Adaptive Sales Forecasting System for Perishable Product Procurement Optimization

The client experiences procurement inaccuracies with current systems achieving approximately 70% sales prediction accuracy, leading to overstocking or stockouts of perishable products. These inaccuracies cause losses due to product expiry and missed sales opportunities, adversely impacting profit margins.

A medium to large retail chain specializing in perishable goods seeking to enhance procurement accuracy to reduce losses and optimize inventory management.

• Increase sales prediction accuracy for different product categories by at least 10%.
• Reduce inventory losses caused by product expiry.
• Minimize missed sales due to stock shortages.
• Develop an adaptive and scalable forecasting solution integrated seamlessly with existing enterprise systems.
• Lower hardware resource requirements through the implementation of simple, efficient mathematical models.

• Integration with existing sales and inventory data sources for continuous data ingestion.
• Implementation of multiple simple adaptive sales prediction models tailored for different product categories.
• A model selection mechanism that evaluates recent forecasting accuracy and chooses the best performing model weekly.
• Application of combinatorial theory to determine the optimal number of models to prevent overfitting.
• Generation of actionable procurement recommendations based on accurate sales forecasts.
• Dashboard and reporting tools for monitoring forecast accuracy and system performance.
• Seamless integration with the company’s ERP, Business Intelligence, and procurement planning systems.

• ERP systems for procurement execution data
• Business Intelligence platforms for analytics and reporting
• Historical sales data repositories
• Procurement management systems

• Prediction accuracy improvement of at least 10% compared to existing systems.
• System scalability to handle increasing data volumes across multiple product categories.
• High system availability and reliability for continuous forecasting.
• Resource efficiency with minimal hardware requirements due to simple models.
• Data security and compliance with relevant data protection standards.

The implementation of this adaptive sales forecasting solution is expected to enhance sales prediction accuracy by over 10%, significantly reduce losses from product expiry, minimize missed sales opportunities, and optimize procurement processes, resulting in improved profit margins and operational efficiency.