09 Dec Food manufacturers see potential for AI in NPD

While there are questions about how far AI and machine learning can be used in product innovation, a number of global food groups are embracing the technology.

Over the last few years, some of the world’s biggest food manufacturers have been experimenting with the use of AI and machine learning. Many of them have introduced the technology to different parts of their business, such as automating processes in factories, largely for efficiency gains.

But there are areas where there is scepticism over whether this type of technology can make inroads and a belief tasks will always need to be undertaken by humans. One of those areas is new product development (NPD ), which requires a degree of creativity.

Surely a machine can’t take different data points and create a brand new product from scratch without any human intervention?

Increasingly, some of the larger food manufacturers have started exploring whether or not AI can make a big difference when it comes to creating new products.

Abhinav Agrawal, a US-based MD at management consultancy AlixPartners , says, so far, much of the impact the technology has had has been incremental, rather than genuine, NPD.

“One of my clients had a potato chips brand and a machine learning algorithm suggested one particular [potato chip] flavour for the Hispanic population that they launched in Texas and Miami, which have large Hispanic populations, and it became a pretty good hit,” he tells Just Food.

Cyrille Filott, global strategist for consumer foods, packaging and logistics at Netherlands-based financial-services group Rabobank , sees a potential role for AI to make incremental changes but he’s sceptical as to how far down the line the technology can take brands when it comes to genuine NPD for manufacturers.

“You could take an existing product and you could tweak perhaps one of the ingredients, like the flavour, or you could change the packaging based on the demand trends that you see out there and what you are getting through your data, but I think developing something completely new is still a long way away because you need to change lines and you need to create new packaging formats and all that,” he asserts.

Big Food’s use of AI in NPD

While there are questions about how far AI and machine learning can be used in product innovation, a number of global food groups are embracing the technology.

For instance, Mondelez International has used AI to “guide” the development of new products and new flavours to understand if it can shorten the development time, says Sally Loughlin, VP of global consumer science at the US snacks giant.

“We use AI to ‘supercharge our developers by unlocking the business constraints on human creativity, produce less prototypes and speed up product development,” she explains. “We have also used it to better understand consumers’ reactions to our products and have better feedback to help product development develop products that better meet their needs.”

The Cadbury and Oreo owner first mines historical data to build on what it already knows and then it moves to its AI-augmented product development tool to “get to the best solution faster”, explains Joe Manton, the global lead for digital R&D at Mondelez .

“We know great things are happening when we hear them [our developers] say ‘Ah ha, I never would have thought of that!’”

Manton says the business has already enjoyed some successes in the areas of shortening product development time, better flavour development and deeper consumer feedback..

“We have some clear examples of recipe development in new spaces – not that we would share; [they are] locked up as trade secrets – but also in some of the less exciting, but equally important, space of business continuity, replacing ingredients while maintaining or improving consumer delight and cost.”

Mondelez intends to further use AI as an NPD tool in the future and although the technology is being applied in a few focused product spaces, expansion across categories is beginning…..

Just-food.com: Read the full article here

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