A new study has found a growing urgency among organisations to adopt big data analytics to advance their industrial internet strategy.
The ‘Industrial Internet Insight for 2015’ report from GE and Accenture indicates that less than a third of the 250 executives surveyed are using big data across their company for predictive analytics or to help optimise their business.
However, 65% of companies are using big data analytics to monitor equipment and assets, helping them identify operational issues and enable proactive maintenance.
62% have implemented network technology to help gather vast amounts of data from dispersed environments, such as wind farms or oil pipelines.
According to Gartner’s Kristian Steenstrup and Stephen Prentice: “Few technology areas will have greater potential to improve the financial performance and position of a commercial global enterprise than predictive analytics.”
66% of those surveyed feel that their company could potentially lose market position if they fail to adopt big data in the next one to three years, with 88% claiming big data analytics was a top priority for their company.
Almost half the companies represented in the survey said that new business opportunities which could generate additional revenue streams with their big data strategy are part of the plan going forward. 60% believe they will be able to increase profitability using the information gathered to improve resource management.
“The industrial internet, fuelled by machine-to-machine data inputs, has the potential to drive trillions of dollars in new services and overall growth,” said Matt Reilly, senior managing director, Accenture Strategy. “But to reap those rewards, industrial companies will need to use insights about their customers and their customers’ use of industrial goods to build new offerings, reduce costs and reinvest their savings. To get there, many must work through a multitude of issues to use their machine data for more advanced forms of predictive data analytics, including sourcing the right analytics talent to ensure effective execution and scaling of analytics programs.”
Despite the growing momentum when it comes to adopting big data, there remains factors which stand in the way of adoption.
More than a third of those surveyed said that system barriers between departments prevent the collection and correlation of data, while 29% said it is difficult to consolidate disparate data and use the resulting data repository. Security also presents an adoption challenge, with less than half of those surveyed having an end-to-end solution to defend against cyber-attacks and data leaks.
“The payoff from joining industrial big data and predictive analytics to benefit from the productivity gains the industrial internet has to offer is no longer in doubt,” said Bill Ruh, vice president, GE Software. “The tally of success for industry is evidenced by the greater visibility and speed-to-decision across operations and asset performance management. But data alone won’t generate value. To make information useful requires an investment in new capabilities and talent that will serve as a catalyst for extracting value quickly.”