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!

 

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The Internet of Things’ Essential Truths

I’ve been writing about what I call the Internet of Things’ “Essential Truths” for three years now, and decided the time was long overview to codify them and present them in a single post to make them easy to refer to.

As I’ve said, the IoT really will bring about a total paradigm shift, because, for the the first time, it will be possible for everyone who needs it to share real-time information instantly. That really does change everything, obliterating the “Collective Blindness” that has hampered both daily operations and long-term strategy in the past. As a result, we must rethink a wide range of management shibboleths (OK, OK, that was gratuitous, but I’ve always wanted to use the word, and it seemed relevant here, LOL):

  1. First, we must share data. Tesla leads the way with its patent sharing. In the past, proprietary knowledge led to wealth: your win was my loss. Now, we must automatically ask “who else can use this information?” and, even in the case of competitors, “can we mutually profit from sharing this information?” Closed systems and proprietary standards are the biggest obstacle to the IoT.
  2. Second, we must use the Internet of Things to empower workers. With the IoT, it is technically possible for everyone who could do their job better because of access to real-time information to share it instantly, so management must begin with a new premise: information should be shared with the entire workforce. Limiting access must be justified.
  3. Third, we must close the loop. We must redesign our data management processes to capitalize on new information, creating continuous feedback loops.
  4. Fourth, we must rethink products’ roles. Rolls-Royce jet engines feed back a constant stream of real-time data on their operations. Real-time field data lets companies have a sustained dialogue with products and their customers, increasingly allowing them to market products as services, with benefits including new revenue streams.
  5. Fifth, we must develop new skills to listen to products and understand their signals. IBM scientists and medical experts jointly analyzed data from sick preemies’ bassinettes & realized they could diagnose infections a day before there was any visible sign. It’s not enough to have vast data streams: we need to understand them.
  6. Sixth, we must democratize innovation. The wildly-popular IFTTT web site allows anyone to create new “recipes” to exploit unforeseen aspects of IoT products – and doesn’t require any tech skills to use. By sharing IoT data, we empower everyone who has access to develop new ways to capitalize on that data, speading the IoT’s development.
  7. Seventh, and perhaps most important, we must take privacy and security seriously. What responsible parent would put an IoT baby monitor in their baby’s room after the highly-publicized incident when a hacker exploited the manufacturer’s disregard for privacy and spewed a string of obscenities at the baby? Unless everyone in the field takes privacy and security seriously, the public may lose faith in the IoT.

There you have ’em: my best analysis of how the Internet of Things will require a revolution not just in technology, but also management strategy and practices. What do you think?

Apple ResearchKit will launch medical research paradigm shift to crowd-sourcing

Amidst the hoopla about the new MacBook and much-anticipated Apple Watch, Apple snuck something into Monday’s event that blew me away (obligatory disclaimer: I work part-time at The Apple Store, but the opinions expressed here are mine).

My Heart Counts app

Four years after I proselytized about the virtues of democratizing data in my Data Dynamite: how liberating data will transform our world book (BTW: pardon the hubris, but I still think it’s the best thing out there about the attitudinal shift needed to capitalize on sharing data), I was so excited to learn about the new ResearchKit.

Tag line? “Now everybody can do their part to advance medical research.”

The other new announcements might improve your quality of life. This one might save it!

As Senior VP of Operations Jeff Williams said in announcing the kit,  the process of medical research ” ..hasn’t changed in decades.” That’s not really true: as I wrote in my book, the Quantified Self movement has been sharing data for several years, as well as groups such as CureTogether and PatientsLikeMe. However, what is definitely true is that no one has harnessed the incredible power of the smartphone for this common goal until now, and that’s really incredible. It’s a great example of my IoT Essential Truth of asking “who else could use this data?

A range of factors cast a pall over traditional medical research.

Researchers have had to cast a broad net even to get 50-100 volunteers for a clinical trial (and may have to pay them, to boot, placing the results validity when applied to the general population in doubt).  The data has often been subjective (in the example Williams mentioned, Parkinson’s patients are classified by a doctor simply on the basis of walking a few feet). Also, communication about the project has been almost exclusively one way, from the researcher to the patient, and limited, at best.

What if, instead, you just had to turn on your phone and open a simple app to participate? As the website says, “Each one [smartphone] is equipped with powerful processors and advanced sensors that can track movement, take measurements, and record information — functions that are perfect for medical studies.” Suddenly research can be worldwide, and involve millions of diverse participants, increasing the data’s amount and validity (There’s a crowdsourcing research precedent: lot of us have been participating in scientific crowdsourcing for almost 20 years, by installing the SETI@Home software that runs in the background on our computers, analyzing data from deep space to see if ET is trying to check in)!

Polymath/medical data guru John Halamka, MD wrote me that:

“Enabling patients to donate data for clinical research will accelerate the ‘learning healthcare system’ envisioned by the Institute of Medicine.   I look forward to testing out Research Kit myself!”

The new apps developed using ResearchKit harvest information from the Health app that Apple introduced as part of iOS8. According to Apple:

“When granted permission by the user, apps can access data from the Health app such as weight, blood pressure, glucose levels and asthma inhaler use, which are measured by third-party devices and apps…. ResearchKit can also request from a user, access to the accelerometer, microphone, gyroscope and GPS sensors in iPhone to gain insight into a patient’s gait, motor impairment, fitness, speech and memory.

Apple announced that it has already collaborated with some of the world’s most prestigious medical institutions, including Mass General, Dana-Farber, Stanford Medical, Cornell and many others, to develop apps using ResearchKit. The first five apps target asthma, breast cancer, cardiovascular disease, diabetes and Parkinson’s disease.  My favorite, because it affects the largest number of people, is the My Heart Counts one. It uses the iPhone’s built-in motion sensors to track participants’ activity, collecting data during a 6-minute walk test from those who are able to walk that long. If participants also have a wearable activity device connecting with the Health app (aside: still don’t know why my Jawbone UP data doesn’t flow to the Health app, even though I made the link) , they are encouraged to use that as well. Participants will also enter data about their heart disease risk factors and their lab tests readings to get feedback on their chances of developing heart disease and their “heart age.” Imagine the treasure trove of cardiac data it will yield!

 A critical aspect of why I think ResearchKit will be have a significant impact is that Apple decided t0 make it open source, so that anyone can tinker with the code and improve it (aside: has Apple EVER made ANYTHING open source? Doubt it! That alone is noteworthy).  Also, it’s important to note, in light of the extreme sensitivity of any personal health data, that Apple guarantees that it will not have access to any of the personal data.

Because of my preoccupation with “Smart Aging,” I’m really interested in whether any researchers will specifically target seniors with ResearchKit apps. I’ll be watching carefully when the Apple Watch comes out April 24th to see if seniors buy them (not terribly optimistic, I must admit, because of both the cost and the large number of seniors I help at The Apple Store who are befuddled by even Apple’s user-friendly technology) because the watch is a familiar form factor for them (I haven’t worn a watch since I got my first cell phone, and most young people I know have never had one) and might be willing to use them to participate in these projects.

N0w, if you’ll excuse me, I just downloaded the My Heart Counts app, and must find out my “heart age!”


 

Doh!  Just after I posted this, I saw a really important post on Ars Technica pointing out that this brave new world of medical research won’t go anywhere unless the FDA approves:

“As much as Silicon Valley likes to think of itself as a force for good, disrupting this and pivoting that, it sometimes forgets that there’s a wider world out there. And when it comes to using devices in the practice of medicine, that world contains three very important letters: FDA. That’s right, the US Food and Drug Administration, which Congress has empowered to regulate the marketing and research uses of medical devices.

“Oddly, not once in any of the announcement of ResearchKit did we see mention of premarket approval, 510k submission, or even investigational device exemptions. Which is odd, because several of the uses touted in the announcement aren’t going to be possible without getting the FDA to say yes.”

I remember reading that Apple had reached out to the FDA during development of the Apple Watch, so I’m sure none of this comes as a surprise to them, and any medical researcher worth his or her salt is also aware of that factor. However, the FDA is definitely going to have a role in this issue going forward, and that’s as it should be — as I’ve said before, with any aspect of the IoT, privacy and security is Job One.

 

 

IFTTT DO apps: neat extension of my fav #IoT crowdsourcing tool!

Have I told you lately how much I love IFTTT? Of course!  As I’ve said, I think they are a phenomenal example of my IoT “Essential Truth” question: who else can use this data?

IFTTT_DO_buttonNow, they’ve come up with 3 new apps, the “DO button,” “DO camera,” and “DO Note,” that make this great tool even more versatile!

With a DO “recipe,” you simply tap on the appropriate app, and the “recipe” runs. Presto! Change-o!

As a consultant who must bill for his time, I particularly like the one that lets you “Track Your Work hours” on Google Drive, but you’re sure to find your own favorites in categories such as play, work, home, families, and essentials. Some are just fun, and some will increase your productivity or help manage your household more easily (hmm: not sure where “post a note to your dog’s timeline” fits in (aside to my sons: feel free to “send notes to your data via email”.  If past experience is any indication, there should be many, many more helpful “Do” recipes as soon as users are familiar with how to create them.

As I’ve said before, it’s no reflection on the talented engineers at HUE, NEST, et. al., but there’s simply no way they could possibly visualize all the ways that their devices could be used and/or combined with others, and that’s why IFTTT, by adding the crowdsourcing component and democratizing data, is so important to speeding the IoT’s deployment.

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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.

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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.

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IoT: What Can You Do That You Couldn’t? Heavy Construction

Not sure why, but I’m particularly fascinated by how the IoT can transform parts of the economy that have been around for more than 100 years, such as the way the Union Pacific uses it to reduce derailments — and worse.

One of those tradition-bound industries where the IoT Essential TruthWhat Can You Do Now That You Couldn’t Do Before” is starting to revolutionize both daily practices and strategy is heavy construction, both for buildings and public works.

First of all, heavy construction is inherently dangerous, so anything that can be done to manage that danger is beneficial.

Lots of very heavy machinery; many people, frequently on foot; almost impossible to coordinate all of them in the past, especially as vehicles enter and leave the site.  According to OSHA, in the US alone, 796, or 20.3% of all workers killed on the job in 2003 were killed on construction sites, primarily through falls, struck by objects, electrocution or “caught-in-between.” Of those, lack of coordination probably resulted in most of the struck by objects and “caught-in-between” deaths.

One of the most exciting developments in that regard is SAP’s demonstration program with SK Solutions, which makes anti-collision software, on a construction site in Dubai. They are capitalizing on new construction cranes and construction vehicle  that have sensors built in so their real-time location can be determined instantly. SAP and SK Solutions combine sensor-based data – such as 3-D motion control, location, load weight, equipment usage and wind speed – to avoid collisions with trucks  to enhance worker safety, improve productivity and reduce costs. The site and project managers monitor the equipment via a dashboard.

Less dramatic than collision avoidance is the way that construction companies are using real-time data from the equipment to maximize operating efficiency and reduce maintenance costs through innovations such as “predictive maintenance.”  As my Boston IoT MeetUp co-director Chris Rezendes of INEX Advisors discussed at the recent Association of Equipment Management Professionals Asset Management Symposium, “instrumentation of assets” through digital plans and models, sensors, data and embedded communication devices in buildings and bridges is becoming a key differentiator in the industry. According to Rezendes:

““Everybody in tech wants to instrument your assets, inventories, operations, people and processes… They are looking at instrumenting all manner of industrial machines, equipment and more. And they’re doing it really well…. You should feel threatened, at least a little bit, by big technology companies trying to instrument your assets for you, maybe to you… I’m going to tell it to you straight: He or she who controls the intelligence–the data about those assets, inventories and areas of operation–will control that market, the customer, the regulatory environment and the supply chain. They will control you.”

What a seismic shift from the old days of heavy construction, which was largely a matter of brute force and difficult demands on operators to remain always vigilant in the midst of loud noises.  Add in the sensors that these construction crews are now embedding in bridges’ structure and in buildings to monitor a wide range of stresses and environmental conditions, and the conclusion is inescapable: every industry can and will be fundamentally altered in the coming decade as equipment and processes begin switch the requirements from brawn to brains.

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My take on the IoT at CES

Here I am languishing in bitterly-cold Massachusetts, while all the cool kids are playing with toys at CES!  I’ll try to get over it and give you my impressions of the Internet of Things new product introductions, as filtered through the lens of my IoT Essential Truths:

  • Perhaps the most important development is Samsung’s whole-hearted embrace of the IoT, building on its acquisition of SmartThings.  In his keynote, Samsung CEO BK Yoon struck exactly the right notes, emphasizing the need for open standards and collaboration.Within 5 years, all new Samsung products will be IoT enabled.Don’t forget that Samsung doesn’t just make consumer products, but also critical IoT tools such as sensors and chips.  Its 3-D range sensors that can detect tiny movements may be a critical IoT components.SmartThings CEO Alex Hawkinson was part of the presentation, and stressed:

    “For the Internet of Things to be a success, it has to be open, Any device, from any platform, must be able to connect and communicate with one another. We’ve worked hard to accomplish this, and are committed to putting users first, giving them the most choice and freedom possible.”

  • If was accurate, the GoBe calorie counter could be a great Quantified Self device. I still find it waaay to time-consuming and laboriously to look up specific foods’ caloric content and enter them into an app. However, The Verge says not so fast…..  What might be feasible is the InBody Bend, to measure the result of those calories — your body fat — and your heart rate. It’s also a pedometer and measures your calories burned. Oh, yeah, the Bend also tells time. Best of all, it will go 7-8 days between charges.
  • The HereO children’s watches seem like a great product for worried parents, allowing them to locate the wee ones via GPS.
  • While I think the key to realizing my “Smart Aging” paradigm shift will primarily be tweaking mainstream IoT Quantified Self and smart home devices for seniors’ special needs, there are some issues, such as hearing loss, that particularly affect seniors. In that category, Siemens’ Smart Hearing Aid looks promising, and an interesting example of enhancing a not-so-great existing product using IoT capabilities. A key is the unobtrusive clip-on easyTek  which complements the in-ear device, and can connect (via Bluetooth) to smartphones, computers or TVs, so that the hearing aides also function as earphones for those devices. As The Verge reports, even those with good hearing might end up using it.
  • However, my two favorite CES intros both enhance a decidedly 19th-century product, the bike.They illustrate the Essential TruthWhat Can You Do Now That You Couldn’t Do Before?
    Smart Pedal

    Smart Pedal

    One is a nifty substitute for a plain-vanilla pedal, from Connected Cycle. On a day-in-day-out basis, the pedal is a Quantified Self device, recording your speed, route, incline, and calories burned.

    However, when some miscreant steals your ride, it’s the two-wheel equivalent of Find My iPhone, telling you and the cops exactly where the bike’s located.

    Ok, that’s nice, but the other bike device introduced at CES can save your life!

    Smart Bike Helmet

    In the spirit of IoT collaboration, Volvo, Ericsson & sporting goods manufacturer POC have worked together on a smart helmet.

    The bike’s and the car’s locations are both uploaded to the cloud.

    If the  helmet is connected to a bike app such as Strava, built-in warning lights warn it there’s a car nearby, while a heads-up display on the dash warns the driver at the same time.

    I can’t see Volvo gaining any competitive advantage from this, and, of course, the technology will really only be effective if every hemet and every car are equipped with it, so I hope the partners will release it for universal adoption. Who would have ever thought that the IoT could peacefully bring bicyclists and motorists together. Just shows you that with the IoT, we’ll have to re-examine a lot of long-held beliefs!

 

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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!

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My #IoT predictions for 2015

I was on a live edition of “Coffee Break With Game-Changers” a few hours ago with panelists Sherryanne Meyer of Air Products and Chemicals and Sven Denecken of SAP, talking about tech projections for 2015.

Here’s what I said about my prognostications:

“I predict that 2015 will be the year that the Internet of Things penetrates consumer consciousness — because of the Apple Watch. The watch will unite both health and smart home apps and devices, and that will mean you’ll be able to access all that usability just by looking at your watch, without having to fumble for your phone and open a specific app.

If Apple chooses to share the watch’s API on the IFTTT – If This Then That — site, the Apple phone’s adoption – and usability — will go into warp speed. We won’t have to wait for Apple or developers to come up with novel ways of using the phone and the related devices — makers and just plain folks using IFTTT will contribute their own “recipes” linking them. This “democratization of data” is one of the most powerful – and under-appreciated – aspects of the IoT. In fact, Sherryanne, I think one of the most interesting IoT strategy questions for business is going to be that we now have the ability to share real time data with everyone in the company who needs it – and even with supply chain and distribution networks – and we’ll start to see some discussion of how we’ll have to change management practices to capitalize on this this instant ability to share.

(Sven will be interested in this one) In 2015, the IoT is also going to speed the development of fog computing, where the vast quantities of data generated by the IoT will mean a switch to processing data “at the edge,” and only passing on relevant data to the cloud, rather than overwhelming it with data – most of which is irrelevant.

In 2015 the IoT is also going to become more of a factor in the manufacturing world. The success of GE’s Durathon battery plant and German “Industry 4.0” manufacturers such as Siemans will mean that more companies will develop incremental IoT strategies, where they’ll begin to implement things such as sensors on the assembly line to allow real-time adjustments, then build on that familiarity with the IoT to eventually bring about revolutionary changes in every aspect of their operations.

2015 will also be the year when we really get serious about IoT security and privacy, driven by the increasing public concern about the erosion of privacy. I predict that if anything can hold back the IoT at this point, it will be failure to take privacy and security seriously. The public trust is extremely fragile: if even some fledgling startup is responsible for a privacy breach, the public will tend to tar the entire industry with the same brush, and that could be disastrous for all IoT firms. Look for the FTC to start scrutinizing IoT claims and levying more fines for insufficient security.”

What’s your take on the year ahead? Would love your comments!

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