IoT sensors can predict human behavior in supply chain

An influx of sensors relating to Internet of Things technology is generating a growing volume of data to feed the predictive supply chain, and informs not only operational decisions, but also helps analyze the behavioral patterns of workers.

Just like the in-store environment, shipper departments now can access a wide array of sensors, applications and data that provides real-time updates on where an item is, as well as the condition of the product—temperature and humidity as it relates to perishables, for example. But it's still people driving the trucks, and their patterns can also be understood, said Andy Souders, senior VP of products and strategy for Savi.

"The rise of the Internet of Things, advancements in sensor technology and new analytic capabilities have created an opportunity for (companies) to better manage global supply chains through actionable intelligence," Souders told FierceRetailIT. "We are seeing continued growth in the volume of sensor data which will lead companies to look for new ways to manage it—to use sensor data as their eyes and ears to give the COO insight into employee's assets and how customers are being served."

Those that can figure out how to harness the behavioral analytics information of the drivers they trust with their assets will be able to provide full visibility into their supply chain. "Amidst a growing number of IoT entrants and adopters, demand for a standard IoT protocol is bourgeoning, driving consolidation, and paving the way for new enterprise and commercial innovations," he said. 

The IoT brings computing and communications power to everyday devices and businesses, which will lead to better business models and increased visibility in the business process. Sensor technology is the key force behind this growing market, Souders said. In the business-to-business realm, sensor technology is especially prominent in measuring status of production, location of goods and safety issues.

"The growing volume of data that has been collected by supply chains is opening the door to the predictive supply chain. The industrial supply chain is not just trucks, it's people who are making decisions and that is why understanding human behavior is important, because people tend to follow measurable patterns," he said.

In analyzing this information, companies can identify which drivers are truly stand-out performers and where there is room for improvement. "When best understood, these human behaviors can help optimize performance by providing details on where most drivers stop, how often they stop, and what kinds of routes pose the most issues for these drivers," Souders said.

"When best understood, the human behavior of truckers can help provide insight into the true ETA of deliveries," he said.

Ensuring that shipments maintain their quality throughout the whole journey has always been crucial, but now real-time analytics can help provide valuable intelligence. The data speaks to human behaviors and other factors that could impact the quality of shipments or their arrival time to intended destinations. Some factors can't be controlled, but gaining insight into the drivers' behavior can answer questions like: Did the driver make sure to maintain the temperature throughout the journey? Or, did he or she stay in one location for too long, causing increased humidity?

"Sensors continuously produce information that contains vast potential for commercial logistics and shipping providers with the ability to capture, track and analyze it. Sensors are now cheaper than ever and their real value is in creating a repository of historical data that can be used for predictive analytics that provides benefits in shipping high-security hauls like these," Souders said.

For instance, predictive scenarios can tell when a truck is making a regular stop, is stuck in traffic, or is stopped in a dangerous region where a theft could be possible. This allows companies to make intelligent decisions on when to request assistance from authorities, how to change their routes, or when sensor "noise" might just be bumps on a road.

"By having full visibility into the supply chain, from the actual trucks to the truckers in the driver's seat, the shippers can use big data and behavioral analytics to properly mitigate supply chain risks," Souders said. "Companies can use the collected data to forecast future outcomes, prevent operational disruptions, and improve supply chain performance.

"With visibility into a trucker's behavior en route to its destination, companies will be able to make any necessary decisions regarding a trucker's performance and whether it is enhancing the supply chain journey, or needs improvement." 

For more:
-See this Savi press release
-See these Savi case studies

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