FoodChain ID 2021 Tech Predictions

Dr. Ruud Overbeek, Sr. Vice-President, Corporate Development & Strategic Relationship,  FoodChain IDDr. Ruud Overbeek, Sr. Vice-President, Corporate Development & Strategic Relationship
The need for meaningful data analytics is a primary driver of technology decisions being made in the food and beverage industry. As the industry becomes more digital, the food supply chain provides an increased amount of data that requires robust tools to capture, analyze, and transform data it into valuable insights to better manage food production, reduce risks, and increase food safety.

The abundance of data combined with an increase in consumer demand for transparency has increased the need for: mass data management to normalize the data, AI (artificial intelligence) and machine learning to aid data analysis and modeling, integration of systems to increase data accessibility, and more human capital to provide valuable insights gleaned from the data. This will improve traceability and data management processes across a complex food supply chain. While these digital technologies alone will never eliminate all food risks, they will be able to improve speed to response, cost reduction and limited damage.

While today’s technology can produce a wealth of information, information alone is insufficient for firms to be successful, because of:

1. Analysis Paralysis – it’s far too easy to simply request more information.
2. Easy access to data makes us intellectually lazy – the bigger the dataset, the easier it is to find support for any hypothesis you choose to test.

3. Impulsive and Flighty Consumers of Information –the capacity to focus and concentrate on a specific activity is falling.

4. Learning can be dangerous – democratization of information creates an imbalance, with certain people incapable of interpreting and using information in a sensible way.

5. Generation of information will only increase – there was more information generated in 2020 than in the entirety of human history, resulting in a substantial reduction of the value and life of knowledge.

This leads to what we see as an increase in the adoption of AI and machine learning in 2021.

• AI handles repetitive tasks allowing people to focus on the most engaging part of their jobs. AI-powered chat bots are a great example of this.

• AI will also play a role in food safety to transform complex data into meaningful analytics. It will increasingly help companies make use of their data by consolidating it from a variety of sources, making it available in a central searchable source, allowing analysts to identify important changes and patterns, and predict key business metrics.

• More evolved AI algorithms identify trends, segment data, uncover anomalies, and create detailed reports. AI makes connections within millions of seemingly extraneous signals that humans would never be able to analyze otherwise.

• With companies and governments spending billions on AI annually, with technology giants leading the way, and with AI becoming a more prominent part of the curriculum for leading Universities, disruptive breakthroughs are bound to happen including more powerful AI that could read and understand everything humanity has ever written, and allow AI to increasingly take over tasks that were once thought to be exclusively human. It can only be imagined how this can be useful to all.

AI-powered technology will play a key role in food safety to transform complex data into meaningful analytics. That, along with valuable insights provided by the technology and analysts reporting on it are an emergent trend in 2021.
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