In 2024, experts predict reducing inflation across regions, passing on potential cost savings across the supply chain to CP firms and, with the advent of AI-based technologies increasing in public usage, consumer firms need to stay ahead of the game.
Reducing costs due to inflation
After a year of sustained inflation, many CP brands are facing smaller-than-expected margins, and they have to make tough decisions on what to invest in and where they can cut costs.
At first glance, the costs of building out a new digital-first operating model (centralizing and consolidating digital capabilities) are daunting for many firms. But in the long term, having a central artificial intelligence and data hub can save CP brands money and time across brands, especially when utilizing first-party (1P) data for new large language models (LLMs) and algorithms.
Digital operating models in practice: centralized consumer insights
A global consumer electronics company wants to create a consumer insights hub, where employees can analyze consumer data to personalize marketing for the Gen Z segment.
Smaller regions don’t have the budget to invest in analytics talent, technology and training resources and because they’re organizationally siloed from larger regions, they can’t scale data insights.
If business units from different brands and regions can all access data from the same centralized structure, smaller regions can still access and utilize centralized consumer insights and apply them to their own decision-making to decrease time-to-market.
Rapidly taking advantage of new technology
Given the complex organizational matrix between regions and brands within global CP firms, the operating model is often the key linchpin to success with new technology.
Digital operating models in practice: generative AI incubator
A global spirits company wants to create a conversational AI-powered chatbot for retailers to answer shipping and delivery questions for several brands in the U.S. market, but some brands have fully siloed sales processes, from manual to self-service as well as in-person.
Some brands don’t have the technical capabilities to pilot a chatbot, and any efficiencies from generative AI couldn’t be scaled or transferred across brands in the future.
If digital capabilities were centralized at a company level, new projects and learnings from generative AI could be efficiently scaled across the company and progressively honed over time.
Three opportunities for conversational AI in the CPG industry