Obstacles to unlocking the potential of analytics and data

Key in lockA data-driven era of business offers organizations a valuable opportunity to gain a competitive edge over their rivals. But while businesses understand this opportunity, they often fail to grasp it or identify its true value.

“Knowledge is power,” as the saying goes, but grasping that power may not be straightforward.

Almost all businesses now realize that big data holds the secrets of tomorrow’s competitive advantage. What most have yet to work out, however, is how to unlock this knowledge.

In most organizations, the data and analytics work undertaken so far has been piecemeal and uncoordinated. Few organizations even have a clear view of what their data might be worth.

With sizeable investments now being made in data and analytics tools, such ignorance is no longer tenable. The C-suite cannot be expected to sanction spending on new technologies and techniques – even on a small scale – without a credible assessment of what the return on such investments might be.

Many organizations are becoming frustrated with the limited progress they have made in using their data to generate actionable insights that deliver real commercial benefits.

At the same time, they have little idea of what is preventing them from unlocking this data – and are therefore struggling to improve performance.

Recent EY research has identified eight separate obstacles causing problems for organizations as they seek to derive value from data:

  • Digital distraction
    Too many enterprises focus on what data and analytics technologies could hypothetically be used for, rather than using them to address fundamental business issues.
  • The technology challenge
    Organizations are struggling to cope with the volume, variety, velocity and veracity of data. They lack the tools to cope with and filter a deluge of data, and aren’t able to turn information into business insight quickly enough.
  • A tendency toward silos
    Few enterprises are thinking about data on an enterprise-wide basis. Instead, different functions are pursuing different goals independently, with little thought about what could be achieved through a more holistic approach.
  • Talent shortages
    Organizations are finding it difficult to recruit people with both the technical know-how needed to implement data and analytics strategies, and the business insight to prioritize as required.
  • Concern about information security
    Given the growing danger of cyber attacks, enterprises are anxious about becoming more dependent on data and analytics.
  • Building the business case
    With few big data projects yet to demonstrate measurable returns, particularly in terms of adding revenues rather than achieving operational efficiencies, it is difficult to build a case with realistic forecasts.
  • Compliance complexities
    As regulators in different territories add to regulation in areas such as data security, organizations are growing increasingly worried about the cost of compliance, as well as the damage – both financial and reputational – that a data failure might cause.
  • The need for data
    Organizations need more data in order to power their analytics models, yet customers in many markets are increasingly reluctant to share their information.

    The scale of the challenge should not be underestimated. The question for CIOs is how best to go about overcoming these issues.

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