Can artificial intelligence help slash food and beverage NPD timescales?


According to AI Palette Co-Founder and CEO Som Choudhuri, the tech firm addresses two of the biggest challenges that FMCG food companies face today, which are speed and the creation of successful products.

“Some 90% of products launched by the food industry tends to fail due to poor consumer response,”​ Chouduri told FoodNavigator-Asia​.

“These failures are expensive at roughly US$5mn per failure, not to mention the years of time and effort put into the product development process.”

“Creating successful products is very much like trying to predict the future, it’s a really hard process. Traditional methods are either early but qualitative, such as trend prediction, or quantitative but late. There is clearly abig data gap in the innovation process.”

“The speed to market of new products is also a major problem – previously, this would take about one to two years from creating to perfecting to hitting the market, but this is no longer practical today as consumer preferences are changing a lot faster, Traditional methods of NPD are no longer suitable.”

The AI Palette platform works to overcome these challenges by converting large amounts of unstructured data online into a structured format, which basically allows for the immediate prediction of F&B trends.

The platform can be configured according to each company’s requirements (e.g. according to product categories and targeted regions), so beverage companies for instance would be able to access trends in, say, Vietnam at once without going to traditional market research companies to conduct studies and wait three to six months to get this data.

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