Creating Business Value from Big Data

Creating Business Value from Big Data

Big Data is keeping some of the most innovative business leaders up at night. Not only does it present a big opportunity, it presents a big challenge. While connected products and connected operations are enabling businesses to generate massive volumes of data, the sleep robbing question is: How am I going to create value from all this data?

Enter big data analytics—the process of examining large data sets to uncover hidden patterns, unknown correlations, customer preferences, and other useful information. The analytical findings are helping companies create new products and markets, streamline operations, and improve marketing, customer service and additional areas of business for greater competitive advantage.

Like Big Data, big data analytics is huge. It allows data professionals to analyze the endless streams of machine data captured by sensors connected to the Internet of Things, and data from Web server logs, Internet clickstreams, social media content, text from customer emails and more. Conventional analytics and business intelligence technology simply can’t do this.

“The promise of Big Data and analytics holds many benefits for manufacturers, but many organizational, proficiency, and technical issues need to be overcome,” states David R. Brousell, Global Vice President and Editorial Director of Frost & Sullivan’s Manufacturing Leadership Council, in his recent article summarizing findings from their new survey.

The survey conducted in late 2014 and early 2015 set out to better understand how manufacturers are developing strategies around Big Data, what benefits they expect from analytics initiatives, and what key challenges they face in using key technologies and organizing their businesses around Big Data-enabled decision-making.

“The conclusion that many manufacturers are just starting to become data-intensive, analytically focused organizations is supported by a number of the survey findings,” according to Brousell.  For example, of the survey respondents:

  • More than one-third see Big Data as important
  • There is no dominant organizational approach for identifying and managing Big Data projects
  • Less than one-quarter grade Big Data abilities high
  • Better decision-making and higher revenues are key motivators
  • Demonstrating value and focusing efforts are top management challenges
  • Nearly half say expectations of benefits are being met or exceeded

Regarding the survey overall, Brousell points out that it reflects a changing industry: “Despite all of the challenges, the perceived benefits associated with Big Data appear to add up to a compelling case for manufacturers to step up to the plate, undertake projects, make mistakes, learn, and move forward.”

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