Be aware: Linear Thinking
Why More Effort Doesn’t Always Mean Better Results
Linear thinking is the notion that repeatedly applying the same solution to a problem will produce increasingly better results. While this approach may seem intuitive, it stems from our unconscious decision-making processes and can deliver the opposite results when applied beyond a certain threshold.
For instance, some people might believe that undergoing more plastic surgery will make them more beautiful. However, this often results in the opposite effect, as excessive medical interventions can lead to deformities
Another example is the common belief that working more will inevitably lead to making more money. While this is true to some extent, your financial results are often more influenced by the type of work you do or being bound by a salary than by the amount of work you put in.
There is also the classic example of the 'Thanksgiving turkey meal,' where a turkey gets well-fed only to be slaughtered on Thanksgiving. Here the most important aspect is the analogy: often, we find ourselves in positive situations that suddenly turn negative after reaching a threshold we are unaware of.
Notice that these examples have an 'inflection point' where the outcomes change direction, invalidating the previous trend. More important than knowing when this threshold is reached is being aware that this point exists. Predicting future outcomes is often not feasible, as we are dealing with uncertainties and complexities.
Two important factors to be aware of:
Our default primitive predicting mechanism wants us to do the same thing and always expect the same result.
Use your awareness to understand how much we don’t know about the full context of a situation (the 'turkey problem')."
In conclusion, we must always be mindful of the potential unknown consequences of our decisions, particularly when previous experiences have been successful or when we assume that greater intensity will lead to better results. For those interested in decision-making, I recommend a framework I use called 'Tri-Point Decision.'
