BI Myth: “We Don’t Have Analytic Skills.” Yes, You Do.

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Humans are born analysts with innate analytic skills. Harness that skill within your organization!

I sometimes take part in panel discussions alongside Qlik’s competitors. During a panel at a recent Gartner BI event one of the panelists used a phrase that exposed the real views of the BI old-guard. He said that the spread of self-service BI meant more “fools with tools”. What an arrogant view. People using data discovery are not “fools with tools” just smart people trying to use data to improve how their organizations work.

This opinion is a reflection of another BI myth, the incorrect idea that organizations “don’t have analytic skills” and that giving people the chance to use self-service BI technology is not going to be valuable.

It’s simply not true. People aren’t fools. Quite the opposite – we’re born analysts. Humans evolved in a world of vastly complex information and critical choices. As a result we have outstanding skills in pattern recognition, associative thinking, and an amazing ability to process visual information.

There are four innate analytic skills we use all the time; the first two are explicitly visual:

Pattern recognition – for example when you see a cluster of dots on scatterplot or the upward curve of a line chart. Only a few of us could write the algorithm to statistically cluster data. But we can all see it instantly; in fact we cannot not see it.
The next capability is how naturally we spot outliers, the unexpected items that fall outside the norm. These spikes or aberrations are often where new insights can be found, giving us a visual clue that something isn’t as expected.
The second two capabilities are less visually driven:

Sorting is natural to people as a way of ordering information and things. When young children play they often sort objects by color, shape, size. They’re exercising their analytic instincts when they do so. Give someone a complex set of data and sorting is almost always the first thing they do.
Finally, categorization is another way of attributing sense to the world around us. People use categorization to go beyond simple sorting, using attributes or codification to make mental models instinctively.
I’m not saying things are perfect. Data literacy is an emergent skill that needs nurturing. It is also true that we lack enough skills when it comes to the field of data science (previously called operations research and statistics until about three years ago). Data scientists are still too few on the ground and we certainly need our education systems to deliver more of these skills. As such, it’s not surprising that there are only a few in organizations or none at all in many others. However, even if we could hire data scientists it would not deliver what our organizations really need. Why? Well, as you may have heard my colleague Donald Farmer say before, “Data analysis is too important to be left to the data scientists!”

What organizations need is technology that democratizes data analysis for the majority, making use of the innate analytic skills we all have. Data scientist driven expert analysis can add a great amount of value to complex analytic tasks. For the myriad everyday questions we need to answer: we are well equipped with analytical skills.

Get beyond the false idea that we don’t have analytic skills in organizations. We do. We just need to free people to use them – and that’s not just down to technology. It’s about an attitude, a culture that encourages people to use data while recognizing that they’re not “fools with tools” at all.

There’s lots of proof that this approach works. At the same Gartner event I listened to Scott Silverthorn describe with passion how fast-growing cosmetics vendor Lush uses Qlik. Lush gives all its store managers open access to apps that make use of their innate analytic skills, curiosity and natural competitiveness. Scott quoted a number of his colleagues, but my favorite was from Clare, who manages Lush’s shop in Dundee, Scotland: “It’s like being in the middle of a big crowd but with QlikView you are elevated and can see further than immediately around you.”

Fools with tools? No way. Brains with gains.

By James Richardson in QlikBlog

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