85% accuracy in demand forecasting achieved by a leading computer hardware manufacturer through predictive modeling techniques
Business Challenge: Issues with inventory management process.
The client wanted to optimize its inventory management through improvement in demand forecasting.
Situation: Constant issues with inventory management resulting in reduced customer satisfaction levels and profitability.
The client was facing constant issues around stock outs, large inventory levels, inaccurate lead times, and inaccurate demand forecasting. These issues were affecting the customer satisfaction levels and profitability.
Solution/Approach: Regression model to predict future demand based on historic data.
We deployed a regression model to conduct analysis on historic information on products, sales and inventory levels. In addition, we also conducted analysis on customer data to predict purchase patterns, trends and buying behavior. On the basis of this analysis, we were able to conduct demand forecasting, uncover irregularities, and determine optimal inventory levels.
Impact: Improved accuracy of demand forecasting and improved inventory management.
Our solutions for the client improved the accuracy of their demand forecasting up to 85%. They were also able to streamline the order management process and achieve better inventory management. This resulted in improved customer satisfaction and profitability.