Data Is the Hub: How the IoT and Circular Economy Build Profits

Fasten your seatbelts! I think I’ve finally zeroed in on the Internet of Things’ (IoT’s) most important potential economic benefit and how it could simultaneously help us escape the growing global environmental crisis:

make real-time IoT data* the hub of a circular economy and management mentality. It’s both good for the bottom line and the planet.

I started writing about circular business models back in the 90’s, when I consulted on profitable environmental strategies, i.e., those that were good both for the corporate bottom line and the planet.  It galled me that executives who railed about eliminating inefficiency thought reducing waste was for tree-huggers. Semantics and lifestyle prejudices got in the way of good strategy.

Ford’s River Rouge Plant (1952 view)

I could see that it was vital that we get away from old, linear models that began with extracting resources and ended with abandoned products in landfills. Ford’s massive 1 x 1.6 mile River Rouge Plant, the world’s largest integrated factory, was the paradigm of this thinking: ore was deposited at one end, made into steel, and cars came out the other (Hank’s penchant for vertical integration even led him to buy rubber plantations! If you have any illusions about the ultimate impossibility of top-down control, watch the PBS documentary on Ford — he simply couldn’t share power, even with his own son — and it almost ruined the company). The linear model worked for a long time, and, truth to tell, it was probably the only one that was feasible in the era of paper-and-pencil information flow:  it was so hard to gather and transmit information that senior management controlled who got what information, and basically threw it over the transom to the next office.

As for any kind of real-time information about what was actually happening on the factory floor: fugetaboutit: all that was possible was for low-level functionaries to shuffle along the assembly line, taking scheduled readings from a few gauges and writing them on a clipboard. Who knew if anyone ever actually read the forms, let alone made adjustments to equipment based on the readings?

Fast forward to 2015, and everything’s changed!

The image of the circular corporation popped back into my head last week while I was searching for an image of how the IoT really can change every aspect of corporate operations, from product design to supply chain management.  I was happily surprised that when I Googled “circular economy” I found a large number of pieces, including ones from consulting gurus Accenture and McKinsey (the most comprehensive report on the concept is probably this one from the Ellen MacArthur Foundation), about the bottom-line and environmental benefits of switching from a linear (‘take-make-dispose’) pattern.

But how to make the circular economy really function? That’s where the IoT comes in, and, in my estimation, is THE crucial element.

Visualize everything a company does as a circle, with IoT-gathered real-time data as its hub. That’s crucial, because everything in a profitable circular company revolves around this data, shared in real time by all who need it.

When that happens, a number of crucial changes that were impossible in the era of linear operations and thinking and limited data became possible for the first time:

  • you can optimize assembly line efficiency because all components of the factory are monitored by sensors in real time, and one process can activate and regulate another, and/or managers and assembly-line workers can fine-tune processes (think of the 10,000 sensors on the GE Durathon battery assembly line).
  • you can integrate the assembly line with the supply chain and distribution and sales network as never before (provided that you share the real-time data with them), so materials are delivered on a just-in-time basis) and production is dictated by real-time data on sales (the SAP smart vending machine, integrated with logistics, is a great example).
  • you can optimize product redesign and upgrades and speed the process, because sensor data from the products as they are actually used in the field is immediately fed back to the designers, so they have objective evidence of what does, and doesn’t work properly (think of how GE has improved its product upgrade process). No more ignorance of how your products are actually used!
  • from an environmental standpoint, having sensors on key components can make it possible for you to recover and profitably remanufacture them (closing the loop) rather than having them landfilled (I was excited to learn that Caterpillar has been doing this for 40 years (!) through its Reman Program, which “reduces costs, waste, greenhouse gas emissions and need for raw inputs.”).
  • you can create new revenue streams, by substituting services for actual sales of products.  I’ve written before about how GE and RollsRoyce do this with jet engines, helping clients be more efficient by providing them with real-time data from jet turbines in return for new fees, and Deere does it with data feeds from its tractors. Now I learn that Phillips does this, with industrial lighting, retaining ownership of the lighting: the customers only pay for the actual use of the lights. Phillips also closes the loop by taking the lights back at the end of their life and/or upgrading them.

As I’ve written before, creating the real-time data is perhaps the easier part: what’s harder is the paradigm shift the circular economy requires, of managers learning to share real-time data with everyone inside the enterprise (and, preferably, with the supply chain, distribution network, retailers, and, yes, even customers). When that happens, we will have unprecedented corporate efficiency, new revenue streams, satisfied customers, and, equally important reduce our use of finite resources, cut pollution, and tread lightly on the earth.  There you have it: the secret to 21st-century profitability is:

real-time IoT data, at the hub of the circular enterprise.


*Oh yeah, please don’t drop a dime on me with the grammar police about the title: in fact, I’m a retired colonel in the Massachusetts Grammar Police, but I’ve given up the fight on “data.” From my Latin training, I know that data are the plural form of datum, but datum is used so infrequently now and data with a singular verb has become so common that I’ve given up the fight and use it as a singular noun.  You can see the issue debated ad nauseum here

Live Blogging from the IoT Global Summit

Keynotes:
Came in on end of presentation by Rep. Suzan DelBene, D-WA, co-chair of the House IoT Caucus and an IT industry vet. Her litany of federal inaction in the face of rapidly-evolving 2015_IoT_Summittech — especially regarding privacy protections, where  the key law was enacted in 1986 — was really dispiriting, although it’s good to know there are some members of Congress who are aware of the issue and working on it.

EU Ambassador to the US, David O’Sullivan: the IoT is a “quantum leap” because of combining digital and physical world, and will have huge implications.  Europe has created single digital market. Major investments in IoT & funding research on it.  Very open research projects.  Key is breaking down barriers within the economy. They’re doing research on every aspect of IoT. Priority must be overcoming vertical silos, such as cars and health care. Must balance regulation and innovation. Security and privacy: working on a new set of protections.

Dean Brenner, SVP for Gov. Affairs, Qualcomm: everything will need some form of connectivity. Will need new connectivity paradigm. 4G LTE gives solid foundation for cellular IoT growth.  5G will be fully-deployed by 2020.

Dr. Rakesh Kushwaha, Mformation (hmmm?) Business Leader, Alcatel-Lucent: securing IoT devices. Tech & standards that are already in place to secure mobile devices can be model for I0T devices: they worked with whole range of devices. Fundamental principle of the security: securely update through device/firmware update package.   Only about 40% of IoT will be cellular-based.  Alcatel securing vehicle-mounted devices using FW/SW updates. They will launch a project called IoT Connect.

Session 2: Security for the IoT

Dean Garfield, president & CEO, Information Technology Industry Council: think of security as a design feature, not afterthought. Have to think of it in global sense (including between vertical silos). Chinese government security demands are actually counterproductive. Security can be a differentiating feature.

Joseph Lorenzo-Hall, chief technologist, Center for Democracy and Technology: “IoT Spectrum of Insanity” — such as #IoT door locks, require protections be built in. Security by design. He thinks privacy is a bigger factor than security.

Stephen Pattison, vp of Public Affairs, ARM. Hacker only has to get it right once. You have to get it right every time!  Sensors will have to be very cheap ($5 or less), which will require real creativity.  Security will drive acceptability of IoT. Security breaches will be a major risk for IoT companies.

Chris Boyer, asst. vp, Global Public Policy, AT&T: different security concerns in each vertical domain. Functional classification determines the risk (for example, some affect interruption on critical infrastructure, or life risk). Virtualize security around the end device. Industry activities: application layers, service layer, network layer, access technologies. Looking 4 acceptable risk management levels.

Rory Gray, global head of sales, Intercede: “need world of trusted digital identities.” “Identity is the new currency.”

Government procurement standards may drive privacy and security by design.

Adam Thierer: are we overestimating how much people really care about IoT security (vs. the “cool” factor??).

Afternoon Privacy Panel:

Gary Shapiro, president & CEO, CSA: he disagrees that you should HAVE to give permission to have your info shared: cites all the benefits of sharing data. Thinks we went overboard with HIPPA & privacy. Announcing agreement on guiding principles for sharing health info from #QS devices. A sense that products will be unwelcomed if they create privacy or security issues: example of an Intel engineer who has vision problems. On a personal basis, his mother had terrible time with Alzheimer’s: he’s upset he won’t have access to a Google face recognition technology.

Rob Atkinson, president, Information Technology and Innovation Foundation: “privacy fundamentalists” argue really heavy regulation is way to protect privacy.  BUT, no empirical studies underlying that. Pew survey showed few people believe their landline or credit card data will be private, YET almost everyone uses credit cards or phones: i.e., no correlation between people’s belief in privacy of various technologies and their actual use of the technology.  Overly stringent privacy regulations will reduce their availability. Much of real value of IoT data is from secondary use of the data, which would be undermined by tough regulation. Way too early to put regulatory regime into place for IoT: too early.

Maneesha Mithal, assoc. director, Division of Privacy & Identity Protection, Bureau of Consumer Protection, FTC: two fairly controversial aspects of their 2013 workshop: minimizing data collection debate — said you shouldn’t collect all sorts of data forever, BUT, perhaps collect less sensitive data if they could still derive value. Second issue was “notice and choice.” Tried a middle ground: room for notice and choice,  Discussion of regulation: middle ground on regulation: shouldn’t have specific IoT regulation, but should have general, baseline privacy and security protections. We don’t bring “gotcha cases.”  Could have program that would provide incentives for self-regulation.

Gilad Rosner, Founder, Internet of Things Privacy Forum:  “notice & choice” has been the default privacy & security approach for Internet, but it “fundamentally places the burden of privacy protection on the individual.” A presidential group said the responsibility should rest with the provider, not the user.  Hallmark of a civil society is being regulated.

Day Two:

smart health panel:

You can access my “Smart Aging” presentation on Slide Share.

Peter Ohnemus of dacadoo, a Swiss company, gave an overview of IoT and healthcare and talked briefly about his company’s Health Score, a 0-1000 score assigned to participating individuals based on their real-time scores on factors including movement, nutrition, sleep and stress.

Chantal Worzala of the American Hospital Association gave an overview of issues such as information interoperability and new wellness incentives.

Robert Jarrin, senior director of gov. affairs for Qualcomm, talked about some of the policy issues. FDA now has dedicated staff for electronic devices, and they are now not requiring regulatory compliance for some basic devices.

Smart Home panel:

Hmm. Little actual focus on smart homes in this one…

Cees Links, ceo, Green Peak Technologies: they are a chip manufacturer, “wireless plumbers.” Shipped 1M Zigbee chips. “IoT is not about things, it’s about services.” “Smart Home should be called a butler.” Confusion about IoT standards: thinks ZigBee & Bluetooth will survive, proprietary standards won’t.

Ilkka Lakaniemi, chair, European Commission’s Future Internet Public-Private Partnership Program: working on smart cities strategies, esp. ones that are scalable. Working with NIST on common standards for the demo grants in US & EU. 61 cities involved.

Tobin Richardson, president & ceo, ZigBee Alliance. ZigBee, wi-fi & Bluetooth will form basis of a stable ecosystem. Dollar chip is the goal, getting there quickly.

Paul Feenstra, sr. vp of government & external affairs, The Intelligent Transport Society of America: evolution over last 5 years from car focus to a really varied multi-modal transportation industry. Shocking how we accept the high death rate & congestion on highways. 80% of crashes could be avoided by connected cars.

Business Models for the IoT:

Ana Sancho, Libellium: they manufacture sensor networks for the IoT. Solve problems from smart cities to agriculture & water resources. More than 90 different sensors. They just see very early testing the water with IoT on part of their clients: not widescale implementation.

 

 

 

 

 

 

 

Deloitte provides process for nuanced IoT strategy decisions

So much of the Internet of Things is still in the gee-whiz stage that we haven’t seen much in terms of nuanced IoT strategies. By that I mean ones that carefully weigh tradeoffs between companies and consumers to try to find strategies that are mutually beneficial and recognize there are new factors at play in IoT strategies, such as privacy and data mining, that may have positive or negative consequences for the customer/company interplay.

Deloitte’s “University” has made an important step in that direction with its “Power Struggle: Customers, companies and the Internet of Things” paper, co-authored by Brenna Sniderman and Michael E. Raynor.

In it, they explore how to create sustainable strategies that will be mutually beneficial to the customer and company — which are not always immediately apparent, especially when you explore the subtleties of how these strategies might play out in the new reality of the Internet of Things.

The study’s goal was to understand the factors that can distort IoT’s benefits, and instead create win-win IoT strategies.

Sniderman and Raynor suggest there are four quadrants into which a given strategy might fall:

  1. (the sweet spot!) “All’s well: Sufficient value is created, and that value is shared between customers and companies sufficiently equitably such that both parties are better off and feel fairly treated.
  2. “Hobson’s choice: A Hobson’s choice exists when you’re free to decide but only one option exists; thus, it is really no choice at all…. Even when customers come out ahead compared with their former options, their implied powerlessness can lead to feelings of unfairness.
  3. “Gridlock: In their quest for value capture, both sides are pulled in opposite directions, with neither able to move toward an optimal outcome. Here, both parties recognize IoT enablement as something that should lead to success, but neither party is able to reach it, since their competing interests or different value drivers are working at cross purposes.
  4. “Customer is king: Although particular IoT deployments might make economic sense for companies, customers end up capturing a disproportionate share of the new value created, pulling this outcome more in the customers’ favor; Craigslist is an obvious example.”

According to the authors, a key to finding the win-win, “all’s well” solution is the Information Value Loop (which I first discussed last Spring) that creates value out of the vast increase in information made possible by the IoT.

As I mentioned then, “This fits nicely with one of my IoT ‘Essential Truths,’ that we need to turn linear information flows into cyclical ones to fully capitalize on the IoT.” When you do that, it’s possible to design continuous improvement processes that feed back data from actual users to fine tune products and processes.  GE has found it leads to much shorter iterative loops to design improved versions of its products.

Here’s the gussied-up version of the cool hand-drawn visualization from the Deloitte brainstorming session that led to the Information Value Loop (print it & place it on your wall next to the one on privacy and security that I wrote about a while ago):

Deloitte Information Value Loop

The information no longer flows in linear fashion: it’s created from using sensors to record how things act in the real world, then goes through the various stages of the loop, each of which is made possible by one of the new technologies enabling the IoT.  The goal is either enhanced M2M integration among things, or improved actions by humans, and, to be sustainable over time:

“A value loop is sustainable when both parties capture sufficient value, in ways that respect important non-financial sensibilities. For example, retailer-specific and independent shopping apps can use past browsing and purchasing history—along with other behaviors—to suggest targeted products to particular customers, rather than showing everyone the same generic products, as on a store shelf. Customers get what they want, and companies sell more.

…  “The amount of value created by information passing through the loop is a function of the value drivers identified in the middle. Falling into three generic categories—magnitude, risk, and time—the specific drivers listed are not exhaustive but only illustrative. Different applications will benefit from an emphasis on different drivers.”

OK, so how does this theory play out?

Sniderman and Raynor picked a range of IoT-informed strategies to illustrate the concept, some of which may include unintended consequences that would harm/turn off customers or companies. For example, “An ill-considered push for competitive advantage could well overreach and drive away skittish customers. Alternatively, building too dominant an advantage may leave customers feeling exploited or coerced, a position unlikely to prove viable in the long term.”

Understanding the underlying structure of each type of loop is critical, because they naturally pull an IoT strategy in a particular, divergent way.

The example they pick to illustrate the “all’s well” quadrant of results is the dramatic increase in built-in diagnostic technology in cars.  This is of great personal interest: genetic testing has revealed that I am one of the approximately 10% of men who are missing the male car gene: I can’t stand the things, and view them as a big block of metal and plastic just waiting to develop problems (or, ahem, get hit by deer …), so I need all the help I can get. Sniderman and Raynor zero in on maintenance as one area for win-win benefits for drivers and dealers through the IoT:

“Customers often have little understanding of which repairs are necessary, feel inconvenienced by having to go without their car during maintenance periods, and are frustrated by potential overcharges. In response, automakers are embedding sensors that can run a wide range of reliable diagnostics, allowing a car to “self-identify” service issues, rather than relying on customers (“Where’s that squeaking coming from?”) or mechanics (“You might want to replace those brake pads, since I’ve already got the wheels off”). This creates a level of objectivity of obvious customer value and enables automakers to differentiate their products. Interactive features that work with customers’ information can further add value by, for example, potentially syncing with an owner’s calendar to schedule a dealership appointment at a convenient time and reserving a loaner vehicle for the customer, pre-programmed with his preferences to minimize the frustration of driving an unfamiliar car.

In this scenario, both parties collaborate to provide and act on data, in a mutual exchange of value. The customer captures value in multiple ways: He enjoys increased convenience and decreased frustration, improved vehicle performance and longer operating life, reduced maintenance charges, and—since almost everything about this interaction is automated—fewer occasions for perceived exploitation at the hands of unscrupulous service providers.

Value capture extends to companies in the form of ongoing customer interaction. Linking maintenance programming to the dealership encourages customers to return for tune-ups rather than go elsewhere, ideally leading to continued purchases in the long term. OEMs can also access data regarding vehicle maintenance issues and may be able to identify systematic malfunctions worthy of greater attention. Dealers also have an opportunity to make inroads into an untapped market: Currently, just 30 percent of drivers use the dealer for routine maintenance…”

Kumbaya! But then there’s the opposite extreme, according to Sniderman and Raynor, represented by smart home devices, which would lead to the lose-lose, gridlock scenario.  I think they seriously underestimate the understanding already by manufacturers in the field that they need to embrace open standards in order to avoid a range of competing standards (Zigbee, Bluetooth, etc.) that will force consumers to invest in a variety of proprietary, incompatible hubs, and therefore discourage them from buying anything at all.  All you have to do is look at new hubs, such as Amazon’s Echo, which can control devices from WeMo, Hue, Quirky, Wink — you name ’em, to realize that sharing data is already the norm with smart home devices.

Because this missive is getting long, I’ll leave it to you, dear reader, to investigate Sniderman & Raynor’s examples of the “customer is king” scenario, in which the customer grabs too much of the benefit (have to admit, a lot of the location-based IoT retail incentives still give me the creeps: I hate shopping under the best of circumstances, and having something pop up on my phone offering me an incentive based on my past purchases makes a bad experience even worse. How about you?); and the “Hobson’s choice” one, in which usage-based car insurance runs amok and insurers begin to charge unsafe drivers a surcharge — as documented by the devices such as Progressive’s “Snapshot” (I was dismayed to read in the article that Progressive is in fact doing that in Missouri, although I guess it’s a logical consequence of having objective evidence that someone consistently drives unsafely).

I can’t help thinking that the 800-pound gorilla in the room in many of these situations are the Scylla and Charybdis of the IoT, threats to privacy and security, and that makes it even more important that your IoT strategies are well thought out.

They conclude that, from my perspective, data isn’t just enough, you also need the decidedly non-technical tools of judgment and wisdom (aided by tools such as their Information Value Loop) to come up with a sustainable, mutually advantageous IoT strategy:

“Identifying where the bottlenecks lie (using the Information Value Loop), how each party is motivated to respond, and seeking to shape both incentives and the value loop itself puts companies more in control of their destinies.

“Second, taking a hard look at who benefits most from each IoT-enabled transaction, understanding when a lopsided value-capture outcome tips too far and becomes unsustainable, and taking steps to correct it may also lead to long-term success.

“Lastly, an honest assessment of where IoT investments may not have an appreciable benefit—or may decrease one’s potential for value capture—is just as crucial to a company’s IoT strategy as knowing the right places to invest.”

I may quibble with some of their findings, such as those about smart homes, but bravo to Sniderman and Raynor for beginning what I hope is a spirited and sustained dialogue about how to create sustainable, mutually-advantageous IoT strategies!  I’ve weighed in with my Essential Truths, but what are you thinking about this critical issue, often overlooked in our concentration on IoT technologies? 

The IoT Will Reinvent Replacement Parts Industry

Of all the Internet of Things’ revolutionary impacts on industry, perhaps none will be as dramatic as on replacement parts, where it will team with 3-D printing to reduce service time, inventory and costs.

I came to that realization circuitously, upon noticing Warren Buffett’s blockbuster purchase of Precision Castparts, the major precision parts supplier to the aeronautics industry.  Having read last year about yet another breakthrough innovation by Elon Musk, i.e., the first totally 3-D printed rocket engines, I was curious to see what Precision was doing in that area.  Unless my search of their website was flawed, the answer is zip, and that suggests to me that Buffett, who famously once said he doesn’t invest in technology because he doesn’t understand it, may have just bought …. a rather large dinosaur.

I noticed that one of Precision’s biggest customers is GE, which not only is using 3-D jet fuel nozzles on its engines but also ran a high-profile contest to design a 3-D printed engine mount that was open to you, me and the kids trying out the new 3-D printer at our little town’s library (note to Mr. Buffett: might be good to schedule a sit-down with Jeff Immelt before one of your biggest customers takes things in-house). As I’ve written before, not only is GE a world leader in the IoT and 3-D printing, but also in my third magic bullet, nanotech: put all three together, and you’re really talking revolution!

OK, I know 3-D printing is sloow (in its current state), so it’s unlikely to replace traditional assembly lines at places such as Precision Castparts for large volumes of parts, but that doesn’t mean it won’t rapidly replace them in the replacement parts area.  I talked to a friend several years ago whose biz consists of being a broker between power plants that need replacement parts yesterday and others with an excess on hand, and couldn’t help thinking his days were numbered, because it was predicated on obsolete technology — and thinking.

Think of how the combined strengths of the IoT and 3-D printing can help a wide range of industries get replacement parts when and where they need them, and at potentially lower cost:

  • sensors in IoT-enabled devices will give advance notice of issues such as metal fatigue, so that repairs can be done sooner (“predictive maintenance“), with less disruption to normal routine, cheaper and reducing the chance of catastrophic failure.
  • because data can be shared on a real-time by not only your entire workforce, but also your supply chain, you can automate ordering of replacement parts.
  • perhaps most important, instead of a supplier having to maintain a huge inventory of replacement parts on the possibility they may be needed, they can instead be produced only when needed, or at least with a limited inventory (such as replacing a part in inventory as one is ordered). This may lead to “re-shoring” of jobs, because you will no longer have to deal with a supplier on the other side of the globe: it might be in the next town, and the part could be delivered as soon as printed, saving both delay and money.
  • your company may have your own printer, and you will simply pay the OEM for the digital file to print a part in-house, rather than having to deal with shipping, etc.

And, as I mentioned in the  earlier post about GE’s leadership in this area, there are other benefits as well:

  • “We’ll no longer do subtractive processes, where a rough item is progressively refined until it is usable.  Instead, products will be built atom-by-atom, in additive processes where they will emerge exactly in the form they’re sold.
  • “Products will increasingly be customized to the customer’s exact specifications. The products will be further fine-tuned based on a constant flow of data from the field about how customers actually use them.”

Sooo, Mr. Buffett, it’s time that you come to terms with 21-st century technology or Berkshire Hathaway’s financial slide may continue.

 

The IoT Can Improve Safety and Profitability of Inherently Dangerous Job Sites

You may remember I wrote several months ago about a collaboration between SAP and SK Solutions in Dubai (interesting factoid: Dubai is home to almost 25% of the world’s cranes [assume most of the rest nest at Sand Hill, LOL], and they are increasingly huge, and that makes them difficult to choreograph.

I’m returning to the subject today, with a slightly broader emphasis on how the IoT might manage a range of dangerous job sites, such as mining and off-shore oil rigs, allowing us to do now that we couldn’t do before, one of my IoT Essential Truths.

I’m driven in part by home-town preoccupation with Boston’s bid for the 2024 Olympics, and the inevitable questions that raises on the part of those still smarting from our totally-botched handling of the last big construction project in these parts, the infamous “Big Dig” tunnel and highway project.

I’m one of those incurable optimists who think that part of ensuring that the Olympics would have a positive “legacy” (another big pre-occupation in these parts) would be to transform the city and state into the leading example of large-scale Internet of Things implementation.

There are a couple of lessons from SAP and SK Solutions’ collaboration in Dubai that would be relevant here:

    • The system is real-time: the only way the Boston Olympic sites could be finished in time would be through maximizing efficiency every day. Think how hard that is with a major construction project: as with “for want of a nail the kingdom was lost,” the sensitive interdependence between every truck and subcontractor on the site — many of which might be too small to invest in automation themselves — is critical. If information about one sub being late isn’t shared, in real-time, with all the other players, the delays — and potential collisions — will only pile up. The system includes an auto-pilot that makes immediate adjustments to eliminate operator errors. By contrast, historical data that’s only analyzed after the fact won’t be helpful, because there’s no do-overs, no 2025 Olympics!
    • The data is shared: that’s another key IoT Essential Truth.  “Decision-makers using SK Solutions on a daily basis span the entire organization. Besides health and safety officers, people responsible for logistics, human resources, operations and maintenance are among the typical users.”  The more former information silos share the data, the more likely they are to find synergistic solutions.
    • The system is inclusive, both in terms of data collection and benefits: SK Solutions’ Founder and Inventor Séverin Kezeu, came up with his collision-avoidance software pre-IoT, but when the IoT became practical he partnered with SAP, Cisco, and Honeywell to integrate and slice and dice the data yielded by the sensors they installed on cranes and vehicles and other sources.  For example, the height of these cranes makes them vulnerable to sudden weather changes, so weather data such as wind speed and direction must be factored in, as well as the “machinery’s position, movement, weight, and inertia…. The information is delivered on dashboards and mobile devices, visualized with live 3-D images with customizable views. It’s also incredibly precise.”As a result, by using SAP’s HANA platform, a system developed to reduce construction accidents also makes predictive maintenance of the cranes and other equipment, and lets the construction companies monitor Key Performance Indicators (KPIs) such as asset saturation, usage rates, and collisions avoided.  McKinsey reports that construction site efficiency could improve dramatically due to better coordination: “One study found that buffers built into construction project schedules allowed for unexpected delays resulting in 70 to 80 percent idle time at the worksite.Visibility alone can allow for shorter buffers to be built into the construction process.”

Several other great IoT solutions come to mind at the same time, both relating to dangerous industries. Off-shore oil rigs and mining were treated at length in the recent McKinsey omnibus IoT forecast, “The Internet of Things: Mapping the Value Beyond the Hype:”

  • off-shore rigs: “Much of the data collected by these sensors [30,000 on some rigs] today is used to monitor discrete machines or systems. Individual equipment manufacturers collect performance data from their own machines and the data can be used to schedule maintenance. Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.” (my emphasis). 
  • mining: “In one mining case study, using automated equipment in an underground mine increased productivity by 25 percent. A breakdown of underground mining activity indicates that teleremote hauling can increase active production time in mines by as much as nine hours every day by eliminating the need for shift changes of car operators and reducing the downtime for the blasting process. Another source of operating efficiency is the use of real-time data to manage IoT systems across different worksites, an example of the need for interoperability. In the most advanced implementations, dashboards optimized for smartphones are used to present output from sophisticated algorithms that perform complex, real-time optimizations. In one case study from the Canadian tar sands, advanced analytics raised daily production by 5 to 8 percent, by allowing managers to schedule and allocate staff and equipment more effectively. In another example, when Rio Tinto’s (one mine) crews are preparing a new site for blasting, they are collecting information on the geological formation where they are working. Operations managers can provide blasting crews with detailed information to calibrate their use of explosives better, allowing them to adjust for the characteristics of the ore in different parts of the pit.”
 In all of these cases, the safety and productivity problems — and solutions are intertwined.  As McKinsey puts it:
“Downtime, whether from repairs, breakdowns, or maintenance, can keep machinery out of use 40 percent of the time or more. The unique requirements of each job make it difficult to streamline work with simple, repeatable steps, which is how processes are optimized in other industries. Finally, worksite operations involve complex supply chains, which in mining and oil and gas often extend to remote and harsh locations.”
Could it be that the IoT will finally tame these most extreme work situations, and bring order, safety, and increased profitability?  I’m betting on it.

Energy to Power the #IoT: it’s really just a matter of child’s play

Posted on 12th June 2015 in energy, environmental, Internet of Things, M2M, mobile, sensors, wearables

Saving the Earth from global warming is going to require reducing our use of fossil fuels, yet we keep coming up with new technologies, such as the Internet of Things, that will require even more energy. So how do we reconcile the two needs?

In part, through harvesting ambient energy, and, most cleverly, kinetic energy generated in the process of doing something else, from moving liquids through pipelines, wheels as vehicles move, or even as we humans move about in our daily lives.

As you’ll see from the examples below, there’s enough projects in the field that I’m confident a growing number of sensor networks will be powered through ambient energy in the future. Equally important, in the not-too-distant future we’ll laugh that we once plugged in our smartphone and watches to charge them, rather than harvesting the energy we generate every day simply by moving around.

I saw an incredible example at the recent Re-Work IoT Summit in Boston, courtesy of Jessica O. Matthews of Uncharted Play. By my calculations, Matthews’ own energy output would allow shutting down 2.3 nukes: before her session began, I saw this striking woman on the stage — Matthews –skipping rope.

In high heels!

Then the fun began. Or should I say, the energy production.

Matthews, an MIT grad, works largely in Africa, creating very clever playthings that — ta da! — harvest energy, such as the very cool Soccket ball shown in the video above (you can see here how it’s made).  It has a battery built in that’s charged by the large amount of kinetic energy created by kids on the playground who are just having fun.  At night, they take the ball home and, voila, plug a socket into the side of the ball and they have precious light to read by. How incredibly cool is that?

The Pulse jump rope powers two lights

Matthews’ jump rope (“The Pulse”)? The kinetic energy from that  powers TWO lights!

But there’s a lot of other neat stuff going on in terms of capturing kinetic energy that could also power IoT devices:

  • Texas Instruments has harvested energy to run sensors from changes in temperature, vibrations, wind and light.  I knew about harvesting the energy from pipeline vibrations, but hadn’t thought about getting it from the temperature differential between the interior of pipes carrying hot water and the outside air. TI says that yields a paltry 300-400 millivolts, but they’ve figured out how a DC-to-DC switching converter can increase it to 3-5 volts — enough to charge a battery.
  • TI is also researching how kinetic energy could charge your phone:”To power wearables, the company has demonstrated drawing energy from the human body by using harvesters the size of wristwatch straps.. It has worked with vibration collectors, for instance, about the same size as a key.”It’s possible that a smartwatch could use two harvested power sources, light and heat, from the body. These sources may not gather enough power to keep a smartwatch continuously operating without action by the user to charge it, but it may give the user’s device a lot more battery life.”
  • Perhaps most dramatically of all, as I reported before, there’s some incredible research on ambient energy underway at the University of Washington, where they use “ambient backscatter,” which: ‘…leverag[es] existing TV and cellular transmissions, rather than generating their own radio waves. This novel technique enables ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible.’”

    PoWiFi, harvesting ambient energy

    Now, a member of that team,Vamsi Talla, has harvested energy from ambient wi-fi,  “PoWiFi,” as it’s called, to power a temperature sensor and to let a surveillance camera take a picture every 35 minutes (given how pervasive surveillance cameras are today, that could really be a godsend — or a nightmare, depending on your perspective). “For the experiment, hot-spots and routers were modified to broadcast noise when not being used for data transmission. This is because Wi-Fi signals are broadcast in bursts across different frequencies which makes the energy too intermittent to be useful.”  (TY 2 Jackie Bassett of  SealedSpeed for this one).

Bottom line: forget those charging pads that are starting to crop up. In the future, you’ll be powering your phone, and the very devices that sensors are monitoring will be powering them. A win for the IoT — and the environment!

PS: jury’s still out on whether we’ll all have to register with FERC as utilities….

Sensors remain critical to spread of Internet of Things

What happens with sensor design, cost, and security remains front-and-center with the Internet of Things, no matter how much we focus on advanced analytical tools and the growing power of mobile devices.

That’s because, on one hand, truly realizing the IoT’s full potential will require that at least some sensors get to the low-power, tiny size and cheap costs needed to realize Kris Pister’s dream of “smart dust” sensors that can be strewn widely.

On the other hand, there’s the chance that low-end sensors that don’t include adequate security firmware can’t keep up with the changing nature of security risks and may give hackers access to the entire network, with potentially disastrous effects.

That’s why several reports on sensors caught my eye.

PWC released a report, Sensing the Future of the Internet of Things, zeroing in on sensor sales as a proxy for increased corporate investment in the IoT, and concluding that by that measure, “the IoT movement is underway.” Based on its 2014 survey of 1,500 business and technology leaders worldwide, there was one eye-popping finding: the US lags behind the entire rest of the world in planned spending on sensors this year: 26% of Asian and almost as many from South America (percentage not given)  followed closely by Africa, with 18%.  The surprising laggards? Europe with 8% and North America, dead last at only 7%.  Hello?????

Equally interesting was the company’s listing of the industry segments leading the deployment of sensors and examples of the sensors they’re using:

  • Energy & Mining: 33%. “Sensors continuously monitor and detect dangerous carbon monoxide levels in mines to improve workplace safety.”
  • Power and Utilities: 32%.  Instead of the old one-way metering, “Internet-connected smart meters measure power usage every 15 minutes and provide feedback to the power consumer, sometimes automatically adjusting the system’s parameters.”
  • Automotive: 31%.  “Sensors and beacons embedded in the road working together with car-based sensors are used for hands-free driving, traffic pattern optimization and accident avoidance.”
  • Industrial: 25%. “A manufacturing plant distributes plant monitoring and optimization tasks across several remote, interconnected control points. Specialists once needed to maintain, service and optimize distributed plant operations are no longer required to be physically present at the plant location, providing economies of scale.”
  • Hospitality: 22%. “Electronic doorbells silently scan hotel rooms with infrared sensors to detect body heat, so the staff can clean when guests have left the room.”
  • Health Care: 20%. “EKG sensors work together with patients’ smartphones to monitor and transmit patient physical environment and vital signs to a central cloud-based system.”
  • Retail: 20%. “Product and shelf sensors collect data throughout the entire supply chain—from dock to shelf. Predictive analytics applications process this data and optimize the supply chain.”
  • Entertainment: 18%. “In the gaming world, companies use tracking sensors to transfer the movements of users onto the screen and into the action.”
  • Technology: 17%. “Hardware manufacturers continue to innovate by embedding sensors to measure performance and predict maintenance needs before they happen.”
  • Financial Services: 13%. “Telematics allows devices installed in the car to transmit data to drivers and insurers. Applications like stolen vehicle recovery, automatic crash notification, and vehicle data recording can minimize both direct and indirect costs while providing effective risk management.”

The surprises there were that health care penetration was so low, especially because m-health can be so helpful in diagnosis and treatment, while the examples of telematics seemed off the mark in the financial services category. Why not examples such as ApplePay?

More compelling were the relatively high rates of sensor deployment in high-stakes fields such as energy, utilities, and automotive: those are such huge industries, and the benefits of real-time data are so compelling that they show the IoT is really maturing.

Finally, the percentage of companies investing in sensors grew slightly, from 17% to 20%, with 25%of what PWC labels “Top Performers” are investing in them compared to 18% the previous year. Surprisingly, most companies don’t get it about sensors’ importance: only “14% of respondents said sensors would be of the highest strategic importance to their organizations in the next 3–5 years, as compared to other emerging technologies.”

Most important, 54% of those “Top Performers” said they’d invest in sensors this year.


 

Sensors’ promise as the size decreases — radically — and functionality increases was highlighted by The Guardian.  It focused on PragmaticIC Printing, a British firm that prints tiny, hairlike sensors on plastics. CEO Scott White’s hope is that:

” the ultra-thin microcircuits will soon feature on wine bottles to tell when a Chablis is at the perfect temperature and on medication blister packs to alert a doctor if an elderly patient has not taken their pills.

“With something which is slimmer than a human hair and very flexible, you can embed that in objects in a way that is not apparent to the user until it is called upon to do something. But also the cost is dramatically lower than with conventional silicon so it allows it to be put in products and packaging that would never justify the cost of a piece of normal electronics,” said White.

 

These uses certainly meet my test of real innovation: what can you do that you couldn’t do before. Or, as White puts it, “It is the combination of those factors [price and size] which allows us to start thinking about doing things with this which wouldn’t even be conceivable with conventional silicon based electronics.”

Another article that really caught my eye regarded a new category of “hearable” — and perhaps even, more radically, “disappearables” –sensors which the headline boldly predicted “As Sensors Shrink, Wearables Will Dis-appear.” But they were barely here in the first place, LOL!  The article mentioned significant breakthroughs in reducing sensors’ size and energy requirements, as well as harvesting ambient energy produced by sources such as bodily movement:

“Andrew Sheehy of Generator Research calculates that, for example, the heat in a human eyeball could power a 5 milliwatt transmitter – more than enough, he says, to power a connection from a smart contact lens to a smartphone or other controlling device.”

 The same article mentioned some cutting-edge research such as a Google/Novartis collaboration to measure glucose levels in tears via a contact lense, and an edible embedded microchip — the size of a grain of sand — and powered by stomach juices, which would transmit data by Bluetooth.
Elsewhere, a sampling of sensor design breakthroughs in recent months show the potential for radical reductions in costs and energy needs as well as increased sensitivity and data yield:

HOWEVER, as I said above, here’s what worries me. Are developers paying enough attention to security and privacy? That could be a real downfall for the IoT, since many sensors tend to be in place for years, and the nature of security challenges can change dramatically during that time.  Reducing price can’t be at the expense of security.

Let me know what steps you’re taking to boost sensor security, and I’ll mention them in a future post!

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!

 

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?

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.”