The Challenge

The promise of artificial intelligence, or AI, has permeated nearly all areas of business.  Supply chain planning and operations is one area with the potential for major impacts, from demand and supply planning and logistics to inventory management and controls. 

Artificial intelligence is the use of complex computing to solve problems generally reserved for humans.  AI can review data, visualize images, make associations, and identify patterns.  Machine learning, a subset of AI, occurs when programs learn on their own by evaluating sets of data.  The combination of AI’s critical thinking with other technologies, such as cloud computing and remote sensors, such as those in internet-of-things devices, is creating a perfect storm of technologies to solve complex business challenges.

food chain optimization guide

Why Now?

AI is rising to meet the unique challenges faced by food supply chains.  It can rapidly rebalance supply plans to meet shifting consumer demands.  In logistics, AI is able to monitor external data such as weather and traffic; when the Suez Canal was recently blocked, AI was able to reroute ships to avoid the blockage.  AI can also monitor shipments to be sure products are being shipped in the right conditions and notify both suppliers and buyers about breaches before the product is received.

AI is enabling supply chains to be more flexible while reducing risk both to timelines and quality.  Recently, the US FDA launched The New Era of Smarter Food Safety.  This initiative represents a broader approach to food safety and traceability to reduce instances of food-borne illness with a key focus on tech-enabled traceability, improved outbreak prevention and response, shifting food business models, and fostering an overall culture of food safety.  AI has a direct role in all these areas, from providing end to end visibility, to predicting the path of a food-borne outbreak. 

The FDA’s focus could not be timelier.  Food supply chains are seeing tremendous stress and older technologies and processes struggle to maintain safety and compliance.  The global pandemic has shifted consumer’s demand pattern and put tremendous strains on food processors trying to maintain production and balance employee safety.  Some producers found themselves diversifying their supplier base to avoid tariffs, while others are buying elsewhere to avoid poor yields due to shifting weather patterns.  AI is a hopeful beacon in addressing these issues.

AI Benefits in Food Supply Chains

AI promotes end to end visibility across the supply chain by making it easier to achieve tight processes and data sharing among all the participants.  At the start of the supply chain, agribusiness is beginning to use AI.  AI’s ability to evaluate multiple separate but related data sets like weather, moisture, soil conditions, and pesticide prices are helping growers better predict yield and prices.  In turn, buyers are placing contracts much more effectively, helping to reduce last minute sourcing and mid-season shortages.  The data collected in fields also helps suppliers validate label claims such as fair trade or non-GMO.

AI is improving inventory management in food and beverage production centers, reducing waste and helping producers focus on value and quality.  Adroit Outperform Planning, a leading supply chain planning tool, utilizes AI to assign values to expected orders lost due to anticipated stock outs our quality holds.  AI can then suggest adjustments to supply and demand plans to reduce the financial losses.  Rather than suggesting material be put on hold, Adroit Outperform Planning is able to predict the issue and focus the planner’s attention on potential uses for the material before it’s quarantined, avoiding waste and reducing risk to the consumer.

supply chain planning for food and beverage

Looking Ahead

The impact of AI extends beyond managing inventory within the four walls.  AI is beginning to help supply chain professionals rapidly rebalance supply and demand across complex networks of suppliers, producers, and shipping partners.  Older technologies like distribution requirements planning and material requirements planning used static data parameters to calculate recommendations.  Today, AI is able to predict a late shipment, gauge its impact, and provide a targeted suggestion in a matter of seconds.

It is easy to see how AI stands to impact the entire food chain, from growers and agriculture to producers and retailers.  Already, AI is helping supply chain professionals reduce waste and risk by predicting issues before they arise, targeting recommendations and providing visibility up and down the chain.  This adds time back in the day for supply chain planners to focus on value, quality, and safety in the supply chain.