Senior Executives Describe Their Organizations’ Decision-Making As More Intuitive Than Data-Driven

July 13, 2018

This article is included in these additional categories:

Analytics, Automated & MarTech | Customer-Centric | Data-driven

Since the advent of data and analytics there’s been a strong push to make decision-making more about data than intuition. However, a new study from MIT Sloan Management Review and Think with Google finds that decisions are still being made more on the basis of intuition than data.

The survey – conducted among more than 3,200 senior executives around the world, roughly half of whom are marketing executives – found that 38% describe their organization as intuitive in its decision-making, compared to 27% who describe it as data-driven. (The remaining 35% say their organizations are equally data-driven and intuitive.)

That brings to mind earlier research from PwC, which found that many billion-dollar decisions were being made on the basis of intuition rather than data and analysis. Another study on the topic found many business decision-makers saying it’s often necessary to rely on “gut feelings” when making decisions, and that soft factors should be valued as highly as hard factors.

Some senior executives, though, appear to be more advanced in their ability to use data to drive decision-making. The report divided its respondents into 3 groups based on their answers to 6 questions about their use of KPIs: Measurement Leaders (top quintile – 20% – based on their answers); Measurement Capable (middle 60% based on responses); and Measurement Challenged (bottom quintile).

Measurement Leaders were about as likely to say that their organizations’ decision-making is primarily data-driven (32%) as to say they’re based on intuition (35%), with the rest believing them to be equally data-driven and intuitive.

The Measurement Challenged group, by contrast, was almost 3 times more likely to be driven by intuition (51%) than data (18%).

Part of the problem for the laggards relates to the prioritization of automation and machine learning. Although 84% of Measurement Leaders report that their organizations are investing in new skills or training this year to make marketing more effective in using automation and machine learning, only one-third (33%) of the Measurement Challenged agree. Furthermore, fewer than 1 in 5 from the Measurement Challenged group have incentives or internal functional KPIs to use more automation and machine-learning technologies to drive marketing activities, compared to more than three-quarters (77%) of Measurement Leaders.

There are problems beyond prioritization, too. The Measurement Challenged have less access to other C-suite or functional leadership KPIs, are less able to drill down to see the underlying data or analytic components aggregated into their KPIs, and are much less likely to have functional KPIs that help their function develop a single, integrated view of their target customers.

About the Data: The results are based on a survey of 3,225 executive-level respondents, more than 1,600 of whom are marketing executives. These individuals come from 107 countries and 20 industries.

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