Big Data & Analytics Sensors Supply Chain

How Analytics Are Changing the Potential of Sensors

Sensors have been used in the supply chain for a long time. There are millions of sensor types designed for narrow, singular purposes, such as sending point-in-time messages regarding position/location, light, temperature, humidity, shock/vibration, pressure, electrical fields, etc.

There are no standards and many different data formats and protocols with little interoperability. They have memory constraints, with very little memory storage, which results in sensor data that is akin to machine language. This yields an enormous number of small messages, or what is known as “big data.” An advanced sensor data analytics solution is needed to make sense of these messages.

With an advanced analytics solution, you will have not only point-in-time information, but you will also have the ability to find patterns within the data to uncover insights to prevent risk and optimize operations.

To explain more, let’s take a look at how advanced analytics solutions provide risk management and operational benefits based on a few sensor types and scenarios:


A pharmaceutical company needs to make sure that the temperature of their goods is properly regulated throughout a shipment. Sensors are able to track the temperature of goods, but if a temperature becomes too high or too low during a shipment, the company isn’t able to determine where on the route or for how long the temperature was altered. With an advanced sensor data analytics solution, the company would be able to know exactly where temperatures are altered during a shipment. After analyzing temperature patterns over the course of multiple shipments, analytics would be able to predict areas on the route to avoid and recommend safer routes for shipments.


A CPG company is concerned that a high percentage of their goods are delivered in a damaged condition. They use sensors to track moments of shock and vibration. Although, there are different types of shock, such as shock from poor handling or shock from unfavorable road conditions, and they don’t have the technology to make sense of the data from their sensors to discover exactly where or how the damage is occurring. With advanced sensor data analytics, the company would be able to locate precisely where the most shock occurs during a shipment, it could also uncover if a specific carrier, driver, or distribution center is responsible for causing the most damage due to poor handling. The company would be able to pinpoint areas and causes of damage and develop new processes or alternate routes to prevent further damage events.