Big Data in Consumer Goods

You’ve heard it before. A convergence of consumer, economic and business trends have led to dynamic changes in the consumer goods industry. Consumers are socially active, mobile enabled, always on, information hungry and more value conscious than ever before. Manufacturers operate in an environment of rising input costs, tighter regulations, increased supply chain complexity, and questionable marketing ROI.

One such trend supposedly causing seismic shifts in the industry is the explosion of consumer and enterprise data, and the associated assumption that the analysis of this “Big Data” is, in and of itself, a desirable pursuit for manufacturers.

In Edgell Knowledge Network (EKN)’s view, the fundamentals of the consumer goods industry are sound, and at an over simplified level not much different from the traditional view of what a consumer goods manufacturer needs to do to succeed.

  • Design products in response to rapidly changing consumer needs and preferences (innovation, product development)
  • Manufacture products quicker and at a lower cost (sourcing, manufacturing)
  • Optimize the cost of delivering the product to the consumer (logistics)
  • Fulfill demand with increased certainty and reduced cost – reduce stock-outs, optimize inventory holding (inventory management, retail collaboration)
  • Build a stronger emotional connection with the consumer (customer development, branding, sustainability)
  • Increase the return on marketing investment, including optimizing trade promotions (marketing, trade promotion)

Undeniably, consumers and enterprises produce more data today than ever before. This data not only resides in enterprise systems but in a multitude of new data sources that include:

  • Email inboxes
  • Machine logs & customer service call logs
  • GPS logs of your truck fleet
  • The thousands of “likes” on each of your product pages on Facebook and in the consumer aspirations expressed on Pinterest
  • The video reviews of your products on YouTube and in the location awareness of their check-ins on Foursquare
  • The navigation path they follow on your website
  • Publicly available Census data

What is important to establish, however, is that the real opportunity for manufacturers is not in building the technological capability to capture, store and analyze this data, but in identifying specific outcomes that enable better, more profitable decisions in the context of the above fundamentals of success in the CG industry. Big Data, therefore, is a misnomer. Big Decisions would have been more apt.

Software tools and technological advances such as in memory computing are active enablers that make it possible for organizations to think about data and analysis in ways never before possible. However, to equate them with Big Data would be to miss the forest for the trees.

Manufacturers have already taken strides towards increased analytics maturity in areas such as supply chain insights (downstream data), shopper insights (category management) and trade promotion optimization. Big Data presents an opportunity to expand the scope of these use cases to include larger data sets, new data sources and speedier analysis. The insights ultimately offer input that improve existing decisions, or uncover opportunities to make new ones.

Big Data is about business decision-making. It has to be. This report will focus on the larger picture of Big Data; moving the spotlight away from the semantics of its definition and technological underpinnings to more important aspects such as use cases for the Consumer Goods industry, the changes required in organization structure and capabilities, and how and where to get started.

Edgell Knowledge Network (EKN) conducted a survey of 50 consumer goods (CG) manufacturers to benchmark the industry’s awareness, readiness and impact assessment of Big Data.

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