The next great technology problems to solve are out there in rail yards, power plants and farm fields. If Silicon Valley is going to drive this "Internet of things," it needs to build closer ties with companies in established industries.
Big Data Talent War: 7 Ways To Win
(click image for larger view and for slideshow)
The industrial Internet, or what's more commonly called the "Internet of things," needs a new wave of innovation and invention to advance. Better analytics software, better sensors, new business models. If the Silicon Valley technology startup ecosystem is going to drive that invention, it needs to build closer ties with companies in established industries in order to understand their problems and opportunities.
Uber didn't arise because taxi companies called a conference to ask for technology to disrupt their industry. It started with three guys who had a problem calling a cab. So how do you let those "three guys" know about the everyday problems of running railroads, power plants, mines and farms?
We need ways for more people to tinker with industrial Internet problems without each industry's permission. Silicon Valley needs to figure this out, but so do established companies searching for the next wave of efficiency and revenue from technology.
The industrial Internet promises to deliver that boost via machine-to-machine online connections -- putting sensors on equipment and infrastructure, including tractors, airplanes, electricity grids, medical systems and gas turbines, in order to collect data. Using analytical software to make sense of that data can let companies do things like predict when a jet engine part is starting to wear out and replace it long before it fails. GE recently forecast that the industrial Internet could add as much as $15 trillion in worldwide economic growth in the next 20 years.
Silicon Valley startups and venture capitalists will want their cut of that $15 trillion, but is the startup ecosystem sufficiently plugged in to these problems to work its magic?
Consider this advice from investor Paul Graham, from his recent essay on How To Get Startup Ideas, which anyone remotely interested in business innovation should read:
"The way to get startup ideas is not to try to think of startup ideas. It's to look for problems, preferably problems you have yourself. The very best startup ideas tend to have three things in common: they're something the founders themselves want, that they themselves can build, and that few others realize are worth doing."
The problem isn't that these industrial Internet problems are inherently harder because they involve sophisticated equipment such as power plants and jet engines. Consumer Internet companies such as Google and Facebook, with their massive-scale database, analytical and data center technology, connect with billions of people. That's what showed us that connecting hundreds of billions of machines and making sense of the data is possible.
The risk is that people in the traditional startup talent stream: a) don't know what industrial problems exist; b) aren't jazzed by the problems (see Graham's "something the founders themselves want"); and c) don't see a big enough opportunity in solving those problems.
You get excellent Silicon Valley perspective on this challenge from an intriguing panel discussion led by Tim O'Reilly last week at a conference GE held about the industrial Internet.
On the subject of needing to know that problems exist, EMC chief strategy officer Paul Maritz framed things this way. The first generation of Silicon Valley was plugged into enterprise IT needs and was wildly successful at automating companies' paper processes. The next generation pioneered the consumer Internet. Now the two worlds need to come together, to use the Internet to solve industry-specific problems.
But Silicon Valley lacks the deep industrial domain knowledge. "What we haven't had happen yet is the education of what does it mean to move a locomotive all the way from Long Beach to Chicago?" said DJ Patil, a former LinkedIn executive who's now data scientist in residence with the venture fund Greylock Partners.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
Join us for a roundup of the top stories on InformationWeek.com for the week of December 14, 2014. Be here for the show and for the incredible Friday Afternoon Conversation that runs beside the program.