Over half the world lives in a death trap - and we designed it that way.

We place significant faith in data to help us make decisions. I believe we have been conditioned to not realise that an alarming amount of data is missing when we make those decisions - resulting in poorer decisions and even poorer results. These poorer results are not just for our own jobs, but for our families, communities and nations as well.

Fact check. Did you know that common symptoms for a heart attack include stomach pain, breathlessness, nausea and fatigue? It is not just chest and left arm pain. That longer list of symptoms are considered “atypical”, because they don’t conform to the “Hollywood heart attack”. Atypical, because they are a woman’s experience. This despite the fact that for over 30 years, more women die from heart disease than men.

Here's another one. Did you know that the majority of EU standards around crash test dummies only require a 50th percentile male dummy to represent the majority of the population? This despite the fact that women are 47% more likely to be injured, and 17% more likely to die. Why is this the case? Basically because car designers seem to think that women aren’t doing it right. You can guess how much pregnancy has been considered in that same car design.

Why am I sharing this?

I recently read Invisible Women: Exposing Data Bias in a World Designed for Men from Caroline Criado Perez, and found it both a fascinating/enraging read.

The book is dense with cited research on numerous aspects of society where data collection and analysis methods have failed to identify women, and reviewing the impact of this gap. Why does this happen? Because we are still stuck with Freud's riddle of femininity. Women are too complicated, too hard, too expensive - and the cost of not doing so doesn’t visibly effect the majority of the people making those decisions (men).

To be clear, it is not just all life and death either: it is the practical as well. The height of shelves in your kitchen are designed from average male heights and arm lengths. Clothing worn by US armed forces cater for all sorts of environments, but if you want to go to the loo, you're assumed to be male. Air conditioning has been modelled off the average male metabolic resting rate - meaning the typical office is about 5 degrees too cold for women. The average female hand is smaller than the average male hand, yet, phone handset manufacturers ignore this for all their flagship models.

Caroline writes:

"Routinely forgetting to accommodate the female body in design, whether medical, technological, or architectural has led to a world that is less hospitable and more dangerous for women to navigate. It leads to us injuring ourselves in jobs and cars that weren't designed for our bodies. It leads to us dying from drugs that don't work. It has led to the creation of a world where women don't fit very well."

The book was enraging, because I felt an alarming sense of helplessness. What does one person do in the face of so much injustice across so many different parts of society? This was a difficult question, because the book didn’t leave me a clear cut next step about how I could help.

I looked at my own world, and my life, and eventually realised there are two things I can do.

1) Generate awareness of the problem.

My wife, my friends and my colleagues have had to put up with my references repeatedly over the past few weeks. I find myself seeing these stats that are currently top of mind, playing out in the real world. For example, Sydney Trains recently calculating carriage occupancy levels by weight, but not having sex-disaggregated data on transport patterns means that this calculation is likely to be off. Update: see end of post for interactions with Sydney Trains about this.

The most practical thing I can do is tell other people about this book, and draw their attention to read it for themselves. Hopefully with enough sharing, something in these areas can change, and with enough groundswell, all the other examples of missing data that aren’t covered in the book also get addressed - because we think of women just as automatically as men when segmenting data.

Part of the point of this post is to do exactly that - encourage you to read this book, and gain some awareness of this gap.

2) #StopTheInterruption.

The self-perpetuating part of this is that many decisions in society are made by individuals with little awareness or consideration for the fallacies in their data. As men see the confirmation of their data in their own experience, they feel validated in their decision, and it continues.

Caroline has a whole chapter on the agency of women in leadership, and I won’t attempt to steal her thunder on that. Long before women are aspiring to be the leaders of nations, they are striving to lead companies, divisions, teams and projects. And for anyone to succeed at their given aim, they must be heard.

A 2015 study found that females are twice as likely to be interrupted by men, as men are to be interrupted by women. That’s Caroline’s data point, which is already reasonably damning, but when I did some casual Googling, I found the numbers could be much worse. I acknowledge that from childhood, boys and girls are socialised differently with regards to how assertiveness is viewed, but a culture of interruption does not help.

How can women be heard if we keep cutting them off?

Something I can begin practicing today is to stop interrupting other people.

While I deplore the idea that I too carry unconscious bias, these statistics have to come from somewhere. I’m sure that I am contributing to the current state of affairs, and this is at least one thing I can begin doing today that will make a difference.

I post this publicly in the hope that my colleagues and clients can help hold me accountable to this goal, but also to inspire them to consider doing the same. Bit by bit, if we all try to cut back on interrupting, we will make a difference. More women will be heard, and we'll set up a better pattern for the next generation to be socialised by.

#StopTheInterruption, and let women finish their sentences.

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Summary

I originally titled this article "When "data-driven decision making" misses the mark", as so much data ignores women, but realised it needed more sass to draw people in. I believe that by failing to identify women, we not only serve their needs poorer, but we serve the needs of society as a whole poorer. Diversity in leadership leads to better decisions - and these are better decisions are for all people, not just women.

I encourage you to read Invisible Women: Exposing Data Bias in a World Designed for Men from Caroline Criado Perez, and decide for yourself what action you can take to make a difference.

All of the above statistics (aside from the Sydney Trains example) are credit to her research and diligence. If you still aren’t convinced, read an excerpt first and tell me you don’t want to know more.

If you'd like to join me, share this post with your network with the #StopTheInterruption hashtag and make your commitment to let women be heard.