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Report: Growing urgency to embrace Big Data analytics to advance industrial internet strategy

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Report: Growing urgency to embrace Big Data analytics to advance industrial internet strategy

Less than one-third of companies have predictive analytics capabilities although big data analytics is a top priority for 88% of executives.

A new global study from GE and Accenture reveals there is a growing urgency for organizations to embrace big data analytics to advance their Industrial Internet strategy. However, less than one-third of the 250 executives surveyed for the study are using big data across their company for predictive analytics or to optimize their business.

But progress is underway. The majority of the companies (65%) use big data analytics to monitor their equipment and assets to identify operating issues and enable proactive maintenance.  Sixty-two percent have implemented network technology to help gather vast amounts of data in dispersed environments such as remote wind farms or along oil pipelines.  

"Few technology areas will have greater potential to improve the financial performance and position of a commercial global enterprise than predictive analytics,” according to Kristian Steenstrup and Stephen Prentice, Gartner.   

Two-thirds (66%) of the executives surveyed across eight industrial sectors believe they could lose their market position in the next one to three years if they do not adopt big data, which the report suggests is needed to support their Industrial Internet strategy.  Additionally, with 93% already seeing new market entrants using big data to differentiate themselves, 88% of the executives stated that big data analytics is a top priority for their company.  

Nearly half of the companies represented in the study said they plan to create new business opportunities that could generate additional revenue streams with their big data strategy while 60% expect to increase their profitability by using the information to improve their resource management.

“The Industrial Internet, fueled by machine-to-machine data inputs, has the potential to drive trillions of dollars in new services and overall growth.  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,” said Matt Reilly, senior managing director, Accenture Strategy.  “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.”    

Paving the Way to Adoption
Despite the sense of urgency, there are roadblocks to realization. More than one-third of the executives (36%) said system barriers between departments prevent collection and correlation of data. Twenty-nine percent said it is difficult to consolidate disparate data and to use the resulting data repository.  Security also ranks high as a challenge with less than half (44%) reporting 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.”  

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