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Episode # 161: Restaurant forecasting can feel impossible when demand changes fast and yesterday’s playbook stops working. Sales might be steady while traffic quietly drops, or a shift to delivery lifts revenue but creates new labor, inventory, and margin problems. We want forecasts that explain what is happening, not just a number that misses with confidence.

We walk through a driver-based restaurant forecast built on what leaders can manage: traffic, average check, and mix. That means getting painfully clear about definitions like transactions vs guest counts, then showing how pricing, discounts, add-ons, day part, and channel mix move the check. We also dig into why forecasts fail in the first place: treating stockouts and closures like normal demand, assuming last year is automatically comparable, and letting different teams run on different assumptions. If you only measure total sales accuracy, you can miss the real problem and never learn from forecast error.

From there, we talk practical AI for restaurant demand forecasting. A useful machine learning approach can forecast transactions by restaurant, day part, and channel, then estimate check and menu mix to project item quantities for purchasing and prep. Inputs like POS history, menu changes, promotions, loyalty data, weather, and local calendars matter, but testing matters more. We share how to backtest models under realistic conditions and why you should compare AI results to both your current manual forecast and a simple seasonal baseline.

If you want a restaurant forecasting process that improves staffing decisions, reduces waste, and makes promotions less of a gamble, this is for you. 

Episode outline:

1. Why a dynamic forecast matters more than ever,
2. Build the forecast from its critical drivers,
3. Develop a more robust forecasting process and continue to improve it. 

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Stephen is an experienced Finance Professional and Leader who offers fractional CFO services and development opportunities. Please visit his LinkedIn profile or Finance Leader Academy for more information.

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