One of the areas I was constantly trying to improve was: how to make better decisions. How to improve my decision making ability. Decision is usually based on two main elements: gathering information and defining what are the dimensions of a problem, rank them and make decision based on solution that is bringing the best result in solving the problem. Since technology has influenced both areas of decision making with growth of data availability and complexity of defining proper dimensions of a problem (as consequence of development of communication and collaboration platforms), my quest was becoming even harder.
From intuition to evidence based
Main issue that I was trying to understand was: how to move my decision making process from intuition into evidence based decision making. Or at least how to improve their division. Some decisions, especially ones where speed is crucial, will always be based on intuition. Those should be tackled by improving their execution with training and not so much improving them with understanding their mechanism. When looking at quality of my decision-making process two main obstacles I could identify were:
- How to fight with my biases – understanding them and detect them, when they are influencing my decision-making process.
- How to separate signals from the noise in information that serve as base for decision-making.
So basically, I came to understanding, that I was always estimating my decision based on result of their execution. By doing so I could not make good analysis of them, since I was totally disregarding luck factor. Especially weak was my understanding of connections between quality of inputs, estimation of probability, my reference framework and end result.
In order to tackle my weaknesses I put a lot of effort into understanding those areas:
- to understand what I can control,
- to improve my input mechanism in a way to introduce quality control for inputs (different sources, additional confirmations, introducing other validators of inputs, using broader base for inputs),
- to put a lot of effort in controlling my ego, biases and emotions and trying to understand when they influence my decisions,
- to use a broader circle to get better advice, since in general bigger groups are more correct then smaller ones (since the balance is better and influences are better controlled) and
- I tried to separate influence of luck and quality of decisions when analyzing results.
Diagnosis is sometimes easier part of process. Knowing our limitations doesn’t mean that we will always remove them. In order to at least work on prescription, maybe we can base our behavior on some of the bellow mentioned directions. That is at least what I am trying now:
- Don’t be overconfident about your ability.
- Control what you can control.
- Expand input area and gather different point of views.
- Be systematic about how you are making your decisions.
- Be compassionated about estimating failures.
- Be aware of luck influence.
But even if we follow all that, reality is that we are all making our decisions based on data that we have gathered so far. Data that created our mental framework and patterns. In reality, people are even worse at important decisions (than everyday ones) since their occurrences are rear and so we don’t have a good database for making them.
By introducing technology support for our decision making in a form of better analysis of bigger data sets and more objective algorithm processes, that are less prone to biases and less prone to influence of noise, we have a chance to improve our decision making. We can do that by using artificial intelligence for recurring decisions based on data from previous situations and for suggestions about potential future scenarios. Using our capacity for abstraction, supported with AI input, will enable us to focus on using those prepared inputs for making better bets on future development and hopefully put as in a better position for making big decisions on rare occasions.
Organizational decision making
Since organizations are in better position to improve their decision-making then individuals, we can see a lot of developments in that area. Organizations are working on: how to improve inputs, how to make better decision-making framework with introducing more horizontal decision structure, how to build better decision-making mechanisms with algorithms, how to get better at estimating probabilities, how to build better resilience for uncertainty and how to build more forgiving environment for failures. This could lead to overall improvement of decision-making in general. Again, that doesn’t always guarantee better individual result, never forget about luck element. But if we believe in rule of big numbers, result can be improved on general level.