If you care about food, these statistics about applying artificial intelligence from a recent Progressive Grocer article Grocers Embrace AI to Optimize Supply Chain might alarm you:
- 43 percent of grocers are challenged by lack of real-time inventory visibility
- 48 percent of grocers rate their forecasting technology from very poor to average
- 43 percent of retail supply chain professionals say their technology can’t keep up with business demands
These are flashing red lights – with the above data illustrating significant problems within the fresh food supply chain – problems that lead to food waste, dissatisfied customers and reduced product margins.
Here’s what’s alarming: Without visibility into their supply chain, grocers tend to enter a cycle in which they overstock, prompting over correction/compensation, resulting in understocking and thus bringing them back around again.
For example, if a grocer receives a pallet of romaine lettuce at their distribution center and doesn’t know this lettuce has only four days of remaining freshness, they may hold it for a few days and send it to stores where it then spoils on the shelf. Out of stock and fielding disappointed customers, they order more, maybe even too much, also resulting in the surplus of produce spoiling on the shelves. It’s an unsustainable roller coaster of a ride.
Money down the drain. Waste in the landfill.
Applying Artificial Intelligence to the Supply Chain
Fortunately, grocers are taking steps to address these challenges. In fact, many grocers (half) are turning to post-harvest technologies, such as those using artificial intelligence (AI), to transform their supply chain operations. The Progressive Grocer article states:
“One in three of [grocers] surveyed claims to have incorporated AI capabilities into his or her supply chain, and one in four is working toward that goal.”
Retailers believe AI’s strongest potential to improve supply chain management is with the quality and speed of planning insights.
When it comes to improving the management and visibility of the fresh food supply chain, AI – when combined with the right data – can optimize reduction of waste associated with overstocking and understocking and even improve delivered freshness.
Freshness Management is Key
Certainly “AI” is popular across the technology industry. In fact, some companies have changed their name to incorporate “AI”, as if that demonstrates their value. However, AI is merely a tool, albeit a very powerful one. What’s important is understanding how to apply it with a clear objective in mind.
To utilize AI to optimize visibility of the fresh food supply chain and reduce waste, freshness management is critical. Freshness management provides grocers with the ability to know the actual remaining shelf-life of a product they’re receiving at their distribution centers to improve planning and inventory management and reduce waste.
By appropriately utilizing AI, machine learning and predictive analytics to know the actual remaining shelf-life of produce, grocers can more accurately plan for when and where to send it. As a result, there are fewer “surprises” because guess work (often based in inaccurate visual inspections) is taken out of the equation. This smooths out the bumps in inventory management and improves supply chain visibility.
But You Need the Right Data for Applying Artificial Intelligence
The insights gathered from applying artificial intelligence-based systems and post-harvest technology solutions are only as good as the data that goes into the system and helps build and tune the models. For far too long, the fresh food industry has assumed that all produce harvested on the same date will have the same amount of freshness and shelf-life.
This is simply not the case.
Changes in freshness and shelf-life begin in the field when produce is harvested. If you assume that all pallets are identical, you will continue experiencing issues with delivered freshness and you won’t solve the problem. Simply put, that assumption will result in a “garbage in, garbage out” result.
Instead, you need to know the freshness capacity (or maximum shelf-life) of that lettuce, as well as data about the condition of the lettuce from the time it’s harvested. By combining that data (best collected with autonomous IoT sensors throughout the supply chain) with machine learning and predictive analytics, we can accurately determine how long that produce will last. This enables grocers to improve inventory management and produce freshness while reducing costs and waste.
Learn more about how Zest Fresh for Produce utilizes artificial intelligence, machine learning and predictive analytics to improve the fresh food supply chain.