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The software world is changing fast, and the only way for enterprise companies to stay relevant is to change with it, Pivotal CEO Paul Maritz said today at the Code Conference in Rancho Palos Verdes, Calif.
Maritz spent 14 years at Microsoft until 2000, and was once on the short list of potential candidates to take over as CEO. He landed at storage and IT giant EMC via that company’s acquisition of Pi Corporation. He later ran VMware, EMC’s cloud software unit, and was tapped to run Pivotal in 2013.
Pivotal is a division of EMC and focuses on two things: Building software and big data and analytics. Its conceit is keyed to the notion that pretty much every company is a software company in some fashion, in that each has its own custom processes that could be improved or automated with software.
“Everything that’s going to be made, from your socks to a jet engine, is going to be attached to the Internet,” Maritz said onstage at Code. “Companies need to learn how to catch people in the act of doing something and affect the outcome.”
Pivotal takes it a step further by marrying that concept to big data, the notion that businesses can glean useful money-saving or money-making insights from the mountains of data — Pivotal actually prefers to call them “data lakes” — that they collect.
Data offers a path forward for companies that might not otherwise have the nimbleness to evolve, Maritz said.
“The whole enterprise space is in transition,” Maritz said. “When transitions happen, you can’t just do business as usual. You create a group of people whose job it is not to protect legacy.”
Maritz declines to call his team “consultants,” but said he sees Pivotal’s job as effecting both cultural and technological change at companies that need it.
“We can go to them and say, ‘We can write software for you, but we really want to write software with you,'” he said.
Pivotal has teamed up with Hortonworks, a player in the world of Hadoop, the open-source big data software intended to simplify the process that leads to those insights.
The point of it all is to learn more about whatever complex system a company may be operating — jet engines, factories, oil platforms — so that it can perform better, faster, more efficiently and at lower cost.
One textbook example comes from GE, a Pivotal investor. It gathers a lot of data on the efficiency of the jet engines it builds. Last year it used Pivotal’s “data lake” to conduct an analysis on the fuel consumption of 15,000 commercial flights on 25 airlines. It’s a big job because of the amount of data involved: The sensors placed in GE engines generate about 14 gigabytes of data on a typical flight.
GE said it cut the amount of time required to do its analysis from months to days. And one airline was able to shave one percent of its fuel costs, real money when you consider that U.S. airlines spent $46 billion on jet fuel last year.
This article originally appeared on Recode.net.
