The likes of Union Pacific, GE Power & Water, and ConocoPhillips are turning IoT hype into reality, but they want to do more. Here's what's still getting in the way.
GE is using isn't as timely, complete, or accurate as it wants (timeliness is the biggest challenge). So Fowler has taken two main steps to improve data quality.
One, a year ago he assembled a data science team that includes a data quality group, which is looking for ways to automate areas where employees collect critical data manually. Two, he created a data quality portal that shows the top 10 problems the group is trying to improve. The unit's CEO sees a report monthly.
As CIO, Fowler thinks he should "own every piece of data in our environment" but that business unit leaders must see and understand the data-collection problems that cause bad data, so they can have a hand in fixing those quality problems.
Some data just isn't available. While we hear a lot about early implementations of "smart meters" or Nest-type home automation thermostats that provide real-time insight into power use, there still isn't a lot of energy demand data coming into power generators. This winter was brutally cold, and some power plants saw surges -- and resulting outages -- unlike any they've seen before. If the plants had had accurate data on that rising demand, they could have run at higher capacity. "That linkage is one of the next big areas to look at," Fowler says.
Networks aren't ubiquitous. Cellular networks cover a lot more ground than they did even a few years ago, and 4G networks are expanding, but once you move beyond big metropolitan areas, you still can't count on cellular.
ConocoPhillips spread its own radio towers across parts of Texas to transmit sensor data in order to optimize gas and oil well production. But newer techniques and sensors could generate 100 times more data than those wells gather and transmit today -- more than the network can handle for real-time analysis. "Wired pipe," for example, lets a driller put fiber optic cable miles down the well to collect sound, pressure, and seismic data in a constant stream. "Then you're talking about gigabytes of data flowing off this all the time," says Richard Barclay, ConocoPhillips' manager of infrastructure and operations.
Does the company need to pipe all that data back to some command center for analysis? If so, how quickly? Or can it crunch some of that data at the wellhead to guide urgent decisions about drill pressure and speed, and send less-urgent data back for historical analysis? Barclay says his team is examining what amount of data, measured at which intervals, people really need to make a decision.
The future Internet of Things model often will combine on-machine processing for urgent needs and batch-data uploads for less timely analysis. Bill Ruh, VP of GE Software, describes this as "real-time, big data processing at the machine. We don't have anything like that today."
For companies tying the Internet of Things into their products, the concern is less that there isn't a network available. Instead, the worry is that the network becomes key to the customer experience, yet it's something the product maker doesn't control. "You're dealing with almost a massive outsourcing of your brand, in terms of the eyes of the customer," says Alex Brisbourne, president of Kore, a company that provides wireless machine-to-machine connectivity.
Integration is tougher than analysis. Connected devices and machine-to-machine communication no doubt generate a lot of data. But analyzing that data to get useful insight is not, surprisingly, among the top barriers to the Internet of Things. "Analytics is the least of our problems," says Union Pacific's Tennison.
Data analysis does take expertise -- data-savvy people who understand the business problems their companies are trying to solve and the opportunities they're trying to seize. Companies often must change their business processes to let employees respond to and use the insights the data analyses present.
But the hard part isn't crunching the data; it's connecting all the systems needed to paint a complete data picture, says Richard Soley, executive director of the Industrial Internet Consortium. A group of big-name companies -- led by AT&T, Cisco, GE, IBM, and Intel -- created the Industrial Internet Consortium to spur the kind of integration, authentication, and security
Chris Murphy is editor of InformationWeek and leader of its Strategic CIO community. He has been covering technology leadership and strategy issues for InformationWeek since 1999. Before that, he was editor of the Budapest Business Journal, a business newspaper in Hungary; ... View Full Bio
InformationWeek Tech Digest, Nov. 10, 2014Just 30% of respondents to our new survey say their companies are very or extremely effective at identifying critical data and analyzing it to make decisions, down from 42% in 2013. What gives?