Since labor costs are one of your restaurant's biggest expenses, you'll want to make informed, data-based decisions about staffing levels. With the forecasts on the iiko platform, you can align your staff schedule and labor cost (CoL) more precisely with expected demand. Restaurant forecasting helps restaurant owners make informed and accurate decisions about staffing, purchases, profitability, etc. Inventory forecasting uses data to drive decision-making.
It consists of applying information and logic to ensure that you have enough product available to meet customer demand without exaggerating or asking too much and then having to pay the warehouse. Forecasters are creating more complex tools, such as advanced computer-based simulations and futures markets, to create demand forecasts. Inventory forecasting helps companies find a balance between having too much cash tied up in inventory and having enough inventory to meet demand. The basic premise of inventory forecasting is to analyze the historical demand for your products and forecast the quantity you will need to meet customer wishes.
This technology allows you to incorporate a wide range of factors that influence demand into your forecasts, something that more basic demand forecasting software cannot do. You can improve the level of accuracy of your forecasts over time by correctly comparing the estimated sales forecast with actual sales, identifying any discrepancies and taking them into account for your next forecast. Excel also includes a forecast function that calculates the statistical value of a forecast using historical data and assumptions of trend and seasonality. But what does employment forecasting actually entail? Perhaps an easier way to understand labor forecasts is to divide them into a simple equation.
As employment forecasts are increasingly intertwined with employee scheduling and workforce planning, companies around the world are starting to take advantage of the benefits of optimized forecasts. AI forecasting works by providing customer data (sales, foot traffic, orders) and external data (weather, holidays, events, etc.).
