This project was done in a retail environment.
One way to maximize profitability is to lower the cost of goods sold. The client’s distributor offered volume discounts for a variety of products. The volume discounts ranged from 9% to 29% depending on the quantity purchased. The distributor sold over 120 products to the client. Our goal was to determine what volume to purchase per individual product.
Pros of a Large Volume Purchase:
- Reduces the Per Unit Cost
- Enables Lower Product Price
- Less PO’s per Month
- Strengthens Relationship with the Distributor
Cons of a Large Volume Purchase:
- Impacts Cash Flow
- Lowers the Inventory Turn Over Ratio
- Increases inventory shrinkage
- Requires large warehouse space
The challenge was to choose the volume to purchase to reach the optimum produt price while maintaining a healthy inventory.
Techniques used: Price Optimization, Cash Flow Analysis, Large Dataset Analysis
Steps Used in the Process:
- Extract historical Sales, Pricing, and Cost data for each of the 120 products through SQL queries.
- Document final negotiated volume discounts per product. Calculate # Units per Volume Level
- Construct Price vs Profitability Curves from Price-Demand and Contribution Margin tables
- Calculate the Estimated Time for Depletion (ETD) for each product for each purchase volume level.
- Build a decision algorithm for each product to maximize profitability without hurting ITR metrics
This is the typical price-demand curve constructed for each of the 120 products. The x-axis is the price of the product and the y-axis is the average weekly sales volume.
SQL queries served to create the datasets for each product.
This is the cost per unit resulting from four volume discounts offered by the distributor for one of the products.
The four levels were:
- Less than a pallet, 0% discount
- 1 pallet, 9% discount
- 5 pallets, 20% discount
- 12 pallets, 29% discount
The algorithm ran various scenarios of prices and cost combinations to maximize profitability while minimizing the ETD. For each product, the algorithm recommended the best volume to purchase. The following curve is representative of the analysis done:
The algorithm recommended the following for this product:
- Purchase 5 pallets
- The expected ETD is 15 weeks
- Set market price at 2 for $3.00
The market price of the product offered by the customer was 31% less than the current price of its competition.
Weekly profitability jumped from $72 to $158. Total profitability over the 15-week period increased by 120%.
In this project, volume purchases were recommended for less than 14% of the products. The main factor was the elasticity of demand for the product.
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