Reduce the demand forecasting error for Morato Pane
Morato Pane was established in 1970 in an artisan workshop in Vicenza. Today the company produces various lines of bread products for large-scale distribution, for a total volume of 22,000 tons per year distributed in the Italian and foreign markets, which make it the second largest Italian group in the market for industrial bread substitutes.
Customer needs
In a context in which we relied on historical and personal experience of the single product and for each individual customer over a period of one month, the desire to organize production over shorter periods and with more reliable statistical data began to emerge. Key points for a company that produces a primary product, as widespread and as perishable on the shelf as bread.
Morato Pane’s need was to be able to find a solution capable of processing, analysing, validating and sharing forecast demand with the other company functions, based on the promotions and discounts applied, with the aim of balancing demand and production.
The Demand Planning solution developed to meet the needs of Morato Pane is made up of the following three modules:
ALGORITHMS
Mathematical-statistical algorithms to analyze historical data and optimize demand forecasting.
WEB PORTAL
Web portal dedicated to the commercial network, as a personalized interface for interacting with demand data, in order to incorporate market knowledge into forecasts.
KPI LIBRARY & ANALYSIS
Aggregated data visualization, management and analysis tool dedicated to Demand Planning process managers.
THE CASE STUDY ALWAYS WITH YOU, WHEN YOU WANT
Click here if you want to know more about this Demand Planning project. *The document is in italian version*
Halving the error in forecasting demand: this is the bet achieved in a few months thanks to the Demand Planning system developed by beanTech for Morato Pane. […] Thanks to this project we have improved customer service, arriving at an order fulfillment approaching 100%, and we have rationalized our logistics and production efficiency. Before, we relied on past and personal experience on a single product and for a single customer over a period of one month, now the values of Demand Planning allow us to organize production over shorter periods and with significantly more reliable statistical data.