Industryweek 34636 Sharing Data

Ask: Who Else Can Use This Data?

April 8, 2019
The attitudinal shift vital to full IIoT transformation

Remember the stories—apocryphal or not—about executives in the 1990s who heard about some new technology called “email,” and told their assistants to sign them up?  Each morning, right where the old memos had been, was a crisp pile of e-mail for them to read and dictate a reply. 

Moral of the story? You can adopt new technologies, but if you cram them into an obsolete mindset, you’ll never get their full benefit.

Fast forward to today, and the equivalent might be the Industrial Internet of Things (IIoT), which has the potential to revolutionize every aspect of your products and operations—but can’t, if you don’t make equally sweeping attitudinal shifts to bring your policies into line with the new potential.

That potential for change with the IIoT comes from the fact that we no longer must depend on fragmentary, after-the-fact data about how things (whether those things be assembly-line machinery, cows in a pasture, or our bodies) work, to make decisions about future design modifications, optimizing assembly lines, and/or maintenance.  Instead, the IIoT’s combination of sensors on these things, instant data communication, and advanced analytics, mean that what I call the “Collective Blindness” of the past (caused by our inability to monitor them instantly) is lifted and we really know about things’ status right now.

In this case, the potential for change results not just from that monitoring ability but from the new-found ability for everyone who needs real-time data to make better decisions or do their job more precisely to share (as you’ll see, the verb is crucial!) that information instantly.

The obstacle is that since the birth of the Industrial Revolution, we’ve evolved management structures to cope with the old lack of information, which can block the new capability to share data.  Because it was so hard to gather data—and equally hard to communicate it in the past—hierarchy and linear data transmission made sense: senior management would determine who had access to what, and would parcel it out accordingly.

Because of the resulting data silos, by the time the data reached the last functional group, it was hopelessly corrupted and/or so old it had no value.  Worst of all, almost none of the data would reach those who could benefit the most: assembly line workers who could apply it to fine-tuning operations (see my last column).

Part of the difficulty in abandoning the old hierarchical and linear distribution of data is the fact that central control of data conferred a strategic advantage: if I had data and you didn’t, I was a winner and you were a loser. That accounted for the old U.K. laws making it a crime to take the plans for one of the early woolen mills out of the country, because it gave the country a strategic advantage. The same thinking persisted until the recent past: in Boston in the 1980s, we enjoyed the tech revolution/economic expansion known as the Massachusetts Miracle, with mini-computer firms such as DEC and Prime profiting because their proprietary operating systems made their customers dependent on them—until, of course, open-source software was widely adopted.

Equally important, with various parts of the company operating in isolation from each other, refinements that might have resulted from up-front data sharing were impossible. I’m reminded of a story from the ‘70s, in which a car design team came up with a slick new model that went into production and sales without a hitch—until, that is, the first buyer went in for his first routine oil change. The mechanic scooted under the car and quickly scooted out: the $30 oil change would instead cost several hundred dollars, because the engine would have to be dropped to access the oil drain plug. The design team hadn’t included a field mechanic who would have spotted that problem instantly!

Today, senior management must make a very painful shift, away from centralized control of data controlled by them, to the real-time sharing mentioned above, if they want to enjoy the IIoT’s full benefits. Let’s not underestimate how difficult that will be. Empowering subordinates means losing some of your own power, but the results will more than justify the sacrifice, so your most fundamental attitude change must be to start automatically asking a previously unimaginable question: Who else can use this data? 

If you’re doing it right, this will be an uncomfortable, challenging process, because it will probably lead to decisions that will rob you of at least some of the personal power and control you have enjoyed in the past.  The reward? New potential for operating efficiency, precision and unleashing creativity that is only possible when you use the IIoT to empower others with different experiences, skills and perspective, and work simultaneously with the data that affects all of your roles.

These examples will show you the benefits of instantly sharing, rather than hoarding, that new real-time data:

Design: THINGK’s Slab, a smart kitchen scale/digital timer, was substantially improved by the Italian product development company’s decision to give users contributing to its crowdfunding campaign the opportunity to participate directly in the design process.  That let the design team have an upfront reality test of how the design might (or might not!) work in the hands of people with different needs, attitudes, and backgrounds.  As a result, what was originally conceived as two separate devices was merged into one.

Manufacturing: Workers at an auto assembly plant couldn’t determine why paint applied later in the day didn’t dry as well. Through their industrial IoT platform by Telit called deviceWISE, they were able to connect up to 50 different systems, from power sourcing equipment (PSEs) to robot controllers, as well as monitors throughout the assembly line. As a result, the workers discovered that there was a small temperature rise between the first and second shifts because of heat generated by the robots—so little that the workers didn’t notice it, but enough so the paint didn’t dry.  Adjusting the AC level and power units based on the data eliminated the issue.

Maintenance: Thyssenkrupp repair personnel use a combination of Microsoft’s Azure suite, and Microsoft’s HoloLens “mixed reality” headset so they can work hands-free without having to refer to a printed manual while simultaneously conferring with more experienced technicians located at other sites. Combined with sensors that detect possible problems in their earliest stages, the technicians can order parts and do predictive maintenance that is quicker, cheaper, and reduces service interruptions.

Supply Chain: if you really want to improve your overall efficiency and precision, when you ask “Who else can use this data?” you should really include your supply chain — companies and people who you can only control indirectly, making it more risky to give them proprietary information they couldn’t access in the past. However, Wisconsin-based crane manufacturer Manitowoc has benefited from letting go: according to a recent webinar presentation the company gave, it runs all its processes on a single, unified platform that integrates with legacy systems, sharing information and collaborating with suppliers in real time on order confirmation, shipment notifications and invoice process.

Marketing: in a great example of asking “who else can use this data?” smart home device manufacturers are increasing sales by supplying their Application Programming Interfaces (APIs) to sites such as IFTTT (If This Then That). The site creates clever algorithms (intentionally named “recipes” to entice amateur device owners with no coding background). The device owners can then combine the APIs so that the same command (“hey Siri, it’s time for bed”) can simultaneously make, for example, the Schlage lock close, the Ecobee thermostat go down, and the Philips Hue lights go black. Three products, three companies, and they all become more valuable and salable by sharing data.

Adding IIoT technologies such as digital twins are critical, but so is attitudinal change if you are to realize the full benefits of applying real-time data throughout your enterprise. Begin today to ask: who else can use this data?  Trust me, someday it will become automatic,.

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