We have plenty of data, now what? In the age of interconnectedness, more and more people are finding themselves asking that question. Technology companies and research firms alike estimate the number of connected devices to be 20-50 billion by 2020. There has been a rapid increase in mobile computing, consumerization of IT and sensor technologies and big data analytics that all work together to push IoT adoption. This increase is leading to an astounding amount of information at our disposal, but for what?
There are stages of analytics when it comes to the data that is at our fingertips.
- Descriptive
- Predictive
- Prescriptive
Descriptive analytics has low complexity but also a low business value. Descriptive data help answer questions like: What happened? When did it happen? What is happening?
Predictive analytics is slightly more complex and has a higher business value. Predictive data help answer: What is likely to happen? When could it happen? What could happen?
The final stage, Prescriptive analytics, is the most complex and provides the highest level of business value. Prescriptive analysis allows you to answer: How can we make it happen? How can we influence what happens? What’s the best course of action?
There are few industries in which having this amount of data, and actually using it, can have the impact that will be seen in the coming years in the supply chain industry. Here are some examples of how the Internet of Things is working to transform the supply chain:
Increase ROI Through Successful Warehouse Slotting
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Predicting Equipment Failures
Union Pacific Railroad is using the IoT to monitor the condition of its equipment. The company’s system can predict equipment failures thanks to acoustic and visual sensors on the tracks. Each day, nearly 20 million temperature readings are processed via data analytics. Several cars per day are now pulled from operation for maintenance in order to prevent derailments, which can result in costly delays and expensive cleanup efforts.
Protecting the Cold Chain
The IoT allows for continuous, real-time assessments into the safety and quality of food and pharma products relating to their temperature during transportation. AI can use predictive analytics to provide forecasting based on data that might indicate a heightened risk during transport. This helps companies take prescriptive action such as planning and accommodating for hazards during transportation as they arise.
Asset and Associate Tracking
A Canadian mining company is using the IoT to connect its end-to-end mining operation. This includes vehicles, mobile device cameras, lights, fans, associates and more. Supervisors are able to track equipment as it moves throughout the mine. This comes into play when the company needs to ensure blast sites are cleared of associates and equipment, resulting in greater safety and output.
In distribution centers, Wi-Fi sensors are placed on pallets, cartons, forklifts, mobile scanning devices and associates, and they are integrated with inventory management, warehouse management and control systems. This provides visibility to item locations and a free-flow of real-time data, allowing for fast picking and order fulfillment – leading to increased customer satisfaction.
As you can see, the internet of things offers nearly limitless application in both the supply chain and our everyday lives. The goal of supply chain leaders should be to get to that prescriptive analytics level using the data at their fingertips thanks to the internet of things. enVista is committed to helping organizations accomplish that goal. We are already overcoming the incredible feats mentioned above, even with only 1-3% of devices being IoT-connected. It’s exciting to imagine what the supply chain, and world as a whole, will look like as we continue to increase that percentage.