Contextual metrics and cognitive biases

Imagine management presenting the below report in one of your IT meetings. While the facts and figures are intimidating for a chronic smoker to think twice before lightening another bud (or is it?), the report is completely out of context. But the presenter, due to his/her biases, makes it appear important and derive some relationship with the present context.

False cause fallacy: Presuming that a real or perceived relationship between things means that one is the cause of the other.

Every day we are bombarded with metrics which are out of context or irrelevant. But we allow ourselves to be influenced by those unrelated reports and interpret the results by filling in the gaps, again due to our biases.

Framing effect: You allow yourself to be unduly influenced by context and delivery.

Barnum effect: You see specifics in a vague statement by filling in the gaps.

Even my thinking of the above is due to my own bias, which makes me rationalize my belief to support the conclusion.

Belief Bias: If a conclusion supports your existing beliefs, you'll rationalize anything that supports it.

So, continuing with my belief - 95% of our brain activities are based on intuition and instinct and only 5% of rational thinking. Then does it make sense to feed a plethora of data and metrics just to convince that 5% of the brain when actually 95% of it is seeking some emotional appeal and makes a decision?

Continuing the context of smoking and its effect, we may be able to successfully trigger the neural networks of our highly active emotional brain with an individual's story, like below.

But then how many of us know Barb Tarbox to be able to emotionally relate with? Again, here the context is important. We may be able to get a better emotional response if someone local we can relate to is referred to in the message. Again, I may be having a flaw in my reasoning.

Appeal to emotion: Manipulating an emotional response in place of a valid or compelling argument.

Conclusion:

• Identify some of your most common biases and fallacies in identifying key metrics.
• Because of the power of emotions, it’s critical to consider emotions among the key metrics.
• Add a pinch of context to your metrics, KPIs and dashboards etc. to make it relevant and appealing.

As Pearl Zhu said, “Don’t just play the number game, but connect the contextual dots and focus on the overall business objectives.”

Reference: https://yourbias.is/