Peter Mehring, CEO Zest Labs, 31 May 2018
With all the technological advances we’ve made, from self-driving cars to IoT-enabled personal assistants, it’s hard to understand why we still waste nearly 40% of the fresh food produced in the United States. Certainly, some of it can be chalked up to consumer carelessness — we routinely buy things, including food, that we end up throwing away. However, a close study of the numbers reveals that roughly half of food waste occurs at the consumer level, meaning the other half happens somewhere within the fresh food supply chain, between the grower or processor and the retailer. With all the technology available to us today, how can our food supply chain still be this inefficient?
The short answer is that technology, particularly IoT, has historically been underutilized in post-harvest agriculture. Yes, there are drones and irrigation monitors in preharvest agriculture, but when it comes to post-harvest agriculture, once product is picked or harvested, advanced technology hasn’t been broadly applied — yet.
In the world of post-harvest ag-tech, IoT sensor technology coupled with cloud-based analytics have the power to transform the fresh food supply chain by improving decision-making at every step and, as a result, dramatically reduce food waste. IoT sensors can transform a supply chain that still operates based on assumptions into one that operates based on the real-time, granular data that provides visibility as to how to truly optimize decision-making. By adopting a data-driven approach enabled by IoT and cloud analytics, growers, processors, distributors and retailers can address the hidden issues currently impacting the fresh food supply chain to reduce waste — and improve food safety and supply chain transparency as well.
Over the past few decades, the time and distance our fresh food travels has increased from a few days to a more typical six to 10 days. This was a result of large retail grocers and restaurant chains wanting to buy from large suppliers who drove growing efficiencies by consolidating farms in preferred growing regions. While there has been a trend back to locally grown fresh food, it has not been significant in terms of volume. So, where strawberries were once locally grown, the variation in delivered shelf life from seven to 11 days was not a big deal. However, now that the bulk of strawberries are grown in California (summer time), they can travel six to eight days just to arrive on the store shelf — leaving little room for variations in shelf life. New processing techniques have improved the ideal strawberry shelf life to roughly 12 days, but in typical operations, the actual variation of delivered product is from seven to 12 days, as not all product is processed according to best practices. This variation leads to food waste due to unexpected early spoilage. The supply chain assumed all the product had the same consistent shelf life, and reflected that misperception with date labels. However, inconsistent processing leads to considerable variability that remains unaccounted for today.
This is where IoT can save the day. None of the issues impacting remaining freshness become actual issues if supply chain professionals know about them as they are happening. Remaining freshness is a function of product handling from field to shelf. An IoT sensor placed in each pallet of produce that monitors a wide range of variables, combined with cloud-based predictive analytics, can provide an up-to-the-minute snapshot of the product’s handling and accurately forecast its remaining freshness. If the IoT sensor detects a pallet has a temperature excursion, an alert can be sent in real time to proactively take action to minimize the impact on the freshness and quality. Further, if the data from the IoT sensor is analyzed to identify that a pallet has only eight days of shelf life instead of the desired 12, the supplier can modify the shipping decision to have the pallet routed locally instead of cross-country. This allows supply chain professionals to proactively manage based on real product data, rather than the current simplifying assumptions based on harvest date (assumes uniform processing) or visual inspection. Current visual freshness checks have been ineffective in reducing waste as visual freshness indicators only change in the very last days of remaining freshness, which is often too late to prevent waste. IoT sensors and cloud analytics provide product-level feedback to make improved decisions that avoid food waste.
There will always be bumps in the road, and expecting the supply chain to operate perfectly 100% of the time is not realistic. But now we can do away with poor assumptions in favor of actual product data collected in real time by IoT condition sensors. This data drives improved decision-making, providing growers, distributors and retailers alike with a better view into the freshness and quality of the food that is being harvested, shipped and displayed on store shelves.
By making use of the power of IoT and cloud analytics, growers, processors, distributors and retailers no longer have to accept the losses associated with food waste as the cost of doing business. By proactively managing their products through the supply chain, growers can improve profitability on the food they work so hard to produce, retailers can deliver a top-quality product to their customers, and consumers gain confidence in their purchases.
You can’t address an issue if you don’t know about it or only react to it after it has happened. IoT and cloud analytics can make the food supply chain proactive and enable growers, distributors and retailers to actively manage issues as they happen, preventing losses.
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