GE & IBM make it official: IoT is here & now & you ignore it at your own risk!

Pardon my absence while doing the annual IRS dance.

While I was preoccupied, GE and IBM put the last nail in the coffin of those who are waiting to launch IoT initiatives and revise their strategy until the Internet of Things is more ….. (supply your favorite dismissive wishy-washy adjective here).

It’s official: the IoT is here, substantive, and profitable.

Deal with it.

To wit:

The two blue-chips’ moves were decisive and unambiguous. If you aren’t following suit, you’re in trouble.

The companies accompanied these bold strategic moves with targeted ones that illustrate how they plan to transform their companies and services based on the IoT and related technologies such as 3-D printing and Big Data:

  • GE, which has become a leader in 3-D printing, announced its first FAA-approved 3-D jet engine part, housing a jet’s compressor inlet temperature sensor. Sensors and 3-D printing: a killer combination.
  • IBM, commercializing its gee-whiz Watson big data processing system, launched Watson Health in conjunction with Apple and Johnson & Johnson, calling it “our moonshot” in health care, hoping to transform the industry.  Chair Ginny Rometty said that:

“The Watson Health Cloud platform will ‘enable secure access to individualized insights and a more complete picture of the many factors that can affect people’s health,’ IBM says each person generates one million gigabytes of health-related data across his or her lifetime, the equivalent of more than 300 million books.”

There can no longer be any doubt that the Internet of Things is a here-and-now reality. What is your company doing to catch up to the leaders and share in the benefits?

 

Deloitte’s IoT “Information Value Loop”: critical attitudinal shift

Ever so often it’s good to step back from the day-to-day minutia of current Internet of Things projects, and get some perspective on the long-term prospects and challenges.

That’s what Deloitte did last December, when it held an “Internet of Things Grand Challenge Workshop,” with a focus on the all-important “forging the path to revenue generation.”

The attendees included two of my idols: John Seely Brown and John Hagel, of Deloitte’s “Center for the Edge” (love the pun in that title!).

The results were recently released, and bear close examination, especially the concept of how to foster what they call the “Information Value Loop”:

Deloitte IoT Information Value Loop

Deloitte IoT Information Value Loop

“The underlying asset that the IoT creates and exploits is information, yet we lack a well- developed, practical guide to understand how information creates value and how companies can effectively capture value. The ‘Information Value Loop’ describes how information creates value, how to increase that value, and how understanding the relevant technology is central to positioning an organization to capture value. The Information Value Loop is one way to begin making sense of the changes we face. The Loop consists of three interconnected elements: stages, value drivers, and technologies. Where the stages and value drivers are general principles defining if and how information creates value under any circumstances, it is the specifics of today’s technology that connect the Loop to the challenges and opportunities created by the IoT.”

This fits nicely with one of my IoT Esssential Truths,” that we need to turn linear information flows into cyclical ones to fully capitalize on the IoT.  No pussy-footin’ about this for these guys: “For information to create any value at all, it must pass through all the stages of the Loop. This is a binary outcome: should the flow of information be blocked completely at any stage, no value is created by that information.”

IMHO, this is also going to be one of the biggest challenges of the IoT for management: in the days when it was sooo difficult to gather and disseminate information, it made sense for those in the C-suite to control it, and parcel out what they felt was relevant, to whom and when they felt it was relevant. More often than not, the flow was linear and hierarchical, with one information silo in the company handing on the results to the next after they’d processed it. That didn’t allow any of the critical advantages the IoT brings, of allowing everyone who needs it to share real-time data instantly.  But saying we need to change those information management practices is one thing: actually having senior management give up their gatekeeper functions is another, and shouldn’t be understated as a challenge.

So here are some of the other key points in the conference proceedings:

  • In line with the multi-step strategy I outlined in Managing the Internet of Things Revolution, they concluded that incremental improvements to existing processes and products are important, but will only take you so far, at which point radical innovation will be crucial: “At first blush, the early IoT emphasis on sustaining innovation seems reasonable. Performance and cost improvement are seldom absent from the priorities of stakeholders; they are relatively easy to measure and their impact is likely more immediate than any investment that is truly disruptive. Put simply, the business case for an IoT application that focuses on operational efficiencies is relatively easy to make. Many decision makers are hard-wired to prefer the path of less resistance and, for many, truly innovative IoT applications seem too far-flung and abstract to risk pursuing. Still, organizations cannot innovate from the cost side forever.”
  • Melding the public and private, “Cities have inherent societal challenges in place to serve as natural incubators of IoT solutions.” Yeah!
  • As in everything else, those contrarian Millennials (who aren’t so hung up on buying stuff and often prefer to just use it)  are likely to save us when it comes to the IoT:  “From an innovation perspective … some of the new technologies are first marketed at the consumers. Thus, many believe that near-term innovation in IoT applications will come out of the consumer sector – spurred by the emergence of the tech-savvy Millennial consumers as a driving economic force.”
  • As I’ve written before, while some customers will still prefer to buy products outright, the IoT will probably bring a shift from selling products to marketing services based on those products, creating new revenue streams and long-term relationships with customers: “As IoT makes successful forays into the world of consumer and industrial products, it may radically change the producer—buyer transactional model from one based on capital expenditure to one based on operating expenditure. Specifically, in a widely adopted IoT world, buyers may be more apt to purchase product service outcomes on some kind of “per unit” basis, rather than the product itself and in so doing, render the physical product as something more of an afterthought. The manufacturer would then gradually transform into a service provider, operating on a complete awareness of each product’s need for replenishment, repair, replacement, etc.”

    Or, a hybrid model may emerge: “What may ultimately happen in a relatively connected product world is that many may accept the notion of the smartly connected product, but in a limited way. Such people will want to own the smartly connected product outright, but will also accept the idea of sharing the usage data to the limited extent that the sellers use such data in relatively benign ways, such as providing advice on more efficient usage, etc. The outcome here will also rely upon a long term total cost of ownership (TCO) perspective. With any fundamental purchasing model changes (as is taking place in owned vs. cloud resources in the network / IT world), not all suppliers will be able to reap additional economic benefit under the service model. Buyers will eventually recognize the increase in TCO and revert back to the more economical business model if the economic rents are too high.”

  • It’s likely that those players in the IoT ecosystem who create value-added data interpretation will be the most valuable and profitable: “…are certain building blocks of the IoT network “more equal” than others?

    “Some have argued that the holy grail of the IoT value loop resides in the data and that those in the IoT ecosystem who aggregate and transform massive amounts of raw data into commercially useful intelligence capture the real value in the IoT environment. This notion holds that commercially useful data provide insights that drive action and ultimately represent the reason that the end user pursues a smart solution in the first place. Put another way, the end customer is more apt to pay for a more comprehensive treatment of raw data than for a better sensor. Indeed, some even believe that as time passes, the gap in relative value captured by those who curate and analyze the data and the rest of the IoT ecosystem will only widen and that, on a long-term basis, players within the “non-data” part of the IoT ecosystem will need to develop some data analytics capabilities simply to differentiate themselves as something more than commodity providers. Of course, some think that the emphasis on data is overblown and argue that where the real value in the IoT ecosystem is captured depends on application. Time will tell of course. But there can be little doubt that the collection and enhancement of data is highly coveted, and analytics and the ability to make use of the vast quantities of information that is captured will serve as critical elements to virtually any IoT solution.”

I urge you to download and closely analyze the entire report. It’s one of the most thoughtful and visionary pieces of IoT theory I’ve seen (no doubt because of its roundtable origins: in keeping with the above-mentioned need for cyclical information flow for the IoT [and, IMHO, creativity in general], the more insights you can bring together on a real-time basis, the richer the outcome. Bravo!

 

IBM picks for IoT trends to watch this year emphasize privacy & security

Last month Bill Chamberlin, the principal analyst for Emerging Tech Trends and Horizon Watch Community Leader for IBM Market Development (hmmm, must have an oversized biz card..) published a list of 20 IoT trends to watch this year that I think provide a pretty good checklist for evaluating what promises to be an important period in which the IoT becomes more mainstream.

It’s interesting to me, especially in light of my recent focus on the topics (and I’ll blog on the recent FTC report on the issue in several days), that he put privacy and security number one on the list, commenting that “Trust and authentication become critical across all elements of the IoT, including devices, the networks, the cloud and software apps.” Amen.

Most of the rest of the list was no surprise, with standards, hardware, software, and edge analytics rounding out the top five (even though it hasn’t gotten a lot of attention, I agree edge analytics are going to be crucial as the volume of sensor data increases dramatically: why pass along the vast majority of data, that is probably redundant, to the cloud, vs. just what’s a deviation from the norm and probably more important?).

Two dealing with sensors did strike my eye:

9.  Sensor fusion: Combining data from different sources can improve accuracy. Data from two sensors is better than data from one. Data from lots of sensors is even better.

10.  Sensor hubs: Developers will increasingly experiment with sensor hubs for IoT devices, which will be used to offload tasks from the application processor, cutting down on power consumption and improving battery life in the devices”

Both make a lot of sense.

One was particularly noteworthy in light of my last post, about the Gartner survey showing most companies were ill-prepared to plan and launch IoT strategies: “14.  Chief IoT Officer: Expect more senior level execs to be put in place to build the enterprise-wide IoT strategy.” Couldn’t agree more that this is vital!

Check out the whole list: I think you’ll find it helpful in tracking this year’s major IoT developments.

Gartner study confirms senior managers don’t understand IoT

Posted on 21st February 2015 in Internet of Things, M2M, management, manufacturing, marketing, strategy

The “Managing the Internet of Things Revolution” e-guide I wrote for SAP was aimed at C-level executives. Even though it’s proven popular enough that the company is translating it into several languages, it appears we need to redouble our efforts to Managing_the_Internet_of_Things_Revolutionbuild IoT awareness among executives.

I say that because Gartner has just come out with a survey confirming my suspicions: even though a lot of companies now think the IoT will have a major effect on them, they’re clueless about how to manage it and most have yet to launch major IoT initiatives.

In fact, “many survey respondents felt that the senior levels of their organizations don’t yet have a good understanding of the potential impact of the IoT.” (my emphasis)

 

That’s despite the fact that a key conclusion of my guide was that (even though the IoT is a long way from full maturity) companies can and should begin their IoT strategies and implementation now, because they can already achieve significant savings in operating costs, improve marketing, and create new revenue streams with the current early stage sensors and analytical tools. Getting started will also build their confidence and familiarity with IoT tools and strategy before they begin more dramatic transformational strategies.

Consider these findings from the survey of 463 business and IT leaders:

  • 40% of companies think the IoT will at least bring new short-term revenue and cost reduction opportunities in the next three years — or perhaps even transform them. More than 60% think that will be true over 5 years or more.
  • Fewer than 25% said their company had “established clear business leadership for the IoT,” — even among the companies predicting a significant  – this includes those who said they expect the IoT to have a significant or transformational impact, says Gartner (however, 35% of them came from this group).
  • Yet, few have delegated specific responsibility for IoT strategy and management: “… less than one-quarter of survey respondents has established clear business leadership for the IoT, either in the form of a single organizational unit owning the issue or multiple business units taking ownership of separate IoT efforts.”
  • “attitudes toward the IoT vary widely by industry. For example, board of directors’ understanding of the IoT was rated as particularly weak in government, education, banking and insurance, whereas the communications and services industries scored above-average ratings for senior executive understanding of the IoT.”

Gartner concluded most companies have yet to really create IoT strategies:

“‘The survey confirmed that the IoT is very immature, and many organizations have only just started experimenting with it,’ said Nick Jones, vice president and distinguished analyst at Gartner. ‘Only a small minority have deployed solutions in a production environment. However, the falling costs of networking and processing mean that there are few economic inhibitors to adding sensing and communications to products costing as little as a few tens of dollars. The real challenge of the IoT is less in making products ‘smart’ and more in understanding the business opportunities enabled by smart products and new ecosystems.’ However, a lack of clear business or technical leadership is holding back investment in the technology.” (my emphasis)

In line with my current preoccupation, privacy and security, the survey did show companies are concerned with both issues, as well as with finding talented new staff who understand the IoT and how to benefit from it. According to Steve Kleyhans, Gartner’s research vp:

 “While a single leader for the IoT is not essential, leadership and vision are important, even in the form of several leaders from different business units. We expect that over the next three years, more organizations will establish clear leadership, and more will recognize the value of some form of an IoT center of excellence because of the need to master a wide range of new technologies and skills.”

If you haven’t launched any IoT projects or begun to create a strategy, the writing’s on the wall: get going!


Carpe diem: I take this survey as an omen that there’s a desperate need for When Things Can Talk: profiting from the Internet of Things revolution,” my proposed full-length book on IoT corporate strategy. Let me know if you can suggest a possible publisher!

Management Challenge: Lifeguards in the IoT Data Lake

In their Harvard Business Review November cover story, How Smart, Connected Products Are Transforming Competition, PTC CEO Jim Heppelmann and Professor Michael Porter make a critical strategic point about the Internet of Things that’s obscured by just focusing on IoT technology: “…What makes smart, connected products fundamentally different is not the internet, but the changing nature of the “things.”

In the past, “things” were largely inscrutable. We couldn’t peer inside massive assembly line machinery or inside cars once they left the factory, forcing companies to base much of both strategy and daily operations on inferences about these things and their behavior from limited data (data which was also often gathered only after the fact).

Now that lack of information is being removed. The Internet of Things creates two unprecedented opportunities regarding data about things:

  • data will be available instantly, as it is generated by the things
  • it can also be shared instantly by everyone who needs it.

This real-time knowledge of things presents both real opportunities and significant management challenges.

Each opportunity carries with it the challenge of crafting new policies on how to manage access to the vast new amounts of data and the forms in which it can be accessed.

For example: with the Internet of Things we will be able to bring about optimal manufacturing efficiency as well as unprecedented integration of supply chains and distribution networks. Why? Because we will now be able to “see” inside assembly line machinery, and the various parts of the assembly line will be able to automatically regulate each other without human intervention (M2M) to optimize each other’s efficiency, and/or workers will be able to fine-tune their operation based on this data.

Equally important, because of the second new opportunity, the exact same assembly line data can also be shared in real time with supply chain and distribution network partners. Each of them can use the data to trigger their own processes to optimize their efficiency and integration with the factory and its production schedule.

But that possibility also creates a challenge for management.

When data was hard to get, limited in scope, and largely gathered historically rather than in the moment, what data was available flowed in a linear, top-down fashion. Senior management had first access, then they passed on to individual departments only what they decided was relevant. Departments had no chance to simultaneously examine the raw data and have round-table discussions of its significance and improve decision-making. Everything was sequential. Relevant real-time data that they could use to do their jobs better almost never reached workers on the factory floor.

That all potentially changes with the IoT – but will it, or will the old tight control of data remain?

Managers must learn to ask a new question that’s so contrary to old top-down control of information: who else can use this data?

To answer that question they will have to consider the concept of a “data lake” created by the IoT.

“In broad terms, data lakes are marketed as enterprise wide data management platforms for analyzing disparate sources of data in its native format,” Nick Heudecker, research director at Gartner, says. “The idea is simple: instead of placing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion, like transformation. Once data is placed into the lake, it’s available for analysis by everyone in the organization.”

Essentially, data that has been collected and stored in a data lake repository remains in the state it was gathered and is available to anyone, versus being structured, tagged with metadata, and having limited access.

That is a critical distinction and can make the data far more valuable, because the volume and variety will allow more cross-fertilization and serendipitous discovery.

At the same time, it’s also possible to “drown” in so much data, so C-level management must create new, deft policies – to serve as lifeguards, as it were. They must govern data lake access if we are to, on one hand, avoid drowning due to the sheer volume of data, and, on the other, to capitalize on its full value:

  • Senior management must resist the temptation to analyze the data first and then pass on only what they deem of value. They too will have a crack at the analysis, but the value of real-time data is getting it when it can still be acted on in the moment, rather than just in historical analyses (BTW, that’s not to say historical perspective won’t have value going forward: it will still provide valuable perspective).
  • There will need to be limits to data access, but they must be commonsense ones. For example, production line workers won’t need access to marketing data, just real-time data from the factory floor.
  • Perhaps most important, access shouldn’t be limited based on pre-conceptions of what might be relevant to a given function or department. For example, a prototype vending machine uses Near Field Communication to learn customers’ preferences over time, then offers them special deals based on those choices. However, by thinking inclusively about data from the machine, rather than just limiting access to the marketing department, the company shared the real-time information with its distribution network, so trucks were automatically rerouted to resupply machines that were running low due to factors such as summer heat.
  • Similarly, they will have to relax arbitrary boundaries between departments to encourage mutually-beneficial collaboration. When multiple departments not only share but also get to discuss the same data set, undoubtedly synergies will emerge among them (such as the vending machine ones) that no one department could have discovered on its own.
  • They will need to challenge their analytics software suppliers to create new software and dashboards specifically designed to make such a wide range of data easily digested and actionable.

Make no mistake about it: the simple creation of vast data lakes won’t automatically cure companies’ varied problems. But C-level managers who realize that if they are willing to give up control over data flow, real-time sharing of real-time data can create possibilities that were impossible to visualize in the past, will make data lakes safe, navigable – and profitable.

Good Checklist for Creating #IoT Strategy

Still not ready to tackle an analysis of the November Harvard Business Review cover story, by PTC CEO Jim Heppelmann and Professor Michael Porter, on How Smart, Connected Products Are Transforming Competition, but I did want to do a shout-out to a companion piece, Digital Ubiquity: How Connections, Sensors, and Data Are Revolutionizing Business, by two HBS profs, Marco Iansiti and Karim R. Lakhani.

In particular, I wanted to suggest that you use the last section of the paper, “Approaching Digital Ubiquity,” as a checklist of priorities to create your own IoT strategy (I’d be remiss if I didn’t also mention my “Managing the Internet of Things Revolution” i-guide and this blog’s “Essential Truths” as references as well..).

Here are their points, and my reflections on them:

  1. Apply the digital lens to existing products and services.
    This is a profound transformation, because we’ve become so accustomed to working around the gaps in our knowledge that were the reality in an analog world.As Iasanti and Lakhani say, you now need to ask:
    “What cumbersome processes in your business or industry are amenable to instrumentation and connectivity?
    Which ones are most challenging to you or your customers?”
  2. Connect your existing assets across companies.
    We “get” competition, but collaboration, especially with competitors, is a little less instinctive.

    “If you work in a traditional analog setting, examine your assets for new opportunities and look at other industries and the start-up world for new synergies. Your customer connections are especially valuable, as are your knowledge of customers’ needs and the capabilities you built to meet knowledge of customers’ needs and the capabilities you built to meet them. Nest is connecting with public utilities to share data and optimize overall energy usage. If you work in a start-up, don’t just focus on driving the obsolescence of established companies. Look at how you can connect with and enhance their value and extract some of it for yourself.knowledge of customers’ needs and the capabilities you built to meet them. Nest is connecting with public utilities to share data and optimize overall energy usage. [my note: this is a great example of thinking expansively: even though your product is installed in individual homes, if data can be aggregated from many homes, it can be of real value on a macro scale as well. The smart grid is a great example of bringing all components of energy production, distribution, and use together into an integrated system.]  If you work in a start-up, don’t just focus on driving the obsolescence of established companies. Look at how you can connect with and enhance their value and extract some of it for yourself.”

  3. Examine new modes of value creation.
    Just because you make tangible products doesn’t mean that you’re limited to just selling those products to make money in the future. You’ll be able to make money by selling customers actionable data that will allow them to improve productivity and reduce maintenance. Perhaps you’ll stop selling altogether, and make money instead by making your products the cornerstone of profitable services.

    Begin to ask:
    “What new data could you accumulate, and where could you derive value from new analytics?”
    “How could the data you generate enable old and new customers to add value?”

  4. Consider new value-capture modes.
    “Could you do a better job of tracking the actual value your business creates for others?”
    “Could you do a better job of monetizing that value, through either value-based pricing or outcomes-based models?”
  5. Use software to extend the boundaries of what you do.
    You will still make products, as in the past, and that gives you a tangible basis for the future. But you’ll need a digital component as well.

    “Digital transformation does not mean that your company will only sell software, but it will shift the capability base so that expertise in software development becomes increasingly important. And it won’t render all traditional skills obsolete. Your existing capabilities and customer relationships are the foundations for new opportunities. Invest in software-related skills that complement what you have, but make sure you retain those critical foundations. Don’t jettison your mechanical engineering wizards—couple them with some bright software developers so that you can do a better job of creating and extracting value.”

    What do you think?  Any more questions you’d add? Let me know!

I’ll be on SAP Radio Again Today: the IoT and Big Data

I’ll be on SAP’s “Coffee Breaks With Game Changers” radio again today, live @ 2 EST, appearing again with SAP’s David Jonker, again talking about the IoT and Big Data.  This time I plan to speak about:

  • Integrating real-time and historic data in decision-making:  in the past, it was so hard to glean real-time operating data that we had to operate on the basis of inferring about how to manage the future based on analysis of past data.  Now we have a more difficult challenge: learn to balance past and real-time data.
  • Sharing data in real-time: In the past, data trickled down from top management and might (or might not) eventually get to operators on the shop floor.  Now, everyone can get immediate access to it. Will senior managers continue to be the gatekeepers, or will everyone have real-time access to the data that might allow them to do their jobs more effectively (for example, fine-tuning production processes).

  • Revolutionizing decision-making: Decision-making will also change, because of everyone being able to have simultaneous access to data. Does it really make sense any more for sequential decision-making by various siloed departments when they might all benefit by making the decisions simultaneously and collaboratively, based on the data?

Tune in!

I’ll be on “Game Changer” Radio Today @ 3 EST Talking About IoT

Huzzah!  I’ll be a guest on Bonnie Graham’s “Coffee Break With Game Changers” show live, today @ 3 PM to discuss the Internet of Things. SAP Radio

Other guests will include David Jonker, sr. director of Big Data Initiatives at SAP, and Ira Berk, vice-president of Solutions Go-to-market at SAP, who has global responsibility for the IoT infrastructure and middleware portfolio.

Among other topics that I hope to get to during the discussion:

  • The “Collective Blindness” meme that I raised recently — and how the IoT removes it.
  • The difficult shift companies will need to make from past practices, where information was a zero-sum game, where hoarding information led to profit, to one where sharing information is the key. Who else can use this information?
  • How the IoT can bring about an unprecedented era of “Precision Manufacturing,” which will not only optimize assembly line efficiency and eliminate waste, but also integrate the supply chain and distribution network.
  • The sheer quantity of data with the IoT threatens to overwhelm us. As much as possible, we need to migrate to “fog computing,” where as much data as possible is processed at the edge, with only the most relevant data passing to the cloud (given the SAP guys’ titles, I assume this will be of big interest to them.
  • The rise of IFTTT.com, which means device manufacturers don’t have to come up with every great way to use their devices: use open standards, just publish the APIs to IFTTT, and let the crowd create creative “recipes” to use the devices.
  • Safety and security aren’t the other guy’s problem: EVERY device manufacturer must build in robust security and privacy protections from the beginning. Lack of public trust can undermine everyone in the field.
  • We can cut the cost of seniors’ care and improve their well being, through “smart aging,” which brings together Quantified Self fitness devices that improve their care and make health care a doctor-patient partnership, and “smart home” devices that automate home functions and make them easier to manage.

Hope you can listen in.  The show will be archived if you can’t make it for the live broadcast .

Perhaps Most Important Internet of Things Essential Truth: Everything’s Linked

PROCEED WITH CAUTION!

You see, I’m thinking out loud (that accounts for that sound of gears grinding….) — I really am writing this post as I mull over the subject for the first time, so you’re forewarned that the result may be a disaster — or insightful. Bear with me…

I’m working on a book outline expanding on “Managing the Internet of Things Revolution,” the introduction to IoT strategy for C-level executives that I wrote for SAP. One of the things I’ve been looking for is a theme that would bring together all of the book’s parts, which include product design, manufacturing, marketing and corporate organization, among other topics.

I think I’ve got that theme, and I think it may be the most Essential Truth of all the ones I’ve written about regarding the IoT:

Everything’s Linked!

When you think about it, there have been a lot of dead-ends in business in the past:

  • we haven’t been able to know how customers used our products. We’ve actually got a lot more information about the ones that failed, because of warrantee claims or complaints, than we have about the ones that worked well, because that information was impossible to gather.
  • data that could help workers do their work better has always come from top down, filtered by various levels of management and only delivered after the fact.
  • customers can’t get the full value of our products because they operate in isolation from each other, and often were slow to react to changing conditions.
  • assembly-line machinery has frequently been hard to optimize, because we really didn’t know how it was operating — until it broke down.
  • key parts of the operation, such as supply chain, manufacturing, and distribution, have been largely independent, without simultaneous access to each other’s status.

With the Internet of Things, by contrast, everything will be linked, and that will change everything:

  • we’ll get real-time data about how customers are using our products. Most radically, that data may even allow us, instead of selling products and then severing our ties to the customer as in the past, to instead lease them the products, with the pricing dependent on how they actually use the products and the value they obtain from them.
  • everyone in the company can (if your management practices allow!) have real-time access to data that will help them improve their decision making and daily operations (hmm: still looking for an example of this one: know any companies that are sharing data on a real-time basis??).
  • products will work together, with synergistic results (as with the Jawbone UP turning on the NEXT), with their operation automatically triggered and coordinated by services such as IFTTT.
  • the assembly line can be optimized because we’ll be able to “see” into massive equipment to learn how it is operating — or if it needs repairs in time to avoid catastrophic failure.
  • access to that same data may even be shared with your supply chain and distribution network — or even with customers (again, looking for a good example of that transformation).

There’s won’t be dead ends or one-way streets where information only flows one way. Instead, they’ll be replaced by loops (in fact, I thought loops might be an alternative theme): in many cases, data will be fed back through M2M systems so things can be optimized.

If that’s the case, we’ll be able to increase the use and value of tools such as systems dynamics software, that would help us model and act on these links and loops. Instead of massive oscillations where we’re forced to make sudden, major corrections when data finally becomes available, machinery will be largely self-regulating, based on continuous feedback. We’ll delight customers because products will be more dependable and we’ll be able to fine-tune them by adding features based on actual knowledge of how the products work.  Workers will be more efficient, and happier, because they’ll be empowered. We’ll tread lightly on the earth, because we’ll use only what we need, precisely when we need it.

By George, I think I’ve got it! I’m excited about this vision of the Internet of Things linking everything. What do you think?? Please let me know! 

GE & Accenture provide detailed picture of current IoT strategy & deployment

I’ll admit it: until I began writing the “Managing the Internet of Things Revolution” guide to Internet of Things strategy for SAP, I was pre-occupied with the IoT’s gee-wiz potential for radical transformation: self-driving cars, medical care in which patients would be full partners with their doctors, products that customers would be able to customize after purchase.

GE_Accenture_IoT_reportThen I came to realize that this potential for revolution might be encouraging executives to hold off until the IoT was fully-developed, and, in the process, ignoring low-hanging fruit: a wide range of ways that the IoT could dramatically increase the efficiency of current operations, giving them a chance to experiment with limited, less-expensive IoT projects that would pay off rapidly and give them the confidence and understanding necessary to launch more dramatic IoT projects in the near future.

This is crucially important for IoT strategies: instead waiting for a radical transformation (which can be scary), view it instead as a continuum, beginning with small, relatively-low cost steps which will feed back into more dramatic steps for the future.

Now, there’s a great new study, “Industrial Internet Insights Report for 2015,” from GE and Accenture, that documents many companies are in the early stages of implementing such an incremental approach, with special emphasis on the necessary first step, launching Big Data analytics — and that they are already realizing tangible benefits. It is drawn from a survey of companies in the US, China, India, France, Germany, the UK, and South Africa.

The report is important, so I’ll review it at length.

Understandably, it was skewed toward the industries where GE applies its flavor of the IoT (the “Industrial Internet”): aviation, health care, transportation, power generation, manufacturing, and mining, but I suspect the findings also apply to other segments of the economy.

The summary underscores a “sense of urgency” to launch IoT initiatives:

“The vast majority (of respondents) believe that Big Data analytics has the power to dramatically alter the competitive landscape of industries just within the next year, and are investing accordingly…” (my emphasis).

84% said Big Data analytics “has the power to shift the competitive landscape for my industry” within just the next year, and 93% said they feared new competitors will enter the field to leverage data.  Wow: talk about short-term priorities!

It’s clear the authors believe the transformation will begin with Big Data initiatives, which, IMHO, companies should be starting anyways to better analyze the growing volume of data from conventional sources. 73% of the companies already are investing more than 20% of their overall tech budget on Big Data analytics — and some spend more than 30%! 80 to 90% said Big Data analytics was either the company’s top priority or at least in the top 3.

One eye-opening finding was that 53% of respondents said their board of directors was pushing the IoT initiatives. Probably makes sense, in that boards are expected to provide necessary perspective on the company’s long-term health.

GE and Accenture present a  4-step process to capitalize on the IoT:

  1. Start with the exponential growth in data volumes
  2. Add the additional data volume from the IoT
  3. Add growing analytics capability
  4. and, to add urgency, factor in “the context of industries where equipment itself or patient outcomes are at the heart of the business” where the ability to monitor equipment or monitor patient services can have significant economic impact and in some cases literally save lives [nothing like throwing the fear of God into the mix to motivate skeptics!].
For many companies, after implementing Big Data software, the next step toward realizing immediate IoT benefits is by installing sensors to monitor the status of operating assets and be able to implement “predictive maintenance,” which cuts downtime and reduces maintenance costs (the report cites some impressive statistics: ” .. saving up to 12 percent over scheduled repairs, reducing overall maintenance costs up to 30 percent, and eliminating breakdowns up to 70 percent.” What company, no matter what their stance on the IoT, wouldn’t want to enjoy those benefits?). The report cites companies in health care, energy and transportation that are already realizing benefits in this area.
Music to my ears was the emphasis on breaking down data-sharing barriers between departments, the first time I’ve seen substantiation of my IoT “Essential Truth” that, instead of hoarding data — whether between the company and supply-chain partners or within the company itself — that the IoT requires asking “who else can use this data?” It said that: “System barriers between departments prevent collection and correlation of data for maximum impact.” (my emphasis). The report went on to say:

“All in all, only about one-third of companies (36 percent) have adopted Big Data analytics across the enterprise. More prevalent are initiatives in a single operations area (16 percent) or in multiple but disparate areas (47 percent)…. The lack of an enterprise-wide analytics vision and operating model often results in pockets of unconnected analytics capabilities, redundant initiatives and, perhaps most important, limited returns on analytics investments.”

Most of the companies surveyed are moving toward centralization of data management to break down the silos. 49% plan to appoint a chief analytics officer to run the operation, and most will hire skilled data analysts or partner with outside experts (insert Accenture here, LOL…).

The GE/Accenture report also stressed that companies hoping to profit from the IoT also must create end-to-end security. Do do that, it recommended a strategy including:
  1. assess risks and consequences
  2. develop objectives and goals
  3. enforce security throughout the supply chain.
  4. use mitigation devices specifically designed for Industrial Control Systems
  5. establish strong corporate buy-in and governance.

For the longer term, the report also mentioned a consistent theme of mine, that companies must begin to think about dramatic new business models, such as substituting value-added services instead of traditional sales of products such as jet engines.  This is a big emphasis with GE.  It also emphasizes another issue I’ve stressed in the “Essential Truths,” i.e. partnering, as the mighty GE has done with startups Quirky and Electric Imp:

“Think of the partnering taking place among farm equipment, fertilizer, and seed companies and weather services, and the suppliers needed to provide IT, telecom, sensors, analytics and other products and services. Ask: ‘Which companies are also trying to reach my customers and my customers’ customers? What other products and services will talk to mine, and who will make, operate and service them? What capabilities and information does my company have that they need? How can we use this ecosystem to extend the reach and scope of our products and services through the Industrial Internet?'”

While the GE/Accenture report dwelt only on large corporations, I suspect that many of the same findings would apply to small-to-medium businesses as well, and that the falling prices of sensors and IoT platforms will mean more smart companies in this category will begin to launch incremental IoT strategies to first optimize their current operations and then make more radical changes.

Read it, or be left in the dust!


PS: as an added bonus, the report includes a link to the GE “Industrial Internet Evaluator,” a neat tool I hadn’t seen before. It invites readers to “see how others in your field are leveraging Big Data analytics for connecting assets, monitoring, analyzing, predicting and optimizing for business success.” Check it out!