How Augmented Analytics Find Patterns That Humans Can’t

How Augmented Analytics Find Patterns That Humans Can'tHuman beings are incredibly good at finding patterns. We can infer the meaning of a whole article by skimming a few sentences, instantly spot a friendly face in a crowd, or recognize a favorite song from just a few notes. Our brains are so good at looking for patterns, we see them when they aren’t even there — seeing animals in clouds, for example, or little faces in 3-prong electric outlets.

 

But while we’re great at intuiting patterns, when it comes to crunching data systematically, our abilities are decidedly more modest. Just looking through a couple hundred entries in a spreadsheet will make most people’s eyes glaze over, and as organizations grow, human limits become a more significant problem. 

 

Once you’re dealing with hundreds of thousands of transactions, a human can’t examine the data in a systematic way without help from a machine, let alone analyze it across hundreds of axes like modern analytic software can do. And as a new Gartner poll demonstrates, businesses are increasingly turning to machines to detect the patterns hidden in masses of data that humans can’t find. 

 

The Transformative Power of Augmented Analytics

 

In the new Gartner Data and Analytics Summit poll, over 60% of respondents believed that augmented analytics “will have a high or transformational impact on their ability to scale the value of analytics in their organization.” Respondents were enthusiastic about the potential of analytics to give insight “in analytics and BI platforms,” as well as more generally within their organizations. 

 

To illustrate how augmented analytics provide insights humans miss, Gartner cites the case of a fast-food restaurant that happened to move its fountain drinks (which are more profitable than bottled drinks) during a remodel. Their augmented analytics system found that this movement led to a 20% increase in fountain drink sales, something a human wouldn’t have known to even look for. Without the machine, it would have been a fortuitous and temporary condition that probably would have passed unnoticed. But because the system was able to recognize the pattern, they were able to change the store design to maximize drink profits. 

 

Augmented Analytics Are Key to Tomorrow’s Insights

 

These sorts of augmented analytic insights are becoming common across industries. Businesses use cases for augmented analytics range from preparing data to aid analysts, to comparing groups of customers, to capturing and systematizing tribal knowledge before experts retire. And as the use cases multiply and the technology continues to mature, these tools will increasingly determine the winners and losers across the business world. 

 

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