Dragonflies swarmed around, as I stood in the balcony, sipping my hot cup of tea. Zigzag they flew, as each made their way from a nearby muddy pool to the huge tree outside my balcony. My visual systems made notes, observing Mother Nature’s randomness being enacted by these little actors.
I wondered how they made a decision to make the next movement in their flight. Which in turn, made me curious about our own methods of decision making. Considering this sample of random dragonfly movements; either we are still the four legged primates who fail to understand how Mother Nature functions, or we are unwilling to accept that Mother Nature is simply full with randomness that cannot be measured.
In the latter case, this got me wondering about how humans make decisions in a continuously uncertain world (more popularly known as VUCA – volatile, uncertain, complex, ambiguous). After all, if I could even get an inkling to the workings of this phenomena through statistics, then making users pay for a product might become easier; as I would be able to pinpoint the true factors and nudge them to make that decision (acquisition), and keep them coming back (retention), thereby impacting positive cash flow and the business.
With this inspiration, I set out to plot myself (a sample of the homo sapiens) as a data point. However, a data point like the above has multiple dimensions (eg – upbringing, work experiences, partners, food preferences, etc). Since measuring in multi dimensions is difficult for me; for the sale of the argument, I shall stick to two dimensions.
Cognitive Dissonance – The independent variable
To put it in simple words, people make mistakes, think they are right, and honestly believe in it. If one had the chance to interview Hitler just before he popped the pill, it is very unlikely that he would have admitted that he had made any mistakes. Instead, he would have offered a remarkable perspective that not only had he done good but also acted in the best interests of the future of humanity.
A relatively simpler example would be of a human that faces a difficult time integrating two conflicting beliefs, such as “I’m in a decent situation” and “I messed up”. Therefore, the second step the person takes is producing responses to diminish the less desirable belief (“I messed up”) in favor of the highly desirable belief (“I’m in a decent situation”).
“The brain is designed with blind spots, optical and psychological, and one of its cleverest tricks is to confer on us the comforting delusion that we, personally, do not have any. In a sense, dissonance theory is a theory of blind spots—of how and why people unintentionally blind themselves so that they fail to notice vital events and information that might make them question their behavior or their convictions.”
Confirmation Bias – The dependent variable
To convince oneself that the higher desirable belief is the correct one, one narrowly focuses on the evidence supporting the higher desirable belief and ignores the lesser one.
As dissonance increases (eg – faulty data, beliefs, etc lead to a hypothesis), the person becomes biased to prove that it is true (drawing a wrong conclusion based on a wrong hypothesis). Additionally, it creates an erroneous bias in the person with whom one is communicating in the real world. (eg – negotiations leading to bad blood, making a decision to buy a product & regretting it, believing in the wrong team, making a wrong statement in an interview, etc).
Having varied experiences (personally and professionally), and interacting with users through multiple products; my neural network has evolved to a state of recognizing that confirmation bias was at play when those users made decisions (positive and negative). However, I am no guru and have been equally susceptible to falling prey to cognitive dissonance over and over again. Those decisions impacted my bias towards the negative on the Y-axis and lead to erroneous decisions.
If bad times / bad luck are the usual stated philosophy, this essay is an attempt to correlate the abstract with a statistical phenomenon. It is a mix of the social sciences, statistics and product management in an attempt to map the under the hood workings of the why of bad decisions.
“At all ages, people can learn to see mistakes not as terrible personal failings to be denied or justified, but as inevitable aspects of life that help us grow, and grow up.”
- The observed sample of dragonflies might not be a true representative sample because my thoughts happened in that particular time period. A constant recording of this behavior across time would be nearly impossible. Additionally, there could be multiple other reasons causing variances in the behavior of the dragonflies (eg – temperature, humidity, wind direction, availability of prey, etc), which led to the perceived flight movement in that particular time period.
- I am cognizant about the lack of appropriate data set to support these arguments. However, this concept might need to be measured with sufficient research and does not in any way indicate a lack of data driven abilities on my part.
- My own decisions, and the persistence to keep working along the journey of understanding people & becoming an even better product manager (because a product professional ultimately serves end users / customers).
- Mistakes Were Made (But Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts (Link)
- Explorations on the basics of statistics, data science, machine learning and artificial intelligence.
- Readings on some of the great mathematicians of the 20th and 19th centuries.