Shortly after the turn of the millennium in the aftermath of Y2K, Consumer products companies across all channels began concentrating on the expansion of knowledge and intelligence about the consumer, and, more importantly, the ability to predict outcomes. The global big data initiative was catapulted off the flight deck and the mission of shopper reconnaissance was executed in earnest. The digital transformation we are neck-high in now is just beginning; but it has already brought us significant breakthroughs in data acquisition and management as well as near and real-time consumer intelligence. Big Data technology (both hardware and software) is evolving at supersonic rates, and the corporate strategy seems to be coalescing into three main areas: (1) acquisition and maintenance, (2) integration, and (3) use case development.
It has always been the primary mission of a consumer products company to drive demand. For over a century, these companies have leveraged revenues along with independent consumer research to attempt to measure effectiveness of their messages and positioning. Trade promotion, almost two centuries old, was used as an incentive for the retail channels to buy enough product to keep the shelves stocked with the brand and reach the local shopper with the message of price and where to buy. This was, at best, a marginal assessment, leading old John Wannamaker to utter the famous phrase, “I know half of my advertising is effective…I just don’t know which half that is.”
Well…now we can know – through the relatively young business process and technology of demand signal management. First, a bit of history.
In the early 1990’s, Walmart’s Retail Link program enabled their suppliers to receive and use point of sale (POS) data to enable direct, near real-time tracking of their products’ sales at Walmart stores everywhere. Shortly thereafter, other retailers did the same including Target and Kroger. Not soon afterward, independent research companies like Vision Chain/Orchestro (now e2Open), R3, Retail Velocity and Retail Solutions, Inc (RSi) began acquiring direct POS data from hundreds of retailers and reselling the data to the consumer products manufacturers. These companies would provide technology to clean and harmonize the data that enables their CPG clients to better generate actionable intelligence.
Because the consumer products manufacturers have a wealth of other data including revenues, promotion performance, supply chain and logistics, and consumption marketing research, it became sensible to combine and align this data into a single repository from which they can better sense, understand, respond and predict consumer demand. These are aptly named Demand Signal Repositories or “DSR’s.” These days, almost every manufacturer either has one or is about to pull the trigger on buying or developing one.
I have had some deep involvement with the development of DSR solutions. Beginning with the 2008 “New Ways of Doing Business” initiative between Oracle, Wegman’s and Smucker’s, I was fortunate to be a member of the design and development team that created a DSR to accommodate the rich findings from that project. This led to the creation of one of the early DSR platforms that still provides strong POS-driven insights for Oracle customers today. I was equally fortunate to be part of the SAP version of the DSR which is called “DSiM” where we could integrate POS along with other critical internal and external data to generate actionable insights that supported both supply chain and trade promotion execution. Today, both solutions are examples of global data management tools that can and do impact how effective trade promotion performance can be.
POS data, though, often gets an unfair shake among the industry data mongers because they view it as primarily a planning data component. If you look across the spectrum of consumer data we have now, POS is more critical than ever as the one figure that says “a product was sold.” This is what it is all about, isn’t it?
John Beckett is one of the pioneers in POS data management and a widely recognized domain expert in DSR. In fact, his company, Retail Velocity, is providing many CPG companies with clean, harmonized POS data. One of their largest is SAP. The DSiM solution at SAP integrates Retail Velocity’s POS data with an array of other data sources that provide better insights and predictability. I spoke with John recently about his view on POS and how his company sees the future of downstream data and demand signal management. “Incorporating retailers’ daily POS and inventory data into TPM and TPO processes dramatically increases a CPG’s visibility and control over their sales to consumers. It’s like going from watching a game on tape-delay to being on the field in the game,” he explains. Most people I speak with about downstream data use cases take a rather simplified view of POS as a game changer. Mr. Becket disagrees. “Traditional TPM relies on sell-in and syndicated data weeks after the fact to evaluate promotions while a DSR with more accurate, complete and timely data offers the opportunity to improve their outcomes.”
If POS, as the anchor content of downstream data is exclusively used as a source of planning content for ROI, then we will miss some of its most important use cases, including real-time monitoring of promotion performance. More importantly, it drives actionable insights that enable on-site tweaking to the promotion tactics, saving a potential failed promotion. “Daily POS data provides more accurate and timely information before and during the promotion. Monitoring store-level inventory allows you to put your hands on the levers to optimize execution and improve future promotion planning,” Beckett points out. The Demand Signal Repository is the ‘engine’ that makes that happen.
Remember my blog on Clientelling and Trade Promotion a few weeks ago? (http://supplychaininsights.com/clientelling-and-trade-promotion/) Go back and check that out; then listen to your inner innovator begin thinking of ideas!
For several years now, Retail Velocity has been providing POS data to fuel SAP’s DSiM Solution and has produced some very strong results. Along with a powerful trade promotion optimization solution, SAP can convert the finished POS and other data (such as inventory, revenue, previous trade promotion transaction history, and consumer marketing data). These two technology partners are exemplary of the type of value that can be provided to consumer products suppliers to take important steps forward in their quest to convert consumer engagement into higher revenues and margins for both manufacturer and retailer in the consumer chain.
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