How to Have No Idea Where You Are Going

Thu 18th Oct 2018

Nomad
noun \'nəʊmæd\

“A person with no settled home, one who does not stay long in the same place; a wanderer.”


One day you have life firmly in the grasp of your hands, you feel empowered, in control and have a spring in your step. The next day you wake up and realise you are, in fact, completely lost.

This is the reality of breaking away from the traditional rat race. Choosing instead to tread your own path can be a lonely journey with no end and a longing for a beginning.

But being a nomad and having to deal with the uncertainties in life does bring some values. Mainly, it makes you resilient to change. Change can come at you from many angles, sometimes you can see the change coming from a distance, at other times it can blindside you at 4pm on some idle Tuesday. Either way, by having nothing fixed means you can adapt faster to change happening.

That’s all well and good, but when the world is your oyster, how then do you choose where to swim, which direction to take, and which untrodden path to create?

There is of course no single answer, everybody is different, but below I share my personal way I see uncertainty and decision making in the most optimal approach. This decision making applies from very simple and logical things like what meal-deal to buy at the supermarket, to seemingly broad and life changing decisions like which country should I move my life to next or what do should I do as my career.

To me, each decision we come across is a split in the pathway, a branch in a decision tree, of your own life (I emphasise the phrase your own life here as this is something worth remembering; whilst decisions have the potential side-effect of affecting other lives, each decision tree here is one life. Your life. So focus on your decisions and outcomes only). And this decision tree, as with any decision trees in scientific approaches, has the potential to be optimised on some metric.

 


The pathway of a decision. Each decision leads to a new path in life. Once the new path is taken there is no point in trying to change it. Rather it is best to optimise the next chapter of the path.

 

The branches in this tree grow and each decision leads to future decisions, future outcomes, of which there are more potential decisions and outcomes to take and make (it’s turtles all the way down). But here’s the catch, at a single state in time the outcome of the current decision is uncertain. This in turn makes the next level of decisions more uncertain and this uncertainty grows exponentially into the future.

So, how in the world do we choose which path to go down? Well, I apply some quick happiness logic to this decision tree. I chose the metric happiness as this is currently what is important to me. The happiness metric can be replaced with whatever metric you value. In my past this metric used to be money. Sometime in the past few years the money metric has become less and less important and happiness has become the main driver in my decision making metrics. Whilst you cannot easily quantify happiness (something I wish was possible, even if just to plot a graph of it against life) you can generally rank the relative happiness outcome of one decision against another.

Whatever metric you choose, assign a value to each branch that reflects the metric given that decision. The tree below shows such an example with a classic decision of choosing between job paths.


The tree above denotes a simple decision of choosing between 3 jobs. The metric is not defined, but it could be money or it could be happiness. The running total is denoted in brackets at each branch.


I mentally map out this tree of decisions level by level. On the first level are the immediate effects of making the current decision I am faced with. The subsequent levels become more hypothetical, but likely scenarios that you might be faced with taking that decision path. As you work your way down the tree you weight the future paths with less significance because of the higher uncertainty associated with those paths. Depending on the problem at hand might mean you only go a couple of levels deep. The final step at the end of this process is to take the running sum at each branch. From that running sum you can then work out which branches are the riskiest, which are the safest, and which have the best payoffs for your metric.

The decision of what denotes the most optimal payoff is not always as simple as taking the highest sum. Sometimes the highest sum involves the highest level of risk that you are not willing to take. Your own comfort level of risk has to be your own decision (with that said I encourage a healthy risk taking attitude to life!).

And that is it! A simple yet powerful way to visualise the path ahead of you. The decision can be a choice of the potential best outcome, or depending on circumstance it might have to be choosing the least-worst outcome when the decision involves an event of misfortune. It can also be a life changing decision process, or simply a process of deciding what conversation to make.


A path of 3 decisions. The shaded area around the paths denotes the uncertainty. As time progresses these decisions more and more, but the uncertainty in these deviations also grows.

Whilst I have provided the tool, only you can decide how to traverse the decision tree yourself for whatever outcome you think is best. Just remember, don’t look too far ahead, there’s too much uncertainty in looking too far forward, whilst this helps optimise decisions in the short term, nobody has any idea where they are going in the long term.