The Business Challenge/Situation
The client, a large textile manufacturer in UK, wanted to build a reliable model that complements or takes over their in house traditional approach to forecasting for their product lines. Currently, chunks of data are stored in multiple spreadsheets and this makes it very difficult for decision makers to aggregate and take decisions on time. Additionally, in-house models were built into these spreadsheets by managers who worked primarily on gut instinct. The Customer currently incurs huge spend caused due to stock outs, large inventory levels and resource costs.
Market Equations Role
Market Equations studied the data in detail to uncover hidden patterns within the data. Once this was done the data was extracted and loaded into SPSS, to analyse trends and segments within the data. Analytics techniques were applied to analyze past sales history and EPOS data from the customers client, to uncover patterns caused by seasonal variations, lead times, minimum quantities, re-order quantities, extraordinary usage (special orders) etc.
Client Impact:
The Analyses resulted in providing an automated system, managed by our team virtually, built with predictive models that resulted in a close to 60% accurate forecasting over a period of 6 months. Market Equations continues to engage the customer and is continuously reporting insights daily with a team of three full time Stat programmers. Market Equations intends to optimize the forecasting to bring in an accuracy of 75% in the next six months.
ME maintain a fantastic relationship with the company and representatives are always eager to provide their references whenever required.
Explore how the Market Equations Consultative Approach to decision making works wonders.
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