Machine Learning

Machine Learning, Analytics Offer Untapped Potential, McKinsey Says

Machine Learning, Analytics Offer Untapped Potential, McKinsey Says

Incorporating data analytics' value into corporate culture is essential to competing against digital disruptors. InformationWeek interviewed McKinsey partner and lead researcher Michael Chui about a new report addressing competition in a data-driven era.

Business and industry have only just scratched the surface when it comes to realizing the potential value from analytics. Consulting firm McKinsey predicted huge value to come in its 2011 report, Big Data: The Next Frontier for Innovation, Competition, and Productivity. and while some of that has been realized already, there's plenty that remains untapped, and there's even more than the original McKinsey report anticipated.

The firm released a new report, The Age of Analytics: Competing In a Data-Driven World, to update its previous research, look at some of the new trends, and provide a picture of the current state of analytics in organizations today. InformationWeek spoke with one of the new report's lead researchers and authors, McKinsey Global Institute (MGI) partner Michael Chui in an interview. Overall, MGI still believes there is huge potential for data and analytics to provide value -- even more than anticipated five years ago when the first report was release.

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"But for the most part, most organizations have not been able to capture the majority of the potential yet," in terms of analytics, Chui told InformationWeek. "There's more work to be done. We are not saying that companies are bad. Almost every company has started doing something. What we've said is there's a lot more you can do."

A couple of the underlying factors behind why the potential has not yet been tapped include organizational issues and the unmet need for analytics talent in the market. But there may be more to it than just those issues, as demonstrated by adoption rates across various business domains. For instance, domains such as retail and location-based business services are quite advanced in the adoption and use of analytics, according to Chui. The public sector and healthcare are quite a bit slower, he said. Manufacturing is somewhere in the middle, particularly with its more recent foray into using data from sensors and the internet of things (IoT).

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Chui told InformationWeek that the degree to which companies in particular domains have adopted analytics may coincide with the degree to which companies in these sectors have had to compete against digitally native companies. Consider Amazon's online retail operations and its use of analytics or Uber's rapid spread of its car-service matching engine. Other industries may not yet have felt such significant digital disruption and therefore may not be aggressively pursuing analytics strategies. Yet.

Another big factor in analytics adoption -- or lack of it -- is the talent gap. The 2011 report identified the talent gap and predicted it would continue.



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