Launch of promotional sales ML forecasting for all our key clients opens the door to further explore possibilities of artificial intelligence in other areas of our business. The important elements of a successful project that requires mastering new technologies and "landing" them within a business process are timely training and involvement of end users in the project, as well as having a plan for change management.
The quality of a promotional sales forecast affects the service level, write-offs, customer relations, storage and shipping costs, and much more: the price of improving accuracy by every percentage point can turn into meaningful efficiency gains. Given the fact that the majority of company’s business is related to perishable products, it takes extra effort to build and improve forecasting quality.
Following the company’s global strategy to harness AI technologies in order to improve business process efficiency, the project team, including Danone employees from Supply Chain Management, Marketing Review, IT, and the Data team, sought a next-generation IT solution based on machine learning algorithms. After analyzing the technology market, the decision was to develop a customized ML prediction model, taking into account all the specifics of the business process and the data available to Danone.
The team of consultants developed and launched an ML model for predicting sales during promotions with key national retailer clients:
The accuracy of ML forecast increased up to 74.3% – up almost 4% in comparison with the former IT solution (70.6%).