Sell through comparison across stores and DCs
I was recently part of a set of workshops to identify improvements for a certain client's store experience. The key considerations where generic in nature; enhance the customer store experience, enhance the employee store experience with positive impacts on the company's bottomline.
As part of the discussions we talked about sell through based fulfillment optimization for direct to customer orders. The question that cropped up is whether sell through optimization can be applied uniformly across stores, and whether DCs should be considered at par. Can we just apply the classical sell-through formula or do we bias it?
A simple way of looking at sell-through is to consider it the rate of stock reduction. For the purposes of this discussion lets assume the metric is monthly and the formula is stock sold / stock on hand at the start of the period. Lets also assume that the inventory is seasonal in nature (say fashion) and the stock on hand will not be replenished.
| Month 1 | Month 2 | Month 3 | |
| Sales | 500 | 250 | 125 |
| Start Inventory | 1000 | 500 | 250 |
| Sell-Through | 50% | 50% | 50% |
Here, while the sell through remains the same, the actual absolute sales are reducing. On the other hand, if one takes a cumulative view, and then averages out for the period the real rate of reduction comes through. The formula is Cumulative stock sold / (stock on hand * no of months considered for the cumulative period)
In the case, the sell-through percentages are:
| Month 1 | Month 2 | Month 3 | |
| Sales | 500 | 750 | 875 |
| Start Inventory | 1000 | 1000 | 1000 |
| Sell-Through | 50% | 37.5% | 29.1% |
This now gives a more accurate representation of the actual slow-down in sales!
So, what are the cons of a cumulative weighted sell through for seasonal non-replenished stock?
