Restaurants
Finding the levers to hit daily targets.
The problem
Restaurants run on thin margins in a volatile market. Seasonality, shifting consumer behaviour, menu changes, supply-chain swings and new competition all move demand at once — and the calls that decide whether a site hits its numbers get made on instinct.
Managers are usually told which factors matter, but not how much each one weighs on a given day. Without a read on the relative weight of each demand driver, cutting waste and protecting profitability becomes guesswork — whether you run a single independent eatery or a chain.
What we built
We modelled the localised demand trends inside the restaurant's own booking data and turned them into actionable predictions rather than a static forecast. Each prediction comes with the levers behind it, so the manager on duty can see what to change to meet the day's key metrics and reach break-even earlier.
The output is a set of specific operational levers a manager can pull — where to flex staffing, which covers to chase, how to shape the day — each tied to the demand drivers that justify it.
What it changes
Instead of reacting to the day as it unfolds, managers get an early, explainable read on where it is heading and what to do about it — the same engine working for an independent site or across a chain.