There's no question that the Internet of Things is real — it's imminent and it's big. But it's also ripe for colossal failure if enterprises dive in without properly thinking through why IoT matters, according to Cloudera co-founder Mike Olson in an interview with Bosch's Dirk Slama.
The key, declares Olson, is to start small.
Making IoT real
Pew Research recently polled 1,606 experts on the future of IoT. Rather than randomizing a sample, Pew went straight to the Vint Cerfs of the world to divine the future of IoT. When asked whether the Internet of Things will have widespread and beneficial effects on the everyday lives of the public by 2025, 83% of respondents said "yes" while 17% said "no."
Those in the majority, like internet philosopher Doc Searls, see potential for businesses and individuals to take ownership of the "clouds" formed from such networks of devices, as he related to Pew:
"[I]t isn't necessary for everything to have onboard intelligence, or to be connected full-time to the Net. Intelligence and connectivity can be abstracted away from things themselves to their own Clouds. This means everything is already in a position to have a Cloud of its own.... There will be a hefty business in providing, provisioning, and programming Clouds for things and people, and making it all easy."
Heady stuff, indeed, and pregnant with the possibility that these networks will be used against us. As Joel Halpern, a distinguished engineer at Ericsson, told Pew, "the current email spam problem will be dwarfed by the efforts of business interests to provide us 'information' guiding us towards their commerce."
Putting the IoT cart before the horse
Before we panic, however, we first need to figure out how to get started. Olson reminds us that we're still a long way from full production on IoT:
"The technologies both for generating this type of data — the scale-out proliferation of sensor networks — as well as the infrastructure to capture, process, and analyze this data are new."
As such, Olson reasons, it's best to start small:
"Our experience has been that it is a very smart idea to start with a small-scale proof of concept. Instead of a million devices, maybe start with a thousand devices. And then build a data capture and processing infrastructure that handles that to convince yourself that it's going to work and to educate your people and your organization about how those systems work and what they are capable of. These are new technologies, and adoption of new technologies requires learning and new processes for successful deployment."
In other words, building a successful IoT practice is more than just a technology question: it's also a cultural question.
This is why Amazon Web Services (AWS) data science chief Matt Wood was quick to point out that the cloud can lower the cost of experimentation, such that technological and cultural trial-and-error are more easily managed ("because customers can start experimenting easily at low cost, the growth in skills has been astronomical over the last two years").
Answering the "why" of IoT
With the right infrastructure in place, companies can start small and iterate toward success. Before they even begin, however, there's a larger question to answer: why does IoT matter in the first place?
Olson nails this:
"We talk to a lot of people who are fascinated by the technology of IoT. They are excited about Big Data as Big Data. Those are bad people for us to work with, because they are not fundamentally driven by a business problem.
"It's important when you start thinking about IoT to think about why it matters. What are the business problems you want to solve, what are the optimizations you want to make? And then design your systems to address these problems.
"The 'shiny object syndrome' of engineers who want to play with new technology — I totally get that, I am one of those guys — but those projects generally fail because they don't have clear success criteria."
As with big data, generally, IoT projects will fail so long as they remain cool science projects with no identifiable purpose. For far too many companies, the answer to the "why?" of big data is to punt the question to a data scientist. As Gartner's Svetlana Sicular phrases it, "A data scientist symbolizes to organizations a gaping hole: a magic that can turn big data into big gold by making sense of vast amounts and multiplicity of senseless bits and bytes."
But this misses the point. The point is that all this great new big data technology, including IoT, is a way for us to ask different, bigger questions of our data. To figure out which questions to ask, we need to start small, as Olson stresses. Projects that start with a million-dollar price tag and a million sensors to analyze are doomed to failure.
Matt is currently head of the developer ecosystem at Adobe. The views expressed are his own, not those of his employer.
Matt Asay is a veteran technology columnist who has written for CNET, ReadWrite, and other tech media. Asay has also held a variety of executive roles with leading mobile and big data software companies.