Prudential Algebra is a decision making algebra first invented by Ben Franklin. To boil it down it is a balancing act between the pros and cons of all the options involved in the decision stretched in a time frame of a few days.
The method as written by Ben Franklin in a letter to his friend..
In the Affair of so much Importance to you, wherein you ask my Advice, I cannot for want of sufficient Premises, advise you what to determine, but if you please I will tell you how.
When these difficult Cases occur, they are difficult chiefly because while we have them under Consideration all the Reasons pro and con are not present to the Mind at the same time; but sometimes one Set present themselves, and at other times another, the first being out of Sight. Hence the various Purposes or Inclinations that alternately prevail, and the Uncertainty that perplexes us.
To get over this, my Way is, to divide half a Sheet of Paper by a Line into two Columns, writing over the one Pro, and over the other Con. Then during three or four Days Consideration I put down under the different Heads short Hints of the different Motives that at different Times occur to me for or against the Measure. When I have thus got them all together in one View, I endeavour to estimate their respective Weights; and where I find two, one on each side, that seem equal, I strike them both out: If I find a Reason pro equal to some two Reasons con, I strike out the three. If I judge some two Reasons con equal to some three Reasons pro, I strike out the five; and thus proceeding I find at length where the Balance lies; and if after a Day or two of farther Consideration nothing new that is of Importance occurs on either side, I come to a Determination accordingly.
And thoâ€™ the Weight of Reasons cannot be taken with the Precision of Algebraic Quantities, yet when each is thus considered separately and comparatively, and the whole lies before me, I think I can judge better, and am less likely to take a rash Step; and in fact I have found great Advantage from this kind of Equation, in what may be called Moral or Prudential Algebra.
One aspect about this method is the time frame recommended between different steps. There is enough time for both our conscious mind to spit out everything we know about it and our unconscious mind to spell out what it picked up on the matter. This also spills into a decision journal. Over time, the record of each prudential decision made would be a great feedback loop to assess flaws in your decision making process.
Barnum Effect, also known as Forer Effect, is the tendency to take general statements and interpret it from a personal point of view. A very common example where the Barnum Effect is exploited is in horoscopes and fortune telling. You can commonly see sentences like “When something good lands in our lap, we frequently fail to appreciate it, because we immediately begin the process of protecting, coveting, and ultimately hoarding our treasures.” This sentence can have different meaning because as we read it we relate it to our life experiences.
The more personal input you give in the process, even stronger is the effect. Personality tests like MBTI can seem more accurate then they are. Especially if it is combined with confirmation bias. If the tests, for any reason tells you something that you knew or wanted to be true. It is highly likely that you will believe it. People won’t believe or pay attention to general statements that are considered negative.
What you see is all there is.
Coined by Daniel Kahneman. Even though we like to think of ourselves as rational and objective human beings when making decision. The truth is that we are very well affected by our psychological biases and emotions.
WYSIATI is the bias that leads us to make judgements and conclusions with the information that is available to us. Without considering what other piece of information might be missing. We have the tendency to bend the pieces of the information jigsaw puzzle when some key parts might be missing. Our brain chooses the path of least resistance to form the big picture. It is a machine designed to jump to conclusions.
One way to combat this is to have a structured thinking process and a system to evaluate decisions. Deliberate decision-making can be practiced and it takes time and effort.
Hindsight bias is a tendency to look back at past events and perceive events as more predictable then they actually were. For example, there are many ways a global pandemic could have played out, and there was a lot of uncertainty at the beginning. But now it would seem more predictable as there was no other probable course of action.
When looking at your own past decisions, it might seem that you made the right decisions but for the wrong reasons. We don’t want to be critical of ourselves. And our brain takes a shortcut to avoid that and to explain it in a much easier way with the information of the outcome that you have now.
The only way to keep a check on this is to keep a record of how a decision was made. And evaluating them at a future point of time.
A common shortcut our brain takes during comparing two options is to, at least for the moment assume everything else is the same between the 2 options. Hoping to get a more objective judgement of the situation.
Occam’s razor, if all else is equal, the simpler explanation is preferred over a complex one. However, it is rare in the real world to have to decide between 2 options where they only differ in one dimension.
This mental model can backfire if not used with care in the real world. It is important to understand what are the other parameters that is assumed to be constant. Whether it is possible in the real world where a scenario would exist with similar options in all dimensions but one. The bottom line is that the comparison should be made between 2 possibilities that have a chance of existing in the world. It doesn’t help if the comparison is done between 2 hypothetical situation and using that judgement to choose a real world option.
Figuring out which parameters of the system affect it directly and indirectly is a good exercise to perform. Comparing indirect parameters is a recipe for a disaster. And by direct parameters, I mean parameters that are fundamental to the characteristics of the system. Fundamental, also read as, first order implications instead of derived aspects. For a business, it could be profit after tax, for a business loan it could be interest and time period.
That said, sensitivity analysis uses this principle and is a good method to get a better understanding as to how different variables affect the outcome and behaviours of the system under question.
A term I came across from Mental Models Vol. 1. But this is something that I have found myself doing and has been useful in helping me make decisions.
When presented with a decision that is a) affected by a lot of uncertainty the future holds b) a large set of possible outcomes can be guessed, then having a theoretical world generator helps.
Having a checklist of aspects to consider is a good idea. A set of checklists covering different dimensions. Maybe they can be classified as internal or intrinsic aspects and external ones. Or can be classified in terms of time.
Thinking about the possibilities in a form of a tree can also help.
After mapping out most of the outcomes and possibilities. The next step is to individually think about the probability of each outcome from happening.
Now here is the kicker. What makes this a really neat is that we have to start thinking about the different outcomes and work our way backwards to the event&decision. Thinking forward and backward through a possibility tree.
This exercise can easily backfire too. So figuring out on what problems this approach works and doesn’t is key. This takes a lot of trial and error, increasing domain knowledge and in general being able to ingest a large amount of information before running the TWG.
TWG is a good way to evaluate your past decisions. Given the information that you had at the time and if you run a TWG now for this decision, how would your decision change.
“I rather be roughly right than be precisely wrong”. Avoid the craving to go into details of outcomes of trigger that should happen. Keep it as broad as possible. When it comes to figures and statistics, look at ranges and trends not at actual figures down to decimal
A note on decision making. A decision is good or bad not based on the outcome but based on what information was available at the time the decision was taken and what heuristics were applied to reach a particular decision. Tweets like these are quite common. “If you had invested 10$ in X 10 years ago now you would be a millionaire”. And that is evaluating a decision based on its outcome. But what you should be thinking is what information did you have then, what was missing, what could have been predicted given the information you had, what mental models and principles were at play and why that happened. This kind of thinking is crucial to improve how you think and to make it better. Dwelling on your past decisions for most is a more tiresome exercise than a fruitful one. To apply this without messing it with your head requires a good amount of self-awareness and discipline.
Comparative advantage describes how trading parties will choose to produce more of a good that they have a comparative advantage of, and use that to trade for other goods that they don’t have a comparative advantage in. Comparative advantage forms a foundation for international trade.
Comparative advantage is why there are call centers in India, manufacturing in China and highly specialized capital intensive labor in the US. It makes sense for China to do all manufacturing electronic goods and trade it to other countries that are specialized in producing other goods.
Conversely, an oil producing country will have a cheaper access to raw material for chemical products. They have a lower opportunity cost of producing more chemical products compared to countries that do not have access to cheap raw materials. This drives more chemical production in oil producing countries.
However, there are cases where countries, governments and business lobby together to protect niche interests. This can effectively keep foreign, cheaper goods out of the market to protect domestic businesses. However, in the long term, this might not good solution as neighbouring countries will be better off as they have to spend less to get the same goods.
The Lindy effect is a phenomenon where the future life expectancy of an item increases with each year survived. Counter-intuitive as it may seem, there are a few explanations to this effect. The effect mainly applied to non-perishable items. Items that do not have an expiration date governed by unstoppable forces. Time plays an imprtant role in this effect. Longer an item is in play, the better fine-tuned it becomes. More equipped it will become to survive the coming times.
Books are a good example where this effect can be applied. If a book has been repreinted for the last 40 years, there is a good chance that it will be for the next 40 years. The explanation being that the content of the book has seem to find appeal to a demographic that is renewed over time. Though the medium might change from printed books to kindle to audiobooks.
Items or systems that have built a self-enforcing loop around it tend to follow the lindy effect. Businesses with moats around them are an example. They have a competitive advantage that compounds over time. Such businesses become harder to fail as time passes by.
Choosing what to read can be guided by the Lindy effect. Choose books that are foundational in the area to start with. Coincidentally, those books have been around for some time. The same applies when doing a literature review for some research. Start with survey papers. They, by definition, cannot go out of trend. Hence the popularity of survey papers.
Berkson’s Paradox is a type of sampling bias. This paradox can lead to experimental studies concluding that 2 events are related when they are actually not. This was first identified in case-controlled studies.
A study by Sackett(1979) portrays this paradox quite well. He wanted to study the presence or absence of respiratory disease and locomotor disease. He took 2 samples. One from a random community from the general population and one from the hospital. When looking at the results from the hospital sample, the data points out that the it is much more likely to have a locomotor disease if you have a respiratory disease. But it is not true. This correlation emerges from the fact that it is more likely to have patients that are admitted for both diseases in the hospital, while we are not considering the part of the population that neither has a respiratory disease nor a locomotor disease.
When looking at the results from the community sample it was clear that there is no correlation between the 2 disease.
Control group based studies are common in many studies not only restricted to healthcare. Especially around studies to evaluate industry and consumer trends. It is important to look at where the data is coming from i.e. who is in the sample population and how that relates to the big picture.