Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

4 principles to get full benefit of the Internet of Things


Published on

The 4 "Essential Truths" your strategy needs to get the full benefits of the IoT

Published in: Business
  • Be the first to comment

  • Be the first to like this

4 principles to get full benefit of the Internet of Things

  1. 1. I get excited as the next guy at the incredibly cool new devices and services made possible by the IoT — particularly love this one, the AliveCor. It attaches to the back of your phone, and, in 30 seconds, can give you an FDA-approved accurate ECG reading of your heart — BUT, we’re falling way short of the IoT’s potential for change if we
  2. 2. stop with cool things, because I believe..
  3. 3. .. that the IoT can fundamentally transform our companies and economy ..
  4. 4. •Creating new revenue streams •Delighting customers •Building precision manufacturing •Breaking down information silos •Protecting the planet .. and I could go on all day with other benefits that were impossible to achieve before the IoT! But there’s more to achieving these
  5. 5. breakthroughs than great technology and cool apps, and that’s why my title mentioned Albert Einstein, who famously said…
  6. 6. But,as Albert Einstein said, “You can never solve a problem on the level on which it was created,” or as it’s often paraphrased, “you can’t solve a problem with the same thinking that created it.” We simply won’t realize all of those benefits if we just incorporate IoT technology into our conventional ways of doing business. Capitalizing on the
  7. 7. full potential of the IoT will require that we not only use new technology, but that we make dramatic changes in the thinking and assumptions that underlie our current economy and, unless that mentality is abandoned, will create a drag on the IoT.
  8. 8. These principles — what I call the Essential Truths of the IoT — are dramatic breaks with the past: 1.Make Privacy and Security the Highest Priority. 2.Share Data. 3.Close the Loop. 4.Redesign Products. Let’s explore each of them and why
  9. 9. they are so important to realizing the IoT’s full potential.
  10. 10. I used to list this as the fourth IoT Essential Truth to consider at all times, but I’ve decided to leapfrog it to No. 1, because the sad reality is that not enough companies take privacy and security seriously — right from the beginning. It’s critical to Truth #2, Sharing data, because sharing data in new ways immediately creates risks that it
  11. 11. will be shared inappropriately, especially if it concerns highly personal issues such as health and finances.
  12. 12. Recently there has been a spate of scare headlines about Shodan, which bills itself as the “search engine for the Internet of Things.” I first warned three years ago about the need to take strong security measures, such as NOT using the Real Time Streaming Protocol (RTSP) without requiring password authentication, in order to avoid having a data feed from your
  13. 13. device showing up for anyone to monitor on Shodan. Yet, the amazing array of feeds Shodan provides today, from baby cams to marijuana plantations, shows that privacy and security are still not a high enough priority for many IoT developers.
  14. 14. This is an issue that I know more about than most in the IoT world do. You see, in a prior incarnation, I was was a crisis management consulting for Fortune 100 companies that had done dumb things, and now were in serious, serious trouble with the public, government, and media. Most frequently, the decision makers involved were engineers, and they
  15. 15. seemed particularly insensitive to the role that FEAR played in the public’s reactions to their deeds. A common comment by the engineers, understandable because they were so left-brained and analytical, was to dismiss the validity of fears because they weren’t fact based and rational. What these engineers didn’t seem to understand was that, no matter what its basis, this fear was very real to the public, and they dismissed that perception at their risk. That fear factor is even greater with the Internet of Things, because it often involves personal data mentioned above, or products that, in the wrong hands, could actually kill someone, as with the Jeep that two “white-hat” hackers took over by exploiting a security flaw not in
  16. 16. the car’s drive electronics, but its lowly entertainment system.
  17. 17. That’s why a flip remark by a young developer at the Wearables + Things conference who blithely dismissed the fact he hadn’t addressed security yet “because we’re just a startup – we’ll get to that later” was so distressing to me: with the IoT, you don’t have the luxury of waiting until later to add security and privacy features. They must be an
  18. 18. integral part of the product or service from Day One.
  19. 19. In part that’s because of another reality of crisis management: it is very hard to build public confidence, especially in a new technology where people have immediate fears of personal information being shared intentionally or by hackers – and incredibly easy to lose it. Equally important, fear doesn’t make nice distinctions between the
  20. 20. good guys who design in security and privacy protections and those who don’t: if there are a few high-profile security leaks (one example involved a baby monitor that totally ignored privacy controls, and was hacked. The FTC came down hard on TRENDnet, which had the dubious distinction of receiving the first enforcement action in the IoT arena.), it could undermine the entire industry.
  21. 21. Privacy and security are likely to be never-ending challenges to the IoT industry, because of the proliferation of devices, hackers’ skills, and the vulnerability of sensors, the weakest link, which must be designed to be cheap and to last for many years, making them more easily hacked as hackers’ skills increase. I’d advise that you follow the lead
  22. 22. of some companies that adopt a “privacy by design” strategy: As Gulio Corragio puts it “the principle of data protection by design requires data protection to be embedded within the entire life cycle of the technology, from the very early design stage, right through to its ultimate deployment, use and final disposal. This should also include the responsibility for the products and services used by the controller or processor.”
  23. 23. Individual efforts aren’t enough: more industry-wide collaborations, such as the IoT Trustworthy Working Group are critical. Equally important, though controversial in some industry circles, IoT companies should become active participants in collaborative efforts such as the FTC’s workshop in 2014 to create tough but workable IoT government regulations. These
  24. 24. regulations, provided they are performance-based, rather than prescriptive (which would limit the development of breakthrough IoT technologies), are important to building IoT credibility in the public eye: there have to be penalties for those who don’t take privacy and security seriously because the alternative will be public distrust. .
  25. 25. After assuring privacy and security, sharing data is the next most important Essential Truth, because it is so different from the principle that has been ingrained in us for so long: hoard data. One day in 1789, a young man with few possessions sailed from England to the New World. Few possessions in his hands, that is. In
  26. 26. his head, he held the plans for Arkwright's famous woolen mill. It was illegal to take factory plans from the country at the time because they gave England such an economic advantage, but no one knew what was stored in young Samuel Slater's memory, and when he arrived in Pawtucket, Rhode Island he used that knowledge to build America's first woolen mill, becoming the father of America’s industrial revolution. For the longest time, the kind of proprietary knowledge possessed by the British mill owners was the way to profit: in a zero-sum game, if you had knowledge that I didn't, you were a winner and I was a loser. As recently as the 1980's, the so- called "Massachusetts Miracle" took place because seemingly smart mini-
  27. 27. computer companies built their success around proprietary operating systems that made their customers dependent on them — that is, until open systems came along.
  28. 28. For the longest time, hoarding data made sense, because it was hard to gather & share data.
  29. 29. Typically, that meant an individual worker had to observe and record a gauge’s reading on paper — usually on a regular schedule. But what happened if there was a pressure spike in between the readings? What if his supervisor forget to check the form? What if there was a critical factor, such as metal fatigue, that couldn’t be detected by a gauge?
  30. 30. It was equally difficult to share what data you could gather: typically the information was paper-based, and had to be distributed from a central location to those who it was thought might need it.
  31. 31. Is it any wonder that these restrictions led naturally to the linear and hierarchical organizational structures that still characterize organizations today, and that it was frequently senior managers who decided who got access to information and when? Even if the Internet and new communications technologies have
  32. 32. allowed us to remove some of those limits to communication, and even though there have been some successful efforts to “flatten” hierarchies and remove layers of management, the flow of data in most companies remains downward — and lateral.
  33. 33. The most profound and potentially far-reaching aspect of the IoT is that — for the first time — everyone who needs real-time data to do their jobs more efficiently and/or make better decisions, can share that data — instantly. • Real-time data. • Shared. • Instantly.
  34. 34. Instead of the traditional “need-to-know” criterion for allowing access to information, we must make a radical transformation. Going forward, the default assumption must be the polar opposite: that management should have to justify limiting access to data. What this sharing of real-time data does more than anything is to provide “ground truth” to everyone involved: i.e., instead of having to act on inference, as in the past, when it was impossible to peer “inside” things, now decisions and actions can be based on information provided by continuous, direct observation (albeit by sensors) instead. Decisions and strategy will be fact based.
  35. 35. Perhaps the most obvious benefit of sharing IoT data is in the field of consumer products. Phillips, the Dutch electronics company, was among the first to realize this. In 2013 they released the Application Programming Interface (API), for their Hue lights. Although individuals had already reverse engineered the interface to create hacks, according to
  36. 36. Hue System Architect George Yanni, “.. we actually want to help and grow and encourage this community, and give them tools and proper documentation. Also, we want to give them commitment that this is the API and we’re going to support it and it won’t change overnight.” As a result of this conscious decision by Phillips to give up control, developers have created a wide range of apps to give the Hue lights new versatility (want to make a “grand entrance” [ whatever that might be!] with your Hue lights? There ‘s a IFTTT – If This Then That – “recipe” for that!). Even more impressive, when multiple companies are willing to share their APIs, developers create apps that can trigger simultaneous actions by multiple devices, even ones from different manufacturers. Now, using
  37. 37. Apple’s HomeKit, you can say “hey, Siri,” it’s time for bed, and the Hue lights will gradually dim, the Schlage front door lock will lock the door, and the EcoBee thermostat will lower several degrees. Because data is shared, it becomes more valuable to each participating company, something that was inconceivable in the old days of hoarding data to gain an advantage. The most important result of that kind of willingness to share data is that it triggers “network effects,” the term coined by Ethernet inventor Robert Metcalfe to describe how each individual device become more powerful as more and more of them are networked. In this case, the data becomes more valuable by being shared, as do the products that are
  38. 38. activated by that data. Think what a profound transition that is from the days of proprietary information confirming a strategic advantage: now companies such as Phillips that encourage sharing of data gain a competitive advantage specifically because their products interface seamlessly with those from other companies, making each of them more valuable when combined than they are in isolation.
  39. 39. Sharing data is also a key contribution of the IoT to corporate organization and efficiency in ways that were also impossible before. Think what a transformation is possible now that various departments whose work necessarily also effects and/or depends on several other ones (for example, the product design department and the
  40. 40. marketing department) can now simultaneously study the implications of real-time data about how products are actually used in the field (provided, that is, that management will allow them simultaneous access!) whereas that was a total mystery in the past, and whatever information was available was probably passed along laterally and sequentially. The potential to examine the same data simultaneously, and, even better, make collaborative decisions can lead to fundamentally better decisions and more efficient operations, because each department brings different interests, needs, skills, and insights. When these are exchanged, each team gains a better understanding of the other’s priorities and concerns, and there’s a high likelihood
  41. 41. that synergistic solutions will emerge from their dialogue that no individual team would have devised working in isolation. Combining insights from various departments and various skill sets can lead to findings that none of the groups could have found by themselves, due to the dialectic resulting from simultaneous access to the data. When doctors in the Neonatal Intensive Care Unit at Toronto’s Hospital for Sick Children teamed with data scientists from IBM in “Project Artemis,” to examine the 90 million data points generated daily by the sensors on eight babies’ incubators, they found something astonishing: a full day before there were any external signs that the infants had developed a serious blood infection (late-onset neonate
  42. 42. sepsis), the team was able to diagnose the condition from patterns in the data: they found a consistent pattern of decreased heart-rate variability and were able to administer antibiotics well before there were visible signs of infection, improving the babies’ chance of survival. The doctors credited their interplay with the data scientists, who obviously brought a different skill set to the issue (as well as the critical infrastructure to process and store the vast amounts of data), around the common set of data as critical to the discovery.
  43. 43. Even more dramatic is what can happen when instantaneous sharing of data extends beyond the company walls. For example, SAP has designed a prototype vending machine which contains a variety of sensors, documenting everything from how many bottles remain in the machine to – if the customer opts in – his or her normal product choices,
  44. 44. which might result in a special real-time discount (not to mention the customer being welcomed by name). The marketing benefits alone are remarkable, but the machine also shares the real-time inventory data with the suppliers, so that a delivery truck that might be headed for a given machine might be instantly rerouted (on a Machine-to-Machine, or M2M, basis) to another one where the inventory is lower because of a a spike in demand due to hot weather.
  45. 45. Similarly, applying the principle of real-time data sharing to a factory setting, assembly-line data might also trigger M2M reordering of components from a supplier (which, I believe, might result in “re-shoring” of industrial jobs, since the benefits of true “just-in-time” deliveries would trump any savings from a supplier half-a-world away whose delivery time would be in
  46. 46. weeks, not hours).
  47. 47. The latest tool to allow this instant sharing of real-time data among all who need it is General Electric’s new “Digital Twin.” According to GE, “Every product out there will have one, and there will be an ability to connect a system, or systems of digital twins, easily. The digital twin is a model of an asset, a product such as a jet engine or a model of the blades in a jet
  48. 48. engine. Sensors on those blades pull the data off and feed them into the digital twin. The digital twin is kept current with the data that is run off the sensors. It is in sync with the reality of the blade. Now we can ask what is the best time to change the blade, how the blade performs, options to get greater efficiency.” According to GE VP William Ruh, they’ve created a wind turbine and twin they call the “Digital Windfarm,” which generates 20% more electricity than a nearby conventional turbine. Think if every department interacting with a given product was able to simultaneously examine this “twin,” and how that could allow them to visualize new synergistic strategies to improve everything from product upgrades to operational
  49. 49. optimization.
  50. 50. Closely allied to the second Essential Truth, the third requires that we must get rid of the old linear flow of information, and instead substitute circular, closed-loop processes in which the data flow leads to analysis, which in turn leads to fine-tuning of the process or other feedback that allows for continuous improvement. For example, the difficulty in the
  51. 51. past of gathering information about how cars were actually driven meant that auto manufacturers operated in a vacuum about what improvements were needed. Even worse, the difficulty of gathering information about the cars’ performance meant that customer opinion, a potentially important source of data, was skewed: it was so difficult to submit criticisms and suggestions that those who were either wildly in love with the car or who hated it were willing to make the effort required, leaving out the opinions of the vast majority of users who weren’t at either extreme. By real-time flow of data from its cars (“iPhones on wheels, as some company wags put it because of their extensive instrumentation), Tesla can get a much better picture of actual driver
  52. 52. experience.
  53. 53. According to GE’s Vice President and Global Technology Director William Ruh, the feedback loop from the company’s many sensor-laden products, from jet turbines to medical imaging devices , has reduced the time it takes for them to design upgrades: “G.E. is adopting practices like releasing stripped-down products quickly, monitoring usage and rapidly
  54. 54. changing designs depending on how things are used by customers. These approaches follow the ‘lean start-up’ style at many software-intensive Internet companies. We’re getting these offerings done in three, six, nine months,’ (Ruh) said. ‘It used to take three years.’
  55. 55. One major benefit of the circular data flow is that it increases accountability. In the past, a department that was involved in the early phases of a project often didn’t receive objective feedback on how the project actually unfolded, minimizing their responsibility for the outcome. One story, apocryphal or not, summarized
  56. 56. the problems with this linear data flow: reportedly GM found out only the first time an owner of a new model in the 1970s went in to get an oil change for the first time that just changing the oil filter required dropping the entire engine, a costly and time-consuming process. Why? Because no one thought to involve a shop mechanic in the design process, and no one else flagged the problem, because each step in the design process took place in isolation from the others. Now, with the IoT, everyone involved with a project is literally “in the loop,” and both has a role in deciding the course of action and has instant access to the data about how it actually operates, so they see the consequences and can also be held accountable.
  57. 57. The circular flow of data also allows various departments that previously worked in isolation and sequentially to collaborate and try a new approach of inter-departmental teamwork. Perhaps the best example of this in current business is W.L. Gore, and its famous “lattice” management style. According to CEO Terri Kelly, “Some of the most
  58. 58. impactful decisions at Gore are made by small teams. Within any team you’ll find people with very different perspectives; they don’t all think alike—and we encourage this. We encourage teams to take a lot of time to come together, to build trust, to build relationships, because we know that if you throw them in a room and they don’t have a foundation of trust, it will be chaotic, it will be political, and people will feel as if they’re being personally attacked. We invest a lot in making our teams effective, so when they have those great debates—where a scientist doesn’t agree with a sales associate, or manufacturing doesn’t agree with a product specialist—the debate happens in an environment where everyone is looking for a better solution,
  59. 59. versus ‘you win, I lose.’” The circular data flow, as mention previously, also means that everyone gets valuable feedback on the consequences of their actions and on how things actually work. That leads us to the 4th IoT Essential Truth, that we must re-design products.
  60. 60. Products gain new stature with the Internet of Things. This is largely because of the fact that the ability to monitor them constantly after they leave the factory means IoT products mean we’re no longer clueless about how products actually work after they leave the factory floor, and remain a dynamic part of the daily operations, rather
  61. 61. than an end product that’s no longer part of the flow. Products become players.
  62. 62. Perhaps the most significant example of this transition is that IoT- enabled products improve product reliability, both for the end user and the manufacturer. We can now do “predictive maintenance,” intervening at the first signs of metal fatigue, decreased performance or other metrics. Instead of finding out only after the product has failed,
  63. 63. sometimes catastrophically, a jet turbine can be fixed the next time the plane lands, minimizing cost and inconvenience.
  64. 64. In some cases, products redesigned around the IoT can actually be repaired, and even upgraded, remotely, because of two- way communication. In early 2014, GM and Tesla both faced product recalls. The GM one was terribly handled, costing people their jobs, millions of dollars in service work, and, of course the lives of the poor car
  65. 65. owners who were killed by the faulty ignition systems that triggered it. Tesla’s situation never escalated to the recall level: there was a problem with the suspension that could under some circumstances cause a fire. However, Tesla responded simply by sending out a software patch that was automatically installed in every Tesla one night while the owners slept. Instead of having to offer financial bribes to get owners to come in for the necessary repairs as is often the case with a recall, 100% of the Teslas were fixed.
  66. 66. In some cases, customers actually play the final role in an IoT product’s design: car companies allow drivers to make push-button changes in the performance characteristics – one engine can be used in various ways. Or, while it may be a less-than- earthshattering development, women buying heels from Ishuu, a Lithuanian start-up, can instantly vary their
  67. 67. appearance by choosing a different pattern on the app that controls an e-Ink insert on the side of the shoes.
  68. 68. Similarly, this shift to being able to constantly monitor the product’s status can also allow a significant change in pricing and marketing. No industry has been affected as much by this shift as the jet turbine one. Rolls- Royce’s engine sales have declined significantly in recent years, but they’re not complaining, because they are instead “selling thrust” under the
  69. 69. TotalCare program– charging the customer based on the amount of time the engine is actually in the air and working. As part of the new deal, Rolls also monitors the engine’s operation on a real- time basis to allow for the predictive maintenance, and the airline can also, for an additional fee, receive the real-time data so that it can mash it up with atmospheric data, fuel consumption and other factors to maximize operating efficiency. Everyone wins.
  70. 70. The electric industry is also adapting to these new realities. In the past, the flow of information – and electricity – was totally one way, but they too are closing the loop, with smart appliances and factory machinery sending data to the power plant so that just the right amount of power is dispatched, and at just the right time. Increasingly, as solar
  71. 71. electric and other renewable energy systems become widespread, the end user may also be a generator, dispatching excess power back to the grid, another win-win situation. Also, as mentioned previously by GE’s William Ruh, the continuous data stream fed back to product designers allows them, for the first time, to really know how users work with products, and whether or not improvements are needed, making the upgrade less guesswork and more fact based.
  72. 72. In summary: 1.Make Privacy and Security Highest Priority 2.Share Data 3.Close the Loop 4.Redesign Products As important as advances in technology and analysis are to the IoT’s future, it is these fundamental shifts in attitudes and strategy — the
  73. 73. IoT’s Essential Truths — that will really make the difference in whether the Internet of Things’ full potential is ever achieved. They are difficult to make, because they are so different from prevailing wisdom — remember what Einstein said — but will be more than amply rewarded by the opportunities they create.
  74. 74. Thank you, and now I’d like to take questions!