vs. off-the-rack) in order to reorient what to sell now vs. later
3. Define which circumstances you need full-time labor versus part-time and whether to reward differently
4. Build a better understanding of the true connectedness of your omni-experience by evaluating how your digital spend relates to store visitation and buying patterns

Don’t forget to pilot changes to identify and address unintended consequences, and to determine the real-world impact of what was intended. This is essential not only to avoiding costly missteps but also to gathering valuable feedback that will inform the broader rollout. More importantly you can better align staff with opportunity, so you can grow the top line as well especially as things return to the new normal.

Learn more here about how Axiom Consulting Partners helps retailers improve store effectiveness.