The stages of enterprise IoT adoption
Teresa Tung on building a business case for the Internet of Things.
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It will take a long time, and a great deal of money, to achieve the full dream of the Internet of Things (IoT)—a world whose sensors and machines are connected to the Internet as fluidly as our phones and PCs are today.
That’s why it’s important to plot out intermediate steps in IoT adoption. Companies that launch into the IoT without careful strategic planning are likely to find themselves on an expensive adventure as they connect disparate endpoints like medical devices and industrial machinery and ingest vast quantities of data.
At the Strata Business Summit in March, Accenture Labs managing director Teresa Tung cited a World Economic Forum report on the Industrial Internet to outline four concrete stages in IoT adoption that most companies will pass through as they connect previously dark devices to the internet. Each stage has real business value—an essential aspect for an adoption process that could take a decade or more to be fully realized. (You can view this segment of her talk in the video excerpt at the top of this post.)
The video above is an excerpt from Teresa Tung’s talk at the Strata Business Summit in March 2017. Visit Safari to view the entire session.
The first stage of IoT adoption is operational efficiency. “This is taking existing processes, existing products, and instrumenting them with sensors,” says Tung. It can also involve importing existing operational sensor data for analysis by business units. When Tung polled Strata attendees on how far they’ve come in building IoT systems, most raised their hands at this stage.
The next step is developing new products, services, and business models—often creating new services on top of existing products by connecting them to the internet. For instance, a medical device manufacturer might offer a new service that uploads device readings to the cloud for analysis later.
In the third step, companies focus on the “outcome-based economy,” developing sophisticated new products that guarantee outcomes—for instance, improvements in the collective health of an HMO’s risk pool, or increased total uptime for industrial machinery. These products must encompass multiple industry verticals, and they depend on the emergence of new data and commercial platforms.
The fourth stage of maturity is what Tung calls the “autonomous pull economy,” a final stage in which individual agents publish their own data onto broad platforms and contract with each other for access to it.