It used to be that CPGs and retailers were both at the mercy of market data companies to get access to shopper, market and competitor information to make decisions. However, technology advancements such as affordable cloud, big data and related data-as-a-service providers upended many of those dependencies.
Companies with bigger budgets (including CPG conglomerates) now have in-house data science teams, and many retailers have adopted leading data science practices and predictive analytics solutions. This gives both retailers and CPGs access to myriad insights from various parts of their businesses to improve their relationships beyond the typical areas of merchandising and supply chain.
It seems like it would be a no-brainer for the two sides to collaborate, but with so much of that relationship hinging on the information the other one owns, the two occasionally find themselves on a collision course. However, companies can take steps to minimize these conflicts and maximize mutual success.
Data Savviness Breeds Data-Driven Decisions
One way to avoid those tensions is for both sides to lean on predictive and prescriptive data generated by artificial intelligence and machine learning (AI/ML) to bring objective insights to the conversation. This is now easier: employees across all teams at CPG and retailer companies are now more knowledgeable and data-savvy than ever before.
These “citizen scientists” are knowledgeable enough about an area (i.e.: data analysis) outside of their core responsibility to help them be more strategic with the domain focus of their job.