Making business decisions and dealing with "outliers"

Making business decisions and dealing with "outliers"

I suppose it’s a bit of an unwritten rule that we shouldn’t mix business and politics in a blog like this. I’m going to break that rule now because I am going to use a political example to illustrate the key points I want to make, so I hope you will stick with me – it may be political but it is also impartial!

First of all, let’s define an “outlier”. These can take different forms, as they can be data or they can sometimes be human.

The data outlier is the most common – it’s best defined as a bit of information that is liable to disproportionately affect an analysis of a dataset. For example, a group of teenagers in the park will perhaps have an average age of 16, but if one of them brings their baby sister along the average age will drop, perhaps significantly depending on the size of the group, but in essence is still a bunch of teenagers in the park.

A human outlier might be a person on jury service who will simply not accept a conclusion arrived at by the rest of the jury. This can have a far greater impact than the baby sister, because the output of the jury is intended to be a unanimous, essentially binary, decision, and the presence of this outlier can disrupt that to the extent that it fails.

So where is the politics?

Well, I’m afraid it’s the B-word: Brexit! Politcs is, as we all know, based on a spectrum of beliefs, opinions and ideologies, running from the extreme left to the extreme right.

As with any spectrum, the principle of normal distribution (the bell-curve) applies, in that you will find more people in the centre and immediately to the left and right of that position, than you will at the extremes of the spectrum.

In general, our system in the UK operates by swinging back and forth either side of that centre, and the end result is that many policies are pretty “centrist” in terms of where they lie on the spectrum. The outliers to left and right are able to bring only a limited influence to bear on the decisions of the majority, and that seems to be a fair and proportionate reflection of the “will of the people” (sorry!)

Whatever side of the Brexit debate you fall on, I think all sides can agree that it has not been an auspicious period in British politics. I would suggest that this is because undue weight has been given to (or taken by) outliers, and the disruption caused is the result of many poor decisions made on that basis.

As I said at the start, this is not to make a particular political point – there are outliers on both sides, to the right and the left, which have been equally disruptive in different ways, but the net result is the same: a systemic failure in our collective decision-making capabilities. A logjam, if you like.

In a business, these situations can be quite common – a business decision (big or small) is often made quite quickly, and some organisations don’t possess the flexibility to change those decisions if new information comes to light. It’s tempting to ignore those outliers.

You need to look at outliers in two ways – helpfully, they are either to be ignored, or not to be ignored! Needless to say, the trick is working out which is which!

Commonly, people will raise issues that might be specific to their own experience, so some assumptions that you have made in arriving at a decision can be called into question. If this happens, it can be quite unsettling, as it undermines your confidence in terms of how many other things might you have failed to think about, and so on.

Don’t panic!

Consider a few points:

  • Do you trust the outlier? Are they credible as a point of view?
  • Does what they have said sound like something that many others might also think (so you have just missed something, and this person is not so much of an outlier after all)?
  • If they have expressed a commonly-held view, is it valid or is it just one of those myths of conventional wisdom?
  • Are you falling victim to “confirmation bias”? Does what they have said agree with something that you have secretly supported but felt unable to champion in the decision-making process as a bit of an outlier yourself?
  • On a practical level, what is the impact of this new intervention on the original decision? How much damage will it do to the concept?
  • How easily can you get round it? Are you at a point where you can redefine the decision, or do you need to try and find a workaround to avoid having to go backwards?
  • Does the cost of mitigating this issue affect the original business case?

On the plus side, you may find that the outlier has actually brought a benefit to the end product – perhaps their idea enhances what you are doing, or makes it attractive to a wider audience, or perhaps it has simply opened your eyes to new possibilities.

So the message is that we all need to be aware of what is happening at the extremes of any spectrum – only by listening to and evaluating those opinions will we arrive at widely supported and deliverable decisions. The key skill is in that evaluation – it needs to be fair, as free as possible from preconceptions, but rigorous.

Many of these outlying extreme opinions have no place in the bigger picture, but occasionally they might have a point – just make sure that you neither ignore them nor give them undue weight.

Photo by Vladislav Babienko on Unsplash

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