Smart cars and connected household devices get the lion’s share of IoT attention. It makes sense—consumer devices and cars are sexy and they attract a lot of eyes from a booth at CES. All the while, their geekier, bespectacled sibling, The Industrial Internet of Things (IIoT), is lurking in the background quietly growing at an astounding rate.
The IIoT could add as much as $10 trillion to the economy by 2030, according to estimates by Accenture. There are opportunities abound, from vastly improved operational efficiency (e.g., improved uptime, asset utilization) through predictive maintenance and remote management, and the emergence of an outcome economy fuelled by software-driven and collaboration between humans and machines.
We’re not quite there yet, and there are some significant barriers to more widespread adoption. This article from ReCode does a great job covering some of the biggest challenges and opportunities:
The good news is that, unlike driverless cars, the Industrial Internet of Things is already here, at least among the most forward-thinking companies. The challenge is that most businesses are not ready to take the plunge. According to an Accenture survey of more than 1,400 business leaders, only one-third (36 percent) claim they fully grasp the implications of the IIoT. Just seven percent have developed a comprehensive IIoT strategy with investments to match.
One of the reasons is the as-yet limited ability to leverage machine intelligence to do more than enhance efficiencies on the factory floor and evolve to create entirely new value-added services, business models and revenue streams.
So far, businesses have made progress in applying the Industrial Internet of Things to reduce operational expenses, boost productivity or improve worker safety. Drones, for example, are being used to monitor remote pipelines, and intelligent drilling equipment can improve productivity in mines. Although these applications are valuable, they are reminiscent of the early days of the Internet, when the new technology was limited primarily to speeding up work processes. As with the Internet, however, there is more growth, innovation and value that can be derived with smart IIoT applications.
Imagine a building management company charging fees based on the energy savings it delivers to building owners. Or an airline company rewarding its engine supplier for reduced passenger delays resulting from performance data that automatically schedules maintenance and orders spare parts while a plane is still in flight. These are the kinds of product-service hybrid models that can provide new value to customers.
This transformation in business will also have dramatic implications for the workforce. Clearly, the Industrial Internet of Things will digitize some jobs that have, until now, resisted automation. But the vast majority of executives we surveyed believe that the IIoT will be a net creator of jobs. Perhaps more importantly, routine tasks will be replaced by more engaging work, as technology allows workers to do more. As the focus shifts from products to customers, knowledge-intensive work will be required to handle exceptions and tailor solutions. Virtual teams will be able to collaborate, creating and experimenting in more spontaneous and responsive environments.
The transformation in business models draws a parallel with those sparked by the emergence of electricity. It took decades to move from lighting streets to creating the electric conveyer belt. The mass assembly line soon became commonplace, requiring an entirely new set of skills, management approaches and factory design. The U.S. was the first country to seize that opportunity and create an economy-wide impact with electricity. That helped the nation develop and lead subsequent innovations that became entirely new sectors: Domestic appliances, the semiconductor industry, software and the Internet itself.
Similarly, those countries and companies that adapt fastest to the IIoT will gain a significant first-mover advantage. To get there, we would suggest they address three broad challenges:
Capitalize on the value of data. Decide what data to use and what to share with partners who can add value to it. That means establishing iinteroperability and security standards. But it also requires new financial models that support pay-per-use and other service-based offerings, while appropriately apportioning the rewards of using shared data.
Prepare for the future of work. Adapt to more decentralized working environments as better access to data devolves decision-making to workers on the front line. For example, dealers of industrial equipment will be expected to preempt maintenance issues or offer fleet-management services to customers. Read more at Recode
Read this case study to see how Aria helps companies monetize new connected services and get them to market faster.