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Companies benefit from analytics

Global study from MIT Sloan Management Review and SAS finds companies gain competitive edge by using analytics.
New research released today by MIT Sloan Management Review and SAS reports that 67 percent of companies surveyed are gaining a competitive advantage by using analytics — marking a 15 percent increase from last year and 80 percent increase from two years ago.

The report, "From Value to Vision: Reimagining the Possible with Data Analytics," derived from a global survey of more than 2,500 business executives, identifies a group of companies leading the way in the analytics revolution, dubbed "Analytical Innovators." Companies in this category report both strong competitive advantage and improved innovation from using analytics, which are means of interpreting certain data to gain insight and drive business planning. Analytical Innovators are significantly more likely to exhibit three characteristics: a widely shared belief that data is a core asset; more effective use of more of their data for faster results; and support for analytics by executives.

Another important characteristic of Analytical Innovators is their report of power shifts in their organizations: Analytical Innovators are four times more likely than less analytically inclined companies to say that analytics have shifted the power structure within their organizations.

"This is a significant finding, in that power shifts can be disruptive. They often call into question experience and intuition that managers and employees have built up over years," says David Kiron, executive editor for MIT Sloan Management Review. "Now, those who know how to marshal the data and put analytics behind their decision making are in a position of advantage."

The study also identified two types of companies less analytically sophisticated than Analytical Innovators: Analytics Practitioners (representing 60 percent of respondents), which have made significant progress, but have not achieved the top level of competitive advantage and innovation from using analytics; and the Analytically Challenged (28 percent of respondents), which are less mature in their use of analytics and have not derived as much value from them as the other groups.

"As we studied all three groups, we were able to clearly see the specific differentiators among the groups," says Pamela Prentice, chief research officer for SAS. "This enabled us to develop a framework for companies to evaluate their own standing, and to provide recommendations based on a company's current status."

The study's recommendations for the Analytically Challenged include:
  • Start improvements at the local level before trying to address organization-wide issues of technology latency.
  • To further collaboration, build ongoing relationships, facilitate discussions and share information of value to other departments.
  • Fight inertia by developing an executive communication strategy for your analytics case, including a return on investment rate and recommended actions.
Go to MIT Sloan Management Review to read the full report, or for more information on the MIT SMR/SAS joint Data & Analytics project.

About MIT Sloan Management Review
A media company based at the MIT Sloan School of Management, MIT Sloan Management Review's mission is to lead the conversation among research scholars, business executives and other thought leaders about advances in management practice that are transforming how people lead and innovate. MIT Sloan Management Review captures for thoughtful managers the creativity, excitement and opportunity generated by rapid organizational, technological and societal change.

About SAS
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 60,000 sites improve performance and deliver value by making better decisions faster.

To join the conversation on the study, follow @mitsmr or @SASanalytics on Twitter, or join the groups on LinkedIn at SAS and MIT SMR.

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