Overview

Our client is one of the largest and most innovative long-term care pharmacy companies carrying a broad range of pharmaceuticals, nutraceuticals, and
FMCG brands.

Client wanted to optimize merchandizing strategy of its ‘cardiac care’ and‘diabetes care’ therapeutic categories and reduce sales leakages that were resulting from inventory stock-outs across key brands and SKU variants.

Additionally, client wanted to identify top stores by specific product categories and determine the top SKUs & their quantity to stocks to carry.

Solution

TransOrg developed a clustering and adjacency analysis to improve merchandizing strategy and inventory policy.

TransOrg began by clustering top 45 stores based on variables such as SKU variety, quantity sold, value, SKU classes (based on value and/or quantity sold by SKU). We then analyzed loyalty and non-loyalty card customers’ spend on Cardiac and Diabetes categories and by store clusters. After treating for outliers and anomalies in each store cluster TransOrg identified top Cardiac & Diabetes SKUs that were contributing to either 80% of the total spend or 80% of the total quantity sold.

Transorg then analyzed adjacencies to understand which products (SKUs) are complimentary to each other i.e., bought together.

Output

  • Client rolled out a new improved inventory policy for Cardiac and Diabetes products across its stores
  • Spend on top cardiac & diabetes SKUs and on their adjacent SKUs at 45 stores of all stores was up 41% of total retail customer spend
  • Top 10 adjacency categories in each cluster together contribute approx. 75% of total adjacency spend
Want to learn more about TransOrg’s value proposition, solution methodology and implementation approach?

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