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Insights for more profit in hospitality.
Practical insights on AI, menu engineering, and profit optimization – straight from the industry.
HOSPITALITY · Jul 9, 2026
Why Your Food Cost Checks Out and the Margin Is Still Missing
Your recipe costing says 29%, your books say 33.5%. Here's how to find the gap between target and actual food cost – and what it really means.
HOSPITALITY · Jul 14, 2026Your Menu Is a Year Old. Your Purchase Prices Aren't.
You cost your menu once a year, but you buy every week. Here's how margin hides in that gap – and which price you should actually be using.
HOSPITALITY · Jul 19, 2026Menu Engineering Without Clean Data Is Reading Tea Leaves
Menu engineering is only as good as the contribution margins it sorts by. Three ways the matrix tips over – and how to set it up right.
HOSPITALITY · Jul 24, 2026Twenty Items Drive Your Food Cost
About 20 to 30 items make up 70% of your food cost. How to find them in an hour – and why the rest can wait.
HOSPITALITY · Jul 30, 2026The Expiry Date on Your Recipe Costing
Every recipe costing ages – and the error propagates all the way into menu engineering. How often you actually need to recalculate.
HOSPITALITY · Aug 4, 2026What's Wrong on Supplier Invoices, and Why Nobody Notices
Agreed prices that never arrive. Pack-size changes with no price adjustment. Four discrepancies hiding in almost every supplier invoice – unnoticed.
HOSPITALITY · Aug 9, 2026Labor Cost as a Percentage of Revenue Is the Wrong Metric
Your labor cost ratio says more about your revenue than about your team. Three metrics that actually measure productivity.
HOSPITALITY · Aug 14, 2026Food Waste Starts in Purchasing, Not the Kitchen
Food waste gets discussed mostly around portion sizes. The real lever sits three days earlier, at the order.
PRODUCT · Aug 19, 2026The Three Numbers You Need Every Day
A dashboard with 30 tiles steers nobody. Three numbers you can actually remember – and why the rest belongs in the monthly report.
AI · Aug 24, 2026Reactive Is Over
It almost never fails on analysis. It fails on timing. Why data should reach out to people, instead of the other way around.