AI data analytics in CPG needs a reality check

Post by 
Cecilia Wu
Published 
January 29, 2019

We think AI driven data analytics solution probably has been gaining solid traction, especially common in the sector of consumer packaged goods (CPG). That is why BCG conducted a joint study last year with Google in which they interviewed executives at 25 medium and large size FMCG players and 5 niche brands, 100 industry experts worldwide. BCG concludes that:

  • by using AI and advanced analytics at scale and turning existing data into valuable insights, CPG companies can generate more than 10% revenue growth

BCG highlighted 10 primary applications that represent most of the AI and advanced analytics opportunity for CPGs:

Unfortunately, such theory only draws a rosy picture. Implementing these applications across the organization still eludes most of the CPGs.

According to BCG, there could be many roadblocks on the way:

  • Timid support from senior management
  • Fragmented divisions
  • Limited data governance: the company has no process in place for data management, quality or ownership
  • Lack of internal AI talent leads to an overreliance on external vendors

Although it is easier to build a small proof of concept (POC), scaling-up remains a thorny issue for corporate leaders. There even could be the syndrome of “POC explosion and dilution”: a company launches multiple small pilots with various vendors but performs no follow-through.

BCG derives that the typical process of scaling an AI advanced analytics application should take two to three years coupled with careful planning in mind.

It is a long journey. Even though you can get high-level buy-in, you are very likely facing push-back or reluctance from the mid-level as the process will often end up either adding extra workload or challenging existing habits throughout the company.

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