Triumphal march of big data? More like a plod

Triumphal march of big data? More like a plod

Summary: Despite all the talk of big data and the benefits of analytics, a significant number of businesses are still at a loss as to how to apply the technology.


The road to big-data heaven is proving bumpy for many organisations, with about one in four saying integrating data from different sources has actually become less manageable over the past year.

Many companies are still struggling to figure how, where and when to use analytics

Those firms are in fact outnumbered by ones that see improvements but, taken with businesses seeing no change at all, still amount to more than 50 percent of organisations, according to new research.

The picture is even worse when it comes to using data to establish objectives and strategy, with fewer than one in three saying they rely mostly or entirely on analytics for the task, the study from MIT Sloan Management Review and business-intelligence firm SAS found.

In fact the figure for data-driven strategy falls to 18 percent for UK companies, with North American organisations on 27 percent against a worldwide average of 31 percent.

Analytically challenged

The report's authors categorised the 2,500 firms surveyed according to their use of business analytics, describing only 11 per cent as innovators in their application of the technology, with 60 percent of the total classed simply as practitioners, and 11 percent as "analytically challenged".

"Increasingly, top thinkers in academia and business believe analytics, especially analytics connected with big data, is going to be a driving force in our economy and society in the next 10 to 20 years," write the report's authors.

But in conclusion to Reimagining the possible with data analaytics, they point out: "Many companies are still struggling to figure how, where and when to use analytics." The report says those working in organisations using the technology successfully share a belief in the value of data, which is backed by senior managers, and use more data to produce faster results.

Adverse effect of analytics

Although most organisations are seeing benefits from the use of analytics, about one in four thinks access to more information and insights is having an adverse effect. The increase in data insights available is actually making taking decisions more difficult.

When asked to rate their organisation on its ability to aggregate and integrate information, 26 percent of North American organisations described their business as very or somewhat ineffective, slightly worse than the global figure of 24 percent.

However successful they are at employing analytics, most businesses share a belief that the technology will ultimately yield significant benefits, with two-thirds saying it will make them more competitive, up from a figure of 37 percent in 2010.

The study recommends that organisations that are struggling with analytics should start at a local level rather than try company-wide projects and try to foster collaboration between departments.

Firms should also develop a communications plan to build support at the top of the organisation

Topics: Big Data, Enterprise Software, Business Intelligence

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  • Not just local, but visual

    "The study recommends that organisations that are struggling with analytics should start at a local level..."

    Agreed, but I would go further and suggest that the nature of analytics should be simple to start with; *go visual*, before you consider algorithms, data mining or predictive analytics.

    It's important to frame analytics - too many organisations use the term to refer to regular business reporting. Analytics is the science of logical analysis; to engage in analytics is to go looking for "known unknowns" rather than addressing the "known knowns" of management reporting.

    Visual Analytics ( offers an easy entry point for organisations wishing to explore their data, make sense of it and discover interesting stories about business performance. Better still, information uncovered through Visual Analytics is easily communicated, and understood, by a non-analytical audience - that is, the results of strong visual analysis are easily presented, discussed and actioned, without the audience requiring the ability to either understand statistics or accept that a 'black box' has discovered a valid insight.

    In the longer-term, Visual Analytics provides both a rapid prototyping environment for predictive and algorithmic approaches, and a means of presenting the outcomes of ML-based analytics, so that we humans can interpret analytical findings and select appropriate actions.

    Guy Cuthbert
    Managing Director
    Atheon Analytics Ltd