Reduced Cost of Goods Sold through Modeling

 

Situation:   A leading retailer was preparing for its annual contract negotiations with manufacturers of a key product line, with the goal of purchasing sufficient quantities to meet anticipated demand at the lowest total cost.  The cost structure of the product line was distinguished by the high cost of transportation and storage (20-50% of the final total product cost).  Because of the company’s large East Coast footprint of 20 distribution centers (DCs), any individual production plant could serve – at most – 8-12 DCs before transportation costs became prohibitive.  In addition, the company wished to offer several varieties of product in each region, while most individual plants currently produced only a single variety.

 

There were nearly 30 geographically dispersed candidate suppliers and the company’s goal was to negotiate the volumes and prices that allowed it to offer the target product mix in each of its markets at the lowest total cost.  The company also wanted the ability to model “what if” scenarios, considering those pricing points that may make a particular supplier more attractive, and therefore a candidate to take on higher volumes than originally planned.  This last point was key – the company wanted to easily test various scenarios so they could use insight gained as negotiating leverage. 

 

Approach:  Ops Partners conducted a supplier assessment that included list pricing, product type(s) sold, and estimated available volumes for each vendor, along with recently quoted trucking and rail rates into those DCs that could be served by a given supplier and transportation mode.  In addition, handling and monthly storage costs were collected for each DC. 

 

Using the collected cost data, we built a linear optimization model, with the goal of identifying the optimum combination of suppliers and volumes that yielded the lowest total product cost.  Constraints in the model included vendor price (which could be modified for running various scenarios) and volumes required in each of the client’s geographic markets.

 

Results:  The optimization tool was used throughout purchasing negotiations to prioritize cost-advantaged suppliers and to discuss pricing levels that would result in additional committed volumes.  The team’s efforts resulted in a 20% reduction in Cost of Goods Sold compared to the prior year.

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