How this retailer increased profit by $8.9m from rostering more hours
There has been a lot of speculation on why we are losing retailers so fast. An interesting research piece from the US presented an alternative hypothesis that generalises the issue down to rostering for profit rather than rostering to control costs.
For context – If you were given the choice of increasing revenue by 5% or reducing costs by 5% in order to create the most profitable outcome, what would choose?
A “back of the hand” calculation would show that reducing costs increases profit more than the equivalent uptick in revenue.
Accordingly, most retailers choose option two.
This makes sense if you assume the two scenarios are independent of each other, but what if the cost was your employees?
This is where the problems arise. For industries like retail, where staff have a direct impact on sales, it’s not as simple of a question as cutting costs to increase profit.
In a study led by Professor Marshall Fisher from Wharton, he and his research team constructed a conceptual model from historical data to identify stores within a US-based retail chain that had the highest potential to benefit from increased labour spend.
Importantly, the strategy was actually implemented at 168 retail sites over a 26-week period to validate the model, with the retailer electing to implement the strategy further.
The result: A near $8.9 million increase in profit of the stores included.
The labour cost challenge
The challenge in allocating labour budgets lies in the tradeoff between the known immediate payroll cost and the less certain increase in sales that could be achieved with more staff on hand.
The researchers point out that retail managers have a tendency to overweigh the decision to reduce the known payroll cost than the less certain increase in sales which could be achieved by allocating additional labour spend.
The labour budget death spiral
The study highlights the limitation of the most common retail strategy — setting labour budgets as a portion of sales. Fisher points out that this approach creates a circular problem by failing to take into account how store labour spend can positively impact sales, with the worst case leading to a spiraling effect of reduced sales forecasts reducing labour spend which reduces sales further and so on.
Quantifying the impact of labour spend on revenue
Creating labour budgets that are designed to maximise profit requires retailers to know on a store-by-store basis the correlation between labour-spend and sales. One way to do this is by looking at times when staffing levels deviate from the original schedule.
If ten staff were scheduled on a particular day, but on that day only eight turned up, did sales also decrease by the same portion? If not, by how much?
If the answer to the above is that sales didn’t decrease at all, the store is likely overstaffed. If there is a measurable impact, the inverse scenario is likely true and the store may be losing sales by being understaffed.
This is the same approach used in the study, which found the relationship between random staffing deviations and impacts on sales was statistically significant. Results showed an increase in labour spend pointed to increased sales at varying degrees, depending on known store attributes.
Implementing the strategy for profit
The study identified stores in a US retail chain which had the highest market potential, making them good candidates for an increased labour spend. The market potential factored in attributes like average basket value and proximity to competitors, which would create scenarios that allow workers to have the highest impact on converting sales.
In the study, 168 stores were selected this way, then allocated a 10% increased labour budget over a 26-week period, of which 75% of the increase was actually consumed in practice by the stores.
The outcome was a 4.5% increase in revenue at the impacted stores and resulting in a near $8.9 million profit increase.
Learning from the strategy
The study shows empirically why the common practice of setting labour budgets as a fixed proportion of forecasted revenue is often self-defeating when applied in a retail setting.
An opportunity exists to all retailers to leverage this same profit-centric model for defining labour budgets. The data required is available to all retailers however, it may just be a matter of leveraging that information with the right systems.
An integrated forecasting strategy that integrates foot traffic, sales, and employee scheduling data is a practical opportunity afforded to retailers of any size to optimise their labour resource allocations.
The interesting part is, Fisher’s research is readily available to all retailers who are looking to drift away from the traditional method of fixing labor budget rosters. The next step is to get this method of labour resource allocation battle tested in the Australian markets.