Do You Have It Right?

In the retail environment shelf space allocation is limited. It is therefore critical that you utilize this premium space to showcase your best performing items. This will ensure that you maximize revenues and increase market share. The alternative is unacceptable.

Identification of the \”Top 10 Items\” per category and acting on this information is standard performance improvement practice in the industry.

What if your \”Top 10 Items\” list is wrong?

Two critical questions need to be addressed:

1. Does my list of \”Top 10 Items\” accurately represent the actual ten fastest moving items?
2. Do the top ten best selling items necessarily represent the top ten items with the best sales potential?

The brief analysis that follows provides insight into these vital issues and outlines methodology into maximizing performance.

Sell-out Information

The most common reason for not having the right \”Top 10 Items\” is lack of precise sell-out information. In many cases there is a perceived inability to collect complete, timely and accurate sell-out information. This leads wholesalers to define their \”Top 10 Items\” by assuming that the sell-out information collected from their captive retail outlets or from an EDI system, which typically provides information for only a portion of their market, represents the sell-out information across their network. In many cases this assumption is wrong. In some extreme cases companies assume that their sell-in information represents their sell-out. The negative impact of such assumptions on their business is obvious.

Today there are tools available that can collect accurate sell-out information in real-time. The impact of this information within the organization is measurable and significant.

Best \”Sales Potential\”

In the best case scenario, assume that you have complete, accurate and timely sell-out information. Unfortunately, the \”Top 10 Items\” in terms of sell-out are not necessarily the \”Top 10 Items\” in terms of sales potential.

The important measure is which items presently have the highest sales rates and not which items had the highest sell-out.

There are many instances that impede the actual sell-out of certain products and obscure their real sales potential. These are related to the relative level of consumer exposure to the products being offered. For example:

A new product that just been introduced and was not yet available throughout the complete sales network.
A product that sold out from the retail outlets. This is the well-known phenomenon of the \”Bullwhip Effect in the Supply Chain\”.

In order to reveal the sales potential of a given product we need to know the level of consumer exposure. The only reliable method of evaluating consumer exposure is by factoring the number of POS (Points of Sale) that stocked the product during the period in question.

To obtain the \”Top 10 Items\” in terms of potential one must divide the number of units sold by the number of POS that stocked the product at any given time frame. The higher the result, the higher is the sales rate and hence sales potential of the product.

Two examples for illustration:

The retailers of a given product range sold 10 units of Product X and 20 units of Product Y in a certain day.

In a typical \”Top 10 Item\” list, product X will appear to be an inferior seller to product Y.

But on that day the Product X was stocked at 20 POS and Product Y was stocked by 100 POS.

Accordingly, a new metric of \”sales potential\” is proposed:

The ranking for Product X would be X=10/20=0.5

The ranking for Product Y would be Y=20/100=0.2

This new \”Sales Potential\” metric highlights that Product X has a higher potential to generate sales. Although more Product Y was sold, given the equivalent exposure, Product X will outsell Product Y (by a factor of 250%). Distribution of Product X throughout the sales network, even at the expense of Product Y will increase revenues.

The \”Sales Potential\” algorithm may be fine-tuned by drilling down and comparing sales figures within the retail outlets that stocked both Product X and Y. The metric can be computed over the duration of any given time period (e.g. week, month, quarter).

In order to generate this type of information it is important to monitor sell-out and stocking levels in real-time. Most wholesalers collect sell-out and inventory data on a weekly or even monthly basis and proceed to replenish stock accordingly. The consequential penalty for delayed and inaccurate information cannot be stressed enough.

Today there are simple and cost effective tools that collect accurate inventory and sell-out information in real-time which compute and present the above mentioned data in a user-friendly manner.

Conclusion:

In order to identify the \”Top 10 Items\” precisely, wholesalers must constantly collect complete, accurate and timely sell-out and inventory information from their retail network, preferably in real-time.

Having an errant list of the \”Top 10 Items\” can strongly impact a wholesaler\’s ability to exploit the sales potential of their products, thereby reducing their competitiveness and gross margins.

Ranking products according to a new \”Sales Potential\” metric will optimize sell-in management and contribute to better purchasing decisions from the manufacturers.

Author Bio: Ofer Yourvexel is the CEO of WRNTY.com, a company that provides wholesale distribution software for wholesalers with complete end-to-end solutions to manage their businesses based on sell-out information.

Category: Business
Keywords: wrnty wholesale distribution software