The Internet of Things’ Essential Truths

Posted on 17th March 2015 in collaboration, communication, data, Essential Truths, Internet of Things, M2M, management, manufacturing, marketing, open data, paradigm shift, privacy, security, strategy, supply chain

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?

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Remember: The IoT Is Primarily About Small Data, Not Big

Posted on 16th March 2015 in data, Internet of Things, M2M, management, manufacturing, open data

In one of my fav examples of how the IoT can actually save lives, sensors on only eight preemies’ incubators at Toronto’s Hospital for Sick Children yield an eye-popping 90 million data points a day!  If all 90 million data points get relayed on to the “data pool,” the docs would be drowning in data, not saving sick preemies.

Enter “small data.”

Writing in Forbes, Mike Kavis has a worthwhile reminder that the essence of much of the Internet of Things isn’t big data, but small. By that, he means:

“a dataset that contains very specific attributes. Small data is used to determine current states and conditions  or may be generated by analyzing larger data sets.

“When we talk about smart devices being deployed on wind turbines, small packages, on valves and pipes, or attached to drones, we are talking about collecting small datasets. Small data tell us about location, temperature, wetness, pressure, vibration, or even whether an item has been opened or not. Sensors give us small datasets in real time that we ingest into big data sets which provide a historical view.”

Usually, instead of aggregating  ALL of the data from all of the sensors (think about what that would mean for GE’s Durathon battery plant, where 10,000 sensors dot the assembly line!), the data is originally analyzed at “the edge,” i.e., at or near the point where the data is collected. Then only the data that deviates from the norm (i.e., is significant)  is passed on to to the centralized data bases and processing.  That’s why I’m so excited about Egburt, and its “fog computing” sensors.

As with sooo many aspects of the IoT, it’s the real-time aspect of small data that makes it so valuable, and so different from past practices, where much of the potential was never collected at all, or, if it was, was only collected, analyzed and acted upon historically. Hence, the “Collective Blindness” that I’ve written about before, which limited our decision-making abilities in the past. Again, Kavis:

“Small data can trigger events based on what is happening now. Those events can be merged with behavioral or trending information derived from machine learning algorithms run against big data datasets.”

As examples of the interplay of small and large data, he cites:

  • real-time data from wind turbines that is used immediately to adjust the blades for maximum efficiency. The relevant data is then passed along to the data lake, “..where machine-learning algorithms begin to understand patterns. These patterns can reveal performance of certain mechanisms based on their historical maintenance record, like how wind and weather conditions effect wear and tear on various components, and what the life expectancy is of a particular part.”
  • medicine containers with smart labels. “Small data can be used to determine where the medicine is located, its remaining shelf life, if the seal of the bottle has been broken, and the current temperature conditions in an effort to prevent spoilage. Big data can be used to look at this information over time to examine root cause analysis of why drugs are expiring or spoiling. Is it due to a certain shipping company or a certain retailer? Are there re-occurring patterns that can point to problems in the supply chain that can help determine how to minimize these events?”

Big data is often irrelevant in IoT systems’ functioning: all that’s needed is the real-time small data to trigger an action:

“In many instances, knowing the current state of a handful of attributes is all that is required to trigger a desired event. Are the patient’s blood sugar levels too high? Are the containers in the refrigerated truck at the optimal temperature? Does the soil have the right mixture of nutrients? Is the valve leaking?”

In a future post, I’ll address the growing role of data scientists in the IoT — and the need to educate workers on all levels on how to deal effectively with data. For now, just remember that E.F. Schumacher was right: “small is beautiful.”

 

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

Posted on 23rd February 2015 in collaboration, data, Internet of Things, M2M, management, privacy, security, strategy, Uncategorized

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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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!

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The #IoT Can Kill You! Got Your Attention? Car Security a Must

Posted on 11th February 2015 in automotive, data, government, Internet of Things, M2M, marketing, mobile, privacy, security, transportation, US government

The Internet of Things can kill you.

Got your attention? OK, maybe this is the wake-up call the IoT world needs to make certain that privacy and security are baked in, not just afterthoughts.

Markey_IoT_car_reportI’ve blogged before about how privacy and security must be Job 1, but now it’s in the headlines because of a new report by our Mass. Senator, Ed Markey (Political aside: thanks, Ed, for more than 30 years of leadership — frequently as a voice crying in the wilderness — on the policy implications of telecomm!), “Tracking & Hacking: Security & Privacy Gaps Put American Drivers at Risk,” about the dangers of not taking the issues seriously when it comes to smart cars.

I first became concerned about this issue when reading “Look Out, He’s Got an Phone,!” (my personal nominee for all-time most wry IoT headline…), a litany of all sorts of horrific things, such as spoofing the low air-pressure light on your car so you’ll pull over and the Bad Guys can get it would stop dead at 70 mph,  that are proven risks of un-encrypted automotive data.  All too typical was the reaction of Schrader Electronics, which makes the tire sensors:

“Schrader Electronics, the biggest T.P.M.S. manufacturer, publicly scoffed at the Rutgers–South Carolina report. Tracking cars by tire, it said, is ‘not only impractical but nearly impossible.’ T.P.M.S. systems, it maintained, are reliable and safe.

“This is the kind of statement that security analysts regard as an invitation. A year after Schrader’s sneering response, researchers from the University of Washington and the University of California–San Diego were able to ‘spoof’ (fake) the signals from a tire-pressure E.C.U. by hacking an adjacent but entirely different system—the OnStar-type network that monitors the T.P.M.S. for roadside assistance. In a scenario from a techno-thriller, the researchers called the cell phone built into the car network with a message supposedly sent from the tires. ‘It told the car that the tires had 10 p.s.i. when they in fact had 30 p.s.i.,’ team co-leader Tadayoshi Kohno told me—a message equivalent to ‘Stop the car immediately.’ He added, ‘In theory, you could reprogram the car while it is parked, then initiate the program with a transmitter by the freeway. The car drives by, you call the transmitter with your smartphone, it sends the initiation code—bang! The car locks up at 70 miles per hour. You’ve crashed their car without touching it.’”

Hubris: it’ll get you every time….

So now Senator Markey lays out the full scope of this issue, and it should scare the daylights out of you — and, hopefully, Detroit! The report is compiled on responses by 16 car companies (BMW, Chrysler, Ford, General Motors, Honda, Hyundai, Jaguar Land Rover, Mazda, Mercedes-Benz, Mitsubishi, Nissan, Porsche, Subaru, Toyota, Volkswagen (with Audi), and Volvo — hmm: one that didn’t respond was Tesla, which I suspect [just a hunch] really has paid attention to this issue because of its techno leadership) to letters Markey sent in late 2013. Here are the damning highlights from his report:

“1. Nearly 100% of cars on the market include wireless technologies that could pose vulnerabilities to hacking or privacy intrusions.

2. Most automobile manufacturers were unaware of or unable to report on past hacking incidents.

3. Security measures to prevent remote access to vehicle electronics are inconsistent and haphazard across all automobile manufacturers, and many manufacturers did not seem to understand the questions posed by Senator Markey.

4. Only two automobile manufacturers were able to describe any capabilities to diagnose or meaningfully respond to an infiltration in real-time, and most say they rely on technologies that cannot be used for this purpose at all. (my emphasis)

5. Automobile manufacturers collect large amounts of data on driving history and vehicle performance.

6. A majority of automakers offer technologies that collect and wirelessly transmit driving history data to data centers, including third-party data centers, and most do not describe effective means to secure the data.

7. Manufacturers use personal vehicle data in various ways, often vaguely to “improve the customer experience” and usually involving third parties, and retention policies – how long they store information about drivers – vary considerably among manufacturers.

8. Customers are often not explicitly made aware of data collection and, when they are, they often cannot opt out without disabling valuable features, such as navigation.”

In short, the auto industry collects a lot of information about us, and doesn’t have a clue how to manage or protect it.

I’ve repeatedly warned before that one of the issues technologists don’t really understand and/or scoff at, is public fears about privacy and security. Based on my prior work in crisis management, that can be costly — or fatal.

This report should serve as a bit of electroshock therapy to get them (and here I’m referring not just to auto makers but all IoT technologists: it’s called guilt by association, and most people tend to confabulate fears, not discriminate between them. Unless everyone in IoT takes privacy and security seriously, everyone may suffer the result [see below]) to realize that it’s not OK, as one of the speakers at the Wearables + Things conference said, that “we’ll get to privacy and security later.” It’s got to be a priority from the get-go (more about this in a forthcoming post, where I’ll discuss the recent FTC report on the issue).

I’ve got enough to worry about behind the wheel, since the North American Deer Alliance is out to get me. Don’t make me worry about false tire pressure readings.

PS: there’s another important issue here that may be obscured: the very connectedness that is such an important aspect of the IoT. Remember that the researchers spoofed the T.P.M.S. system not through a frontal assault, but by attacking the roadside assistance system? It’s like the way Target’s computers were hacked via a small company doing HVAC maintenance. Moral of the story? No IoT system is safe unless all the ones linking to it are safe.  For want of a nail … the kingdom was lost!

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I Have Seen the Future of Agriculture & It is the IoT (Grove Labs)

Posted on 28th January 2015 in agriculture, design, energy, environmental, home automation, Internet of Things, M2M, smart home

Agriculture is a passion of mine, partially because of environmental concerns, and also because I love veggie gardening. There has been an encouraging trend in the US recently, with the advent of Community Supported Agriculture (CSA) and the localvore movement. However, that’s counterbalanced by the terrible continuing California drought, and the sobering realization that, worldwide, there are more than 805 million who are undernourished. Clearly, we need to produce more food — and do it much more efficiently and in line with natural principles.

Grove Labs Aquaponics system

That’s why I’m so excited about the new Grove Labs system being developed in, of all places, Somerville MA (which has become a start-up haven for ag-related companies through the Greentown Labs incubator. They include Freight Farms [ I will blog about them later..], which is pursuing a similar closed-loop approach on a larger scale, and Apitronics, which presented at one of our Boston IoT Meetups last year.).

It was developed by two young MIT grads, Jamie Byron (who became “obsessed” with the problems of current worldwide agriculture while on an internship) and Gabe Blanchet, who created the primitive precursor of the aquaponics system in their frat house. Now, in its beta testing form (sign up ASAP if you live in the Hub to buy a prototype!), the “Grove” is an integrated ecosystem attractive enough to be placed in your kitchen.

According to The Verge  (which pointed out that dope growers’ experience with hydroponics may have helped Byron and Blanchet, LOL!):

“The Grove system looks like a 6-foot-tall wood cabinet with four LED-lit boxes for plants. Three are smaller, for leafy greens and herbs, and one is larger, for things like tomatoes or peas. On the bottom left is an aquarium whose fish provide fertilizer for the plants. The fish are what make the system ‘aquaponic,’ a particularly organic variant on traditional hydroponics.

….” ‘Essentially we took the philosophy and biology of an actual ecosystem and shrunk it down and put it in a bookshelf tower,’ Blanchet says. The fish produce ammonia in their waste, which gets pumped to the plants, where bacteria convert the ammonia to nitrate. The plants consume the nitrate, filtering the water, which gets returned to the fish. ‘If you keep the system running optimally you can grow plants faster than you can outside,’ says Blanchet.”

A critical component that qualifies the system as an IoT one is the “Grove” app, which will tell owners important information about lighting schedules, when to add nutrients, etc. The all-important sensors will provide critical real-time data about growing conditions and what’s needed.

The Grove isn’t a panacea for world hunger: for one thing, it’s pricey ($2600), although economies of scale when the company is in full swing may bring that down. It also requires involvement by the owner: you can’t just sit there and admire how things grow. You’ll need to actively monitor the app and do routine maintenance. The LED lighting system, as efficient as it may be, won’t work in remote, poor areas where there’s no electricity (but that might come from an nearby PV panel!

Nonetheless, I can see the grove playing a growing (groan, sorry for the pun..) role in meeting the world’s food needs, and, best of all, doing so in a way that capitalizes on one of my key beliefs about the IoT, that it will bring about an era of unprecented precision in use of raw materials, manufacturing, whatever, because of real-time monitoring, and, increasingly, M2M systems where a sensor reading on one device will trigger operation of another. Large-scale farming is also getting more precise due to systems such as John Deere’s FarmSight, so count agriculture as yet another industry that will be revolutionized through the IoT.

The Grove Labs approach really resonated with me because I’ve been using two 8′ x 4′ 30″ high modules for my own veggies for the last twenty years, planted according to engineer/gardener Mel Bartholomew’s great “Square Foot Gardening” system, with varying levels of success. I had grand visions of manufacturing modules from recycled plastics and adding greenhouse-fabric domes to extend the season, and an app to remind owners of when to plant and fertilize but never followed through, so I really admire those who did, and the way they’re incorporating IoT technology.

New Alchemy’s Institute’s “Ark” (in rear)

When I contacted the co-founders, they were unaware that they stand on the shoulders of giants who have developed a natural systems-based approach to agriculture right here in the Bay State, especially John Todd, who (I believe) pioneered the approach with his wonderful New Alchemy Institute on the Cape, where he methodically added new elements — plexiglas water storage, tilapia, etc. — to the passive-solar “Ark” until he had a balanced, self-sustaining system.  John, who has since gone on to develop great natural-systems based wastewater treatment facilities, had a young apprentice, Greg Watson, who went on to become the Commonwealth’s incredibly innovative ag commissioner.

Oh well, it appears these guys have more than reinvented the wheel! Good luck to them.

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Management Challenge: Lifeguards in the IoT Data Lake

Posted on 20th January 2015 in collaboration, data, Essential Truths, Internet of Things, M2M, management, manufacturing, open data, paradigm shift, strategy, supply chain

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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Good Checklist for Creating #IoT Strategy

Posted on 15th January 2015 in design, Essential Truths, Internet of Things, M2M, management, paradigm shift, 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!

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IoT Security After “The Interview”

Posted on 22nd December 2014 in defense, Internet of Things, M2M, management, privacy, security, US government

Call me an alarmist, but in the wake of the “Interview” catastrophe (that’s how I see it in terms of both the First Amendment AND asymmetrical cyberwarfare), I see this as a clarion call to the #IoT industry to redouble efforts to make both security AND privacy Job #1.

Here’s the deal: if we want to enhance more and more parts of governmental, commercial, and private lives by clever IoT devices and apps to control them, then there’s an undeniable quid pro quo: we MUST make these devices and apps as secure as possible.

I remember some bright young entrepreneurs speaking at a recent wearables conference, where they apologized for not having put attention on privacy and security yet, saying they’d get to it early next year.

Nope.

Unacceptable.

Security must be built in from the beginning, and constantly upgraded as new threats emerge.  I used to be a corporate crisis manager, and one of the things that was so hard to convince left-brained, extremely rational engineers about was that just because fears were irrational didn’t mean they weren’t real — even the perception of insecure IoT devices and apps has the potential to kill the whole industry, or, as Vanity Fair‘s apocalyptic “Look Out, He’s Got a Phone” article documented, it could literally kill us. As in deader than a doornail.

This incident should have convinced us all that there are some truly evil people out there fixated on bringing us to our collective knees, and they have the tech savvy to do it, using tools such as Shodan. ‘Nuff said?

PS: Here’s what Mr. Cybersecurity, Bruce Schneier, has to say on the subject. Read carefully.

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My #IoT predictions for 2015

Posted on 10th December 2014 in collaboration, data, Essential Truths, health, home automation, Internet of Things, m-health, M2M, management, manufacturing, open data, paradigm shift, privacy, Quantified Self, security, smart home, strategy, supply chain, voice-overs

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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