Emmanuel Okedele

Originally published on Medium. View the original →

Assumptions guide, Hypotheses guide

The world is seemingly made up of random events and processes which when further investigated could show surprising relationships; some dependent and others, mutually exclusive. As a result, making assumptions can be likened to making conclusions without critical thought. It could mean saying “yes”, without duly considering what “no” implies. It may also be described as making decisions without ample research/information with an excessive reliance on bias.

In all fairness, It’s primal for humans to rely on instincts, but learning to probe things more and finetune one’s instinct is much more reliable. A case in point is the sudden boom in Peloton’s revenue during the first half of 2020. According to the BBC, Peloton recorded a global membership base of around 3.1million at the end of June, more than double the figures reported a year earlier.

An assumption could be that Peloton’s marketing team worked wonders, and through dedicated, aggressive efforts, were able to double the company’s sales. One could also opine that Peloton’s new range of products captured a new market segment, resulting in massive growth. This is similar to electric vehicles and Tesla’s growth.

However, the time frame coincided with the start of the pandemic where total lockdowns meant the closure of gyms and afforded people extra time. This resulted in a behavioural shift and an increase in demand for at-home workouts. In this same period, home streaming services and gaming services also recorded huge leaps in numbers.

The hypothesis here is to attribute the increase in sales to the stand-still moment imposed by the lockdown. We can say people had enough time on their plate from lack of work, or school and had more time for their leisure, fitness, and movies.

Following the clue

With hypothesis, these hunches/guesses can be seen as a starting point, the journey is the series of critical thought processes and research done, and the destination is the decision. In essence, a decision is continually checked under several conditions (see it as an audit of some sort), validating or disproving where appropriate. Although the right answer is not guaranteed at the end of this process, it conclusively sheds more light on the pros and cons of said decisions. It may also give a clearer picture of what alternative possibilities entail.

Assumptions and impulsiveness go hand in hand while an extremely structured decision-making process could lead to rigidity and a mechanical approach that ignores the nuances of the decision-making process; the little screws that hold big wheels in place. A hypothesis should be seen as little clues and pointers to the real deal.

Say you were playing a game of “hide and seek”. An approach would be to use recently ruffled areas as clues or look out for trailing legs. You cross out each guess when you do not find your subject. These informed guesses are hypotheses, and you continuously check your results against them.

An example, applicable to colour blind people: There are two balls, one orange in colour, the other yellow. With a light glance, yellow may appear as orange. But when placed side by side with orange, even with a light glance, the eye notices a slight difference. Such is the case of leading with a hypothesis, then continuously assessing. In a grand sense, nothing is truly assured. Decisions should thus be viewed as bets and not absolutes.

Further on, the dynamism of systems (e.g. life and investing) alludes to why this is a continuous/agile practice. You may have been right yesterday, but wrong today. It’d be a good practice to consistently validate one’s hypothesis, especially if a major system is built upon it. Systems are dynamic. Things change, so can the underlying condition.

A case in point is the bullish effect of bitcoin ETFs approval on crypto market sentiments towards the end of 2021 and now, early 2022, the current bearish feeling due to probable legislations on DeFi(Decentralised Finance), stablecoins. Another example is the nature of the UK workforce pre and post-Brexit.

Filtering the noise

This is by no means an exhaustive method or a sure-fire way to make the right decision. Nonetheless, it gives room for critical thinking.

Questions that can be asked include: what assumption is this based on? Is mimetic desire at play here? Do I have sufficient knowledge about this to make an informed decision? Also, a risk-reward analysis can be done; is there a considerable upside to this? What is the downside?

Clarity is the sole aim. That’s the major rubric for standard decision making. Clear the fog, wipe the dew off the glasses. Take a view from different perspectives, aggregate the parts. Let your instincts be the appetiser, not the main course. Lead with hypotheses, possibilities, and not assumptions.

An argument for bias and instinct

A valid counter to this would be to call this decision-making process overthinking. Like, what’s the point of all of this structured framework? Let’s go with the flow and see where it leads. As stated earlier, instincts are nurtured over the years through specialised knowledge, so are mental models and decision-making models. What seems to be an impulse could be an instinct.

Instincts can be modelled as a script with conditional programming (If x then y, else if z then b) similar to how artificial intelligence systems are built. As even avid computer programmers know, this can leave out a lot of possible scenarios. This is why programmers refactor code to further include more use cases. Learning to consider all possible scenarios can prove important in any form of prediction.

Bias, not to be conflated with instinct, is an inclination towards a particular result. Bias is often built by a successful track record and a high percentage of correctness from this favoured approach. In this case, the probing questions would be: what could deter the usual result? Are the usual conditions of performance the same as they are now? Is the level of motivation the same or has complacency set in? the popular phrase “other things being equal” comes to mind.

Decision making and leverage

Decision making and leverage are twins with one umbilical cord which leads us to the concept of risk, lopsided bets and doubling down with conviction. I believe there are two approaches to this: averaging out risk by taking small bets in many forms or doubling down on a couple of bets.

The former is also referred to as the batting average, and it’s based on the premise of unlimited options, while the foundation of the latter is laser focus which requires strong conviction and research. Applications of this can be seen in investment and marketing strategies.

Consider this: Hedge funds often have diversified portfolios and spread their bets. This is a robust system, and it somewhat ensures that drastic market dumps don’t wipe out their portfolio. Conversely, a retail trader may be better off concentrating his fund in a few markets with considerable upside.

Conclusion

To conclude this, I’ll refer to my starting example about Peloton’s revenue and the reason attributed to it. After examination of successive revenue, it was seen that there was a major drop that coincided with the relaxation of the lockdown. Thus, our hypothesis about the lockdown freeing time up for people to indulge in their hobbies holds.

The purpose of this article is not to provide a standard set of rules to rid yourself of biases, because it has its positives. Instead, it is an attempt, at the very least, to make one aware of the possible pitfalls that come with bias and a one-dimensional form of decision making. It is to make you conscious of a logical, algorithmic approach to decision making. However, I believe an optimal approach is the mix of both, finding the balance between sentiment and logic is the sweet spot. Decisions are bets, uncertainties; learn to embrace this.

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