As AI technologies become more accessible, more industries are eager to adopt this technology to enhance their operations.
The food industry is no exception. Since this is a large and quickly changing market, it is important to stay ahead of the competitors and predict what foods will be popular. And what better way to do that than with the help of advanced artificial intelligence – not only can it offer accurate predictions, but also help companies enhance the manufacturing process.
To find out more, Cybernews sat down with Johan Langenbick, CEO of Foodpairing – a data & business intelligence company that predicts successful products and accelerates the product development process by connecting the right data, insights, and algorithms.
How did Foodpairing originate? What has your journey been like?
Foodpairing, as a company, was created in 2009 after the Flemish Primitives Event. The company began its journey by analyzing different ingredients (three thousand, as of today). Currently, we possess the largest flavor database in the world. One of our key focuses today is to predict successful products and achieve business growth for CPG companies by connecting the right data, insights, and algorithms.
Can you introduce us to what you do? What technology do you use to predict successful products?
Foodpairing is a data & business intelligence company. We predict successful products and accelerate the product development process of CPG companies by connecting the right data, insights, and algorithms. We use prescriptive analytics and provide insights on not only what products to launch but also on the likelihood of success of these new products. Our algorithmic models are customized to each client’s product and target group to give them the most relevant insights. Our CFI technology creates a virtual world and combines food data with consumer data to predict the most successful product concepts and formulations. Each product concept is supported by: the trial prediction (how interested the target audience will be in buying the product), the average liking (how much the target group likes the product), and the reasons for the product’s success (supporting statements on why this concept will be successful based on insights retrieved from the client-specific model).
What would you consider the biggest challenges surrounding the product development process?
For many years companies have tried to bring the customer into the product development process. This was done in various ways: customer co-creation, interviews, consumer panels, and so on. But also digital tools have increased consumer-centricity within the New Product Development (NPD) processes such as social listening, digital communities, etc. Digitalization has strengthened the understanding of consumer needs a lot.
However, interactions between CPG companies and brands are expensive to obtain, time-consuming, and fragmented across the product development and launch process. There are many functions within R&D, and all of them need specific tools. The biggest need, however, is still to have agile processes that are consumer-centric. There is also a lack of infrastructure and data, which makes it a very challenging endeavor. Digital Twin technology has the ability to solve these problems and to take up a central role within NPD. By using a Digital Twin of your consumer, companies can consult the consumer at every single step of the NPD process in a standardized manner. This is fast, accurate, and cost Effective.
In your opinion, which industries would greatly benefit from AI-powered Solutions?
Every industry which has the need to predict future market insights, such as purchasing the intent of the consumer as well as the liking of the consumer, would benefit from AI-powered solutions. Additionally, AI-powered solutions can help to solve a wide range of problems, from discovering white spaces/gaps in the market to finding the next best-selling product (including the final formulation) as well as reformulating your current product in line with new regulations (low salt, low sugar, and low fat.)
How did the recent global events affect your field of work? Were there any new challenges you had to adapt to?
The food industry has traditionally been slow in embracing digitalization, but since Covid, things have changed. More and more companies have realized the importance of AI and have been taking steps to incorporate this in different parts of their process. Within the world of product development and specifically, the concept and formulation development, making simulations at a molecular level is a new emerging playfield.
Since food is your main field of focus, how do you think this industry is going to evolve in the upcoming years?
It's likely that the food industry will continue to evolve in the direction of personalization and customization in the next few years. This is due to several factors, such as increasing consumer demand for healthier and more tailored food options, as well as advances in technology and data analytics that enable companies to better understand and respond to individual consumer preferences and needs. Additionally, the rise of alternative protein sources is expected to have a significant impact on the food industry. As consumers become more conscious of the environmental and ethical implications of their food choices, the demand for these alternative protein sources is likely to increase.
Overall, we can expect to see a continued focus on health and wellness, sustainability, and personalization in the food industry in the coming years, as companies work to meet the evolving needs and preferences of consumers.
What other parts of our daily lives do you hope to see digitized or enhanced by data in the next few years?
Food intake and its relationship to gut health and microbiome. By linking this data to other personal data like sleep or mood, we will be able to understand much better how personalized food should be developed. We had the pleasure of working with Richard Spraque, who did groundbreaking research in this area.
In this age of ever-evolving technology, what do you think are the key security practices both businesses and individuals should adopt? Share with us, what does the future hold for Foodpairing?
At Foodpairing, we are convinced that data is the new gold standard, and hence it should be treated with the utmost care. Security is a layered responsibility which implies that each and every actor in the whole process must adopt a set of rules that mitigate potential risks as soon as possible. We enforce encryption and segregation of data both in rest and in transit. Central identity management and multi-factor authentication are at the core of our solutions and are managed by industry-leading technologies, which allow us to have full traceability of each and every bit of information that is being processed. Deployment and configuration of cloud infrastructure are fully automated and treated as any other piece of code, which allows us to scan for potential vulnerabilities before they reach a certain quality stage. Periodic security awareness training and external security audits allow us to stay at the top of our Game.
What is your ultimate vision for the future role that AI solutions like those developed by Foodpairing will play in future innovation?
We believe that AI solutions for NPD will become commonplace by 2028. More and more companies will see the value in adopting a more agile way to develop new products. The key benefit of AI solutions will be that they will help companies predict market disruptions early on. Of course, the key winner in this situation would be the consumer.
Why is this relevant? Regulations will force food companies to produce foods that are healthy, sustainable, and delicious. This is a complex problem, and Foodpairing takes up the mission to help to make the transformation to healthy and sustainable foods and products much faster.
Additionally, disruptive innovation is part of the DNA of Foodpairing. We have always pushed the boundaries by using technology in a creative manner. In its early days, Foodpairing invented a new way for culinary chefs to create menus based on flavor pairing. Today Foodpairing takes that same innovator's role in the context of New Product Development for CPGs. How? The availability of data, computational power, Machine Learning, knowledge graphs, and Digital Twins allowed Foodpairing to reimagine the entire traditional stage-gated development process into a new agile and predictive workflow. By doing this, we are able to develop and improve product formulations at an unseen pace, from months to days.
Will it make it faster and cheaper to bring out new products that resonate more deeply with consumers?
Definitely. The advantage of using the right data and algorithms is efficiency. It adds predictability, making the process way faster and way cheaper than just doing a lot of concept and trial tests. Usually, it can take 3-5 months, while in a few weeks, we can get similar results. Also, adding extra insights that usually some of the teams do not necessarily have in the traditional way of working. We can enhance the whole flow with extra data and make the process richer.