Kesko Oyj
Summary
Kesko Oyj
Company Sizes- 200-300
- Retail
- Supply chain / procurement
Project
Project types- Operational excellence
- 100 001 – 1M€
- 2024
- Finland
- English
Implementation
Implementation levels- Production
- Predictive analytics
- Solita
- Azure
- Python
No
Kesko needed to improve forecasting accuracy in its grocery division to reduce waste, optimize shelf availability, and better align procurement with consumer demand across its large retail network.
Solution
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
Outcome
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
ROI
Achieved full ROI within 12 months due to cost savings in waste and improved sales through better availability.
Yhteyshenkilö
Erkki Esimerkki
Titteli
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Kesko Oyj
Summary
Kesko Oyj
Company Sizes- 200-300
- Retail
- Supply chain / procurement
Project
Project types- Operational excellence
- 100 001 – 1M€
- 2024
- Finland
- English
Implementation
Implementation levels- Production
- Predictive analytics
- Solita
- Azure
- Python
No
Kesko needed to improve forecasting accuracy in its grocery division to reduce waste, optimize shelf availability, and better align procurement with consumer demand across its large retail network.
Solution
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
Outcome
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
ROI
Achieved full ROI within 12 months due to cost savings in waste and improved sales through better availability.
Yhteyshenkilö
Oletko AI Finlandin jäsen ja haluat tietää lisää projektista itse asiakasyritykseltä?
Blah blah enter your email and an optional message.
Otsikko
Summary
Kesko Oyj
Company Sizes- 200-300
- Retail
- Supply chain / procurement
Project
Project types- Operational excellence
- 100 001 – 1M€
- 2024
- Finland
- English
Implementation
Implementation levels- Production
- Predictive analytics
- Solita
- Azure
- Python
No
Kesko needed to improve forecasting accuracy in its grocery division to reduce waste, optimize shelf availability, and better align procurement with consumer demand across its large retail network.
Solution
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
Outcome
Implemented a predictive analytics model using machine learning to analyze historical sales data, weather patterns, seasonal trends, promotions, and local events. The system continuously updates and improves forecasts in near real-time, enabling store-specific demand planning.
ROI
Achieved full ROI within 12 months due to cost savings in waste and improved sales through better availability.
Yhteyshenkilö
Oletko AI Finlandin jäsen ja haluat tietää lisää projektista itse asiakasyritykseltä?
Blah blah enter your email and an optional message.