Fast Five Shorts | Buy or Sell: Reckitt’s Claim AI Has Reduced Product Development Lead Times By 60%

Summary

Omni Talk Retail Podcast Summary

Episode Title: Fast Five Shorts | Buy or Sell: Reckitt’s Claim AI Has Reduced Product Development Lead Times By 60%
Release Date: March 14, 2025
Hosts: Chris Walton and Anne Mezzenga
Special Guests: David (former Reckitt employee), Shannon Eisenhart (Reckitt's CFO)

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Introduction

In this episode of Omni Talk Retail, hosts Chris Walton and Anne Mezzenga delve into Reckitt's recent claim that their integration of generative AI (Gen AI) has slashed product development lead times by 60%. This significant reduction has potential implications for the consumer goods industry, particularly in areas like speed to market, product quality, and marketing efficiency. The discussion features insights from David, a former Reckitt employee, and Shannon Eisenhart, Reckitt's CFO, providing a comprehensive analysis of the technology's impact on Reckitt's operations and the broader retail landscape.

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Reckitt's AI-Driven Product Development

Chris Walton introduces the topic by highlighting Reckitt's increased product development output through the application of Gen AI. According to ConsumerGoodTechnology.com, early findings indicate that generative AI has reduced Reckitt's development time by up to 60% while simultaneously improving product quality[^00:00]. Reckitt has been piloting this technology within its finish brands, utilizing years of past research and test data to create new, scientifically grounded product concepts based on consumer insights.

Key Quote:
"Reckitt has increased its product development output, allegedly via AI... new generative AI tools would be rolled out across its R and D function in 2025 to drive productivity and product superiority."
— Chris Walton, [00:00]

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David's Analysis: Buy or Sell?

David, a former Reckitt employee, provides an in-depth analysis of Reckitt's AI implementation. He reflects on Reckitt's culture of prioritizing speed over perfection, a mindset crucial for consumer goods companies aiming for growth through incremental product launches[^00:57]. David emphasizes that reducing time to market by 60% can allow Reckitt to capitalize on current trends more effectively, driving incremental sales and optimizing product launches.

Key Insights:

• Speed and Quality: Balancing rapid development with maintaining high quality is essential for successful product launches.
• Market Trends: Faster lead times enable companies to stay ahead of trends, avoiding the common pitfall of launching products after trends have waned.
• Execution: David expresses cautious optimism, noting that while the concept is strong, successful execution will determine the true impact.

Key Quote:
"If Reckitt can actually reduce the time to launch by 60%, they can actually be there while the trend is happening, drive those incremental sales earlier and then also optimize a new product launch to actually then be more scaled and more efficient."
— David, [02:59]

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Chris and David on AI's Role in Innovation

Chris echoes David's optimism, referencing a favorite quote from IDEO: "Enlightened trial and error succeeds over planning every time." He connects this to how AI facilitates rapid experimentation and innovation, enabling quicker market introductions.

Key Quote:
"AI is enlightening the trial and error which enables them to bring products to market faster and to innovate more quickly."
— Chris Walton, [03:14]

David expands on this by highlighting the importance of iterative improvement based on consumer feedback, reinforcing the value of speed in getting products into consumers' hands quickly.

Key Quote:
"If you're worried about perfection, what you really need to do is get the product in consumers' hands, listen, learn, improve it and then continue to grow."
— David, [03:14]

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Anne Mezzenga's Perspective on AI Integration

Anne Mezzenga supports the discussion by sharing insights from her interactions with CPG executives. She points out that early adopters of AI in R&D are leveraging AI agents to validate findings, acting as a third-party check on AI-generated data[^04:27]. Anne anticipates that the integration of AI will continue to advance, with companies pushing the boundaries of how generative AI tools are applied to product development.

Key Quote:
"There are already companies that are light years ahead on really trying to maximize how they're applying gen and AI tools to this process."
— Anne Mezzenga, [05:22]

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Operational Considerations and Challenges

David raises important questions about the operational aspects of integrating Gen AI, such as how AI accounts for route-to-market and production capabilities[^05:26]. He emphasizes that understanding logistics and production capacity is essential for transforming AI-generated concepts into market-ready products. David expresses interest in seeing how these challenges will be addressed in the near future.

Key Quote:
"I would love to understand how does Gen AI take into account your actual route to market and production capabilities."
— David, [05:26]

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Shannon Eisenhart on Marketing and Launch Efficiency

Shannon Eisenhart, Reckitt's CFO, adds another layer to the discussion by highlighting the impact of AI on marketing campaigns[^06:27]. She explains that beyond product design and feature innovation, AI also accelerates the localization and adaptation of marketing messages for different regions. This dual acceleration in both product development and marketing allows for a faster overall go-to-market strategy.

Key Quote:
"It speeds up the innovation process. It also speeds up the marketing campaigns and launch process to get you that faster go to market time."
— Shannon Eisenhart, [07:24]

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Conclusion and Final Thoughts

The episode concludes with Chris summarizing the consensus among the panel that Reckitt's use of Gen AI represents a significant advancement in the CPG sector. While the potential benefits are substantial, the true impact will depend on how effectively Reckitt can manage the operational challenges and fully leverage AI's capabilities across both product development and marketing.

Final Quote:
"I think this is probably real, the devil be in the details from the operations perspective."
— Chris Walton, [06:27]

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Key Takeaways

• Generative AI's Impact: Reckitt's adoption of Gen AI has the potential to revolutionize product development by significantly reducing lead times and enhancing product quality.
• Speed to Market: Faster development cycles enable companies to better capitalize on current market trends, driving incremental sales and ensuring timely product launches.
• Operational Challenges: Successful integration of AI requires addressing logistical and production capabilities to transform AI-generated concepts into market-ready products.
• Marketing Synergy: AI not only accelerates product development but also enhances the efficiency of marketing campaigns, facilitating quicker and more effective go-to-market strategies.
• Industry Outlook: The consumer goods industry is poised to benefit greatly from AI advancements, provided companies can navigate the complexities of implementation and execution.

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This comprehensive discussion underscores the transformative potential of generative AI in the retail and consumer goods sectors, illustrating how technological advancements can drive both innovation and efficiency when effectively harnessed.

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[^00:00]: Timestamp at the beginning of the transcript. [^00:57]: David's initial analysis. [^02:59]: David discusses the implications of reduced lead times. [^03:14]: Chris and David explore the role of AI in innovation. [^04:27]: Anne shares insights from CPG executives. [^05:22]: Anne continues her discussion on AI applications. [^05:26]: David raises operational considerations. [^06:27]: Chris summarizes final thoughts. [^07:24]: Shannon discusses marketing implications.

Transcript

[Chris]

Reckitt has increased its product development output, allegedly via AI. According to ConsumerGoodTechnology.com early findings of gen AI applications in product innovation have reduced development time for REKT by up to 60% while also improving quality. The company has been piloting the technology with its finish brands to analyze years of past research and test data to develop new product concepts, quote, grounded in science and consumer insights. End quote and shout out to all our Finnish listeners. And Shannon Eisenhart, Reckitt's cfo, said during the company's recent earnings call that new generative AI tools would be rolled out across its R and D function in 2025 to drive productivity and product superiority. Before adding you had better check yourself before you wreck it yourself. David, are you buying or selling? Records claim the generative AI has reduced its product development lead times by 60%.

[David]

So so that disclaimer that Chris was talking about is yes, I did work at Reckitt for a few a decade ago now. One of the things that really resonated with me during my time was that there was this concept of speed over perfection and that really has resonated with me. Not sure if it's still embedded in their core culture, but what I liked about that is when it comes to consumer goods companies, the way to drive significant growth outside of geographic scale is incremental new product launches. And so you really have to nail that. Your entire year is based on how do you launch, drive, grow scale new product. And so the two big things around there is speed to market and then quality which drives incrementality. And so if they're actually hitting both, that could be huge. So conceptually I'm buying from an execution standpoint I don't think it's as simple as that. Leveraging that real time data to have understanding from consumers where you can then make those changes. I mean right now most consumer goods companies it's anywhere from 12 to 24 months to actually launch a product from concept to in market. And oftentimes by the time you launch that trend or fad is already late, it's already passed. And so if, if, if reckon can actually reduce the the time to launch by 60%, they can actually be there while the trend is happening, drive those incremental sales earlier and then also optimize a new product launch to actually then be more scaled and more efficient. So if they can can do this, this could be huge. And so I'm really going to be looking forward to seeing what happens with this. So I'm buying this technology if it actually says what it does.

[Chris]

So you're buying it. Yeah. It reminds me of one of my favorite quotes too which is I think from ideo, which is enlightened trial and error succeeds over planning every time. And what you're saying is that AI is enlightening the trial and error which enables them to bring products to market faster and to innovate more quickly.

[David]

Yeah, I mean if you think about it, you don't actually know what's going to happen with the consumer till they try it. So if you're worried about perfection, what you really need to do is get the product in consumers hands, listen, learn, improve it and then continue to grow. And so I think it's a continuous process. So without a doubt, yeah, I'm buying it too, man.

[Chris]

I mean particularly the applications of Gen for me, for CPGs relative to retailers I think are much, much stronger and much more readily available too. That's a point that we've made on this show a number of times because and I'll never forget last year I sat in at Shop Talk on a Kellogg professor talking about how to do. Yeah, he had basically built out an entire process for how to do this. And I was sitting in there speechless, like my mouth was just hanging open like oh my God, look what you can do from a product development perspective. And if I was a CPG executive or if I was in charge of private label brand development at a retailer, the first thing I would have done is gone up to that guy and be like I want you to take this to my company right now. And I'm sure if he can do it, other people can do it. And so yeah, I'm with Dave. Like I think, I think this is probably real, the devil be in the details from the operations perspective. But Ann, what do you think?

[Ann]

Yeah, no, I completely agree. I, I've actually been talking to quite a few CPG executives in preparation for a session I'm doing at Shop Talk. And what I think is even crazier, Chris, and might blow your mind this year at Shop Talk is how they've take the, the smart early investors in AI for their R and D processes and collection of trend data, purchase data, focus groups, all data that they're collecting to inform where they take their products. Now they're building AI agents to go in and kind of cross check what, what the AI has found, what the people working at the CPG organization have found as like a third party check on what's been happening here. So there's already companies that are like Light years ahead on really trying to maximize how they're applying gen and AI tools to this process. So it's. I'm 100% buying it because what a.

[Chris]

CPG does is different than what a retailer does fundamentally. End of the day. Correct.

[David]

And one of the things I would love to understand is how does Genai take into account your actual route to market and production capabilities. So you can, you can fundamentally say this is the next trend, this is the next product you have, but if you don't have the capacity, the capabilities, the actual logistics, that then it's more of a conceptual, theoretical piece. So I think that would be interesting. And as it relates to a lot of cpg, you know, it's not fast fashion as it relates to beauty and retail. So I would love to see how this can actually be democratized to where speed is the most important thing for innovation with certain categories like that. So I think there's a lot of interesting things with Chennai that, that we're going to see in the next, you know, 3, 6, 12, 18 months. I'm really excited to see where it goes.

[Chris]

It's kind of crazy that we're still in year two of this whole thing. All right, all right, other Chris, what are your final thoughts on this record story?

[Shannon]

No, I think you guys had some really good points. We talked a lot about like in customer insight and sentiment generation and how that'll help you reframe, you know, possibly failing products or invent new products. I think that's. That's all. It makes a ton of sense. The other thing is, I think, like, when you think about speed to market, there's like product design and like feature innovation and all that. But there's the second half of that. Speed to market is like the marketing campaigns too, which I think this will also help of how do you localize and adapt the main marketing messages from wherever the product originated to, to the, you know, if you're a multinational 30, 40 other countries where you're trying to sell this product, which can actually slow down that speed to speed to market as well, I think is a whole nother interesting kind of lens too. Right. It speeds up the innovation process. It also speeds up the marketing campaigns and launch process to get you that faster go to market time.

[Chris]

Yeah. And that was the number one use case that I heard loud and clear throughout most of last year with the CPG brands that Ann and I were talking to.