Dependence on traditional market segmentation strategies that did not yield expected returns and profits.
A global electrical components manufacturer wanted to improve its customer segmentation in order to achieve better revenue and profits.
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Manufacturing plan incoherent of a vast amount of customer data.
The client had access to huge volumes and a variety of customer data but was unable to utilize them effectively in order to develop manufacturing plans as per changing customer segments and their requirements. This was resulting in lower than expected returns from the manufacturing investment.
Big data analytics and predictive modeling to map demand for manufacturing.
We integrated data from various silos, and mapped them against the client’s existing manufacturing strategies through big data analytics, to identify gaps and create a better manufacturing plan based on customer segmentation. We also developed a predictive model for the assessment of profitability levels of customers and segment them accordingly.
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Improved ROI by USD 23 million.
The client was able to understand and anticipate the demand from various customer segments and created a more demand centric manufacturing policy. This reduced stock-outs and wastage, and improved the ROI by USD 23 million.