Minds + Machines = A New Generation Of Analytics
Last year I spoke at GE’s “Minds + Machines” event in Chicago. The event was both a product-oriented conference from a leading vendor in the emerging “industrial internet” category, and a fascinating example of how a big company like GE can embrace data-driven products and services.
GE is by culture a “big iron” company, and the iron increasingly has sensors embedded in it. For example, the photo (below) is of a rather substantial data-gathering device: a 50,000 pound “double ram” oil-drilling blowout preventer that GE had on display at the event (in fact, the keynotes were held in an outdoor tent on Chicago’s Navy Pier constructed around the unwieldy device). This thing has 30 or so sensors built in and gathers about 200,000 pieces of data a day on things like temperature, pressure, and ram position. It can sit as far underwater as two and a half miles down. The goal of all this information, of course, is to allow continuous drilling operations without any unscheduled downtime.
That is also the goal for many of the other GE data-driven offerings described at the event, which embed sensors, analytics, and remote communications into a variety of devices from jet engines to wind turbines to MRI machines. Basically GE is angling for a “smart services” business for these industrial devices that incorporates conditional maintenance, predictive maintenance, and intelligent service diagnostics. Smart services will also enable new service relationships in which the customer doesn’t own the device, but rents the capability it provides from GE.
In addition to providing an overview of how all this will work (primarily from Jeff Inmelt, GE’s obviously committed CEO, and Bill Ruh, the head of its software and analytics business), GE announced a series of products and platforms for the industrial internet. I’m certainly not enough of an expert on energy or aviation management tools to know whether GE’s new offerings are competitive, but to go from zero to 24 offerings in a couple of years is pretty good for a behemoth like GE. Inmelt said he’d like to see about double the rate of product development that GE is displaying today, and he’s probably right that such a pace is necessary in the realm of data products and services.
As I wrote here recently, Google Analytics alone announced 70 new product offerings in a year.
I also wrote on this site about the “Analytics 3.0” movement, and GE is a poster child for it. If a huge, big-iron-focused company like GE can jump headfirst into the data economy, any firm should be able to do it. Creating data and analytics-based products and services for customers is a hallmark of Analytics 3.0, and Minds + Machines was all about that objective—successfully achieved so far in my judgment.
The other aspect of Analytics 3.0 is implementing analytics-based internal decisions at speed and scale. I don’t know whether GE has done this or not, but it’s not apparent from the outside. Inmelt did say that he and his management team have had to be retrained to think more analytically in their decision processes, which is a good sign. I know that GE Global Research has also done some good internal decision-focused work—one project was in GE Energy Finance, where they developed a substantially improved analytical decision method for deciding which projects to finance—but I think GE probably has much more opportunity to explore in this regard.
The key message here is that we are entering a new period of analytics, where they have come out of the back room and into the realm of customers and senior managers. I was excited to be at the GE event and to gaze on the sensor-packed blowout preventer because they herald a new and exciting era for what we do with data.
Originally published by WSJ’s CIO Journal.