One of the challenges of IoT is figuring out the value of the data coming from so many connected devices. In industrial settings, there are frameworks for assessing the value of data. Does it improve operational efficiency, allow for preventative maintenance, or is it useful for asset tracking?
But increasingly I wonder if other new and creative uses can be mined from that data.
I spent some time earlier this year with executives from ThingWorx, a leading software platform provider for the industrial IoT. ThingWorx serves diverse industries including life sciences, medical devices, mining, smart grid, and water infrastructure. We looked at a number of industrial use cases, including the story of JoyGlobal.
Joy Mining provides products and services for the mining of coal, copper, iron, oil sands and other mineral resources. Initially the company used ThingWorx’s IoT solution to tackle typical industrial problems like preventative maintenance that are important in reducing downtime as well as some other innovations like altering the revenue model by moving from paying per product to paying per tonnage of earth mined.
The company also added hundreds of sensors to mining equipment so that the underground equipment could be managed from above ground. We see this as a continual theme in the mineral resources industry where there’s a premium on remote control of hard to reach assets as well as a shortage of qualified service technicians whose time must be optimized. Operators only have to be deployed when there’s an actual equipment failure that must be addressed.
All of this is interesting from an IoT perspective but what was truly creative was what JoyGlobal did next. They allowed customers of their mining equipment to opt into providing all of their sensor data to JoyGlobal. This data provides a picture of how efficient a given mining company’s operation is at extracting minerals.
In exchange JoyGlobal benchmarked that data against an anonymized set of data from across the industry to let its customers know how they were stacking up against competitors using the same mining equipment. Customers could compare the exact yield they were getting from a piece of mining equipment versus other companies using the same equipment.
I’ve written previously about benchmarking as a business model in IoT. Agtech startup Farmlink, which raised a healthy $40 million last summer, has built its business around benchmarking agricultural fields to a granularity of 150 square feet. Farmers are able to see not just how their farms compare to neighboring farms but can also assess productivity across their own farm.
Benchmarking isn’t a direct boost to operational efficiency but it’s an example of how analytics and intelligence inform managers precisely how efficiently their machinery is working. And it invariably leads to important competitive questions like, if the farm down the road or the mining machinery across the globe are performing at a certain yield, why isn’t my operation performing at that level? This line of inquiry tends to push managers to pinpoint areas where operations can be improved.
For JoyGlobal, adding benchmarking as a service to their existing line of mining machinery services has opened up a potential new line of revenue and perhaps even a new business service. Interestingly, JoyGlobal is similar to Farmlink in that both had other revenue streams related to either selling or renting hardware. Farmlink rents combines, which do large scale harvesting. But by adding connectivity to those combines to collect data regarding yield, Farmlink built an entirely different revenue model. In both of these situations, the existing machinery was in the hands of customers. It was exploring the value of that data and adding benchmarking that created new value.
All of this begs the question: What other industries where there is already significant machinery deployed across a sector could benefit from benchmarking services? For now, I’d bet we might see more of this type of strategy in machinery involved in physical type actions like power turbines or construction. But as we’re seeing, once the machinery is already deployed and connected, there exist real possibilities of building new business services from the collected data.