Business analytics is atop most companies' apps wish lists. The business goal, of course, is to make sense of the enormous amount of data and information housed in their servers--and stop making critical decisions from the gut.
"The combination of an increasingly complex world, the vast proliferation of data, and the pressing need to stay one step ahead of the competition has sharpened focus on using analytics within organizations," notes a new study by IBM's Institute for Business Value and MIT Sloan Management Review.
"The adoption barriers organizations face most are related to management and culture rather than being related to data and technology," states the IBM/MIT study, which surveyed nearly 3,000 executives and business analysts from 108 countries and 30 industries.
Here are the top obstacles to widespread corporate adoption and use of analytics (up to three answers were accepted):
* 38 per cent Lack of understanding of how to use analytics to improve the business
* 34 per cent Lack of bandwidth due to competing priorities
* 28 per cent Lack of skills internally in the line of business
* 23 per cent Existing culture does not encourage sharing information
Surprisingly, the study pointed out that "getting the data right" (a.k.a. "data quality" and "one version of the truth") was near the bottom of the barriers to adoption list: Approximately one in five of the respondents cited concern over data quality or ineffective data governance as a primary obstacle to adoption.
"Organizations that use analytics to tackle their biggest challenges are able to overcome seemingly intractable cultural challenges and, at the same time, refine their data and governance approaches," notes the study.
Even given those hurdles, respondents in the study said that they remain bullish on information analytics and how it will help their companies make better and faster decisions.
"Over the next two years, executives say they will focus on supplementing standard historical reporting with emerging approaches that make information come alive," states the IBM/MIT study."These include data visualization and process simulation, as well as text and voice analytics, social media analysis, and other predictive and prescriptive techniques."
Based on this study, execs might want to ensure that those employees tasked with using these new analytical tools are actually ready, willing and able to carry out their assignments.
Thomas Wailgum covers Enterprise Software, Data Management and Personal Productivity Apps for CIO.com. Follow him on Twitter @twailgum. Follow everything from CIO.com on Twitter @CIOonline. E-mail Thomas at firstname.lastname@example.org.
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