CASE STUDY

85% Accuracy in Demand Forecasting Achieved by a Leading Computer Hardware Manufacturer through Predictive Modeling Techniques

Sep 22, 2016

Business Challenge

Issues with the current inventory management process.

The client wanted to optimize its inventory management through improvement in demand forecasting.

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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 customer satisfaction levels and profitability.

Solution/Approach

Regression model to predict future demand based on historic data.

We deployed a regression model to conduct an analysis of historic information on products, sales, and inventory levels. In addition, we also conducted an analysis of 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.

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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.

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