Danone Poland has carried out a comprehensive nine-month project to improve demand planning processes in its three main divisions: Danone, Nutricia and Zywiec Zdroj. The project aimed to integrate and optimize planning operations for a wide range of products, including dairy products, specialty nutrition products and water bottles, distributed by 17 warehouses with a total of 9,000 unique products. The ambitious venture aimed to use advanced technologies and collaborative strategies to streamline and improve the efficiency and accuracy of their planning operations.
Implementation of IBP at Danone Poland
Integration of Demand Planning Processes at Danone Poland using SAP IBP



Integration and Data Management
A significant challenge was the integration and use of a wide range of data from various sources, including marketing, sales and weather data. The distributed nature of this data added complexity in managing and analyzing the data for effective demand planning.A significant challenge was the integration and use of a wide range of data from various sources, including marketing, sales and weather data. The scattered nature of this data added complexity in managing and analyzing the data for effective demand planning.
Accuracy of Forecasts
The project aimed to overcome the limitations of existing statistical models, which were insufficient to provide the needed forecasting accuracy for effective inventory management, leading to problems such as overstocking or shortages.
Implementation of Advanced Technologies
Implementing machine learning algorithms to improve forecasting accuracy was a key goal, requiring advanced data analysis and integration.
A Common Approach to Planning
Moving to a consensus planning methodology was key to fostering a collaborative environment, ensuring that planning decisions were well-informed and in line with company goals.
Increased Accuracy of Forecasts
The project achieved up to 97% forecast accuracy for key product groups by integrating sales and weather data with machine learning algorithms, significantly improving planning reliability.
Optimized Inventory Levels
More accurate demand forecasts have led to optimized inventory levels, reducing waste and inefficiencies, contributing to a more sustainable operation.
Improved Inventory Turnover
The initiative has resulted in improved inventory turnover, indicating a better match between supply and demand, based on data-driven planning decisions.
The Success of Cooperation
Adopting a consensus planning approach has enabled a more collaborative and efficient planning process, with departments working together toward common goals.
Danone Poland’s project to revamp its demand planning processes through SAP IBP implementations, leveraging machine learning and moving to a collaborative approach to planning.