With which key lever to start an analysis based on store sell out data?
Gilles Dallest
For a manufacturer, starting to receive sell out data by store from a distributor’s must be a change and should impact the way the entire company operates, from sales to marketing, shopper marketing, supply chain and finance. It means starting a journey to integrate in the day to day of the company the learnings and insights derived from this new and rich source of information to improve its operational excellence.
The key levers that can be activated thanks to the availability and processing of sell out data are the classic ones that define the Revenue Growth Management process in FMCG:
- Efficient distribution and assortment
- Pricing
- Reduction of out of stocks / OSA
- Effective promotions
- Effective introduction of innovation
Obviously, we would like to implement everything at once, but as previously said, it is a “journey” and the best way to put a solid foundation to a strategy and operations based on data is to go step by step reaping the fruits of this new process at each stage.
So, to the question: “with what key levers to start a basic sell out analysis?” I would answer: “with the one that seems to be most relevant for the category and the channel in question”.
Perhaps it is an answer that helps very little, but it is the most logical. For a manufacturer of “liquid” products such as milk, water or beer that have as characteristics large pack sizes and high levels of rotations leading to in-store replenishment problems, reducing out of stocks will clearly be a priority. On the other hand, for those who are dedicated to manufacturing chocolate bars, a category where fierce competition is focused on the field of promotions, it will be necessary to optimize above all promotional mechanisms and visibility.
However, if we have to choose only one lever as the first one that will condition all the others, it will surely be “presence”. As one of my sales masters told me many years ago, “if the product is not in the store, it will not be sold”. It seems such clear evidence that I almost have a hard time writing a blog post on the subject, but sometimes it is not so simple to see the “low hanging fruits” or easier achievements when they are in front of our eyes.
The availability of sell out data by store allows to know what is sold in each store from which information is received with a monthly, weekly, and even daily periodicity. As the sale of an SKU means that it is present in the store, we have at hand a permanently updated and almost real time follow-up of the physical distribution of the assortment. It allows us thus to have a benchmark of the different points of sale and / or clusters that facilitates the analysis and elaboration of plans.
The availability of this information facilitates the work of the sales force that does not have to check the presence of the entire assortment on the visited stores’ shelves, which not only generates cost savings, but ALSO allows to know the presence of the key references in ALL the points of sale including the ones that are not usually visited as smaller supermarkets or convenience stores. An analysis of distribution gaps makes it possible to define the potentials that can be exploited and quickly take the necessary measures.
In addition to assortment, daily or weekly sales are also the source of a very important KPI: the rotation of references. Rotations are the store sales of a SKU over a period that can be the day, week, or month depending on the availability of the information. Combining the presence information of the references with the comparison of the rotations between stores defines the effectiveness of the assortment and it is possible to make changes so that each store has on its shelves the ranges that best respond to the expectations of the shopper.
Once the presence of the effective assortment in the target distribution universe is assured, we can begin to move an additional step forward in the deployment of Revenue Growth Management tools based on sell out data according to the characteristics of the category and implement tools to control out of stocks, effective promotions or pricing.
One safe step at a time and the journey towards implementing data-driven strategies and processes will be done safely and robustly!
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