Most Industries Are Nowhere Close to Realizing the Potential of Analytics

Most Industries Are Nowhere Close to Realizing the Potential of Analytics

Most Industries Are Nowhere Close to Realizing the Potential of Analytics

Back in 2011, the McKinsey Global Institute published a report on the transformational potential of big data—and it would take a supercomputer to process all of the articles that have appeared since then urging companies to get on board before some digital disruptor renders them obsolete. And yet for all the hype, most industries have still not come close to realizing the full potential of data and analytics.

MGI’s latest research with McKinsey Analytics on the state of the big data revolution measures the progress various industries have made toward capturing the revenue and efficiency gains we envisioned five years ago. Spurred on by digital-native competitors, the retail sector has captured about 30% to 40% of the margin improvements and productivity growth we identified in 2011. Manufacturing has captured some 20% to 30% of the potential, while the public sector and health care make the worst showings, realizing only 10% to 20% of the value.

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Lurking behind these numbers are glaring disparities in performance between a few firms at the cutting edge and the average company in any given industry. An examination of the telecom industry, for example, shows that the analytics leaders have posted three to five times higher returns on their big data investment than the typical telecom company. Lower returns cannot be simply chalked up to the fact that companies are not investing at scale. On the contrary, many executives have made big technology bets but are now wondering why those investments haven’t yielded the kind of payoff they expected. McKinsey recently surveyed more than 500 executives representing companies across the spectrum of industries, regions, and sizes, and 86% reported that their organizations were only somewhat effective at meeting the goals they set out for their data and analytics initiatives.

In many cases, the culprit is a gap between launching a few analytics experiments and embedding these insights into the operating model of the larger organization. Many companies invested in analytics systems without fully appreciating that turning data into real value requires a profound reshaping of their day-to-day workflow. Others are still lagging behind in terms of fully digitizing transactions and processes to generate and collect all the data that could be useful.

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An effective transformation strategy starts with clearly articulating how data and analytics will be used to generate value and how the results will be measured. Once the strategic vision is in place, senior leadership, including the CEO, will need to champion it personally in order to overcome institutional resistance and break down silos between departments.

 



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