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Consumer Packaged Goods in the Digital Age

March 4, 2022

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The past couple of years have been — to say the least — interesting for the consumer packaged goods (CPG) sector. As Erik Larson (@erikdlarson), Founder and CEO of Cloverpop, observes, “The consumer packaged goods industry is experiencing unprecedented change. CPG leaders were already struggling to navigate a more volatile, uncertain, complex and ambiguous (VUCA) commercial landscape with fewer resources while leading an increasingly transient workforce. Covid-19 has only accelerated these changes.”[1] An infographic prepared by the staff at Concentric reports, “[Nearly 80% of] CPG executives say the COVID-19 crisis will have a lasting impact on their customers’ needs”; however, “[less than a third of them] say their companies are well-equipped to address such changes.”[2] One of the reasons they are ill-equipped to deal with change is because their analytics capabilities are lacking. An infographic prepared by Retail Aware reports that a survey found, “70% of CG executives [taking the survey] selected the inability to integrate data from multiple sources as the top analytics challenge.”[3] Mastering data analytics is the sine qua non for success in the Digital Age.

 

Joining the Data Revolution

 

Giusy Buonfantino, Vice President of CPG Industry Solution at Google Cloud, observes, “At heart, the consumer packaged goods business is about brands, and today brands face all kinds of new challenges and opportunities. The COVID-19 pandemic has changed the way many of us live and shop forever, and digitally savvy consumers are constantly switching brands. Omnichannel consumption — the blended physical and digital consumption via services like mobile shopping, curbside pickup, or social shopping — put pressure on brands to innovate in how they market to consumers.”[4] Regardless of the path-to-purchase selected by consumers, data is, more often than not, generated as a result of their transactions. This data is important for understanding the changing CPG landscape. Buonfantino insists, “One common way for companies to succeed and prosper: Master the data revolution.”

 

If mastering the data revolution was easy, there wouldn’t be so many CPG executives indicating they were struggling to understand today’s business environment. According to Buonfantino, “The first step to solving any challenge is to understand it, and understanding comes from measuring and analyzing with the best data possible.” As noted above, CPG manufacturers generally have access to lots of data, but, as Buonfantino notes, it needs to be the best of the right data. She adds, “CPG companies have years of data about their own business, their products and partner relationships, and their customers. There are new sources of information about things like shipping and weather, and troves of public data. In 2022 we expect to see more companies taking control of their entire enterprise data estate and investing in digital twin initiatives, essentially expanding the use of first-party consumer data to create a view across the value chain, which is crucial for greater agility and predictability.”

 

Data and Decision-making

 

The staff at SupplyPike observes, “CEOs of successful consumer packaged goods companies know they need to make clear-cut decisions in order to be true business leaders. One poor decision can be disastrous. As far as the CPG industry is concerned, employing a data-backed business strategy is crucial for success where there is minimal scope for wrong decisions. There can be no substitute for a data-driven, well-informed, business decision-making.”[5] Larson adds, “Decisions are made to respond to change or to make change happen. That’s why [today’s] increased rate of change places CPG companies under unprecedented decision-making pressure.” He asserts, “To adapt to this new normal, organizations must rethink their decision-making processes.”

 

Business decisions are seldom black-or-white. Because so many decisions fall into the “shades of gray” area, CPG executives are best-served when they have a variety of options from which to choose. As Buonfantino noted, one way to generate these options by leveraging digital twin technology. Another way to provide options is to leverage a platform that can rapidly generate and explore various scenarios. The Enterra Global Insights and Decision Superiority System™ is one such platform. It utilizes advances in Autonomous Decision Science™ (ADS™), which combines mathematical computation with semantic reasoning and symbolic logic. The Enterra ADS™ system analyzes data, automatically generates insights, makes decisions with the subtlety and judgment of an expert, and executes those decisions at machine speed with machine reliability.

 

Larson suggests a third method he calls “the decision-back” approach.” He explains, “The decision-back approach maps decisions as the central framework for coordinating the people involved and the data needed to inform analyses and generate better decisions.” According to Larson, the decision-back approach involves three steps: Identifying essential levers that will make the decision succeed; listing the critical decisions that need to be made for each lever; and, finally, breaking down each decision into a decision tree of key business issues that need to be analyzed. He adds, “Only start connecting data required after creating a complete decision tree that describes all key business issues and sub-questions. This clarity makes data collection, research and analysis activities far more efficient.”

 

In addition to data, the thread that ties all these approaches together is artificial intelligence (AI). Journalist Tim Denman (@TimDenman) writes, “The fact that AI is providing CGs with unprecedented analytic firepower is not particularly newsworthy ― the technology has become table stakes in vital business functions like demand planning and supply chain execution.”[6] The staff at Stradigi AI add, “It’s hard to argue with the bottom-line results of a data-driven approach. The use of AI and advanced analytics has been shown to generate at least 10% in revenue growth for CPG companies, achieved through the three Ps of prediction, planning and personalization. All three are vital in competing in the continuum that includes everything from e-commerce behemoths and traditional brick-and-mortar channels to smaller, nimbler specialists. Harnessing the wealth of data that you already have at your fingertips is where you’ll find those all-important and actionable insights that can turn things to your advantage.”[7]

 

Concluding Thoughts

 

Buonfantino writes, “There used to be a saying: ‘Tough times don’t last, but tough people do.’ Today, it’s digitally-based challenges that will go away, while companies that organize and react to the digital opportunities will create new and lasting value.” In order to react, companies need to leverage the power of cognitive technologies. The Stradigi AI staff concludes, “Agility and resilience [are] two concepts that have been on the tip of everyone’s tongue. … And the CPG industry is no different. Adapting to shifting customer demands is paramount to surviving and thriving in the market of today and tomorrow. Those who will be leading the charge will be the ones who unravel what AI has to offer: better and faster forecasts using existing data, more accurate insights into changing consumer segments and trends, the opportunity to create personalized experiences that resonate with customers’ ever-shifting behaviors and preferences, and the ability to plan ahead more efficiently to make an uncertain world more uncertain.” These are not new insights. Over half-a-dozen years ago, Bain analysts, Michael C. Mankins and Lori Sherer () observed, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.”[8]

 

Footnotes
[1] Erik Larson, “How To Drive CPG Growth From Within Using The Decision-Back Approach,” Forbes, 18 January 2022.
[2] Concentric, “Infographic: Matching the Speed of Change With Prescriptive Analytics,” Consumer Goods Technology, 25 February 2021.
[3] Retail Aware, “Infographic: The Future of Retail Brings CGs New Data Opportunities,” Consumer Goods Technology, 24 February 2021.
[4] Giusy Buonfantino, “2022 CPG Predictions: Mastering the Power of Data Revolution,” Consumer Goods Technology, 6 January 2022.
[5] Staff, “Data Analytics For Your CPG Company,” SupplyPike’s SupplierWiki, 2 July 2020.
[6] Tim Denman, “Developing and Building Meaningful Artificial Intelligence,” Consumer Goods Technology, 31 July 2020.
[7] Staff, “CPG Execs: Stop wincing, start winning with AI,” Stradigi AI Blog, 1 November 2020.
[8] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.

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