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Businesses double down on big data value, analytics ROI

Two new resources released over the past month reinforce the notion that companies are becoming more focused on getting real business value from their analytics initiatives.

Businesses increasingly are done with academic and proof-of-concept analytics projects and are doubling down on extracting real business value from their data. The notion that more companies are now looking for tangible returns on their analytics investments was supported by two announcements over the past month: the release of survey results by IBM showing a heightened focus on big data value, and TDWI's launch of an online tool for assessing the maturity of analytics programs.

IBM says businesses have a need for analytics speed

In a survey of more than 1,000 businesses, IBM found that 63% of the organizations that had implemented big data technology saw an ROI within one year, which is up 10 percentage points compared to the results of a similar survey last year. And nearly three-quarters of the respondents said they expect their business executives to demand faster data-driven insights in the year ahead, according to a report on the survey that IBM issued last week.

Report co-author Glenn Finch, global leader for technology and data in IBM's Global Business Services unit, said those the increasing ROI and greater demand for speed reflect a change in how businesses look at big data analytics. He feels that 2014 has been a "breakout year," in which big data projects went from theoretical to value-focused. And now that businesses increasingly are focused on big data value, they want to speed up their analytics processes to help differentiate from the competition, according to Finch.

"Between the speed and what they're doing, it's a pretty big shift," he said. "Last year, everyone was talking about what they were going to do. This year, they started doing it."

One of the main changes in this year's survey results from previous years is that businesses are now more likely to use their analytics programs to try to improve operational efficiency. In the past, the survey showed that analytics applications were being applied primarily to customer issues, like service or the acquisition of new customers. But 40% of the 2014 respondents said they're using analytics to boost efficiency, up 15 percentage points over last year.

TDWI releases its Analytics Maturity Model

TDWI -- formally known as The Data Warehousing Institute -- last week issued the Analytics Maturity Model, an online self-assessment tool that the research and education group said would help businesses focus their burgeoning analytics projects on the importance of value.

TDWI previously developed business intelligence and big data maturity models, which allow businesses to assess the progress of their projects and compare them to initiatives at other organizations. The new maturity model is the first created by TDWI to focus exclusively on analytics.

The model charts an organization's progress from evaluating software and implementing simple tools to developing a data-driven culture, getting executive buy-in and operating well-established projects with strong data governance.

In a press release, Fern Halper, TDWI's research director for advanced analytics, said the goal of the new model is to help businesses understand where their analytics projects stand and see where they have to improve in order to start getting real business value out of their data. Users who complete the 35 questions that are part of the assessment will receive a score assessing the current status of their analytics efforts.

Cortana scores at predicting NFL games

Microsoft's voice-activated mobile device assistant, Cortana, has quietly been racking up a strong record for correctly predicting the winners of NFL games. So far, it has a record of 108-55 on picks this season.

Cortana's predictions are generated by the same Bing Predicts system that correctly predicted the outcomes of 15 of the 16 knockout stage games at this year's World Cup soccer tournament. The tool uses an algorithm based on team stats, home field advantage and weather. It also mines social media posts to incorporate sentiment analysis. You can find predictions for this week's NFL games on Cortana-enabled devices or at

Ed Burns is site editor of SearchBusinessAnalytics. Email him at and follow him on Twitter: @EdBurnsTT.

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Given the amount of data we possess and generate, big data solutions hold a lot of promise. They definitely can make automated prediction more accurate.