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Data versus Intuition

Data versus Intuition

Could humans and machines working together give rise to better decisions?

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Data vs Intuition

74% of New Zealand CEO’s have overlooked insights provided by data analysis or computer-driven modelling because they were contrary to their own experience or intuition.

See the full KPMG New Zealand CEO Outlook Survey

As the world of business accelerates, leaders are expected to make more complex decisions – at pace. When the data they need is available and known, or there is a long track record of experience and evidence, they can apply cognitive reasoning, analysis and estimation to make the right choices.

However in ambiguous situations, they face an incomplete view of the situation and a lack of data. In these situations, leaders tend to rely on their “gut feel” or intuition to make decisions. Intuition played an important role in our evolution: gathering years of individual data to determine when something doesn’t feel right, and merits investigation. First impressions can draw on our bedrock of instinct –when you interview someone for the first time, or walk into a prospective new home and “something doesn’t feel right”. In many instances, when data is gathered down the track, our initial instinct is proven to be correct.

The explosion of “big data” and the increase of computing power has allowed us to make advances in machine learning, AI and automation. These analytical techniques can be applied to everything from predicting which valuable customer might leave, to anticipating the next best product or service. With this increasingly data-driven and rational approach, it’s easy to wonder if there will still be a place for intuition in the future of business.

One way to approach this is to think of intuition as a starting point and input to decision making. For example, a hypothesis is an intuition about what is going on in your business, where the risks, issues, and opportunities may be, which products to develop, or which future direction to take. You can test these hypotheses by performing experiments, gathering and analysing the data. The combination of intuition and information remains powerful. As analytical tools and approaches become more intuitive, through the rise of “augmented analytics”, increasingly we will see that the combination of humans and machines working in unison gives rise to the greatest success.
 

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