There are many ways to assess staffing at store level.
Some are sophisticated, time intensive, and expensive to implement. Others quickly show whether staffing is broadly aligned with demand or structurally misaligned.
This is one of the latter.
You do not need new complex models, you can start with a simple comparison that links labour directly to demand.
The test
Step 1: Select 2 comparable stores
Choose
two reasonably comparable stores in the same country with similar
revenue order volumes, format, opening hours, and same data period. They do not need to be identical, only comparable enough for the signal to be meaningful.
Step 2: Calculate staffing cost per order
For each store, divide total staffing cost by total orders.
Step 3: Compare the resultsIf staffing cost per order is broadly similar, say +/- 10%, labour practices are generally aligned with demand. If the difference is more than this, the signal warrants investigation.
Step 4: Ask the right questionsWhen differences appear, the follow-up questions are usually revealing. Is one store carrying more management layers. Is the role mix different. Are teams less trained or less flexible. Is process friction forcing manual work. Is demand volatility being absorbed differently.
Step 5: Apply common-sense filtersBefore acting, apply a small number of filters. Is one store still ramping up. Is one constrained by minimum staffing requirements. Are volumes too low to benefit from scale effects. If none of these apply, the difference is real and actionable.
Main benefits of this analysis:
- Takes 5 minutes to pilot
- Directly links staffing cost to customer demand
- Shows under- and over-staffing issues quickly- Makes role mix and management structure inefficiencies visible
- Works across ramp-up, maturity, and decline phases
- Scales quickly across formats & markets with some adjustments and other metrics
- Can be extended across large networks to set demand-based staffing budgets
Why this works ?
This approach bypasses complexity with qualified assumptions, avoids debates about task definitions, and quickly highlights inefficiency.
Sophisticated models have their place. But before investing time, money, and organisational energy, it is often worth starting with a measure that links labour directly to demand.
If the signal is healthy, extra complexity is rarely required. If it is not, the issue is usually structural and worth addressing.
Get in touch
If this analysis raised questions or revealed something worth exploring, we would be pleased to discuss it with you.
Whether you want to
sense-check your results or consider taking the analysis further, feel
free to get in touch for a structured, practical conversation.
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