Insight Connection

When Logic Leads Us Astray


As an evangelist for data driven decision making I am passionate about using data insights to drive the right conversations, that in turn lead to the best decisions. However, data can just as easily lead us astray.

Let me use a personal example to illustrate my point. I am currently looking to buy a house in an area that I have no previous experience with. I can look at the maps, view the streets on Google Maps and take a virtual tour of the house on the real estate site. I even get 20+ photos and floor plans. I can look up the suburb profile and research the local weather, demographics, amenities and economic factors. One could easily say “everything I need to know about this property is available online”.

However, what all that data doesn’t tell me is about those elements that will make each day a pleasure – does it get a sea breeze, how noisy are the neighbours, are there pounding stereos or dogs barking on a regular basis, are people friendly when one passes them on the street, is the water at the beach nice to swim in or is it constantly churned up to a sandy sludge?

There are so many human factors that are not represented in the data available. We have all learnt that one cannot rely on the real estate agency photos – as those wide-angle lenses make rooms look twice as big. There are just as many distortions in other data we rely on in making such an important decision. This is where #theHumanFactor comes into play, over and over again. One needs to visit the area, talk to the locals, experience the cafes and night life, be there during rush hour or school pick ups, wander around the streets at night.

It’s the emotional elements of a living environment that will make us happy – not the construction of the house. For decades, economic models failed to capture emotional factors, which eventually led to highly distorted ‘insights’ being published. Are we in danger of following the same path with business insight, or market insight?

What data does do is provide insight into a myriad of elements that we need to investigate, but when it comes down to resource investment decisions we have to bounce that data against a humanised wall of logic to test how valid it is in meeting the specific human goals we are attempting to achieve.

If you are progressing along the continuum of business insight to data-driven decisions, what are you doing to ensure that the human factors are not overlooked?

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