Stalled IoT pilots: Is the human factor to blame?


People, process, technology: It’s the reigning mantra in high tech, swiping “move fast and break things” and “data is the new oil” right off the menu of things to say when you aren’t paying attention.

Attend any conference and you will hear people talk about how new strategic initiatives are stuck because employees don’t want to learn new skills, or that they feel that new processes or technology are being implemented as a way to take their job.

You’re going to see this story played out quite a bit in the mushrooming market for smart devices and the Internet of Things. Gartner and others regularly measure the opportunity in IoT in the trillions. Nonetheless, Cisco conducted a poll last year where 60% of the respondents said their IoT pilots have stalled out with the main culprit being “human factors” like culture, organisation and leadership.

But let’s think differently (TM, conversational styrofoam, 1997) for a moment. What if it isn’t people, or process?

What if it’s the technology? What if the delays and implementation failures are because the technology isn’t really that good? That it’s difficult to use or only delivers benefits in “soft costs” while the vendor wants hard cash? When was the last time you heard someone praise an ERP upgrade? At best, they will tell you it wasn’t as bad as kidney failure.

Culture, leadership and human factors do play an outsized role in success, but even in organisations tuned like a Ferrari, inept technology can slow you down.

Polls show that data scientists spend 80% of their time in data prep. Think of it: some of your highest-paid, highest-skilled employees are doing the equivalent of digital file clerking because the magical dagical algorithm needs help.

Tesla’s Elon Musk, for instance, recently admitted that one of the likely culprits in the Model 3 delays has been too many robots on the factory line. Tesla built a “crazy, complex network of conveyor belts, and it was not working so [Tesla] got rid of the whole thing.” More humans might be a better idea, he added.

Some engineers will respond by noting that the technology works. The “people” neglected to use it property. I’ll give them that. We’re careless, harried knuckeheads. But that’s a given. Like a network TV exec, you’ve got to live with the fact that only 18% of us have an attention span longer than 22 minutes.

“I often find the best thing you can do with some software developers is fire them,” said Todd Nemet, a former product manager at several Fortune 500 companies when I asked him about a feature on a publishing system I particularly despise. “They think that because they control the server, they control everything.”

My brother clued me into the power of bad technology years ago. He’s an urologist, an advocate for robotic surgery and a frequent critic of online medical records.

“Don’t you get it Angelo? By going online we can cut administrative costs and improve quality of care throughout a patient’s lifetime,” I’d bellow.

True, but he also counters that these applications often force doctors to shift from notes to check-box like diagnoses, eroding the quality of care. The data management systems can be fussy and force him to expend more hours in administration, driving up the cost. Worst of all, you’re no longer looking at the patient. You’re focused on a black box: bad for the doctor and the patient.

The “right idea, wrong tool” phenomenon plays out all over the place. In Guns, Germs and Steel, Jared Diamond noted that New Guinea villagers immediately adopted the sweet potato as a food source when they first encountered it and planted it in vertical hillside rows. Missionaries and aid workers corrected them and told them to plant in horizontal rows. In the first major rainstorms, crops were washed out. Vertical planting returned.

So how will this play out in IoT? On one hand, you’re going to see some tremendous success stories where designers spent the extra cycles to figure out how to bring technology into the workplace without screwing up the day of employees.

You’ll see situations where factory productivity will go up at the same time as safety. Water utilities are already discovering that smart meters and data analytics for finding leaks has become the cheapest and quickest way to beat droughts and meet growing demand for water.

On the other hand, you’ll see smart windows turning noon into night and people spending hours on the phone trying to reverse changes made by intelligent supply chain systems.

Unforeseen problems will abound, and we just can’t respond “it’s the people.”

Want to know more? Read about 7 success stories from Energy & Utilites companies that are leveraging IoT data to improve grid reliability, efficiency and more.

Contributor: By Michael Kanellos

Michael Kanellos is the technology analyst at OSIsoft. He has covered technology for decades writing for CNET, Forbes, Greentech Media, New York Times, Wired and other publications.