Research brief · Retail, restaurants & hospitality
The manager readiness gap in retail and hospitality.
Most of your store, restaurant, and property leaders come up from inside, and AI is moving into their scheduling, forecasting, ordering, and pricing. This brief shows how you can see who is ready to run a location, and help managers become better decision makers.
Inside the brief
- Why the individual manager accounts for 25–35% of the variation in store productivity
- New research on what happens to accuracy and confidence when AI advice is wrong
- Why completion records say little about readiness, and what skills intelligence adds
- Field experiments where managers who adjusted a retail algorithm’s forecast raised profit 4.92%
- 25–35%of the variation in store productivity comes down to the individual managerMetcalfe, Sollaci & Syverson, NBER, 2023
- 4.92%higher profit when people adjusted a retail algorithm’s forecast, compared with no human inputKesavan, Kushwaha & Steele, Management Science, 2026
- Nearly 68%of retail executives expect agentic AI in operations within 12 to 24 monthsDeloitte, 2026 Retail Industry Global Outlook
A look inside the brief.
In two field experiments at auto parts retailers, managers who corrected what the algorithm knew raised profit, and those who overruled what it decided lowered it. Read a few sample pages to see what the research found, and how practice builds the judgment your managers need to know where to step in.
Click a page to read it.
The goal isn’t more overrides or fewer. It’s better ones.
50+ industry awards.
These include three Brandon Hall Group Gold awards in 2025 (Skills Intelligence, Leadership Development, and Simulation Technology) and a place on Training Industry’s Top 20 Experiential Learning Technologies list in 2025 and 2026.
Get the brief.
The research, the field experiments, and a practical look at how you can see, with evidence, which managers are ready to run a store, a restaurant, or a property.
Send me the brief