5 Benefits of AI for CPG R&D Teams

Artificial intelligence can be an extremely powerful tool for a CPG research and development department.

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The right AI system can leverage a multitude of information and transform it into valuable insights on how to quickly develop the right product for consumers at the right price. It can be used to inform an R&D team about what kinds of items the market is looking for. The time it takes to develop those items can be significantly cut down, increasing R&D team productivity and decreasing costs. It can ensure that products comply with regulatory standards for ingredients, and the wealth of knowledge from many research teams across the company can be utilized to improve product design.

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While a Pricewaterhouse Coopers study found that 41% of companies are using data analytics and AI for the digital product development process, most don’t take full advantage of it. Only 5% use AI for a variety of applications — like designing, optimizing the manufacturing process, and quality and product validation.  

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As the economy tightens, it’s a difficult time for CPG companies to expose themselves to new risks. According to research from Harvard Business School professor Clayton Christensen, 95% of new products fail. Using AI to develop new products can help them be a part of the coveted 5% that consumers continue to use and purchase.

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Let’s examine 5 benefits that AI can provide to CPG R&D teams.

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Faster Time to Market

Using AI to digitally develop products will increase companies’ efficiency by 19% during the next five years, according to PricewaterhouseCoopers research. With this efficiency upgrade, 17% will see faster product launches and 13% are expected to have lower production costs, the firm found.

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Where R&D teams previously spent time formulating and testing new and revamped products through a series of experiments, an AI system can more quickly offer possibilities based on data. Information in the system about different ingredients, processes, consumer reactions, and costs could quickly produce better recommendations for prototyping and testing.

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Less product development by trial and error means that fewer tests are needed. Fewer tests mean less cost for R&D for individual products. It also shortens the amount of time needed to get to the prototyping phase, which could get new products into consumers’ hands more quickly.  

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Reduce R&D Costs

AI presents a compelling solution for Consumer Packaged Goods (CPG) R&D teams, particularly in the realm of cost reduction. In a landscape where cost optimization is always a concern, AI holds the potential to revolutionize R&D processes.

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The expenses associated with formulation development, ingredient procurement, and final product pricing often pose significant challenges. By leveraging AI-powered algorithms, CPG R&D teams can significantly decrease the need for resource-intensive physical testing, resulting in optimized resource allocation.

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Additionally, AI's ability to generate formulations that align with predefined cost thresholds empowers organizations to achieve their targeted price points, translating into enhanced affordability for consumers. Ultimately, the incorporation of AI not only augments efficiency but also contributes to a substantial reduction in costs across various dimensions of CPG R&D.

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In an era where every dollar saved and innovation counts, AI can be leveraged as a strategic tool for CPG R&D teams to navigate cost constraints while fostering efficient and market-responsive product development processes.

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Digitalization of Intelligence

In the world of CPG, harnessing intelligence is critical for staying ahead. However, CPG R&D teams often struggle with a shortage of captured data and an abundance of invaluable knowledge residing within tenured developers.

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It's common to find R&D teams with decades of experience, which raises concerns about knowledge loss when these experts depart, especially with close to 290,000 workers 65 and over. Similarly, onboarding new talent or junior product developers can be a time-consuming process. The question arises: How can organizations preserve, amplify, and disseminate this knowledge efficiently?

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Imagine a scenario where a seasoned developer's insights are seamlessly integrated into AI systems. This approach not only captures tribal knowledge but also enables quicker and more effective education for junior scientists, and provides a more complete data set for AI to build more accurate models. It also ensures that insights, methodologies, and nuanced experiences are efficiently documented and made accessible for future use. By doing so, CPG R&D teams pave the way for continuity, innovation, and enhanced decision-making.

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This isn’t just limited to human intelligence, AI systems can consolidate testing, sensory, and consumer data, transforming raw information into actionable insights. In this digital age, where knowledge and data should go hand in hand, the benefits of digitizing intelligence are invaluable for propelling CPG R&D teams toward a future of sustained success.

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Improve Productivity

The very nature of AI can help companies develop better products as they continue to use it. Artificial intelligence uses data to quickly make decisions. But as AI is used more and more, the data it processes increases, and the system can learn from that additional data. Through a subset of AI called machine learning, the system can better recognize patterns in data and learn from mistakes that have previously been made. The end result is a smarter system and better-informed R&D.

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With the successful use of AI, a company can increase its productivity as time goes on. Successes and failures will keep teaching the system how to best design products, making it possible to create a larger number of successful designs in less time.

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Increase Customer Satisfaction

Designing a product that satisfies an R&D team is one challenge, but creating something that resonates with consumers is a larger task. Customer preferences and needs are constantly changing.  Whether it is consuming less sugar or staying clear of certain ingredients and chemicals.  Organizations need to keep up with these changing needs/wants.

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AI can make it easier to discover what consumers are looking for. This type of system can combine data on actual consumer behavior, social media, and sales information to come up with trends and patterns.

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In turn, this can lead to better consumer-centric product development, leaving much less up to chance.

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After all, Steve Phillips of insight consultant firm Zappi wrote in Forbes, that most product failures are essentially caused by a failure to grasp good enough consumer insight. AI can capture those true insights more easily.

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