There’s a great video on TedEd called “backwards” bicycle. I highly suggest you to watch it if you have not seen it, it’s really fascinating!
The story is about this engineer, Destin Sandlin, who created an experiment with the help of a group of welders. They designed a backwards bicycle; when you turn the handlebars to the right, the front wheel turns to the left, and when you turn the handlebars to the left, the wheel turns to the right.
It took him 9 months to learn how to ride this backwards bicycle. In other words, it took him 9 months to unlearn and relearn how to ride a bike. When I was a kid, it took me only a couple of days to ride a bike, so why did it take this long for him to relearn something so familiar that it’s almost second nature?
The backwards bicycle experiment illustrates us how difficult it is for an individual to change cognitive processes, in this case something as simple as riding a bike. Destin Sandlin could not ride the specially modified bike. His brain was programmed into riding bikes a certain way over many years of experience, and now it is impossible for him to just switch. After practicing every day for 9 months, he is finally able to master the new bike.
This experiment is a great example of cognitive bias. A cognitive bias is a mistake in reasoning, evaluating, remembering, or other cognitive process, often occurring as a result of holding onto one’s preferences and beliefs regardless of contrary information. Cognitive biases affect our memory, reasoning, and ultimately how we make decisions.
Types of cognitive bias affecting data analysis
We live in the age of data. There is more data available than ever and increasingly accessible tools to collect, analyze, and visualize it. But even skilled data analysts may reach incorrect conclusions because of Cognitive Bias. So, what are some of the Cognitive Biases that affect data analysis?
Confirmation bias refers to the need to prove a hypothesis and therefore to lean heavily on data that might lead this way. Confirmation bias acts to skew results in that the analyzed data doesn’t actually represent the full picture of the scenario.
Availability bias refers to the way in which people make decisions based only on information readily available to them. This is one of the cognitive biases that affect decision-making in daily life, that most people are unaware is even taking effect.
Confounding Variables results when a correlative relationship between two variables is only true when combined with an overlooked confounding variable.
Assisting users with cognitive bias when making decisions
As cognitive bias is a natural part of human thought and processing, business users needs to be augmented and assisted by analytics platforms to control bias to arrive at valid conclusions.
The analytics platforms should enable users access all of the data, at the granular level in a governed manner to avoid biases resulting from only seeing part of the “big picture”. This is where Qlik’s Associative engine provides advantages overcoming some of the cognitive bias affects. On contrary of the SQL based solutions, where the users can only analyze the data with pre-defined hierarchies and pre-aggregated data, with Qlik, the users can search and explore across all data in any direction.
And now with Insights Advisor and Qlik Cognitive Engine, which is available with Qlik Sense June release, users can get new key insights and analysis suggestions from the system with advanced algorithms, assisting them to ask new questions, gain new insights and generate new hypothesis from the data.
If your brain get stuck with asking the same business questions over and over, maybe it is time to break up! Explore and analyze your data with Qlik Sense June release and let your brain be augmented with an analytics platform that can unlock new analysis pathways in your brain!