Ramesh Kollepara: How Kellanova Is Fine-Tuning Its Internal AI Muscle
Kellanova is doubling down on employee upskilling for artificial intelligence.
With just one in six proofs of concept making it to the final stage of development, and just one in five of these actually scaling, it’s critical for consumer goods companies to temper their expectations, according to a conversation with Ramesh Kollepara, Kellanova chief technology officer, at Groceryshop last week.
“Not every proof of concept actually can scale and make a real impact,” he noted to CGT.
Instead, they’re focused on building a robust ecosystem where ideas can be evaluated and taken through a phased approach, while having the ability to disseminate learnings from each phase to be incorporated within the future.
Fine-Tuning AI’s Impact
In order to have an environment in which AI ambitions can thrive, Kellanova is building on its “Kuriosity” educational sessions, which are held across the company to open dialogues about the potential and practice of artificial intelligence.
Like many companies, Kellanova has developed a multi-layered AI governance task force that evaluates AI use within the organization. Since its start, they’ve fine-tuned some processes to account for the new realities of generative AI and the high-value use cases it can deliver.
Low- and medium-risk initiatives can be taken straight into execution mode, while high-risk projects must be vetted by the council.
Ramesh Kollepara, chief technology officer at Kellanova, talks about the value of employee upskilling.
“We have gone back into more of a culture of learning, bringing those learnings actually into the broader organization, creating that sort of curiosity, and honing that muscle,” said Kollepara. “At the same time, we have also changed the thresholds of barriers for entry for new ideas.”
This retooling is resulting in wins: A consumer engagement pilot with Pringles’ mustachioed mascot Mr. P leverages generative AI to answer their questions, all the while collecting first-party data to provide personalized experiences.
The cylinder chip cans, meanwhile, feature QR codes that consumers can scan for an interactive digital experience known as Poptopia that features promotions, content, and games (and also, of course, collects more 1P data).
Kellanova partnered with Microsoft about 18 months ago to implement Copilot, and the number of employees who are interested in using it is growing. More than 7,000 people have attended the Copilot “Kuriosity” learning session, which educates on such AI skills as prompt engineering.
The company, which is expected to be acquired by Mars, is also continuing its ongoing Year of Development Always (YODA) initiative, which focuses on building up soft skills, technical skills, and business skills, often through the use of hackathons.
Beyond generative AI, Kellanova is heavily focusing on IoT, said Kollepara. Over the last few years, they’ve installed IoT devices within manufacturing plants, obtaining shop floor insights to inform decision making. They’re also exploring digital twins to model their supply chain.
In terms of priorities for generative AI, the technology is effectively moving marketing from a waterfall campaign approach toward a multi-mode, agile model, he said. It’s evolving their customer service from function-specific to an end-to-end engagement across all functions, and they’re exploring the role genAI can have on monitoring, and then reducing, energy consumption at their plants.
Ultimately, while Kollepara concedes there’s a great deal of hype surrounding generative AI, being able to leverage it effectively — while keeping people at the heart of a strategy — is a game-changer. “All the initiatives should start with people at the center. AI is all about augmenting people, not replacing people.”
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