Restaurants and catering at 5 locations swapped guesswork for a daily demand forecast
One kilogram of food in five went in the bin, and the best sellers ran out on Friday evenings. Now the system drafts tomorrow's order for all five locations, the manager approves it with one tap, and by 07:45 the suppliers already have their orders.
- Client
- Restaurant group in Czechia4 restaurants and catering, 6 suppliers
- Service
- demand forecast and POS data from every location
- Status
- In production at the clienttomorrow's order every morning for all five locations
- In numbers
- Food waste: 21% → 7.5%ordering: 40 min → 2 min every morning at each location
The “before” figures, the result and the payback are per client data.
The client's situation
The group runs four restaurants and a catering business in Czechia and buys food from six suppliers. Each location ordered on its own: every morning a chef or a manager looked at yesterday's sales and wrote the order by eye. Nobody saw the stock of the group as a whole, so the same products were bought twice for neighboring locations, and weekend catering orders piled on top of the restaurant orders.
Nobody counted the waste. When they finally did, one kilogram in five was going in the bin: 21% of all purchases, about €170,000 a year. At the same time, the best sellers kept running out on Friday evenings, the busiest hours of the week.
of purchases went to waste: one kilogram in five
per client dataof food a year thrown away
per client dataevery morning spent on orders at each location
per client dataThe main ruleThe model does the math, a human makes the call: orders go to suppliers only after the manager's “ok”.
What the system does
- Pulls sales from the POS at all five locations every day, with no exports or spreadsheets, so the forecast always runs on fresh numbers.
- Keeps one inventory of products and expiry dates for the whole group: you see what is stored where, and a product sitting at one location is not bought again for the one next door.
- Forecasts demand for every item at every location from 12 months of history, taking in the season, holidays, weather, bookings and prices, so every order follows expected demand.
- Drafts tomorrow's order for all locations on its own, with catering on a separate line, so a weekend banquet does not eat into restaurant stock.
- Marks lines “check” where demand is unusual: a large catering job, a banquet or a holiday. The manager reviews a few lines instead of the whole list.
- Shows what changed since yesterday: weather, a holiday, a new booking. It is clear at a glance why an order is bigger or smaller.
- Sends orders only after the manager's “ok”: one tap in Telegram approves all five, and any line can still be changed.
- Sends the orders to six suppliers at 07:45, each one gets only its own items, with no morning calls or message threads.
- Lets the kitchen log waste in 2 minutes per shift, so you see what goes to waste and at which location, and money no longer disappears unnoticed.
- Retrains every week on fresh sales and waste data, so the forecast keeps up with the season and with shifts in demand.
The architecture in plain terms
POS sales land in the group's shared inventory every day. The model forecasts demand for each item and location, the system drafts tomorrow's orders, the manager approves them in Telegram, and the orders go out to the suppliers.
- Data
- POS sales by locationstock and expiry dateskitchen waste logbookings and cateringholidays and weatherprices
- Roles
- manager: approval in Telegramkitchen: waste logsuppliers: orders at 07:45
How it works
- location tillsPOSSales from all five locations every day
- systemInventoryShared stock and expiry dates across the group
- modelForecastDemand per item and location: season, holidays, weather, bookings, prices
- systemOrderFor tomorrow, all locations, catering separately
- manager · TelegramManager's “ok”One tap for all five orders
- systemSuppliersOrders at 07:45, each gets its own
- kitchenWaste2 minutes per shift
- modelRetrainingEvery week on fresh sales and waste
Honestly, no forecast will predict a banquet nobody knew about. That is why bookings and catering go straight into the calculation, and the system marks unusual items “check” for the manager.
Result and payback
of purchases now goes to waste: 2.8 times less
per client dataa month no longer ends up in the bin: ≈€120k a year
per client dataevery morning at each location: the kitchen logs waste, the system drafts the order itself
per client dataProject payback: ≈2 months per client dataWaste fell from 21% to 7.5% of purchases. Of the ≈€170k a year that used to go in the bin, ≈€10k a month now stays in the business, and the system paid for itself in full within 2 months.
What is running
- running
Daily POS sales from all locations and one inventory of products and expiry dates across the group
- running
Forecast per item and location, and tomorrow's order for all five locations, with catering separate
- running
Manager approval in Telegram and orders to the six suppliers at 07:45
- running
Kitchen waste logging in 2 minutes and weekly retraining of the forecast
A similar task in your business?Solomiia, Pavlo's AI assistant, will ask about the details and prepare your conversation with him.
emilus. Procurement
Purchase forecasts and ready supplier orders. You get a list of what to order and how much, and you confirm it before it goes out. Price after the brief.