One sentence. That is all you need to reset your brain from simple biases (a.k.a. mistakes in other words). But let’s start from the beginning.

To sum up, logic is not that straightforward

It all started during my holidays. I thought I would do some reading. Which I did. But, besides giving me some tools for my work, the book also challenged my understanding about humans being logical creatures. The book (“How to measure anything” by Douglas W. Hubbard) also talks about perceptions and games that human brain plays. It talks about classical statistics and Bayesian statistics (I am preparing a book overview for my next post. This post is about my experiment).

One of the phenomenons that the book describes is how various biases affect people’s decisions. How perceptions win over logic (say what???). How people choose to believe few pieces of new information and disregard all of the data and facts that they have at hand historically. Having read that, I felt almost insulted for all of us. Oh my saint naivety!

Off to experimenting!

So I decided to test the methodologies and experiments, described in the book. I took exactly the same question, which was used in the book and started asking people around me: “there are 100 specialists in the room. 95 of them are criminal lawyers and 5 – paediatricians. One person was selected randomly. It turned out to be Jane. Jane likes science and she loves kids. What is Jane’s occupation?”.

I started with my partner. First big surprise! On the other hand… knowing how he bought mascara for me… I decided I needed to increase the sample. I tested it with one of my CIPS class students and I was also surprised, again. The final step was to broaden the audience and get the feedback from more people – which I did with a LinkedIn post. I have received many different replies:

• Statistically most likely. Lawyer. There, I said it – most likely, Jane is a lawyer.
• Statistically less likely. Paediatrician. This is the grey area. It is not entirely incorrect answer. Explanation will follow later in the text.
• Different: politically correct, challenging, sensitive, thoughtful, show-off. Knowing, that everyone is first of all a human with a personality, before becoming a professional – you would not expect anything less, right?

Overall the conclusion is one – people are not statistical machines and they are always prone to biases. The book was right. I was wrong to think that people, as a rule, are logical.

The theory

The reason why I avoided to give “the right” answer is complicated. Even statistics is not that straightforward. There are different approaches to it. The book analyses two different approaches – classical and Bayesian.

Classical statistics makes two assumptions:

1. The data you are analysing has normal distribution.
2. You know nothing else about the phenomenon you are analysing apart the data you are given.

Needless to say, both of these assumptions many times are wrong. Bayesian statistics, on the other hand, says that whenever you are making a [business] decision, you should take into account (or not ignore) other available information.

In the example given above, you have two portions of information: 95 criminal lawyers and 5 paediatricians; and some new information – Jane’s personal characteristics. Which piece of information do you choose to believe? Which part is more facts based and which is more biased (“standards”, sales and marketing statements, clichés)? That is up to the specialist to decide.

The Application

If you think this is not relevant to you, you are wrong. It is not just a story from a book:

• Remember every time you hear a sales pitch of yet another P2P system, which “will solve all of your problems”.
• Remember all the times, when you get a feedback, based on wrong biases and assumptions: no matter if it is recruitment process, annual performance feedback meeting or any other type of feedback.
• Remember tender evaluation process. I have seen too many tenders, where all of the historical information about supplier performance is put aside, purely because during the tender the new sales team made a great sales pitch. A supplier was always late and delivered poor quality service? And you choose the same supplier again because the sales team promised that everything will change? It is up to you to choose what you believe.

People make decisions based on biases and perceptions more often that they think they do. Scary?

The Fix

There is a fix to it! And it works! I also tested it on myself and my test groups. Almost ALL people who initially chose paediatrician as an option changed their decision when I asked this question: “If you had £1000 and had to put it on your option – what would you do?” (That is also a suggestion from the book). If they had to put their own money on one of the options, they would choose lawyer.

Without going into details, I will sum up: if you are asked a question and you want to give a more confident reply, start it by saying “if I had to put my money on it, I would…”. It is proven, that this helps to re-calibrate your brain. You might still choose the same option, but by saying that, you switch on a different part of brain – that means your reply will be considered from different perspectives.

My reply to the tender evaluation could be: “If I had to bet my money, I would say that the supplier will continue being late, despite what they claimed during the tender. However, even knowing this, I would recommend awarding the contract to them. It is a risk that we already know about and we need to work on it together with the supplier. Instead of being undefined threat, it becomes an action plan and, potentially, a strength”.

 

Hope this is helpful. I thoroughly enjoyed receiving the answers to my question on LinkedIn. Thanks to everyone who contributed! Thank you for reading!