A leading sports equipment retailer with nearly 200 brick-and-mortar stores and an e-shop generating CZK 8 billion in turnover needed to forecast product demand, which was strongly influenced by various factors, particularly weather fluctuations. This made warehouse operations more complex.
Demand Forecasting and 10% Warehouse Optimization
Client CountryCzech Republic
- Client typeEnterprise
- IndustryRetail & E-commerce
- Application areasOperations & Process Automation, Strategy, Planning & Decision-Making, Supply Chain & Logistics
- AI technologiesAdvanced Analytics / Data Science, Forecasting & Time Series Analysis
- Business impactsData-Driven Decisions & Planning, Employee Enablement & Productivity
- Data typesStructured Tabular Data
- Delivery modelsConsulting
- DeploymentsHybrid
- Key capabilitiesPlanning, Scheduling & Optimization, Predictive Analytics & Forecasting
- Project stagesInitial Production Deployment
- Solution formsAnalysis, Recommendation, or Report, Automated Backend Process, Plugin / Extension for an existing system
Solution Description
Problem description
Solution
Revolt BI developed a predictive model that forecasts turnover of specific products at the SKU level across all branches and the e-shop with 80–90% accuracy. This enables optimization of intralogistics operations, especially warehouse product placement, picking, and preparation for sudden demand spikes. With demand forecasting, intralogistics processes were optimized to such an extent that the time spent on picking goods decreased, warehouse resource planning improved, and the overall labor intensity of warehouse operations dropped by 10%.
Main Users of the Solution
Logistics and BI Director, Head of BI, Inventory Planners
Technologies used
Power BI, Keboola, MS SQL, Microsoft Dynamics, MS SQL
Additional services
- Data governance and data quality
- Change support and user training
Implementation
Project Owner on the Client's Side
C-level leadership
Form of Supplier Involvement
Joint implementation with the client
Impact and Results
Qualitative Benefits
Looking ahead, demand forecasting will help the company better estimate product flows across stores and ensure it always has a relevant assortment available. The ultimate goal is customer satisfaction, ensuring that customers always find what they need. Management believes that the transformation into a data-driven organization will significantly strengthen competitiveness.
Quantitative Results
The overall labor intensity of warehouse operations decreased by 10%.
Client Feedback
“Going forward, demand forecasting will also help us better estimate product flows in stores, ensuring that we always have a relevant assortment and, most importantly, satisfied customers who can always find what they need. I believe that the transformation into a data-driven company significantly strengthens our competitiveness.”
Lessons Learned and Recommendations
Key Success Factors
Transparent communication on both sides and timely reporting of emerging issues.
Recommendation for Others
We recommend organizations start with high-quality data, clearly define goals, and first test the solution on a smaller sample. The right technology partner and involvement of a team that understands and trusts the outputs are crucial. A data-driven approach significantly strengthens competitiveness.
Promotion
Demo / Public Resources
- CompanyRevolt BI
- ContactBarbora Kalačová
- Emailmarketing@revolt.bi
- Websitehttps://www.revolt.bi
- AddressVoctářova 2449, 180 00 Praha