Previewing “The Future Is Smart”: Siemens Leads Way In IoT Transformation

Huzzah!

On August 7th, HarperCollins’ new Leadership imprint (formerly Amacom) will publish The Future Is Smart, my guide to IoT strategy for businesses and the general public.  BTW: write me if you’d like to arrange a speaking engagement/book signing event!

As part of the build-up to the release, here’s another excerpt from the book, drawn from Chapter 5: “Siemens and GE:Old War Horses Leading the IoT Revolution.” It zeroes in on these two industrial companies from the 19th (!!) century that are arguably among the top IoT companies in the world (although, sadly, GE’s transformation, which I’ll detail in the next excerpt, has not resulted — so far — in a return to its former profitability). I highlighted these two companies in part to give comfort to old-line manufacturers that have been reluctant to embrace the IoT, and in part to shame them: if they can do it, why can’t you?

Siemens is a particularly exciting example, applying IoT thinking and technology to gain a competitive edge in the railroad business, which it has been involved in since the 19th century, and because its Amberg “Factory of the Future” is the epitome of the benefits of applying the IoT to manufacturing,  The excerpt is long, but I think the details on Siemens’ IoT transformation will make it worthwhile reading.

 


For all their (referring to Siemens and GE) own distinctive products and services, there are startling parallels between the two that are relevant to this book, particularly for readers whose companies have been unaware of the IoT or are modestly testing the waters. Both Siemens and GE have fully committed to the IoT and are radically reinventing themselves, their products, and their services. 

At the same time, they are not abandoning the physical for the digital: they still make products such as trains (NB: since this book went to press, GE announced it will quit to locomotive business as it struggles to regain momentum) and large medical diagnostic devices that remain necessary in the new economy, and those devices (as well as the new software lines) are used by many other companies in their own manufacturing. Both companies aren’t just testing the IoT: they are on the bleeding edge of innovation in terms of both IoT technology and services.

Siemens and GE embody most of the marks of the IoT company outlined in the first chapter:

  • Unprecedented assembly-line precision and product quality
  • Drastically lower maintenance costs and product failure
  • Increased customer delight and loyalty
  • Improved decision-making
  • Creating new business models and revenue streams

And, while they haven’t formally addressed the sixth IoT hallmark, the circular management organization, both companies exhibit management characteristics consistent with it.

Bottom-line: if these two relics of the early Industrial Age can make the IoT transformation, why can’t you?

(Siemens’) innovations in industrial automation are now associated with the concept of the digital factory. “Siemens set the course for the digital automation of entire production facilities as far back as 1996, when the launch of its Totally Integrated Automation (TIA) Portal enabled companies to coordinate elements of their production operations and to closely intermesh hardware with software.”

Siemens has benefited in recent years from the German government’s formal strategy for what it calls “Industrie 4.0,” to merge physical products with digital controls and communications. The initiative is supported by funding from the German Federal Ministry of Education and Research and the German Federal Ministry of Economic Affairs and Energy and emphasizes the merger of the digital and physical in manufacturing through cyber-physical control systems. Because the U.S. federal government doesn’t weigh in on specific economic plans to the same extent, the concept is more advanced in Europe, and the term has gathered cachet, especially as specific examples have proved profitable.

Factory of the Future:
The shining example of Industrie 4.0 is the previously mentioned Siemens plant in Amberg. It has increasingly computerized over the past 25 twenty-five years, and now is a laboratory for fusion of the physical and digital.

The plant’s 99.99885 percent quality rate would be astounding by any measure, but is even more incredible when you realize that it does not do daily repetitions of the same mass-production product run. Instead, Amberg is where the company makes the Simatic programmable logic controls (PLCs) .. that are the heart of its industrial output and which are used worldwide to allow Machine-to-Machine (M2M) automated assembly line self-regulation. They are made in more than a thousand variations for 60,000 customers worldwide, requiring frequent readjustments of the production line. In one of the ultimate examples of eating your own dog food, a thousand Simatic units are used to control the assembly line. Total output at the factory is 12 million yearly, or approximately one per second.

One downside of the Amberg system’s efficiency is that automation has nearly eliminated assembly line jobs: the only time humans touch one of the products is to put the initial circuit board on the assembly line. The 1,100-person workforce deals almost entirely with computer issues and overall supervision of the assembly line. Nevertheless, Siemens doesn’t visualize a totally automated, workerless factory in the future:

“We’re not planning to create a workerless factory,” says [Plant Manager Professor Karl-Heinz] Büttner. After all, the machines themselves might be efficient, but they don’t come up with ideas for improving the system. Büttner adds that the employees’ suggested improvements account for 40 percent of annual productivity increases. The remaining 60 percent is a result of infrastructure investments, such as the purchase of new assembly lines and the innovative improvement of logistics equipment. The basic idea here, says Büttner, is that “employees are much better than management at determining what works or doesn’t work in daily operation and how processes can be optimized.” In 2013 the [plant] adopted 13,000 of these ideas and rewarded employees with payments totaling around €1 million.

As Siemens develops new IIoT software, it is deployed at the Amberg factory to control the Simatic control units, which generate more than 50 million data points daily for analysis. Among other programs, the factory runs the NX and Teamcenter project lifecycle management software, allowing the staff to share realtime insights on the assembly line and fine-tune its operation.

Siemens’s strategy of merging the physical and digital has meant that its software offerings constantly expand, and they facilitate the kind of real and virtual collaborative workstyles that will be discussed at length in Chapter 8. Among others, they include offerings that specifically address key aspects of the IoT:

  • Product Lifecycle Management software programs, which let engineers both model new products and extensively test them virtually, without having to build and test physical models. This both cuts costs and allows more experimentation with “what if” variations on a design, because the risk of creating alternatives is so low. As we will see later, products designed with PLM can reach the market 50 percent faster. One particularly interesting part of the PLM offerings is one specifically for additive manufacturing (i.e., 3-D printing), to capitalize on this emerging option. Siemens has brought all of these programs together under the Teamcenter label, emphasizing that it provides an “open framework for interoperability,” a critical example of the “share the data” Essential Truth discussed in Chapter 2, allowing anyone who needs it companywide to access critical realtime data.
  • Digital Twins used in coordination with PLM, discussed earlier (Chapter 4) as the highest manifestation of the digital/physical synthesis, allow rigorous testing of products before they are launched.
  • Perhaps the most important of these software offerings for full realization of the Industrie 4.0 vision is the new combination of Siemens XHQ Operations Intelligence Software with the open-systems Siemens MindSphere cloud that adds advanced analytics and machine learning. Also, because it is cloud-based, the XHQ data can be ported to other cloud-based applications. If your company is considering an IoT initiative, the cloud-based alternative not only can save money compared to self-storage, but also opens the opportunity for using cloud-based Software as a Service (SaaS).

 

Railigent

Fittingly, some of the most dramatic examples of Siemens’s IoT thinking in action have centered on one of its oldest lines of business: those electric trains invented in the nineteenth century.  The company’s Railigent system (which connects to its IoT Mindsphere platform) can:

  • cut rail systems’ operating costs by up to 10%
  • deliver eye-popping on-time performance (only 1 of 2,300 trains was late!)
  • and assure 99% availability through predictive maintenance.

Its new Mobility Services have taken over maintenance for more than fifty rail and transit programs.

Again, the company’s years of experience building and operating trains pays off in the cyberworld. Dr. Sebastian Schoning, ceo of Siemens’s client Gehring Technologies, which manufactures precision honing tools, told me that it was easier to sell Siemens’s digital services to his own client base because so much of the products they already own include Siemens devices, giving his customers confidence in the new offerings.

The key to Siemens’s Mobility Services is Sinalytics, its platform architecture for data analysis not just for rail, but also for industries ranging from medical equipment to windfarms. More than 300,000 devices currently feed realtime data to the platform. Sinalytics capitalizes on the data for multiple uses, including connectivity, data integration, analytics, and the all-important cyber security. They call the result not Big Data, but Smart Data. The platform also allows merging the data with data from sources such as weather forecasts which, in combination, can let clients optimize operating efficiency on a real-time M2M basis.

Elements of an IoT system on the trains that can be adapted to other physical products include:

  • Sensing. There are sensors on the engines and gearboxes. Vibration sensors on microphones measure noises from bearings in commuter trains. They can even measure how engine oil is aging, so it can be changed when really needed, rather than on an arbitrary schedule, a key predictive maintenance advantage.
  • Algorithms: These make sense of the data and act on it. They read out patterns, record deviations, and compare them with train control systems or with vehicles of the same type.
  • Predictive Maintenance: This replaces scheduled maintenance, dramatically reducing downtime and catastrophic failure. For example: “There’s a warning in one of the windows (of the control center display): engine temperature unusual. ‘We need to analyze the situation in greater depth to know what to do next—we call it root cause analysis,’ (says) Vice-President for Customer Support Herbert Padinger. ‘We look at its history and draw on comparative data from the fleet as a whole.’ Clicking on the message opens a chart showing changes in temperature during the past three months. The increased heat is gradually traced to a signal assembly. The Siemens experts talk with the customer to establish how urgent the need for action is, and then take the most appropriate steps.”8 Padinger says that temperature and vibration analyses from the critical gearboxes gives Siemens at least three days advance notice of a breakdown—plenty of time for maintenance or replacement. Predictive maintenance is now the norm for 70 to 80 percent of Siemens’s repairs.
  • Security: This is especially important given all of the miles of track and large crowds on station platforms. It includes video-based train dispatch and platform surveillance using Siemens’s SITRAIL D system, as well as cameras in the trains. The protections have to run the gamut from physical attacks to cyber-attacks. For security, the data is shared by digital radio, not networks that are also shared by consumers.

When operations of physical objects are digitized, it allows seamlessly integrating emerging digital technologies into the services—making these huge engines showcases for the newest technologies. For example, Siemens Digital Services also included augmented reality (so repair personnel can see manuals on heads-up displays), social collaboration platforms, and—perhaps most important—3-D printing-based additive manufacturing, so that replacement parts can be delivered with unprecedented speed. 3-D printing also allows a dramatic reduction in parts inventories, It allows for replacement of parts that may no longer be available through conventional parts depots. It may even improve on the original part’s function and durability, based on practical experience gained from observing the parts in use. For example, it’s often possible with 3-D printed replacement parts to consolidate three or four separate components into a single one, strengthening and simplifying it. Siemens has used 3-D printing for the past last three years, and it lets them assure customers that they will have replacement parts for the locomotive’s entire lifespan, which can exceed thirty years.

The new Mobility Services approach’s results are dramatic:

  • None of the Velaro trains that Siemens maintains for several operators have broken down since implementing Sinalytics. Among those in Spain only one has left more than fifteen minutes behind time in 2,300 trips: a 0.0004 percent lateness rate.
  • Reliability for London’s West Coast Mainline is 99.7 percent.
  • Perhaps most impressive because of the extreme cold conditions it must endure, the reliability rate for the Velaro service in Russia is 99.9 percent.11

Siemens’s ultimate goal is higher: what the company calls (pardon the pun) 100 percent Railability.

When it does reach those previously inconceivable quality benchmarks, Siemens predicts that, as the software and sensors evolve, the next stage will be new business models in which billing will be determined by guaranteeing customers availability and performance. The manufacturing industry is now at the stage where the automation of complete workflows is the only way to ensure a long-term, defendable, competitive position.

Siemens emphasizes that it’s not enough to simply digitize the design process. Everything from design through supply chain, manufacturing, distribution, and service must be linked in a continuous digital web, with “complete digital representation of the entire physical value chain is the ultimate goal.”

 

The fact that Siemens doesn’t just sell these IoT services but makes their own manufacturing the laboratory to develop and test them is an incredible testimonial to the IoT’s transformative potential in every aspect of companies’ operations. So, as I asked above, why are you holding back? Like to think that The Future Is Smart will give you the manual you need to make the transition (why wait for August  7, when you can preorder today?).

Live Blogging #LlveWorx ’18, Day 2

Aiden Quilligan, Accenture Industry X.0, on AI:

  • Mindset and AI: must undo what Hollywood has done on this over years, pose it as human vs. machine.
  • We think it should be human PLUS machine.
  • he’s never seen anything move as fast as AI, especially in robotics
  • now, co-bots that work along side us
  • exoskeletons
  • what do we mean by AI?  Machine learning.  AI is range of technologies that can learn and then act. AI is the “new work colleague” we need to learn to get along with.
  • predictions: will generate #2.9 trillion in biz value and recover 6.2 billion hours of worker productivity in 2021.
  • myths:
    • 1) robots evil, coming for us: nothing inherently anti-human in them.
    • 2) will take our jobs. Element of truth in terms of repetitive, boring work that will be replaced. They will fill in for retiring workers. Some new industries created by them.  Believe there will be net creation of jobs.
    • 3) current approaches will still work.

6 steps to the Monetization of IoT, Terry Hughes:

  • Digital native companies (Uber) vs. digitally transforming companies
  • also companies such as Kodak that didn’t transform at all (vs. Fujifilm, which has transformed).
  • Forbes: 84% of companies have failed with at least one transformation program.  Each time you fail you lose 1/2 billion
  • steps:
    • 1) devices with potential
    • 2) cloud network communication
    • 3) software distribution
    • 4) partner and provider ecosystem
    • 5) create a marketplace.
    • 6) monetization of assets.
  • crazy example of software company that still ships packages rather than just download because of initial cost in new delivery system
  • 3 big software challenges for digitally transforming company
    • fragmented silos of software by product, business unit & software
    • messy and complex distribution channels
    • often no link between software and the hardware that it relates to
  • importance of an ecosystem
    • Blackberry example of one that didn’t have the ecosystem
  • 3rd parties will innovate and add value around a manufacturer’s core products
  • in IoT it’s a land grab for mindshare of 3rd-party innovators.
  • need strong developer program
  • tools for app development and integration
  • ease of building and publishing apps
  • path to discovery and revenue for developer
  • IDC: developer ecosystem allow enterprises to massively scale distribution
  • digitally native companies have totally different models (will get details later…)
  • hybrids:
    • GE Healthcare:  working with Gallus BioPharma
    • Heidelberg & Eig have digital biz model for folding carton printing. Pay per use
  • Ford is heading for mobility as a transformation

 


Bernard Marr: Why IoT, Combined With AI and Big Data, Fuels 4th Industrial Revolution

 

  • connecting everything in house to Internet
  • Spotify: their vision is they understand us better. Can correlate your activity on Apple Watch (such as spinning) & create a play list based on that)
  • FitBit: the photo will estimate your calorie content.
  • John Deere
  • ShotSpotter: the company that monitors gun shots
  • understanding customers & markets better than before:
    • Facebook: better at face recognition than we are. They can predict your IQ, your relationship status.
  • Lot of frightening, IMHO, examples of AI analyzing individuals and responding without consideration of ethics and privacy
  • 3) improving operations and efficiency:
    • self-driving boats
    • drones
    • medicine through Watson

panel on IoT:

  • Don’t be afraid of the cloud
  • Ryan Cahalane, Colfax: prepare for big, start small and move fast. They had remarkable growth with switch to IoT.  Not a digital strategy, but digital in everything they do. Have “connected welders,” for example.
  • Justin Hester, Hirotec: most importatnt strategic digital transformation decision your organization can make is the selection of a platform. The platform is the underlying digital thread that enables your team to meet  the unique and chanding needs of your organization and to scale those solutions rapidly. “Assisted reality” in ThingWorx
  • Shane O’Callahan, TSM (Ireland):  Make industrial automation equipment for manufacturing. Understanding your key value driver is where to start. Then start samll, scale fast and get a win!

Jeffrey Miller, PTC: Digital Transformation:

  • if you start with digital strategy you’re starting in wrong place Start with business strategy. 
  • Couple with innovation vision merged with digital strategy. Add business use cases.
  • Jobs: it’s not how much you spend on R & D, but “about the people you have, you you’re dled, and how much you get it”
  • create an environment for innovation
    • do we encourage experimentation?
    • is it ok to fail
  • identify digital technologies to provide the required operating capabilities:
    • have we conducted proofs of concept?
    • experimented, tested  and validated?
    • reviewed use cases & success studies?
    • delivered small, important, scalable successes?

Matt,  PTC: Bringing Business Value to AR:

  • augmented service guidance
  • remote expert guidance
  • manufacturing: machine setup and turnover, assembly and process
  • example of Bell & Howell towers to store online sales in WalMart stores for customer pickup: very expensive to send one to a store for salesperson to use in sales — now just use AR app to give realistic demo without expense.
  • service: poor documentation organization, wants accurate, relevant, onsite info for technician. Want to remove return visits because the repair wasn’t done 1st time, or there’s a new technician. Manuals in binders, etc. Instead, with AR, requirements are quick access to current info. Finally, a demo.

Suchitra Bose, Accenture: Manufacturing IIoT, Driving the Speed of Digital Manufacturing:

  • convergence of IT and OT
  • expanding digital footprint across your entire factory
  • PTC has wide range of case studies (“use cases” in biz speak…) on aspects of IoT & manufacturing.

I have seen the future, and it’s written in Chalk (PTC’s Vuforia Chalk, that is!)

I just had to take time out from my live blogging of PTC’s LiveWorx ’18 to focus on one of the topics Jim Heppelmann mentioned in passing in his keynote: the new variation on the company’s Vuforia AR app: Chalk.

Significant in its own right, I suspect Chalk will have an additional, critical impact: democratizing AR.

It is an app aimed at, and accessible to, both corporate audiences AND the general public.  Downloadable for both iPhone & iPads & Android devices, I suspect that it will quickly become popular both to support remote repair staff for companies and just plain folks who are trying, for example to help a family member far away to deal with a car or plumbing repair. Not to mention the fact (mandatory disclaimer: while I work part-time for Apple, I’m not privy to any corporate internal strategy) that the spiffy new $329 6th-generation iPad really facilitates AR, and Chalk was developed in conjunction with the Apple ARKit technology so it should really become popular.

Chalk has two components:

  • real-time video and voice sharing of the same view
  • Chalk Marks, simple handswipes that allow one of the participants to highlight the part that is the subject of the question.  The “Marks” appear to be anchored to the subjects they’re “drawn” on.

Real-world uses vary from a remote super-expert helping a field technician to identify and deal with a rare problem to your millennial helping Mom master her personal technology. I saw an amazing demo this morning with one mechanic in Germany (ok, he was actually 2′ away…) directing the mechanic working on a Mercedes how to add coolant.  As the press release announcing the app said:

“Today, remote assistance can be frustrating and cumbersome. People struggle for words to describe things that are unfamiliar, whether it be a new appliance or the back of a cable box. And when the problem can’t be described clearly, it becomes almost impossible for someone else to solve. Vuforia Chalk provides a simple and intuitive solution where people can now use Chalk Marks to get a common understanding of a problem, and the steps required to solve it.”

I’ve written before that I suspected many companies got into e-commerce in the 9o’s because a CEO’s kids got him to order a book from Amazon during the holidays & he came back raving about this new device.  I can’t help thinking that this will be just the kind of low-cost (heck, in this case, no-cost) introduction to AR And the IoT that will break down some companies’ skepticism, pay off with immediate bottom line benefits in cost savings and efficiency in service operations, and get them interested in most expensive AR such as PTC’s digital twins and predictive maintenance.  Or, as ABI analyst Eric Abbruzzes said:

“Mainstream augmented reality is at the beginning of a strong positive inflection point, and Vuforia Chalk is a great example of how AR can transition from enterprise-only to use in everyday life,” said Eric Abbruzzese, ABI Research. “We see Vuforia Chalk as a fundamentally disruptive form of remote communication that will be well received across multiple sectors and for multiple use cases.”

Now to get my granddaughter to download the app so we can collaborate on the 3D-printer that I got her for her 12th- birthday!

Wahoo! Liveblogging #Liveworx ’18!

Always my fav event, I’ll be liveblogging #LiveWorx ’18.  Stay tuned!

Keynote: Jim Heppelmann:

  • “from a place to a pace” — how fast are we moving?
  • no longer OK to think of a future destination, builds inertia (“your main competitor”). Disruption may have already happened. Hard to sustain advantage due to pace of change. Must “embrace a pace of change”
  • Um, this sounds like argument for my circular company paradigm shift!!!
  • Customer Experience Center will occupy top floor of new building.
  • combo of  physical, human and digital — transforming all at once speeds change:
    • physical: been constrained by subtractive manufacturing, while nature improves via cell division (i.e., additive). “Adopt Mother Nature’s mindset.” — new additive aspects of Creo. Example of Triumph cycle sing-arm using additive. CREO uses AI to optimize performance: non-symmetrical design. Still need to use simulation tests: new intermittent, continuous style: they are doing new partnership with ANSYS (product simulation software), unified modeling and simulation with no gaps. Historically, simulation only used at end of design cycle, now can use it throughout the process: “pervasive simulation.”
      • ANSYS “Discovery Live”: optimizes for real-time. Integrates with Creo — instant feedback on new designs. “simulation critical to innovation.”
    • digital: working with Microsoft Azure (Rodney Clark, Microsoft IoT VP). Microsoft investing $5b in IoT.  1st collaboration is an industrial welder: IoT data optimizes productivity.  BAE can train new employees 30-40% quicker.
    • finally, human: “Mother Nature designed ups to interface with the physical. How do we integrate with the digital? — Siri, Alexa, Cortna still too slow.  Sight is our best bet. “Need direct pipeline to reality ” — that’s AR. “Smart, connected humans.” Sysmex: for medical lab analysis. Hospitals need real-time access to blood cell analysis. They have real-time calibration of analysis equipment. Also improving knowledge of the support techs, using AR and digital twins when repairs are needed.
      • Will help 2.5 billion workers become more productive
      • AR can project how a process is being programmed (gotta see this one. will try to get video).
      • All of their human/digital interface initiatives united under Vuforia. Already have 10,000 enterprises using it.
    • Factories are a new focus of PTC. 200 companies now using it in 800 factories. Examples from Woodward & Colfax.  Big savings on new employee training.

Keynote: Prof. Linda Hill, HBS, “Collective Genius”:

  • Innovation= novel + useful
  • Example of Pixar: collective genius “filmmaking is a team sport.”
  • 3 characteristics of creative organizations they looked at:
    • “creative abrasion” — diversity and debate
    • “creative agility” — quickly test the idea & get feedback. Experiment rather than run pilots, which often include politics
    • “creative resolution” — ability to make integrative decisions. Don’t necessarily defer to the experts.
    • sense of community and shared purpose.
  • values: bold ambition, collaboration, responsibility, learning.
  • rules of engagement: respect, trust, influence, see the whole, question everything, be data-driven.

Ray Miciek, Aquitas Solutions. Getting Started on IoT-based Maintenance:

  • his company specializes in asset maintenance.
  • “produce products with assets that never fail”
  • 82% of all asset failures are random, because they are more IT-related now
  • find someplace in org. where you could gain info to avoid failure.
  • Can start small, then quickly expand.

 

Previewing “The Future Is Smart”: 1) Collective Blindness and the IoT

This is the first of an occasional series of posts preceding the August 1st publication of The Future Is Smart. The book will introduce the Internet of Things to business audiences and help them create affordable, profitable strategies to revolutionize their products, services, and even their very way of doing business through the IoT.  Each post will excerpt part of the book, giving you enough detail to be informative, but not — LOL — complete enough that you’ll be able to skip buying the book itself!

The critical point the book makes about revising your products and services to capitalize on the IoT is that it’s not enough to simply install sensors and beef up your data analysis: equally important are fundamental attitudinal shifts to break free from the limits of past technology and realize the IoT’s full capability.

A critical component is what I call “Collective Blindness,” a way of describing how limited we were in understanding how products actually ran in the era when we had almost no data about their operations, let alone real-time data that we (or other machines, through M2M controls) could act on instantly to create feedback loops and improve operating precision and facilitate upgrades.

Let me know what you think (after an horrific hack, I’ve decided to scrap comments on the blog — if I think it’s merited, I’ll feature your feedback in future posts)!


Technologist Jeffrey Conklin has written of “wicked problems” that are so complex they aren’t even known or detailed until solutions to them are found.

What if there had been a wicked problem, a universal human malady that we’ll call “Collective Blindness,” whose symptoms were that we humans simply could not see much of what was happening in the material world? We could only see the surface of these things, while their interiors and actual operations were impenetrable to us. For millennia we just came up with coping mechanisms to work around the problem of not being able to peer inside things, which we accepted as reality.

Collective Blindness was a stupendous obstacle to full realization of a whole range of human and business activities. But, of course, we couldn’t quantify the problem’s impact because we weren’t even aware that it existed.

In fact, Collective Blindness has been a reality, because vast areas of our daily reality have been unknowable and we have accepted those limits as a condition of reality.

For example, in a business context:

  • We couldn’t tell when a key piece of machinery was going to fail due to metal fatigue.
  • We couldn’t tell how efficiently an assembly line was operating, or how to fully optimize its performance by having changes in one machine trigger adjustments in the next one.
  • We couldn’t tell whether or when a delivery truck would be stuck in traffic, or for how long.
  • We couldn’t tell exactly when we’d need a parts resupply shipment from a supplier. (Let’s be honest: What we’ve called “just-in-time” in the past was hopelessly inexact compared to what we’ll be able to do in the future.) Nor would the supplier know exactly when to do a new production run in order to be ready.
  • We couldn’t tell how customers actually used our products once they were in the field, or help those customers adjust operations to make them more efficient.

That’s all changing now.

The wicked problem of Collective Blindness is ending, because the Internet of Things solves it, giving us real-time information about what’s happening inside things.

The Internet of Things will affect and improve every aspect of business, because it will allow us to eliminate all of those blind spots resulting from Collective Blindness, achieve efficiency, and derive insights that were impossible before.

Cisco, which focuses not only on the IoT’s enabling technologies but also on the management issues it will address, understands the Collective Blindness concept. It refers to previously opaque and unconnected things as “dark assets,” and says that, “The challenge is to know which dark assets (unconnected things) to light up (connect) and then capture, analyze, and use the data generated to improve efficiency while working smarter.”

Vuforia “sees” inside Caterpillar device

PTC has created the most literal cure for Collective Blindness: Vuforia, an AR system that lets an operator or repair person wearing an AR headset or using a tablet to go from looking at the exterior of a Caterpillar front-end loader to “seeing” an exploded view of the system that shows each part and how they connect as well as monitoring the realtime performance data of each component, gathered by sensors on the machinery. That insight can also be shared, in real-time, by others who need it.


You may quibble with my choice of the “Collective Blindness” metaphor for the obstacles we and businesses in general, faced before the IoT, but I do think we need some sweeping description of exactly how limited we used to be because the acceptance of those limits, and our inability to “see” how things really did restrict our ability to fine-tone products and their operation — and even now may keep us from re-examining everything now that we have gained this ability. Let me know your thoughts on this — and I hope you’ll stay tuned for more excerpts from The Future Is Smart in coming months.

 

http://www.stephensonstrategies.com/">Stephenson blogs on Internet of Things Internet of Things strategy, breakthroughs and management