Big Data

CPG Industry Levels Playing Field with Power of One

Bill Schmarzo By Bill Schmarzo CTO, Dell EMC Services (aka “Dean of Big Data”) December 4, 2017

Special thanks to Brandon Kaier (@bkaier) for his research and thoughts on the Digital Twins concept.

Unilever, one of the Consumer Package Goods (CPG) industry’s titans with over 400 brands and annual sales greater than $60B, recently bought Dollar Shave Club for $1B. Now normally I would not think twice about such an acquisition, peanuts in the world of mergers and acquisitions.

However, this one feels different.

Two billion people use Unilever products every day according to Unilever’s 2015 annual report. Dollar Shave Club only has around two million members; the vast majority of who are likely already Unilever customers. So I don’t think Unilever bought Dollar Shave Club for their customer base.

The Harvard Business Review speculates in 5 Ways to Help Employees Keep Up with Digital Transformation that “Unilever has acquired Dollar Shave Club, a young startup, for $1 billion in a move to introduce a new model of subscription sales.”

It seems that Unilever could have easily created their own subscription model without having to pay $1B for customers with whom they already have a relationship. So I don’t believe that Unilever just bought a subscription model. Instead, I think Unilever bought a capability; a capability to capture and mine individual customer product purchase behaviors – the frequency, recency, intensity, magnitude and monetary value of purchase behaviors at the level of the individual consumer – and to eventually apply this analytic capability across more of their brands.

Think about the purchase behavior details Dollar Shave Club has on each of its individual subscribers. Unilever has no similar behavioral knowledge or insights at the level of the individual consumer; they only know how much product they push through retailers and distributors like Walmart, Kroger and Target.

To be actionable, Big Data must get down to the level of the individual – the “Power of One.” Big Data enables capturing customers’ individual tendencies, propensities, behaviors, patterns, associations, and relationships in order to monetize the resulting customer, product and operational insights (see Figure 1).

Figure 1: "Power of One" to Understand and Monetize Individual Customer Insights

Figure 1: “Power of One” to Understand and Monetize Individual Customer Insights

The Power of Digital Twins

Digital Twins is a concept that exploits the “Power of One.” Picked by Gartner (“Gartner Top 10 Strategic Technology Trends for 2018”) as one of the top 10 strategic technology trends in 2018, Digital Twins couples virtual and physical worlds to facilitate analysis of data and monitoring of systems in order to avert problems, prevent downtime, develop new opportunities and support planning via simulations[1].

But the Digital Twin concept isn’t new. The concept of a digital twin was originally developed by NASA in order to help manage unexpected “situations” that might occur during space travel (remember Gary Sinise in the movie “Apollo 13”).

NASA grappled with the challenge of designing things that travel so far away, beyond the ability to immediately see, monitor or modify. NASA’s innovation was a Digital Twin of the physical system, a complete digital model that can be used to operate, simulate and analyze an underlying system governed by physics[2].

This Digital Twin concept is being embraced throughout the Industrial Internet of Things (IIOT) world. GE may be the most famous of those IIOT companies in adopting this concept, “Digital Twin at Work: The Technology That’s Changing Industry.”

To quote GE:

Digital twin eliminates guesswork from determining the best course of action to service critical physical assets, from engines to power turbines. Moving forward, easy access to this unique combination of deep knowledge and intelligence about your assets paves the road to optimization and business transformation.

But Digital Twins isn’t just relevant to IOT. The Digital Twins concept, when instantiated via Analytic Profiles, plays a major role in understanding and monetizing human behaviors as well.

Analytic Profiles: Simplifying Digital Twins Concept

I blog and teach frequently on how organizations can embrace Analytic Profiles as a mechanism to help organizations capture, refine and share analytic insights at the level of individual humans and things.

Analytic Profiles provide a storage model (think key-value store) for capturing the organization’s analytic assets in a way that facilities the refinement and sharing of those analytic assets across multiple business use cases. An Analytic Profile consists of metrics, predictive indicators, segments, scores, and business rules that codify the behaviors, preferences, propensities, inclinations, tendencies, interests, associations and affiliations for the organization’s key business entities such as customers, patients, students, athletes, jet engines, cars, locomotives, medical devices, and wind turbines (see Figure 2).

Figure 2: Customer Analytic Profile

Figure 2: Customer Analytic Profile

 

Analytic Profiles provide an operational framework for capturing, refining and sharing the organization’s analytic assets. For example, Analytic Profiles provide the foundation for clustering customers into similar behavioral segments, creating detailed behavioral and usage profiles based upon purchase behaviors, and calculating the current and predicted customer lifetime value (see Figure ).

Figure 3: Leveraging Analytic Profiles to Determine Predicted Customer LTV

Figure 3: Leveraging Analytic Profiles to Determine Predicted Customer LTV

 

See the blog “Analytic Profiles: Key to Data Monetization” for more details on Analytic Profiles.

Without the analytic insights captured, refined and shared within Analytic Profiles, you lack the customer, product, service, operational and market insights that are powering new trends, such as those in Figure 4 below.

Figure 4: Gartner's Top 10 Strategic Technology Trends for 2018

Figure 4: Gartner’s Top 10 Strategic Technology Trends for 2018

 

CPG Firms: Leveling the Playing Field

A company called MoviePass (“Why MoviePass’s Crazy Cheap Subscription Just Might Work”) is promoting what appears to be a totally unsustainable subscription business model – pay $9.95 per month to see any movie in a movie theater that you want, AND the movie theater is reimbursed full price for the ticket. On the surface, that doesn’t seem to make any financial sense. However, the customer and movie insights that MoviePass is gaining about the behaviors, tendencies and inclinations of movie goers and the movies that they watch is likely to open all sorts of new monetization opportunities for MoviePass that can help filmmakers, producers, and studios turn a profit in areas such as movie planning, budgeting, development, customer profiling, customer targeting, promotion, advertising, merchandising, foreign sales, and DVD/TV/Video on Demand streaming rights.

This shift towards subscription business models could give CPGs an opportunity to level the playing field with retailers who have detailed customer transactional data (courtesy of their Point of Sales system and customer loyalty program).  These subscription business model, coupled with analytic profiles, provides an opportunity for CPG firms to gain rich insight into the behaviors of individual customers that can drive research, product development, marketing, advertising, sales and customer service.

With this detailed consumer insights, CPG companies could now start operating more like Netflix in their ability to monetize their customers’ purchase and behavioral insights (see the blog “Netflix Intelligent”: Something Every Company Can Do!).

[1] “What Is Digital Twin Technology – And Why Is It So Important?” by Bernard Marr

[2] “The Rise of Digital Twins”

Bill Schmarzo

About Bill Schmarzo


CTO, Dell EMC Services (aka “Dean of Big Data”)

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Dell EMC’s Big Data Practice. As a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

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