To start with, it would be a selectively inclusive network. Building on established practices and industry standards for business-to-business partnership, it would embrace a large enough group of retailers and manufacturers for all the key players to gain benefits of scope and scale. It would differentiate the offers and assortments of the conventional retail mix, providing varied product categories to diverse retail outlets, so that consumers immediately perceive those shopping experiences as distinct from each other. And it would support the large logistics infrastructure needed for efficient, rapid delivery to all these outlets in their varied locations.
A shelf-centered collaboration network would operate “shelf-forward.” It would anticipate and generate demand with innovative products, assortments, promotions, and displays that recognize consumers’ diverse needs. For example, store displays and shelf mixes would routinely change at certain times of the week, to accommodate the ebb and flow of commuters, stay-at-home parents, young adults, and weekend shoppers through the stores. Stores a mile apart would routinely stock different product mixes tailored to their varied demographics. Displays and products would appear just at the moment that consumers sought them out. It would be rare to find a product out of stock; perennial staples would continually become easier to shelve and less costly to purchase, in part because the range of offerings at any single store would be less complex. New information technology — some of it installed in the shopping cart or accessed through cell phones and personal digital assistants — would enable product promotions tailored not just to neighborhood demographics but to the specific shopper, whose past buying habits would have been meticulously tracked and analyzed. Even advertising would be timed more closely to distribution flow, with POS data used to gain robust insights into the consumer demand patterns for different items, days, and stores.
The network would also operate “shelf-back,” responding immediately to information about consumer purchase patterns and demand with real-time changes in shelf-stocking decisions, displays, supply chain execution, and even product design. Although this general concept may sound familiar to those in the industry — for example, as “demand-driven supply networks” (DDSN) — current practices are often limited to the rapid replenishment of standard merchandise, without tailoring of the product mix or timing to consumer demand patterns. Nor do current practices incorporate the kind of robust analytics that can predict changes in consumer demand. SCC would help manufacturers, along with store and category managers, make far better use of POS data and analytics.
If you wanted to make the most of the network, you would design a way for your marketing, sales, supply chain, and retail infrastructures to meet at the point of sale using their common pool of timely day-by-day sales data, combined with other relevant factors, to generate a statistical signal of predictive demand. You would focus not just on the recent past (as portrayed in category, regional, and weekly statistics) but on the prospective sales of the near future (again, tracked by item, by store, and by day). And unlike many retail marketing programs, this would all be implemented with full transparency for the total value chain costs of each new promotion and sales effort, including the otherwise invisible costs that accrue when one product inadvertently cannibalizes another.
When consumer products companies and retailers design programs and networks to simultaneously operate shelf-forward and shelf-back, they can achieve the integrated capabilities that comprise the full potential for shelf-centered collaboration. (See Exhibit 1.) Rather than pitting them against one another as adversaries, SCC positions them as allies. Working together, they can focus on efficiency for some standard items and differentiate others through promotion and innovation, making the distinction on the basis of actual sales performance, rather than brand share. And they can repeatedly expand their integrated capabilities through continuous improvement based on common data.