Company Background
An over 30 year old footwear manufacturing organization with over 250 store locations across the country. The supply operations are long with material moving from plant to central warehouse to regional warehouses before reaching the store location. Also there is a lead time dependency on the imported raw materials.

 

Need for forecasting
Forecasting is critical to the operations of the firm and the inventory management throughout the supply chain. Large number of SKUs and frequent introduction of new products makes forecasting demand well a necessary but challenging task.

 


Issues in the current process
Despite huge operations, company was relying on excel sheets for forecasting demand. Rules of thumb were used instead of statistical algorithms.

The inventory requirement calculations were manual and comprised of very huge and multiple excel files. The demand planner also had to intervene manually to correct the estimated demand at various levels.The entire process was person dependent and heavily time consuming activity on a monthly basis. This lead to a planning activity which was highly clerical with no analysis or ability to increase throughput and reduce the inventory covers

The change we made
Planamind was tested for forecasting capability. The mandate was to move to a reliable and accurate statistical forecasting system, that removes the person based dependency, and also automate the inventory calculations therby reducing time and effort required in the current process.

Conclusion
Planamind successfully deployed statistical forecasting methods that witnessed immediate improvement in accuracy of ~5%. The system requires minimum intervention and only the effect of demand due to external events.

The new products are forecasted more reliably with the help of analogy method
The inventory calcualtions are automated and the logic was improved during the implementation process.
The bonus with the Planamind was the effective online collaboration between the teams and specially between the demand planning and the sales. In addition the company now has performance dashboards on the Business Intelligence platform that helps drill down to the drivers of forecast accruacy for instance in seconds and also visualize demand patterns by various dimensions. The company has also customized the reports to view inventory imbalances across the locations and drive out the excess stocks.