Industry week webinar on IIot and data visualzation
— and Profits —
Through the IIoT
August 21, 2019
W. David Stephenson
Rich will be back later to detail how Emerson helps companies realize the full potential of the Industrial Internet of Things through data visualizations
But first, I will place their services in a broader context, by giving an overview of the Industrial Internet of Things, or IIoT. As my title says, among many other benefits, the IIoT will allow you to achieve a previously impossible
degree of precision in your operations, while creating new revenue streams and cutting costs to increase your profits.
Still Not Fully
• 12% — fully deployed at least
• 14% — pilot or proof of concept
• 32% — planning or exploration
• 27% — no immediate plans
— 2019 survey
Writing this presentation reminded me that it’s important for those of us who spend our days immersed in the IIoT to step back and dispassionately examine the facts about its adoption — or lack thereof. The truth is, the IIoT is
not as far along as many of us assumed — or would like!
They show that — according to a survey discussed in a recent IndustryWeek webinar — that more than 50% of the companies surveyed either have no immediate plans regarding the IIoT or are only in the planning or exploration
phases. Only 12% have fully deployed at least one full-fledged product.
On one hand, that means that if you’re in that large group that either is ignoring the IIoT or only planning to do something with it, you’re in good company. On the other hand, for those of you who are fans of Clayton
Christiansen’s “disruptive technologies” concept, it means that you may soon find yourself at a competitive disadvantage in a totally transformed economy — if and when the IIoT does fully develop.
• tell if machine was failing
• optimize assembly lines
• predict traffic for supply chain &
• spread timely information throughout
• tell how customers used products
The reason why you may be lulled into a false sense of security and why the IIoT may be so disruptive of that current reality is that in the past we all — no exceptions! — suffered from what I call “Collective Blindness.” It was due
to the fact that there was simply no way for us to objectively gauge, in real time (real-time measurement, BTW, is a key element of the IoT) how things were working — or not.
As a result, with only fragmentary, historical evidence, which was hard to gather and equally hard to process and distribute, we were forced to build our companies, and the economy as well, on a jury-rigged combination of
hunches and work arounds. That left some staggering obstacles that reduced efficiency and precision:
• We couldn’t tell if a machine was failing in time to avoid shutdowns.
• We couldn’t optimize assembly lines, because various steps in the process were hard to coordinate
• We couldn’t optimize our supply chains and distribution plans because we had no idea what traffic problems, detours, etc., might affect deliveries
• Because it was so hard to gather data and equally hard to distribute it, it made sense for senior executives to parcel out information where and when they felt it was needed. By the time that information reached the end of the
enterprise — like the old “Telephone” parlor game, it might bear little or no resemblance to the original — and was ancient history.
• We couldn’t tell how our products were actually used once they were in the field. That meant, among other things, that we had to create “scheduled maintenance” routines that applied to all products, even though some
might need maintenance earlier and some, only late.
• Not being able to tell how products were actually used also meant we couldn’t tell whether our manuals and other documentation weren’t clear to users and led to errors, or whether some features that designers isolated in
the home office felt were important but users ignored, or something about the design that was a consistent problem for users, suggesting possible features for an upgrade. In fact, the difficulty of getting feedback could often
deceive us. For example, since customers found it so difficult to give feedback on what they liked or didn’t, those who either loved or hated the product were over-represented in comments: those in the middle who were
generally satisfied but had a suggestion to improve the product typically wouldn’t take the time and effort to contact you.
•At the heart of it is real-time, location-
•Less understood in terms of its
implications, we can share that data in
•Instead of a linear flow of data from the
executive suite that eventually ends up
at the bottom of the pyramid, it flows in
continuous circle through every part of
Fast-forward to today, and the IIoT combination of ubiquitous sensors embedded in products to collect real-time data from them, new analysis tools, and wireless Internet communications, eliminates the Collective Blindness.
It creates a totally-changed situation in which real-time, location-based data rules.
Also, as I will explain later, one of the IIoT’s most potentially dramatic opportunities for change stems from the fact that it it now possible for everyone — everyone — who needs access to real-time data to make better decisions
and do their jobs more effectively, to share — the verb is crucial — that data instantly.
Finally in terms of overall changes, instead of a linear flow of limited, historical data from the executive suite that eventually ends up at the bottom of the pyramid, it flows in a continuous circle through every part of the
Let’s examine how that affects every aspect of your operations….
•M2M automatic reorders and delivery.
•Sharing data with OEMs may improve
parts design and integration
•Could it lead to restoration of locally-
based supply chain — rather than global
— because of ready access?
As we will see, the IIoT creates the opportunity for a never-ending, cyclical relationship between all components of your industrial ecosystem. That begins with the supply chain.
Let’s face it: when we used to talk about “just-in-time” supply chains it was more like “kinda, sorta just-in-time”: there were just so many imponderables on both your end and the suppliers’ that interfered with true just-in-time.
•Now — if you choose to — you can give your suppliers real-time access to the same data about the assembly line’s status right now that you have.
•Resupply orders may be triggered on a M2M basis, without the necessity of human, manual intervention, assuring a constant flow of parts.
•Deliveries will also be scheduled automatically, and your plant will have a better idea of their actual arrival time based on real-time traffic data.
•Sharing data with OEMs may improve parts design and integration — something that I believe Rich will address.
I’m actually wondering if the predictability value of nearby suppliers who you can depend on to get parts to you in an hour or two may eventually outweigh the price advantages of suppliers half a world away who, because of
ocean shipping and other factors can’t be depended on for that kind of timing, perhaps leading to a resurgence of US-based suppliers. We’ll see!
•Real-time data from one step leads to M2M adjustment of
•Reduced down-time due to predictive maintenance
•Empower workers with low-code/no-code apps driven by
real-time data that lets them adjust processes
•“My Sepp” — instant notification of dangerous
•Nautique: objectified employee review process
•Previously impossible precision: Siemens’ “Factory of the
Future” achieves 99.9985% quality rate
Most important is how the IIoT will directly affect your factory’s operations. The benefits are many, and varied:
• Perhaps most important in a complex assembly line with components from a variety of OEMs is that with the IoT, real-time data from one step can lead to automatic M2M adjustment of following processes so that overall
• Down-time will be reduced and repair costs will be cut due to predictive maintenance.
One little-appreciated benefit will be empowering shop-floor workers with real-time data they can use to better understand assembly-line issues, boost performance, and reduce the chance of workplace accidents.
• low-code/no-code apps driven by real-time data let them create their own drag-and-drop apps, and adjust processes:
• In the Netherlands, the My Sepp” app gives workers instant notification of dangerous conditions
• Nautique, a Florida boat builder, has objectified the employee review process with a no-code app.
Most important, and hard to believe, the IIoT can help you achieve previously impossible precision: Siemens’ “Factory of the Future” is monitored and adjusted by Simatic IIoT devices that are manufactured there. Believe it or
not, the factory achieves a 99.9985% quality rate!
•Real-time traffic reports reduce
on the fly based
Like your supply chain, your distribution network is heavily dependent on local traffic conditions, which will become increasingly well-documented on a real-time basis in the near future with smart traffic lights that automatically
adjust to changing vehicle loads and which will be expedited with autonomous vehicles.
They will also benefit from the growing number of public/private “smart city” partnerships, where a wide range of initiatives, some planned collaboratively and some carried out by a single players, combine to expedite traffic
flow. Perhaps the best example to date is the Columbus, Ohio proposal that won the Obama Administration’s Smart City Challenge. It included using connected vehicle technology in the city’s freight district, including automatic
truck platooning and traffic signal management; and cooperation between the city and truckers on deploying sensors for parking availability. Nearby, the state is building a 35-mile “Smart Mobility Corridor,” with high-capacity
fiber optic cable giving researchers real-time access to data from embedded and wireless sensors to test smart transportation technologies.
I argue that one of the critical attitudinal changes necessary to get the full benefit of the IIoT is to divert some of our attention from protecting proprietary corporate data to instead asking in every case, “who else can use this
In the case of distribution, there’s a great example from SAP, which built a prototype smart vending machine. The machine collects real-time data about purchases to help marketers plan special promotions, etc. but also shares
that data with the supplier’s delivery fleet. As a result of this M2M sharing, a driver on her way to restock a certain machine on a hot summer day might find she’s been automatically rerouted to another machine located on a
beach that’s having a run on soft drinks. Cool!
•Digital twins let designers and
maintenance staff see, in real time, how
things are actually used (or misused), to
perform predictive maintenance and
discover potential features to add in
•Customers can use their phones to
program and control their smart devices
The end of “Collective Blindness” means that customers are now full partners in the enterprise, whether they are aware of it or not .
IoT products’ “digital twins” displayed on your designers’ and maintenance team’s terminals — miles from the point of use — let them see, again in real-time, how the products are actually being used. In some cases, (such as
wind farms) the remote team can actually regulate the individual products so they function more efficiently as a whole. Observing which features are used and which aren’t can give clues to possible future upgrades.
Of course, there’s also the growing ability with the IIoT of bring-your-own-device operation. One of my favorite examples was from GE’s now-closed Durathon battery factory, a paragon of the IIoT. Because precise climate control
was critical for the battery creation, one weekend night the manager used his own iPad at home to alter the HVAC settings during an extreme weather event!
• Risk Reduction
• Especially critical for remote drilling
platforms, pipelines, other remote
• Problems spotted at earliest point
• Repairs quick, minimum cost
& inconvenience to customer
One aspect of the IIoT deserves special attention because it takes something that was previously a necessary evil — maintenance — and elevates it into a critical way to improve precision and even change your business model.
The change is predictive maintenance. The old make-shift model, preventive and scheduled maintenance, is replaced by a flexible model where maintenance and repairs are dictated by the real-time status of every individual
One critical aspect is risk reduction. Think of extreme examples, such as off-shore drilling platforms, miles of pipeline or rail line in isolated areas, or jet turbines overhead. Because the IIoT allows early diagnosis of problems —
such as metal fatigue in a jet turbine — it’s now possible that a situation could be diagnosed while in the air and, due to the precision of the information, when the plane lands, far before there’s any real risk, the mechanic could
be ready with the exact replacement part, and know exactly what part of the engine the problem’s located in. The repair could be made quickly, at minimum cost and inconvenience to the customer.
But that’s not all predictive maintenance can do….
•Jet Turbine manufacturers switch to leases
•Power by the hour
•Builds customer loyalty
.. the jet turbines are a perfect example of how the IIoT can also elevate a tactical service such as maintenance into a strategic game-changer.
Because jet turbines are now so reliable — Pratt & Whitney actually packs in up to 5,000 sensors per turbine — the companies feel confident enough to switch to an entirely new business model: leasing the engines instead of
selling them, with the customer’s cost based on “power by the hour” — airlines pay for the engine only when it’s in the air, generating thrust, not when it’s sitting the the tarmac being repaired.
The companies can even create new revenue steams, offering the airlines the option of paying extra for real-time in-flight data they can mash up with atmospheric data, fuel prices, etc., to maximize operating efficiency.
An added benefit? Customers are more likely to be loyal because their needs are constantly met.
BUT, There Are
•Typical smart factory: 1 petabyte of
•2025: total IoT data 175 zettabytes,
10x 2016 level
•Latency! — Analyze at the Edge.
•Lack of data management skills.
All of these wonders come at a price, however, and that’s too much of a good thing: in this case, data. Rich will deal with this problem at length, so I’ll just touch on it.
There’s simply an excess of real-time data yielded by all those sensors:
•a typical smart factory can yield up to a petabyte if data daily
•by 2025, analysts say the total yield from all types of IoT data may reach 175 zettabytes — ten times the level generated as recently as 2016.
One critical problem this creates with the IIoT is that if you use our current technique for analyzing huge volumes of data, doing it in the cloud, you’ve created a major barrier to use of real-time data: latency. By the time you
collect the data, transmit it to the cloud, analyze it and then return it to the point of collection for use, it is now no longer real-time, and much of its benefit is gone. That’s why, as I covered in a recent IndustryWeek column, the
new IIoT trend is to process data at or near the point of collection, the Edge, for rapid use.
Equally important, most of your staff don’t have degrees in data analysis, and most of us are overwhelmed when we see extensive spread sheets, so visualization makes the key data pop.
•Speeds data use because you don’t
have to wade through spreadsheets
•Correlations that wouldn’t be seen
otherwise pop out
•Democratizes data — doesn’t require
expertise to use it
•Promotes sharing & destroying data
Ever since Dr. John Snow mapped the victims’ locations during an 1854 cholera outbreak and dramatically showed, as no data sheet ever could have, that they all got their water from a polluted well and that was the cause, smart
guys have known data visualization is a powerful, powerful tool. It is ideally suited to the over-abundance of data and fact that most staff don’t have data analysis skills:
•Speeds data use because you don’t have to wade through spreadsheets
•Correlations that wouldn’t be seen otherwise pop out
•Democratizes data — doesn’t require expertise to use it
•Promotes sharing data & destroying information silos
one more thing…..
“.. organizational issues.. now
center stage— no playbook. .. just
beginning .. process of rewriting the
organization chart …”
—Heppelman & Porter
Before I turn things over to Rich, I’d like to conclude by hopefully inspiring you with a vision of how the IoT can possibly do far more than produce all the wonderful improvements I’ve catalogued.
If I’m right, real-time data visualization will be at the heart of this change.
In the second of their articles on the IoT for the Harvard Business Review, PTC’s Jim Heppelmann and Prof. Michael Porter predicted that the changes for management with the IoT could be as dramatic as for manufacturing itself.
They speculated that “for companies grappling with the transition to the IoT, organizational issues are now center stage —and there is no playbook. We are just beginning the process of rewriting the organizational chart that has
been in place for decades.”
I believe that the new organizational chart will be one that would be impossible without the tools of the IoT, especially real-time data and data visualization. I call it…
• Increases precision, rapid response
• Breaks down information silos
• SHARE data between
all users, leading to
• Finally does away
with Industrial Age
hierarchy & linear
.. the circular company. It will be marked by:
•increased precision, and rapid response to changing conditions
•a breakdown of information silos
•sharing (that verb is critical) data, among all who need it to do their jobs and make better decisions, leading to innovation and precision
•doing away with Industrial Age hierarchy and linear processes.
I wrote about this transition in my most recent IndustryWeek column, and I hope you’ll read — and respond — to it!
W. David Stephenson
read my IndustryWeek column
and The Future is Smart,
— a guide to IoT strategy
I want to thank you very much, and turn you over to Rich Carpenter, for an in-depth exploration of the critical need for data visualization as the heart of the IIoT!