AI data analytics in CPG needs a reality check

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.

By: Cecilia Wu