Five Ways Automation Speeds Up Big Data Deployments
A recent GE/Accenture report reveals that companies in the industrial sector want to leverage Big Data for operations, but they’re stymied by integration challenges.
The survey asked enterprises to name their top three challenges in implementing a Big Data analytics program. The most commonly cited problem in the top three challenges was that “systems barriers between departments prevent collection and correlation of data for maximum impact.” The second issue involved consolidating disparate data and being able to use the results. Security concerns also ranked in the top three.
The report rightly notes that this problem will require more than technology integration. Along with data and systems integration, businesses will also need to break down organizational silos, the piece warns.
One way companies are accomplishing that is to centralize analytics.
“For 50 percent of executives surveyed, their companies are moving toward either an overall centralized group to manage Big Data analytics initiatives or a coordinating group within IT functions,” the report states. “Half of these companies (49 percent) also intend to appoint a Chief Analytics Officer responsible for business and implementation strategies concerning analytics.”
The report’s authors suggest another approach: Converging operations technology (OT) and IT. The report contends this approach would help mitigate the integration challenges – but, I note only 26 percent say they’re considering that option.
Still, the pressure is on for operations. The research revealed that 93 percent of enterprises are seeing new competitors in their market who are using Big Data analytics to differentiate their services. Meanwhile, 74 percent report that their primary competitors are already using Big Data analytics to highlight their own strengths.
“The single greatest risk enterprises see from not implementing a big data strategy is that competitors will gain market share at their expense,” the report notes.
That may help explain another key finding in the report: 73 percent of companies are already investing more than 20 percent of their overall tech budget on Big Data analytics. Two in 10 are investing more than 30 percent of their tech budget on Big Data analytics.
While organizations are mostly focused on data analytics and operational efficiency, there are other reasons to invest, the article notes. For instance, companies are intrigued by the potential for the Internet of Things and the Industrial Internet.
If you’re interested in reading about how all of this might play out in operations, check out this Network World Q&A with UPS Senior Director of Process Management Jack Levis featured on CIO.com.
Levis explains how they approach predictive analytics, as well as answering that long-circulating question: Does UPS really reduce gas costs by only making right-hand turns?
Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.
