![]() ![]() Retail and consumer product companies have begun to realize that the traditional approach has its limitations and needs to be reimagined in a rapidly evolving and highly competitive market. Traditionally, the retail and consumer product industries relied heavily on their past statistics for forecasting and used heuristic methods and human judgment to perform a planogram product assortment, resulting in lost sales due to out-of-stock product(s), generating greater waste due to decayed product(s), and entailing high service levels in stocking up merchandise. A blog post by Chida Sadayappan, lead specialist, cloud, data, and machine learning, Deloitte Consulting LLP and Dinesh Kumar, principal machine learning and deep learning engineer, Deloitte Consulting LLPĪ planogram is a model that specifies exactly how much product should be displayed on store shelves to maximize sales and enhance the customer experience.
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