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 .

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!

Why It’s So Hard to Predict Internet of Things’ Full Impact: “Collective Blindness”

I’ve been trying to come up with a layman’s analogy to use in explaining to skeptical executives about how dramatic the Internet of Things’ impact will be on every aspect of business and our lives, and why, if anything, it will be even more dramatic than experts’ predictions so far (see Postscapes‘ roundup of the projections).

See whether you thing “Collective Blindness” does justice to the potential for change?

 

What if there was a universal malady known as Collective Blindness, whose symptoms were that we humans simply could not see much of what was in the world?

Even worse, because everyone suffered from the condition, we wouldn’t even be aware of it as a problem, so no one would research how to end it. Instead, for millennia we’d just come up with coping mechanisms to work around the problem.

Collective Blindness would be a stupendous obstacle to full realization of a whole range of human activities (but, of course, we couldn’t quantify the problem’s impact because we weren’t even aware that it existed).

Collective Blindness has been a reality, because vast areas of our daily reality have been unknowable in the past, to the extent that we have just accepted it as a condition of reality.

Consider how Collective Blindness has limited our business horizons.

We couldn’t tell when a key piece of machinery was going to fail because of metal fatigue.

We couldn’t tell how efficiently an entire assembly line was operating, or how to fully optimize its performance.

We couldn’t tell whether a delivery truck would be stuck in traffic.

We couldn’t tell exactly when we’d need a parts shipment from a supplier, nor would the supplier know exactly when to do a new production run to be read.

We couldn’t tell how customers actually used our products.

That’s all changing now. Collective Blindness is ending, …. and will be eradified by the Internet of Things.

What do you think? Useful analogy?

Why the Internet of Things Will Bring Fundamental Change “What Can You Do Now That You Couldn’t Do Before?”

The great Eric Bonabeau has chiseled it into my consciousness that the test of whether a new technology really brings about fundamental change is to always ask “What can you do now that you couldn’t do before?

Tesla Roadster

That’s certainly the case for the Tesla alternative last winter to a costly, time-consuming, and reputation-staining recall  (dunno: I must have been hiding under a rock at the time to have not heard about it).

In reporting the company’s action, Wired‘s story’s subtitle was “best example yet of the Internet of Things?”

I’d have to agree it was.

Coming at the same time as the godawful Chevy recall that’s still playing out and still dragging down the company, Tesla promptly and decisively response solved another potentially dangerous situation:

 

“‘Not to worry,’ said Tesla, and completed the fix for its 29,222 vehicle owners via software update. What’s more, this wasn’t the first time Tesla has used such updates to enhance the performance of its cars. Last year it changed the suspension settings to give the car more clearance at high speeds, due to issues that had surfaced in certain collisions.”

Think of it: because Tesla has basically converted cars into computers with four wheels, modifying key parts by building in sensors and two-way communications, it has also fundamentally changed its relationship with customers: it can remain in constant contact with them, rather than losing contact between the time the customer drives off the lot and when the customer remembers (hopefully..) to schedule a service appointment, and many modifications that used to require costly and hard-to-install replacement parts now are done with a few lines of code!

Not only can Tesla streamline recalls, but it can even enhance the customer experience after the car is bought: I remember reading somewhere that car companies may start offering customer choice on engine performance: it could offer various software configurations to maximize performance or to maximize fuel savings — and continue to tweak those settings in the future, just as computers get updated operating systems. That’s much like the transformation of many other IoT-enhanced products into services, where the customer may willingly pay more over a long term for a not just a hunk of metal, but also a continuing data stream that will help optimize efficiency and reduce operating costs.

Wired went on to talk about how the engineering/management paradigm shift represented a real change:

  • “In nearly all instances, the main job of the IoT — the reason it ever came to be — is to facilitate removal of non-value add activity from the course of daily life, whether at work or in private. In the case of Tesla, this role is clear. Rather than having the tiresome task of an unplanned trip to the dealer put upon them, Tesla owners can go about their day while the car ‘fixes itself.’
  • Sustainable value – The real challenge for the ‘consumer-facing’ Internet of Things is that applications will always be fighting for a tightly squeezed share of disposable consumer income. The value proposition must provide tangible worth over time. For Tesla, the prospect of getting one’s vehicle fixed without ‘taking it to the shop’ is instantly meaningful for the would-be buyer – and the differentiator only becomes stronger over time as proud new Tesla owners laugh while their friends must continue heading to the dealer to iron out typical bug fixes for a new car. In other words, there is immediate monetary value and technology expands brand differentiation. As for Tesla dealers, they must be delighted to avoid having to make such needling repairs to irritated customers – they can merely enjoy the positive PR halo effect that a paradigm changing event like this creates for the brand – and therefore their businesses.
  • Setting new precedents – Two factors really helped push Tesla’s capability into the news cycle: involvement by NHTSA and the word ‘recall.’ At its issuance, CEO Elon Musk argued that the fix should not technically be a ‘recall’ because the necessary changes did not require customers find time to have the work performed. And, despite Musk’s feather-ruffling remarks over word choice, the stage appears to have been set for bifurcation in the future by the governing bodies. Former NHTSA administrator David Strickland admitted that Musk was ‘partially right’ and that the event could be ‘precedent-setting’ for regulators.”

That’s why I’m convinced that Internet of Things technologies such as sensors and tiny radios may be the easy part of the revolution: the hard part is going to be fundamental management changes that require new thinking and new questions.

What can you do now that you couldn’t do before??

BTW: Musk’s argument that its software upgrade shouldn’t be considered a traditional “recall” meshes nicely with my call for IoT-based “real-time regulation.”  As I wrote, it’s a win-win, because the same data that could be used for enforcement can also be used to enhance the product and its performance:

  • by installing the sensors and monitoring them all the time (typically, only the exceptions to the norm would be reported, to reduce data processing and required attention to the data) the company would be able to optimize production and distribution all the time (see my piece on ‘precision manufacturing’).
  • repair costs would be lower: “predictive maintenance” based on real-time information on equipment’s status is cheaper than emergency repairs. the public interest would be protected, because many situations that have resulted in disasters in the past would instead be avoided, or at least minimized.
  • the cost of regulation would be reduced while its effectiveness would be increased: at present, we must rely on insufficient numbers of inspectors who make infrequent visits: catching a violation is largely a matter of luck. Instead, the inspectors could monitor the real-time data and intervene instantly– hopefully in time to avoid an incident. “

Wow! Mass. IoT market really heating up, as PTC grows again!

Posted on 24th July 2014 in Internet of Things, M2M, manufacturing

One of my roles is as founder and co-chair of the Boston/New England IoT Meetup, so I’m always eager to report positive news about IoT news here in the Hub of the Universe.

Big news today: Needham’s PTC is growing again (after its recent $130 million purchase of ThingWorx), buying Foxboro’s Axceda for $170 million, giving them a good base in both IoT platforms and devices. Both of these purchases are dwarfed by the $3.2 billion Google paid for Nest, but they do show that the industry is growing, and that PTC is suddenly emerging as a Player To Be Reckoned With. Wonder what their strategic plan is?

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If This, Then That (IFTTT): essential crowdsourcing component to speed IoT development

I’ve been meaning to write about IFTTT (If This, Then That, pronounced like “gift,” but minus the g) for a long time, because I see it as a crucial, if perhaps underappreciated, component to spread the IoT more rapidly and increase its versatility — by democratizing the IoT.

That’s because this cool site embraces one of my favorite IoT “Essential Truths.” We must start asking:

who else could use this data?

I first started asking this question in my book, Data Dynamite, which largely focused on a fundamental paradigm shift away from the old view of data, namely, that you could gain a competitive advantage if you had proprietary information that I didn’t have. It was a zero-sum game. Your win was my loss.  

No longer: now value is created for you if you share data with me and I come up with some other way to use that data that you hadn’t explored. Win-win!

As applied to the IoT, I’ve explored this shift primarily in the context of corporate initiatives, where it becomes possible, for the first time, to share data instantly among everyone who could benefit from that data: everyone within the company, but also your supply chain, your distribution network, and, sometimes, even your customers. 

samples of IFTTT recipes

Here’s where the benefit of sharing data with your customers on a real-time basis comes in: there are a lot more of them than there are of manufacturers, and I can guarantee you that they will come up with clever uses that your staff, no matter how brilliant, won’t. Exhibit A: during last year’s World Series, GigaOM’s Stacey Higginbotham, did an IFTTT “recipe” that turned her HUE lights red (too bad for her, the Sox scored more runs. Wait until next year…). What Philips researcher would have ever done that on company time?

By harnessing crowdsourcing of ideas, the IoT will progress much faster, because of the variety of interests and/or needs that individuals add to the soup!

So, how’s IFTTT work?

Here’s a brief outline (or go here for details):

  1. a “recipe” is made up of a “trigger” (i.e., if this happens, such as “I’m tagged in a photo on Facebook”) and an action (then that happens, such as “create a status message on Facebook.”).
  2. the building blocks for recipes are called channels — 116 as of now, and growing all the time — each of which his its own triggers and actions.  The channels include a wide range of apps and products, such as Nest thermostats or Facebook.

There is a wide variety of recipes on the IFTTT site (you can subscribe to have new ones involving a given channel that interests you sent to you as they are shared) or you can easily create your own — with no programming skill required. How cool is that?

Yes, IFTTT can be fun (“email your mother Foursquare checkins tagged #mom. Useful for brownie points“), but I’m convince that it’s also a critically important tool to speed deployment and impact of the IoT, by harnessing the power of crowdsourcing to complement the work of app developers and device manufacturers.

Now get going!

 

My speech on how the Internet of Things will aid Predictive Analytics

I spoke yesterday at the Predictive Analytics Manufacturing conference in Chicago, about a theme I first raised in the O’Reilly SOLID blog, about how the Internet of Things could bring about an “era of precision manufacturing.”

I argued that, as powerful as Predictive Analytics tools have been in analyzing manufacturing data and improving forecasting, their effectiveness has been artificially restricted because, for example, we can’t “see” inside production machinery to detect early signs of metal fatigue in time to avoid a costly breakdown, nor can we tell whether EVERY product on an assembly line will function when customers use them.

By contrast, I argued that the IoT will give us all this information, and, most important, allow everyone (from your supply chain and distribution network to EVERYONE in your company) to share this data on a real-time basis.  I warned that it will be management issues (those pesky IoT Essential Truths again!), such as whether to allow this sharing to take place, and whether to end departmental silos, that will be the biggest potential barrier to full IoT implementation.

Believe me, it will be an incredible transformation.  You can read the full text here.

Calculating Internet of Things ROI — important tool

Just came across this video while researching how to calculate ROI on Internet of Things investments for the e-book I’m writing, and felt compelled to share it.

That’s because it may be hard to calculate ROI fully and accurately for IoT investments if you aren’t thinking in terms of what my friend/patron Eric Bonabeau always pounds into my head: what can you do now that you couldn’t do before?

In the case of the IoT, there are  several things, such as “predictive maintenance,” that weren’t possible before and thus we don’t automatically think of calculating these benefits. It will require a conscious change in figuring ROI to account for them.

According to Axeda CMO Bill Zujewski, there are 6 levels of M2M/IoT implementation, and there are both cost savings and revenue enhancements as you move up the curve:

  1. Unconnected: this is where most firms are today. No M2M/IoT investments.
  2. Connected, pulling data for future use: No return yet.
  3. Service: the investment begins to pay off, primarily because of lower service costs.
    1. Cost reductions:
      1. fewer repair visits  Now that you’re harvesting real-time information about products’ condition, you may be able to optimize operating conditions remotely.
      2. first-time fix rate increases: Now you may know what the problem is before you leave, and can also take the proper replacement parts.
      3. reduced call length: You may know the problem in advance, rather than having to tinker once you’re there to discover it.
    2. Higher Revenues:
      1. Greater customer satisfaction. Customer doesn’t have to pay as much for repairs, down-time is reduced.
  4. Analyze: Putting data into BI and other analysis tools to get greater insights. For example, understand what are bad parts, when they’re failing.
    1. Cost reductions:
      1. fewer service visits: instead of monthly service you may be able to switch to quarterly.
      2. lowering returns
      3. improve product design
    2. Higher Revenues:
      1. Increase product up-time: due to better design and more effective maintenance, longer mean-time-to-failure.
  5. Data integration: begin to integrate data with business processes.
    1. Cost reductions:
      1. warrantees (especially for industrial equipment): fewer claims if you can monitor equipment’s operations, warn owner if they’re using it improperly.
      2. recalls: reduced.
    2. Higher revenues:
      1. pay-as-you-go leases: as we’ve discussed earlier, you may be able to increase revenues by leasing products based on how much the customer actually uses them (which you can now document), rather than selling them.
      2. increased sales of consumables: you’ll be able to know exactly when the customer needs them.
  6. Reinvent the customer experience: According to Zujewski, this is where you “put machine data into the end users’ hands” through a smartphone app, for example, that gives them access to the information.
    1. Cost reductions:
      1. reduced calls to call center: the end user will be able to initiate service and troubleshoot themselves.
    2. Higher revenues:
      1. increases sales: your product will be enhanced, leading to more successful sales calls. You also may be able to charge for some of the new data access services that make the product better.

Zujewski concludes by saying that all of these changes combine into 4 major benefits:

  1. world-class service
  2. business insights (such as better understanding of how your customers are using your products) from all the data and analysis
  3. improve business processes: integrating data allows you to improve the way you perform current processes
  4. highly-differentiated offering due to to the apps and information you can provide users. “You end up demo-ing your apps vs. just the machines”

I was really impressed with this presentation, and it makes sense to me as a framework for calculating ROI on Internet of Things investments (I want to think about other benefits of the IoT that were impossible before to see if there are any other factors that should also be calculated).

I’d be really interested in your reaction: is this a valid methodology? what other factors would you also include?

Best quick intro to the IoT that I’ve seen!

Following up on my last post, I’ve found what I think is the best quick intro to the Internet of Things!

Internet of Things,” released today by the Center for Data Innovation (hadn’t heard of them! BTW, they also get points in my book for covering XBRL, the magic potion for data…) is a quick read: it has short intros to most of the major consumer-oriented areas affected by the IoT, from healthcare to home automation, combined with two examples for each of those topics. I hadn’t heard of some of the examples (thanks, authors Daniel Castro and Jordan Misra!), although most are frequently cited ones ranging from the Nest thermostat to the Vitality GlowCap.  All in all, they’ll show almost any skeptic that the IoT is already a reality and that it will change their life!

The report concludes with brief policy recommendations for government and business alike:

  • (for government agencies) lead by example, i.e., include funding for sensors in bridge projects, etc. Yea (you listening, Obama Administration?).
  • reduce barriers to data sharing (this harkens back to my Data Dynamite book: data gains value by being shared!).
  • give consumers access to their data (again, something I wrote about in Data Dynamite).
  • avoid inundating consumers with notices (a fine line, since they need to be informed, in plain English, about how their data will be used).
  • regulate the use of data, not the collection (in line with Mercatus Center’s advice)

All in all, a nice intro to the IoT!

BTW: Thanx to ol’ friend Pete O’Dell for turning me on to this report!

Two good sites if you’re introducing the IoT

Categorize this under “posts I’ve been meaning to write for a long time!”

For the current writing assignment I’m working on, I’m looking for as many good examples of practical Internet of Things applications that are available right now.

There are two sites that I repeatedly go to for those examples that deserve some praise.

postscapesOne is Postscapes, which I find to be an important all-around IoT news source. It features products (and links to their sites) in the “Body,” “Home,” “City” and “Industry” categories, as well as a DIY/Open Source grouping. The descriptions are well written and it’s attractive.

The other site is a corporate one, from Libelium, the Spanish open source sensor platform. A portion of its site is devoted to “50 Sensor Applications for a Smarter World,” grouped under “Smart Cities,” “Smart Environment,” “Smart Water,” “Smart Metering,” “Retail,” “Logistics,” “Industrial Control,” “Smart Agriculture,” “Smart Animal Farming,” “Security and Emergencies,” “Domotic and Home Automation,” and “eHealth.” There’s a wealth of accompanying information about — surprise! — the Libelium sensors that are matched to each of these applications. Of course it’s marketing for Libelium, but the range of applications does illustrate the wide range of ways that the IoT is already affecting industry, cities, and personal lives.

Check both sites out — and point your skeptical contacts who wonder if the IoT is just a laboratory curiosity to them!