Yesterday, I talked about how I’m a fan of the “moment of truth” concept, and I highlighted how we have gone through three phases in trying to solve the “out of stock” problem, but that a new phase is emerging. This new phase, which has begun only recently at some leading manufacturers, includes making a better link between merchandising and supply chain operations.
Merchandising involves maximizing sales using product design, packaging, pricing, and displays in a way that stimulates consumers to spend more. Merchandizing services can be performed by a third party that visits retail stores to determine whether a manufacturer’s products are in stock and on the shelves; whether they have the agreed upon facings; and whether promotional displays have been built and stocked correctly.
In yesterday’s posting, I also mentioned that many manufacturers have only recently begun to realize how their ability to achieve good in-stock and on-shelf performance is being hampered by inaccurate store-level inventory data and poor in-store execution of promotions. These problems are starting to get addressed with fancy new math and better analytics. Companies like Retail Solutions (RSi) and TrueDemand use advanced math to calculate what should be selling at the SKU/store level and compares it to what is actually selling. If you are running a promotion and a particular store is not selling anything, while the other stores are selling great quantities of the promoted item, it suggests that either the data coming from the store is wrong or store employees are not pulling the promoted items from the back room to the front of the store.
These solutions also provide analytics to determine why a SKU is not selling – for example, incorrect store-level inventory, failure to move inventory from the backroom to the shelf, or replenishment failure from the retailer’s DC. TrueDemand can then trigger execution tasks for the retail account team or in-store merchandising team. Despite several attempts, I have not been able to talk to a manufacturer that is using this new math, so I can’t verify how effective it is at detecting phantom inventory.
However, I did talk to one of Retail Solutions’ manufacturing clients that is using the analytics from the RSi Demand Signal Repository (DSR). In this particular case, a key retailer has installed a DSR from RSi and the manufacturer pays RSi for POS and inventory data by store/by product/by week, and for daily promotional item data.
This manufacturer also uses over 250 people from third party merchandiser Acosta to visit this retailer’s stores. The merchandisers check for out of stocks, make sure the end caps are up, and perform other merchandising activities. This manufacturer can now query things like: Which stores have not sold any of product X in the last 12 weeks? Which stores have more than 20 pieces of any item? They then feed this information to Acosta which uses it to determine which stores to visit. In short, if you have the merchandising analytics, and run the right queries, the advanced math may be unnecessary.
I also talked to a second RSi manufacturing customer that recently began paying for DSR data from a large retail customer. They anticipate that the data will allow them to better phase in and phase out products. With this particular retailer, they pay 50 percent of the base product cost to the retailer once the phase out date has passed. If the product costs $2, they pay the retailer $1 for the effort involved in pulling the product off the shelf and disposing of it or returning it to the manufacturer. This manufacturer can now start monitoring the inventory positions at the stores six months prior to the phase out, and take steps to reduce costs for both the merchandising and the supply chain organizations.
In the supply chain, we have typically viewed marketing, and their ongoing promotions that disrupt the supply chain, as the enemy. But they don’t have to be. Rumor has it that for a very large retailer, better merchandising analytsics was a key impetus for their “green” initiative. This retailer tracks its shelf space data using a metric that is dollars/square inch/time period. In order to improve this metric, the merchandising teams at some manufacturers are developing concentrated products, like detergents, that have the same potency, but contains much less water, thus enabling more units to fit in the same space. This also results in less packaging and more efficient transportation. In short, it was better merchandising decisions that led to a “greener” and more efficient supply chain.
