It’s time to put your party hats on! Business investment in IoT and artificial intelligence is finally bearing fruit, driven by more dollars going into deployments and the increasing value of data as companies connect different aspects of their businesses, according to a report published last week by The Economist Intelligence Unit.
According to the results of its third IoT Business Index, companies are finally implementing their IoT projects. The Economist Intelligence Unit first released the Index, which is sponsored by ARM, in 2013 and subsequently updated it in 2017. Three years ago, the big story was that IoT adoption had pretty much stalled as businesses tried to implement various IoT projects and found they didn’t scale well or didn’t do what was intended. It was referred to as “pilot purgatory.”
But for their external projects, most of the businesses surveyed had moved from an average score of 4.43 (“in planning”) in 2017 to 5.96 (just shy of “early implementation”) in 2020. When it comes to internal projects, survey respondents said they’d moved from 4.34 to 6.82 — into the “early implementation” bracket. (Scores in the 6-8 range represent early implementation while scores in the 8-10 range represent extensive implementation.)
The survey asked 825 business executives around the world about their IoT implementation strategies. Outside of the progress companies were making in implementation, the big takeaway was that IoT was becoming essential to any digital transformation. A full 65% of respondents agreed “somewhat” or “strongly” that IoT was one of the most important parts of their organization’s digital transformation strategy vs. just 46% in 2017.
Which makes complete sense. I’ve been saying for years that the sensors and connectivity associated with IoT deployment are really the physical data-gathering infrastructure that an organization needs to lay down in order to understand its operations. That data can then be analyzed and turned into insights that will help drive efficiencies or visibility into a business. But in order to take advantage of their data, companies needed to make a plan for dealing with it as part of their IoT strategy.
Only 16% “strongly” agree that the use of the IoT at their organization has been informed by an overarching data strategy, with another 42% agreeing “somewhat.” But the more a company invests in IoT, the more it tries to build some kind of data strategy, with 73% of businesses that have reached “extensive” IoT adoption noting they have some kind of plan.
The survey is fairly mum on suggestions for improving the handling of data and creating some kind of unified view on using it to better the business. But respondents do recognize its importance, with 27% agreeing with the statement: “The IoT has sparked a new wave of innovation thanks to data that give us better insights.” And roughly two in five respondents whose businesses have scored in the 8-10 range on the index connoting their “extensive” IoT adoption agreed with that statement as well.
So the more a company implements IoT, the more it recognizes the importance of IoT data. That’s partly because the more data it has, the greater visibility a company has into its operations. For example, data from a factory line could correlate to a product defect that’s causing a high rate of returns or repairs. Or customer usage data could influence future product feature designs, with companies placing expensive-to-build features that are rarely used on a higher-priced product — or dumping those features altogether.
These sorts of insights do more than merely offer a return on investment for connecting a factory line or adding a modem to a product. They help businesses understand their real value to customers, and then optimize around that value. That’s priceless.
So how can companies create flywheel effects using IoT data? The Index authors suggest that they use their IoT data for artificial intelligence, which is apparently not on most companies’ radars. Just over a quarter of survey respondents, or 26%, say that IoT data is pivotal to their current or planned use of AI, with a further 56% identifying them as “one of many important sources.”
The authors also suggest that companies build cross-functional teams from different aspects of the organization to try to use data. For example, it would take someone from manufacturing to make the correlation between a rarely used feature and the cost of producing that feature.
The report reinforces that it is so tremendously difficult to implement IoT that it’s taking far longer and people are still digging in their heels around data sharing and working outside of their comfort zones.