We recently found another wonderful article that the McKinsey team, specializing in FMCG, put together. “Agility@Scale: Solving the growth challenge in consumer packaged goods” defines how to overcome the uphill battle many FMCG categories and their manufacturers currently face. The answer is a combination of what the McKinsey team calls greater agility and new types of scale advantage aligned with the changing consumer, channel, and competitor landscapes. These team members define six different dimensions of Agility@Scalethat align quite closely with what we believe at Middlegame and corresponds with how we regularly try to help our clients make better marketing decisions.
During the last decade, a significant amount of attention has been paid to “Attribute-Based Forecasting” in the demand planning community. The idea originated because new product launches with limited history still require forecasts in various demand planning systems. As manufacturers and retailers offer more and more choices to shoppers, estimating the potential—as well as future demand for all these different variations—has become a major challenge to the supply chain. Similar to the Middlegame Competitive Interaction Analysis (CIA)® platform, data scientists have turned to product attributes (brand, size, package type, flavour, etc.) at the SKU-level as a foundation for preparing and delivering better forecasts.
In 1990, Robert Blattberg published Sales Promotion Concepts, Methods, and Strategies with Scott Neslin. A couple years later, I was eager to get a copy. The book is still on my shelf. The imprint on the first page says: “NU BOOK STORE AUG92 $59.65.” In the days before Amazon, sometimes it took a while to find a book. In this case, the search was worth it. Bob had only recently moved from the University of Chicago to Kellogg. So, during my next trip to Chicago, I took the train again to Evanston with the specific goal of buying the notes to his class that were available at Kinkos. Academic research for marketers had only recently become interested in sales promotion and most journals were behind the times. Trade spending quickly became the biggest item in the marketing budget and the book fully organized the existing research that was available.
We’ve recently connected with Sandy Jap, a Sarah Beth Brown Endowed Professor in Marketing at Emory University, to expand our thinking about transferred demand. I don’t need to ramble any further about the importance of focusing on the concept of incrementality versus transferred demand. However, Sandy is on the forefront of an equally important yet slightly different concept. In the late 1970s, John D.C. Little and the team at Management Decision Systems, Inc. (MDS) —who eventually provided me several of my mentors at IRi after IRI acquired MDS—defined the “data cube”as marketing measures residing in the dimensions of products, geography, and time periods. The overwhelming majority of work that Middlegame has produced focuses on the product dimension related to incrementality versus transferred demand. What about the other two?
In late 2017, Nielsen explained that online FMCG channels were less than ten percent of the total global retail market. However, as explained in “A Look at the Evolving Ecommerce Landscape,” the ecommerce sector grew so fast that it represented almost all of the gains across both online and offline combined. Continue reading →
We have referred to the audit parallelogram a few times in this blog as Middlegame has devoted a lot of focus on assortment, pricing and merchandising for emerging markets. I thought it would eventually be a good idea to explain the audit parallelogram concept in a little more detail, but I got beat to the punch: Last month, a client directly asked for an explanation. Below is a summary of that write-up: Continue reading →
Coverage means different things to different people. Generally, clients refer to it as the comparison between shipments volume from internal auditing systems and the volume reported by a retail tracking service like Nielsen provides. Subsequently, “coverage analysis”is an appraisal of the quality of the overall service including the sampling approach, collection methodology and data processing. In theory, the shipments data and the retail measurement data should be nearly identical. Sometimes a lagged effect helps to converge the two data streams. Continue reading →
While developing several hypotheses for a series of scenario-planning exercises, I noted that the Middlegame “wide-angle view”across the entire category offers an enormous opportunity to expand beyond the simulation capability of traditional marketing response models. I was surprised that I hadn’t shared this before with this client. We immediately started talking about whole new ways to leverage the CIA® platform and quickly address issues that the client thought could only be done by building, fielding and analysing a survey. Continue reading →