Case Study: Partnerships in SKU Rationalization


A major distributor to the convenient store class of trade and one of its key the manufacturers had similar issues; inventory turn performance and activity costs. The manufacturer had successfully implemented a SKU rationalization project within several of its brands. Their results included improved turns, lowered activity, and increased overall sales.

Both the distributor and the manufacturer wanted to know if the SKU rationalization methodology could be applied to a specific category within the distributor. The trading partners implemented a category SKU rationalization initiative, led by the manufacturer who was the category captain. Costs would be shared.

Obviously, the distributor had much to gain. But so did the manufacturer. The manufacturer believed that their product line was the most efficient within the category because of their category management and SKU rationalization experience and expertise. Therefore, the manufacturer would gain recognition of their position and, most likely, improved allocation of facings for their already high selling SKUs.

Dechert-Hampe was asked to manage the joint initiative and to leverage our SKU Rationalization Toolkit and models.



DHC recommended a SKU evaluation and rationalization technique. One division of the national distributor was selected as a test case. The DHC team worked with the distributor to extract SKU metrics for the category from their legacy database systems. Data on shipments, inventory levels, pricing [wholesale and retail], handing costs, manufacturing trade funds, retail points of distribution, order frequency, order lines, etc., were extracted.

DHC went to the distribution center and corporate headquarters to develop high-level activity cost estimates for allocation within DHC’s SKU Rationalization Toolkit. After scrubbing and validation of key data points, the first pass of information was reviewed with both the distributor and manufacturer. Hurdle rates based on key business performance measures [sales, profits, turns, number of customers] were agreed upon by the trading partners.

The SKU rationalization team then went back to load the hurdles into the Toolkit. Running the Toolkit provided the list of SKUs within the current active portfolio that were not meeting the underlying performance requirements of the business. These SKU were reviewed and categorized as part of the analytic process. The model also predicted, in a static case, the impact on inventory and activity costs of reductions in the SKU base.

The model was also used to project the impact on top line sales resulting from the SKU rationalization. Often, marketing and sales associates are concerned that the rationalization of SKUs will reduce the top line. However, experience proves this is typically not the case.


The SKU rationalization data indicated that of the over 800 SKUs within the category, the bottom 36% only generated 3% of sales and 2% of profit for the distributor. With activity costs loaded, the model projected a reduction of over $123,000 annually in activity costs.

Execution of the SKU rationalization recommendations reduced the inventory of the lead division by $92,000 or 8%. Corporate implementation of process was projected to reduce corporate inventory carrying costs by over a million dollars. The distributor also had the option to reallocate existing space and avoid expansion versus taking cost reductions.

The manufacturer, as anticipated, was the category leader in productivity by SKU for the distributor. In fact, of the three leaders in the category, this manufacturer generated 2X the profits per SKU of the next closest competitor.

Incremental analysis of the data also indicated a huge opportunity for the distributor to consider vendor consolidation as the bottom 50% of suppliers were generating only ½% of sales.

© COPYRIGHT 2017 Dechert-Hampe Co.


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