Interview | IIoT Implications for the Outcome Economy

By Grant Gerke, Contributing Editor

I recently talked to Joe Barkai, former vice president of research at IDC, Framingham, MA, and author of a new book, The Outcome Economy: How the Industrial Internet of Things is Changing Every Business. Barkai has been firmly embedded in the industrial-manufacturing arena for more than 30 yr. and has worked with many large entities, such as Caterpillar, Chrysler, Ford, Oracle, SAP, and Siemens.

>> Podcast | Visit bit.ly/mtjbarkai to listen to the entire interview

Barkai’s book outlines several  points between IIoT and manufacturing, while emphasizing the transformative process that is taking place with regard to business models. Barkai sees enterprises and businesses moving to an “outcome economy,” in which companies will “create value not just by selling products and services (using IIoT), but by delivering complete solutions that produce meaningful ‘quantifiable business outcomes’ for customers.”

Below is a portion of our interview, which touches on predictive analytics and how third-party IIoT should evolve. The entire interview, found at bit.ly/mtjbarka, discusses how management may be more receptive to a longer ROI for IIoT projects and why. 

Maintenance Technology: While doing research for the book, what surprises did you encounter with regard to predictive analytics?

Joe Barkai: The predicted-maintenance story is really kind of the holy grail of Industrial Internet of Things (IIoT). Every company investing in IIoT really wants to be able to monitor mission-critical equipment remotely, be notified about impending failure, and given enough detail and ample time to respond to the problem. 

But I was surprised, not by their aspirations but about the optimism that these companies have in regard to the ability to implement those systems in a fashion that is kind of sufficiently robust, scalable, and economic.

However, many companies are really not aware of the difficulty of taking some of these concepts that are very solid. That’s not to say there are no solid examples. Siemens, AG, and the Renfe high-speed rail in Spain is one example that I cite in the book. There are a lot of interesting and economically relevant implementations, but people I think underestimate the effort that it takes to create that level of predictive models and systems.

MT: Do you sense that third-party, predictive-analytic services are ready to emerge due to maintenance-department consolidation within manufacturing?

Barkai: So, let’s say 20 years ago third-party maintenance was a big, big industry to augment workforce, to optimize resources, and so on. I think that we will see some of this coming back, but with IIoT we’ll have new challenges. One of them is the immediate access to equipment and security, which raises concerns about IP linkage.

I’m personally not very concerned about it, but it is a real concern for some companies. So, companies will be somewhat reluctant and will not easily give away access to their equipment.

Another element of this—almost the other side of the coin—IIoT isn’t really about monitoring or even prediction, per se. It’s really about the ability to create new business models—outcome economy. IIoT becomes a platform to offer those business services. The most cited story in the book, of course, is Rolls Royce in “Power by the Hour,” but you’ll see this with Pratt & Whitney, Siemens, and the Spanish Rail.

The point here is not only companies outsourcing to a third party, but trying to outsource the ability to deliver service. The third-party model will be different.

>> Podcast | Visit  bit.ly/mtjbarkai to listen to the entire interview

Grant Gerke is a business writer and content marketer in the manufacturing, power, and renewable-energy space. He has 15 years of experience covering the industrial and field-automation areas.

Visit maintenancetechnology.com/iot and find podcasts, white papers, and video content on all things IIoT for the reliability and maintenance professional.