Challenges: Manual Forecasting and Inventory Issues
House of Spices, Asia’s largest spice company struggled with manual sales forecasting and inventory inefficiencies. With thousands of SKUs, including perishable goods, they faced challenges in predicting demand, especially during seasonal spikes. Their sales forecasts were based on past sales trends, leading to frequent inaccuracies and last-minute procurement changes.
Solution: AI-Driven Forecasting and Real-Time Visibility with Athena
With ConverSight’s Athena AI, House of Spices revolutionized its forecasting and inventory management processes by leveraging AI-driven insights.
Forecasting Models
Athena generates three forecast models—sales team projections, AI-driven forecasts, and actual sales—providing more accurate predictions that align closely with real demand.
Optimized Inventory Management
By incorporating seasonality, price changes, and purchasing behaviours, Athena AI helped House of Spices maintain the right inventory levels while reducing waste from expired products.
Real-Time Adjustments
The procurement team now receives reliable AI-based forecasts, minimizing last-minute changes and ensuring a smoother supply chain process.
Enhanced Sales Performance
Athena ’s predictive analytics empower the sales team to set more achievable targets, leading to improved revenue generation.
Solution: AI-Driven Forecasting and Real-Time Visibility with Athena
| Before ConverSight | After ConverSight |
|---|---|
| Manual forecasting led to inaccuracies and last-minute procurement shifts | AI-generated forecast models aligned planning with actual sales and real demand |
| Difficulty in managing thousands of SKUs, especially during seasonal peaks | Athena accounted for seasonality and behavior trends, reducing stockouts and waste |
| Inventory inefficiencies caused excess stock and product expiration | Optimized inventory levels helped reduce waste and improve shelf availability |
| Sales teams lacked accurate projections to set realistic goals | Predictive analytics empowered better sales planning and improved performance |
Athena has significantly improved our demand forecasting accuracy. We previously struggled with predicting seasonal spikes, but Athena’s advanced modeling and adaptive learning have helped us refine our approach. By continuously analyzing SKU-level data, we can now make better decisions and optimize our supply chain planning. The ability to freeze forecasts for key periods and validate predictions with actual sales data has given us greater confidence in our planning. The improvements we’ve seen in forecast accuracy are game-changing for our operations.
Ruby Gangwar, Senior Planning Manager, House of Spices.
Industry
Food & Beverage Manufacturing and Distribution
Company Type
Wholesale/Manufacturer of Indian Food Products
ERP
Microsoft Dynamics
