Ungrateful Google Plebes Somehow Not Excited to Work on Military Industrial Complex Death Machines

How Complete Beginners are using an ‘Untapped’ Google Network to create Passive Income ON DEMAND

“Don’t Be Evil” has been one of Google’s corporate maxims for over 15 years. But it’s recent dealings with the Department of Defense has put that ideal on ice. For some reason, Google’s workers aren’t psyched about this!

Over three thousand Google employees signed a recent public letter demanding CEO Sundar Pichai shut down Project Maven — a Department of Defense contract to create a “customized AI surveillance engine” — and publicize a clear policy that “neither Google nor its contractors will ever build warfare technology.”

The letter’s got some pretty direct language, calling the company out on its loss of the aforementioned core value: “Google’s unique history, its motto Don’t Be Evil, and its direct reach into the lives of billions of users set it apart.” The commoditization of people’s personal data (ergo, their psyches) not withstanding, obviously.

Gizmodo reported on Project Maven earlier last month, when they described it as “using machine learning to identify vehicles and other objects in drone footage, taking that burden off analysts.” Google and the Pentagon fired back, stating that the technology wouldn’t be used to create an autonomous weapons system that can identify targets and fire without a human squeezing the trigger.

CEO Pichai spun the letter and public exchange with the company as “hugely important and beneficial” in a statement to the New York Times, but of course, didn’t refer to any plans to throw the brakes on the project. Pichai’s statement went on to say that the tech used by the Pentagon is available to “any Google Cloud customer” and reserved specifically for “non-offensive purposes.”

Thing is, Google’s far from the only tech industry player in cahoots with the military. Red flags immediately went up when news broke that a team of researchers from the Korea Advanced Institute of Science and Technology (KAIST) was partnering up with weapons company Hanwha Systems — a company that produces cluster bombs, not exactly a popular form of warfare, as far as these things go. Fifty researchers from thirty countries called for an immediate boycott of the Korean institute.

Microsoft and Amazon both signed multi billion dollar contracts with the Department of Defense to develop cloud services. Credit where it’s due: At least the DOD isn’t trying to spin this as anything other than death machine-making. Defense Department chief management officer John Gibson didn’t beat around the bush when he said the collaboration was designed in part to “increase lethality and readiness.”

So that’s fun! And if Google’s recent advancements in AI tech faced a similar fate, think: Weaponized autonomous drones, equipped with private data, and a sophisticated AI. Not saying this is exactly how SkyNet starts, but, this is basically how SkyNet starts.

The counter to this argument, insomuch as there is one, is that these technological developments lead to better data, and better data leads to better object identification technology, which could also lead to more precise offensives, which could lead (theoretically) to less civilian casualties, or at least (again, theoretically) increased accountability on the part of the military (analog: the calculator should make it exponentially more difficult to get numbers “wrong” on your taxes, so the automated hyper-targeted death robots should make it exponentially more difficult to “accidentally” murder a school full of children).

All of which should go without saying that collaboration between the Department of Defense and various Silicon Valley tech companies is a dangerous game, and we have seen how quickly the balance can tilt in one direction. Having informed tech employees call out their CEOs publicly could hopefully lead to tech companies choosing their military contracts more carefully, or at least, more light being shed on who’s making what technologies, or rather, what technologies Silicon Valley coders are unknowingly working on.

More likely is that it just results in these companies being more discreet about the gobstoppingly shady (but profitable!) death machine work they’re doing. Good thing — like the rest of the world with a brain in their heads — we’re all ears.

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Double vision: Why industrial companies are embracing digital twins

Double vision: Industrial companies set sights on digital twin technologies

Industrial companies are embracing digital twin technologies, with a view to keeping costly assets in good repair and maximising their useful lives. 

Out on the waters of the Gulf of Mexico, some 25 miles south-west of Port Fourchon, Louisiana, the Noble Globetrotter I drilling vessel is hard at work. The ship is drilling for oil under a 10-year contract between its owner/operator, offshore drilling contractor Noble Corporation, and oil giant Shell.

Meanwhile, over 1,000 miles away, in Lisle, Illinois, a digital representation of the Noble Globetrotter I is being closely monitored by engineers working at General Electric’s Industrial Performance and Reliability Centre (IPRC). This is the vessel’s digital twin.

The IPRC runs on a 24-hour basis, seven days a week, with the goal of spotting problems and increasing uptime for GE customers’ industrial assets, in fields as diverse as oil and gas, power generation, mining, and aviation.

The Globetrotter I’s digital twin is based on data collected from physical assets found on the ship: specifically, its drilling control network, along with its power management and dynamic positioning systems. Each of these assets has its own sensors and control systems, which provide steady streams of data. These are harmonised and centralised on the ship, before being transmitted in real time to the IPRC.

There, the Digital Rig solution developed by GE and Noble gets to work, applying advanced analytics to data models based on the digital twin, in order to detect unusual behaviour patterns, which might indicate a problem with equipment onboard the ship.

Read more: Shell joins digital twin initiative for offshore oil and gas assets

Supportive siblings

The digital twin concept is not a new idea, and could be seen as a useful byproduct of CAD. However, the use of live sensor data to model real-world objects seems to date as far back as 2002, to a presentation to industry given at the University of Michigan by Dr Michael Grieves. In his speech, he suggested that a digital representation of a physical system could be used to monitor and support the entire lifecycle of its physical sibling, in order to keep it functioning.

But in recent years, as sensors have become cheaper and the cloud has delivered almost limitless, low-cost storage space and processing power, the idea has really taken off.

Digital twins were one of Gartner’s Top 10 strategic technology trends for 2018, with analysts at the firm predicting that organisations will implement digital twins “simply at first, then evolve them over time, improving their ability to collect and visualise the right data, apply the right analytics and rules, and respond effectively to business objectives.”

Already in 2018, Internet of Business has reported on plans at IBM to create a digital twin of the Port of Rotterdam, Europe’s largest shipping hub.

Then there was the news last week that professional car racing squad Team Penske is teaming with Siemens to create digital twins of its vehicles, enabling engineers to simulate engine configurations, develop new parts, optimise performance, and even predict race results.

And Kärcher, manufacturer of vacuum cleaners and pressure washers, has said that it will use software from Dassault Systemes to create digital twins for “system engineering, configuration, manufacturing, after-sales services and packaging design.”

Read more: Rotterdam and IBM plan to create ‘world’s smartest port’ with IoT

Multiple anomalies

But back to the Noble Globetrotter I. According to GE, Digital Rig has already “captured multiple anomalies” in its physical assets and produced alerts about potential failures up to two months ahead of when they might otherwise have been expected to occur. The goal is for the solution to deliver a 20 percent reduction in operational expenditure across targeted equipment, through high-octane predictive maintenance.

These kinds of results can only come from digitalisation, claims Krishna Uppuluri, vice president of digital product at GE Digital. “If you look at the way that drilling contractors operate, it’s been much the same style for the past thirty to forty years,” he says. “It is predominantly based on experience, gut feel, and calendar-based maintenance.”

In other words, problems are diagnosed on the basis of hunches, and maintenance schedules are strictly observed. Some equipment undergoes maintenance even when it’s running fine, just because it’s due to be inspected.

But now when something starts to go wrong, says Uppuluri, the team at the IPRC can spot it early, and package up an alert with relevant data to send to the vessel’s crew, out on the Gulf of Mexico. This way, they get plenty of warning if they need to order and transport new parts (and experienced engineers to fit those parts) out to the ship.

GE and Noble plan to build digital twins of four different drilling vessels at first, says Uppuluri, and then use these as the basis to roll out the technology to the rest of Noble’s 28-strong fleet.

This kind of project may be just the start. Says Gartner analyst David Cearley: “Over time, digital representations of virtually every aspect of our world will be connected dynamically with their real-world counterparts, and with one another, and infused with AI-based capabilities to enable advanced simulation, operation, and analysis.”

What we’re seeing, he reckons, is a long-term shift to a “digital twin world” – with huge implications for all kinds of professionals, from city planners and digital marketers, to healthcare workers and industrial planners.

Read more: Five predictions on the future of smart warehousing

Read more: MWC 2018: Smart wine, tools and cities from Deutsche Telekom IoT

Internet of Business says

Perhaps the biggest digital twin programme currently in existence can be found at CERN in Geneva, where the 27km loop of the Large Hadron Collider remains the largest machine ever built. Every component in the LHC – and on the CERN campus, which is the size of a small town – is logged in an enterprise asset management (EAM) system as a digital twin. This enables engineers to keep the big science running, and for repairs, upgrades, and replacements to be planned for well in advance.

And the system has another, equally important benefit: in a 27km complex full of expensive equipment, the digital twin system also tells engineers exactly where the tiny bolt that needs replacing is located. That’s not to be sniffed at when a round trip on a slow maintenance vehicle may take several hours.

The post Double vision: Why industrial companies are embracing digital twins appeared first on Internet of Business.

Internet of Business

Smarter weed detection at an industrial scale

A weed-killing sprayer created by Bosch’s R&D team in conjunction with Bayer would sit on the arm of existing weed-spraying equipment. Photo by S. Higginbotham.

At Bosch Connected World, I spoke with Toby Meene of Bayer about weed-killing technology the agriculture giant was developing with Bosch. The technology would compete with the Blue River tech that John Deere acquired last year. However, the Bayer/Bosch weed killer is designed to fit on existing equipment, and covers a field at the current European standard of 12 kilometers an hour.

The machine attaches to the existing sprayer arm and uses a camera with weed and crop detection technology. It also contains a delivery system for three different types of herbicide that can be mixed with water as it’s applied. The system is less granular than the Blue River machine that handles weeds on an almost individual basis.

What struck me about the creation of two products aimed at solving the same problem is that one is offered by a traditional agricultural equipment vendor, while the other is offered by a supplier of seeds and herbicides. Yet both are looking to provide what is essentially improved crop production as a service. Which means that what was once a longer supply chain will flatten, and former partners or neutral vendors in the same supply chain may end up as competitors. Business is going to get tough.

Stacey on IoT | Internet of Things news and analysis

Industrial Design Experts Say HomePod’s White Ring Issue ‘Shouldn’t Be Too Hard to Fix’ for Apple

Last week, Apple confirmed that the HomePod can potentially leave white rings on the surface of wooden furniture with oil or wax finishes. In an effort to help users prevent seeing these rings appear on their own furniture, Apple shared a support document on “Where to place HomePod,” detailing how the interaction between the HomePod’s vibration-dampening silicone base and a wooden surface has the chance to result in a white ring.

Business Insider recently spoke with a few industrial design experts who believe that the problem “shouldn’t be too hard to fix” for Apple.” Gregor Berkowitz, a product development consultant for numerous consumer electronics brands, expects Apple to “re-tool” its HomePod manufacturing process to address the issue with the silicone base, which could take between two to six weeks. Although the fix could take several weeks, the experts said it’s “likely not very costly” for Apple.

Image via Wirecutter

Senior industrial designer at Y Studios, Cesar Viramontes, referred to the white rings issue as something customers will “probably forget about” in the next few months.

Apple may need to “re-tool” the manufacturing process since silicone is manufactured using a different process than the other kinds of elastomer,” said Berkowitz. If that’s necessary, the process could take anywhere from two weeks to six weeks, he noted.

“It’s an issue, but I think it’s probably going to be one that’ll be corrected in the next round of manufacturing,” said Y Studios’ Viramontes. “I think it will be a minor issue, and people will probably forget about it in the next couple of months when it goes away.”

While the experts see a quick fix for the issue coming from Apple, all were surprised it happened in the first place. Product design expert Ignazio Moresco explained that more is expected from Apple’s well-known attention to detail, and the company “should have caught the issue if they followed a rigorous QA process.” The white marks aren’t an Apple-specific problem, but have appeared with other speakers — like Sonos One — that have similar silicone bases.

Berkowitz believes the white rings could be a result of Apple’s “inexperience” with making stationary speakers, in contrast to the company’s familiarity with making mobile products like the iPhone and MacBook.

“This is sitting on a bookshelf. Is it going to work? Or are there going to be problems? A traditional consumer product company or a speaker company or a traditional Hi-Fi company is going to worry about that and think about those problems and have experience with it,” Berkowitz said. “This shouldn’t be new for Apple but it is.”

“They didn’t test the product enough and in the right variety of circumstances, especially considering that a wood surface is a very likely support for the product,” said Ignazio Moresco, a product design expert who has worked at frog design, Microsoft and Ericsson.

For those who have discovered rings on their furniture, Apple said that these marks “will often go away after several days” once HomePod is removed from the wooden surface. Users can hasten this process by wiping the surface gently with a damp or dry cloth. Still, the company explained that if anyone is concerned about these marks, it recommends “placing your HomePod on a different surface.”

Accessory makers are already creating products to act as a fix for the situation, including new leather coasters for HomePod from Pad & Quill. The $19.95 coasters are advertised as letting users place their HomePod on the wooden surfaces that have the potential to be marked by HomePod, without having to worry about the appearance of such marks.

Related Roundup: HomePod
Buyer’s Guide: HomePod (Buy Now)

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Don’t dream big when taking on industrial or enterprise IoT

As inspiring as the phrase business transformation is, I’ve decided that when it comes to industrial or enterprise IoT, it’s better to start small. Most executives by now are well aware that you should begin with a use case, but what’s become more clear as time has passed and projects have failed is that maybe business transformation shouldn’t be your first goal.

Peter Zornio, chief technology officer at ‎Emerson Automation Solutions, says that in his experience, the operations guys in building systems or in a plant want a use case and an ROI, while the IT shops tend to want to install a platform so folks in the business can build their own applications on top of it.

“Tangible ROIs that are easy to see are great,” Zornio says. “Operational guys love that because they have to justify their spend, while the IT guys want to think big. These are the guys that 15 years ago convinced everyone to spend hundreds of millions on ERP systems.”

Zornio isn’t bashing ERP systems, but if you ask ERP buyers if that money was well spent, many of them wouldn’t really know. Which is why Zornio is a big fan of metrics when discussing IoT projects.

He’s not alone. Jason Shepherd, a senior director and IoT CTO at Dell, says, “Too many IoT projects start as science projects (e.g., “Wouldn’t that be neat?”) with no clear metrics for success.” You know what’s really hard to measure? Business transformation.

So if measurement is the key, how should you think about that? In some situations, a use case and the subsequent savings are crystal clear. For example, if you automate data collection that normally requires an employee, calculating the savings is easy.

But Zornio says other use cases, such as ensuring reliability, are more difficult. First you have to come up with the number of times a particular part or machine fails, then you need to figure out the cost to the production process or the team. You also have to factor in the cost and time it takes to make those repairs. Replacing a part that is commonly in inventory vs. replacing something that might have to be ordered will factor into those costs.

Those kinds of calculations are more subjective than calculating the cost of replacing a worker. You could debate how often equipment fails. Or how much it costs when it does fail, depending on what a company values. For example, downtime in one part of the plant might be relatively unimportant because there’s a backup or low demand during certain times of the year. So it’s always better to search for the obvious. Sometimes, the flamingly obvious.

“We had a customer come to us about monitoring pumps. There, the risk wasn’t downtime, but that when one of the pumps failed it tended to catch on fire,” says Zornio. “In that case, the ROI wasn’t about money saved as much as it was about deciding how valuable it was to the organization to avoid fires in their factory.” (That entire conversation has me thinking that an enterprising IoT systems integrator should scour the trade press for industrial disasters to find their next sales prospect.)

Assessing IoT projects’ value isn’t just useful for the companies buying into connected sensors or products. It’s also important for companies trying to build solutions for industrial and enterprise IoT.

That platform mentality is a common one in Silicon Valley, but it’s hard to sell. Especially if you need a deep understanding of specific industry data around costs and functioning of equipment. That’s why many of the big companies are teaming up with those in specialized verticals to pitch their platforms or services.

But again, it appears that success today is found most often in the smaller projects as opposed to the business transformations. Shepherd advises that when choosing a project to ensure that the use case is relatively straightforward so the company can get a “quick win.”

 “A quick win can grow into more advanced benefits, but don’t try and start with too much. For example, start with basic monitoring for visibility and then add analytics,”  he says.

We’ll talk more about what this means in future issues of the newsletter along with the challenges associated with making sure that your employees don’t sabotage your business goals—or the eventual business transformation itself.

Stacey on IoT | Internet of Things news and analysis

Petasense bets on hardware over algorithms for industrial IoT

Petasense co-founders Abhinav Khushraj (left) and Arun Santhebennur (right). Image courtesy of Petasense.

Since this week’s theme so far is data, let’s keep it going with a profile on Petasense, a startup that offers predictive analytics to industrial clients. Petasense was formed in 2014 with a plan to stop downtime at factories by improving plant owners’ ability to understand when their machines would fail. It built a Wi-Fi-connected vibration sensor that collects data from each machine and sends it up to the cloud for analysis.

The resulting data gets sent back in the form of a health score to plant operators. What Petasense founders discovered was that downtime isn’t why companies were interested in the service. Instead, they wanted to use it to avoid scheduled maintenance on equipment that didn’t actually need it. Now plant operators have the ability to set a customized maintenance schedule for each machine, avoiding the downtime and cost that comes with servicing a machine that doesn’t yet need it.

What Petasense is doing isn’t new. GE has been touting its ability to take in data to predict failures for the last five or six years. Startups such as Augury also offer similar services, albeit by analyzing the sounds that machines make as opposed to their direct vibration. Really, the sense is that anyone with a fancy algorithm and access to data can come up with some way to predict the health of a given machine.

But Abhinav Khushraj, one of Petasense’s cofounders, begs to differ. He says that Petasense is different because fancy algorithms are one thing, but access to data is the essential thing. Petasense built its own vibration sensor so it could get clean data to populate its analytics efforts. Controlling the sensor gives Petasense the competitive edge, says Khushraj.

I want to believe this. I can see the value in having clean data and the ability to understand the specifics of the hardware collecting that data. However, I also know that new ways of getting data come along all the time with different incentives to use them. Petasense does make it incredibly easy to buy and deploy its vibration sensor, which goes a long way to assuaging my doubts about its customers finding a new source of vibration data.

The sensor costs between $ 400 and $ 600 and gets glued onto the equipment with industrial epoxy. The battery lasts two years and transmits data every three hours. If it’s as simple as getting someone to walk around sticking a sensor onto every piece of equipment, then that’s not a difficult ask. This assumes it’s easy to put the device on a corporate network. Because it uses Wi-Fi, things could get tricky.

Once the sensor is transmitting data, companies pay about $ 10 per month, per device, for the analytics. The whole service replaces what was typically one person, who would come around and collect vibration data from gear every month or so, and the specialist that person sent the data to, who would then use that reading to see if there was a problem.

Obviously the sensor replaces those two people, but it also collects a lot more information than was previously possible, which presumably leads to better results. Petasense has customers in the utilities industry and customers who use it to monitor HVAC equipment in buildings.

Stacey on IoT | Internet of Things news and analysis

Wireless Industrial IoT startup Shoof Tech raises $4.5M in seed funding

Shoof Technologies, a startup providing wireless technology for the Industrial IoT raised $ 4.5M in seed funding. Kleiner Perkins and Modiva Japan led the round.

The Shoof Solution: Your Assets Never Out of Sight

Shoof’s manufacturing and logistics customers will be able to use the solution for indoor and outdoor asset monitoring and tracking in early 2018. Shoof Tech’s solution consists of a cloud platform and equipment – including base stations and tags. With the current funding, Shoof plans to focus on manufacturing and transportation sector.

The startup’s primary focus in tracking indoor assets as the current wireless technologies such as GPS and cellular connectivity put a lot of strain on sensor battery. The batteries die out in a few hours making the solution inadequate to withstand the ruggedness of industrial settings. This is where Shoof Tech’s solution can fill the gap and provide round the clock industrial-grade internet connectivity to expensive assets.

“We are excited to partner with such reputable firms who share our vision of empowering the supply chain and logistics industries with efficient asset-monitoring and tracking connectivity technologies,” said Ra’ed Elmurib, CEO, Shoof Technologies. The startup operates on a ‘subscription-based’ business model whereby its customers incur a monthly recurring fee hence saving the latter from significant infrastructure set-up costs that any industrial-grade IoT solution requires.

Another asset intelligence startup Alchemy IoT recently raised $ 4M in seed investment.


Postscapes: Tracking the Internet of Things

Filament introduces tech to get industrial devices interacting with blockchains

IoT blockchain company Filament has engineered its latest software/hardware release to more closely suit the deployment needs thrown up by data exchange to and from industrial and enterprise machines and sensors.

Reno, Nevada-based start-up Filament’s software works with its own-branded Blocklet Chip hardware, to provide industrial and enterprise devices with the ability to securely interact with and transact against any given blockchain. Blockchain is a method of creating an ‘immutable’ ledger of transaction records. Initially developed with a view to specific cryptocurrency deployments, blockchain can also be applied to other transactional record bases.

Due to its distributed nature (in other words, it’s held on many computers), a blockchain can be said to be immutable and therefore highly secure – although it should be added that blockchain is not totally unhackable, since its record base can (in some instances) be reverse-engineered through log file analytics, depending on the system of records that it holds.

“From the start, Filament has been dedicated to furthering the value and economics of the digitally connected world, right at the edge of the network. We are taking enterprise and industrial IoT connectivity benefits to the next level where data can be transacted and inherent trust is created,” said Allison Clift-Jennings, CEO of Filament.

Read more: Opinion: Why blockchain matters for the IoT

Device independence just got real

What Filament is essentially doing is enabling e-commerce for devices; that is to say, it is working towards empowering devices with the ability to transact value using distributed ledger technology. This is what we call ‘device independence’, an idea that is establishing itself as a key theme for mobile and IoT technologies.

Filament’s distributed blockchain capabilities use open protocols so that devices are able to independently process and record transactions. That’s (arguably) not a bad thing when it comes to thorny areas like digital trust.

The company’s application software and Blocklet Chip, currently in beta, are designed to communicate and interact with multiple blockchain technologies natively. The software, implemented on existing hardware, will deliver a distributed ledger technology product. The Blocklet Chip will theoretically allow industrial corporations and enterprises to extract the value of recording and monetizing data assets, at the edge of the network, on the sensors themselves.

Filament is supporting the open-source business blockchain framework, Hyperledger Sawtooth, hosted by The Linux Foundation, on its own native hardware. Hyperledger Sawtooth is a modular platform designed for building, deploying and running scalable distributed ledgers that provide a digital record that is maintained without central authority or implementation.  

Approximately 200 members are a part of the Hyperledger consortium, including many Fortune 500 corporations.

Read more: Blockchain Food Safety Alliance launched to tackle supply chain issues

The post Filament introduces tech to get industrial devices interacting with blockchains appeared first on Internet of Business.

Internet of Business

The trouble with the industrial IoT is too much IT

DOUGs keep the lights on.

Much has been made of the difference between information technology (IT) and operational technology (OT) when it comes to the industrial internet of things. The big tech companies have come into the space with their gateways, clouds and wireless networks, sometimes without understanding that for the OT world, automation has been happening for a long time.

In many cases what’s new isn’t the sensors, but the data analytics and ability to start reacting in real time to that data to add more automation. As the IT world grasps what the industrial world wants, providers are spending more time discussing edge computing, security and service level agreements.

But when I travel between the two worlds, people are still baffled by the industrial guys. These are the operational technicians who keep parts functioning, lay wire and generally ensure that all the bits and bobs of whatever automated system continue to work. These technicians have been doing this for decades. It’s what they are paid to do: keep the plant operational.

They frustrate the heck out of any new manager hoping to come in and add mobile apps or IoT analytics to the floor. In a conversation with one such executive who manages a team of OT and IT staffers, he derided the operational guys as DOUGs. It stands for dumb, old utility guys. As in, we wanted to see if we could get our sensors to report an additional data point, but the DOUGs didn’t want us to touch them.

I laughed, but I realized that it wasn’t the DOUGs that were the problem. Litterally their entire job is to build something that works and keep it running no matter what the world throws at it. If you are a lineman for the phone company or a utility and a line gets knocked out, you grab a truck and put it back.

On a manufacturing floor, you add new devices and processes slowly with an eye toward ensuring that nothing breaks and the end product isn’t screwed up. Intellectually we get this. But that is why DOUGs are such a pain in my friend’s butt. Operational guys keep things operating. They don’t think up new features or strive for continual deployment of new services.

They keep the lights on.

Meanwhile in the software world, those who “move fast and break things,” get ahead. Their focus is on agile delivery of new features. Even the emphasis on the cloud a little over a decade ago was all about freeing up operational resources so the IT staff could move quickly and adapt.

Think about your favorite software. I bet it has crashed at some point. Or your last Skype call. Or the last time you had to reboot a modem to get things working again. It’s not to say that technology doesn’t work, but when things fail, the goal is to fix it and get back up again quickly without too much fuss. And the repercussions for failure have historically been low.

But as IT meets the real world, the repercussions for failure are much higher. Consider the real-world effect that computer issues can have on the airline industry — halting travel. Or consider Chrysler’s software error that could prevent airbags from deploying and led to a massive recall in 2017. For as much as the IT world values continuous improvement code, disruption and agility, when the code hits the road lives or livelihoods are at stake.

So as frustrating as the DOUGs are, as we push more IT into OT processes, it’s worth viewing their perspective. Sometimes changing something isn’t as useful as just keeping something up and running. Sometimes moving fast and breaking something is a really dumb thing to do.

And for those in charge of trying to blend IT and OT, maybe understanding the DOUGs will help you succeed in your next project.

Stacey on IoT | Internet of Things news and analysis