How IoT improves the fresh food supply chain

Every company is obsessed with data. Whether it’s a security team monitoring logs or a retail grocer checking temperatures of a trailer filled with fresh produce to ensure its freshness and safety, companies rely on data to make better decisions that improve their business. Effective data capture helps leaders gain a clear view into their operations. However, data collection is only as valuable as the usable insights that it provides. Incomplete or inaccurate data capture — or collecting the wrong data — leads to bad analysis and poor decision-making. This is made worse when data collection is a manual or ad-hoc process that is error-prone and increases costs. Adoption of IoT technology can make a huge difference as IoT sensors, compared to low-tech approaches, do a far better job of autonomously providing the level of data and insight needed to inform proactive decision-making and course correct inefficiencies.

Let’s consider the fresh food industry for example. Food waste is a significant issue in the United States. The NRDC’s recent “Wasted” report states that up to 40% of the food produced in the U.S. goes to waste, and this costs us an estimated $218 billion per year. Much of this is due to challenges within the supply chain where food industry leaders don’t have adequate data and insights for effective decision-making. As a result, about a third of fresh food spoils prematurely, driving up costs for growers, shippers and retailers.

Getting to the root of the issue

To see the fresh food supply chain in action, we can take a deeper look into the significant temperature variations that fresh produce or proteins can experience during processing or in trailers transporting the food to the retailers. Significant temperature variations at the pallet level can result in premature spoilage and food waste. For example, fresh berries should be kept at 34 degrees Fahrenheit throughout shipment from the supplier to the retailer. Twenty-six pallets may be loaded into a trailer that is at an optimal temperature of 34 degrees Fahrenheit. Though parts of the trailer may be at the optimal temperature, it’s the pallets of berries that need to be monitored because studies have shown that pallets in a single trailer load may experience substantial temperature variation that leads to premature spoilage. Pallets near the refrigeration system may be at 34 degrees Fahrenheit, however pallets at the back of the trailer may be at 40 degrees Fahrenheit. In one study, five of 26 pallets (that’s nearly 20%!) experienced temperature variations that had significant impact on shelf-life. Additionally, one pallet was at 46 degrees and lost almost 10 days of shelf-life, meaning it was essentially spoiling as it was delivered to the retailer, leading to waste and lost profits.

The old way and the new way

For decades, across the fresh food supply chain, we have tried to solve these waste and data challenges by using low-tech temperature collection devices, like USB data loggers, to collect trailer-level temperatures. These are often expensive single-use devices and are operationally cumbersome, even prohibitive, to deploy at the pallet-level — but, as mentioned, when it comes to reducing waste, it’s at the pallet level where the valuable data resides. As a result, for years we’ve been collecting the wrong data about the temperature of the trailer, which doesn’t provide accurate insight into the condition or freshness of the pallets of product in the trailer. These antiquated approaches paint an inaccurate picture that is insufficient for making informed decisions that solve the food waste problem as demonstrated by the fact that, for decades, we haven’t reduced waste.

Autonomous IoT sensors that monitor at the pallet level, where the temperature variations occur, do address this insight gap into data capture of food freshness throughout the supply chain. Autonomous IoT sensors don’t require a worker to plug a USB drive into a computer and download and email a spreadsheet for each pallet. Instead they can be read autonomously, and the data can be sent directly to cloud-based applications for analytics and decision-making. IoT implemented at the pallet level provides deeper insights into the product in a trailer that may have experienced a temperature excursion during transit (such as hitting 46 degrees instead of the desired 34 degrees), and therefore may spoil well before its best-by date. Stakeholders can use this data to proactively manage the supply chain and implement techniques, such as intelligent pallet routing, to reduce waste.

Getting holistic

Because IoT sensors collect data autonomously and are less expensive than legacy data loggers, they are cost-effective and are a viable way to optimize the fresh food supply chain. They stay with the product as it makes its way through the supply chain, and the sensors collect the right data at the right time throughout the product’s journey. This complete view delivers accurate insight into the product’s condition that old-style supply chain monitoring technologies are unable to provide. IoT sensors combined with cloud-based analytics quickly deliver the granular data sets that enable business leaders and operational staff to take corrective action, based on real-time product condition rather than incomplete or inaccurate data, such as the temperature of a trailer during one moment in time.

Like the NRDC study explained, data collection is important in order to have insight into the operations of a business, especially with an industry as time- and cost-sensitive as fresh food. However, data collection alone isn’t enough. Capturing the right data is critical to giving transparent and accurate insight into the effectiveness and inefficiencies across the supply chain. Implementation of cost-effective IoT sensors into operations helps draw out insights, properly evaluate the health of a business and make appropriate adjustments as needed, before an incomplete or inaccurate decision spoils business results.

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