Decision Mechanics

Insight. Applied.

A passion for decision analysis

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When discussing the value we offer to clients, the focus is often on technical aspects—experience, understanding the psychology, skill with tools, processes, etc.

However, it occurs to me that often much of the value we bring to the table is energy and a fresh set of eyes. In many circumstances decision-makers have decision fatigue. It might be due to the number of decisions they have to make, or how long they have spent mulling over this particular decision.

When you are exhausted you make poor decisions.

Engaging the support of a decision scientist gets you someone who isn’t drained. In fact, it gets you someone who is excited about looking at your decision in detail, and from all angles. This work isn’t a burden to the consultant. It’s their job.

No-one likes to admit they are just plain exhausted/exasperated. But you can often see the weight of the world lifting off the shoulders of decision-makers when we come in to help.

Photo by Ian Schneider

JavaScript for data science?

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Arquero is a data manipulation library written in JavaScript. It’s modelled on the excellent R dyplr library.

JavaScript isn’t known as a data science language. However, it’s probably the best language for data visualisation—and Google’s relentless optimisation of the V8 engine means it has better performance that Python or R.

The JavaScript ecosystem lacks extensive data science libraries, but Arquero coupled with, say, D3.js makes for a capable data visualisation platform.

Photo by Anton Darius

Human brains hate probability

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There was a great article published last month discussing risk communication.

Statistician Regina Nuzzo is quoted as saying

Human brains hate probability, they hate ambiguity, they hate the uncertainty. We’re just not wired to deal with this sort of thing very well.

Science journalist Tara Haelle explains that it’s difficult to separate reporting from influence. She notes that covering polls about willingness to take a vaccine set behavioural norms.

The more people question vaccines, the more people question vaccines. Vaccine hesitancy is contagious.

So, in summary, we find it difficult to think about probabilities, but are easily lead by opinion. This is why it’s increasingly essential for everyone to develop a degree of statistical literacy. With so much data flying around, and so many people commandeering it to promote their own view, we all need to be able to come to our own informed conclusions.

Photo by Naser Tamimi on Unsplash

Statistical intuition

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The Monty Hall problem is a probability puzzle based on an old US game show. You are shown three doors. One contains a car, while the other two contains goats. The game show host invites you to pick a door. He then opens one of the doors containing a goat and asks, "Do you want to stick with your original selection or switch to the remaining door?"

What should you do…assuming that you don’t wish to own a goat?

I’ll take all the fun out of it. You should switch. It doubles your chances of getting the car.

Convinced? Probably not. Even when presented with the solution, many people struggle to accept it. It’s not particularly intuitive.

Martin Johnsson recently discussed this on his blog. He used paper simulation, computer modelling and mathematics to try and satisfy himself of the wisdom of switching. He concluded

…I’m not sure I have convinced myself of the solution to the generalised problem yet.

Reasoning about probabilities is hard. It’s very easy to be led astray by our "gut". As the eminent statistician Sir David Spiegelhalter has noted

…when asked a basic school question using probability, I have to […] try it a few different ways, and finally announce what I hope is the correct answer.

This dereliction of our instincts means that it’s essential to draw on the formal methods of statistics and Monte Carlo simulation when making important decisions.

Photo by Sergiu Vălenaș on Unsplash