A new survey conducted by GE and Accenture has found growing urgency for organizations to embrace Big Data Analytics in order to advance their Industrial Internet strategy.

The global study, titled, “Industrial Internet Insights for 2015,” surveyed 250 executives in China, France, Germany, India, South Africa, the U.K. and the United States to explore the state of big data analytics and how it is being viewed across eight industry sectors: aviation, wind, power generation, power distribution, oil and gas, rail, manufacturing and mining industries. Over half the respondents were CEOs, CFOs, COOs, CIOs and CTOs, also including vice presidents and directors from information technology, finance, operations and other cross-functional management areas, reports an Accenture news release.

It was found that only 29 percent companies have predictive analytics capabilities even though big data analytics is claimed top priority for 88 percent of executives. However, 65 percent use big data analytics to identify operating issues and enable proactive maintenance of their equipment and assets. 62 percent have implemented network technology to help gather vast amounts of data in dispersed environments such as remote wind farms or along oil pipelines.

Matt Reilly, senior managing director at  Accenture Strategy explains, “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.”

“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,” he added.

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

Non adoption of big data to support Industrial Internet strategy might lead to industries losing market position in the next one to three years, believe 66 percent of the executives surveyed. Moreover, 93 percent are already seeing new market entrants using big data to differentiate themselves.

Half (49 percent) of the companies intend to establish business opportunities to generate additional revenue streams with their big data strategy whereas 60 percent expect to increase their profitability by using the information to improve their resource management.

Although executives acknowledged the importance of big data analytics, there were differences in response varying with sectors :

  • Prioritization: Aviation executives (61 percent) gave more priority on big data analytics as compared to industries such as power distribution (28 percent), power generation (31 percent), oil & gas (31 percent) and mining (24 percent).
  • Adoption: Railroad (40 percent) and power generation (38 percent) companies frequently said their big data analytics capabilities had advanced to a level of maturity that includes predictive and optimization capabilities.
  • Implementation: Wind energy companies most frequently (61 percent) strategize to use big data analytics to create new business opportunities with new revenue streams.  Railroads (73 percent) were most likely to plan to use big data analytics for insights into equipment/asset health for improved maintenance. Mining (71 percent) uses it often to achieve increased profitability through improved resource management.

Read more here

(Image Credit: Dennis Skley)

Previous post

Mattermark and Bloomberg Beta Develop Predictive Analysis Algorithm to Find Future Founders

Next post

BitYota Announces Launch of its Flagship Data Warehouse Service, Promises More Power Packed and Flexible Experience