Right now, many consumer packaged goods (CPG) firms are struggling with innovation. And three-quarters of yearly product launches fail.
AI and GenAI provide a path forward by accelerating the innovation cycle, expanding the range of ideas explored, and surfacing the concepts most likely to appeal to customers.
Despite this, AI is largely an untapped solution when it comes to innovation for many CPG firms.
The So What
The focus of many AI transformations has been on delivering growth through increased productivity.
“There is a natural tendency to focus on time-saving and cost-cutting projects in order to quantify the impact and justify the necessary investment,” explains Fabrice Beaulieu, a senior advisor to BCG.
“But it’s equally powerful to leverage the potential of AI to stimulate demand. Innovation is a good example of where AI and GenAI can help companies find growth in challenging times.”
AI can also be deployed to identify future buyer signals and create strategies based on forward-looking data predicting what customers want next.
Growth is hard to come by for CPG firms in many major markets at present: Inflationary pressures are limiting the scope for premiumization, and more agile challenger brands continue to outpace larger competitors.
In particular, smaller, digital-first companies can more quickly spot trends and land the first-mover advantage.
“The real opportunity is using AI to unearth meaningful insights about customer behavior and preferences from multiple sources of unstructured data—and then structuring those in a meaningful way, such as in line with consumer segments.
“AI can also be deployed to identify future buyer signals and create strategies based on forward-looking data predicting what customers want next,” says Arnaud Bassoulet, a managing director and partner at BCG X, the tech build and design division of BCG.
“That allows brands to become fast followers of the latest trends and increases their chance of being the first to market with innovative products.”
BCG experience suggests using AI and GenAI can accelerate the innovation cycle by up to 30%.
These are some areas where AI and GenAI can do some heavy lifting:
- Identifying market trends by distilling multiple sources of unstructured data at speed.
- Using computer simulations (in-silico testing) to quickly and cheaply test virtual product iterations.
- Helping formulate, reformulate, and then recommend optimal formulae for ingredient combinations.
- Writing product descriptions, and regulatory documents where needed.
- Generating marketing materials and automated content for launch packs.
- Testing performance and providing real-time feedback from multiple sources to aide with post-launch modifications and iteration.
“There’s an imperative to reinvent the innovation cycle so it’s faster, better, and more cost-efficient,” says BCG’s Nicol Zhou, who leads the firm’s work in consumer product innovation.
“And the effective use of AI at each stage of the innovation cycle from insight to concept provides the step change that is needed.”
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Now What
Target transformation rather than point solutions. Success requires an end-to-end overhaul of processes along the value chain rather than focusing on a series of specialized tools for specific use cases. While each point solution may save some time, they will not collectively deliver a broad reshaping of the innovation cycle. The starting point for such a transformation is assessing where most time and effort is expended and mapping that against the best AI tools to accelerate the work.
Prioritize people. The most challenging work is often not in identifying and developing the right technology, but rather in upskilling people and the way they work. Integrating AI into the innovation cycle will change the type of tasks workers undertake, the talent companies need, and the ways teams interact. As such, most effort should be directed toward people-centered strategies. BCG suggests that 10% of a company’s efforts should be focused on algorithms, 20% on technology and data, and 70% on people and processes.
Look one step ahead. While focusing on the potential of AI to reshape functions in the here and now, it’s also important to be mindful about future AI capabilities. This includes the potential of AI to invent break-through concepts. Although this is not happening for many CPG products yet, it is increasingly common in other industries such as drug discovery. It’s also important to think about potential uses of GenAI to enhance the broader product offering including services that increase personalization. For example, deploying a conversational chatbot to advise consumers during the decision-making process will improve the customer experience.
