The Customer
The Customer is a leading Industrial Oil Manufacturer in India. They have one plant from where they supply Finished Goods to multiple distribution centres and to several direct Customers. Business is a complex mix of Make to Stock and Make to Order Products.
The Problem
The customer was scouting for an end to end Supply Chain Planning platform from improving Forecast Accuracy to improving Supply and Dispatch reliability to improving visibility
Challenges
There were 3000+ FG SKU’s comprising of Speciality Oils and Lubricants, which serves OEM’s and After Market for India as well as Export requirements. They were grappling with poor demand planning leading to increased inventories and reduced service levels across distributors spread across India.
Existing Model
Proposed Model
Solutions
Demand Planner
- rhythm’s state-of-the-art AI / ML based forecasting engine was used to generate the forecast.
- Multiple Statistical Forecasting Techniques were used to address Seasonality, Trend and Cyclic Behaviour. System selected the best technique for each SKU at each Location and Cleansed historical data to remove errors, outliers etc.
- Forecasting model was able to adapt to the changed scenarios of Before and After COVID market situations generate accurate forecast
Inventory Planner
♦ Norms are generated for RM,PM and FG level using historical Sales data.
♦ Service Target and Inventory optimized at all depots, Regional hubs, Central Mother hub in form of FG and at Factories in form RM and PM
♦ PM Inventory reduced by 25%
♦ RM Inventory reduced by 20%
♦ FG Inventory reduced by 15%
Reasult
12% Improvement in the forecast accuracy
Forecasting process adherence improved significantly along with better visibility of control over forecast changes
97% Service Level
Different service levels for different SKU-location combinations improved the existing service level by over 10%
20% Reduction in current Inventory Level
Recommended Norms will help to reduce the inventory by over 20% across FG, RM and PM
