Posted: 26 Jun. 2019 05 min. read

Invisible Women

Exposing Data Bias in a World Designed for Men

In the age of information, data has become an incredibly useful and powerful tool. As organisations become increasingly aware of unconscious bias, data provides a way to make evidence-based, objective decisions. But what if the data is itself, biased? What if data is perpetuating – rather than challenging – gender inequality and discrimination? Data becomes not only powerful, but dangerous.

Have you ever noticed your female colleagues wrapping themselves in scarves and blankets at their desk? Or heard a woman say the air-conditioning was ‘too cold’ while for a man it was ‘just right’? Research from the Netherlands found that the standard formula for air-conditioning may overestimate the female metabolic rate by up to 35%, setting the temperature at 5 degrees too low for women (Kingma and van Marken Lichtenbelt, 2015). They argue the need to consider the “thermal demand of all occupants” – i.e. if designing a standard or default, the needs of half the population shouldn’t be ignored or downplayed.

While being too cold in the office is uncomfortable, it’s unlikely to have serious implications. That may not be true for other workplace environment issues. Indeed, workplace injuries and illnesses may be on the rise for women, despite being on the decline for men (Andrzejewski, 2018; Berecki-Gisolf et al., 2015). However, it’s hard to know, as data on workplace health and safety is primarily collected from male dominated industries – such as mining or construction – rather than ‘women’s work’ – such as care work or cleaning. This is despite carers often lifting more than a miner in a single shift, before going home to carry out domestic work (Burrow, 2017). Consistently long hours of paid and unpaid work may be one of the reasons why there have been alarming increases in rates of heart disease and cancer for women (Allard and Yao, 2016). Again, it’s hard to know due to what Caroline Criado Perez describes in her latest book as a large, “female sized ‘absence’ in the data”.

Published in March 2019, Invisible Women: Exposing data bias in a world designed for men provides hundreds of examples similar to those described above, across multiple dimensions of life – from healthcare to politics, the workplace to infrastructure. Perez paints a detailed and troubling picture of widespread, systemic gender bias. The reason? A failure to account for women in data relied on in design and decision-making, argues Perez. Data is either not collected on women, or when it is, the data is not disaggregated by sex. As Perez bluntly puts it, “Garbage in, garbage out.”

So, how can the problem of the ‘missing female’ be solved? The first step is to start collecting the data, the second, is to start considering it in design. The latter, Perez argues, is more likely to happen when women are in the room. The benefits of gender-balanced representation have been explored in many studies, including Deloitte’s own research on women on boards (Deloitte Global Center for Corporate Governance, 2015). For Perez, the argument is simple, “Women don’t forget that women exist as easily as men often seem to…. When women are involved in decision-making, in research, in knowledge production, women do not get forgotten.”

While the research cited may be familiar to many readers, the strength of the book is in its ability to consolidate and synthesize the literature. In doing so, Perez focuses on the effect of the gender data gap, rather than the cause, drawing connections and highlighting themes that bolster her recommendations for action. The strong sense of activism, rather than analysis, is unsurprising given Perez’s experience as feminist campaigner.


The aim of the book is to argue that the world has been designed for the ‘default male’, based on a consolidation and analysis of existing data that reflects the gender data gap, and recommend strategies to create change. Through a distinctly feminist lens, Perez argues that not only are women facing unnecessary and often life-threatening risks, a lack of gender diversity may mean that the population as a whole is missing out on transformative inventions and innovations.

As Perez puts it, “Invisible Women is the story of what happens when half of humanity is forgotten. It is an exposé of how the gender data gap harms women when life proceeds, more or less as normal… Invisible Women is also a call for change… It’s time for women to be seen.”


The book draws together a range of primary and secondary sources – from quantitative research, scientific journal articles and expert interviews, to media articles, blogs and anecdotes – with a total of over 1,000 references.

However, the focus on delivering a persuasive argument seems, at times, to take priority over academic rigour, with references listing only websites. The irony of this has been acknowledged in other reviews given that Perez argues that, in the absence of full name citations, female academics are assumed to be male contributing to male bias in academia (Boyle, 2019).


As discussed, the book provides hundreds of examples of the gender data gap, across academia and research, and in practice across six categories:

1.   Daily life

2.   The workplace

3.   Product design

4.   Healthcare

5.   Public life

6.   Disasters and emergency relief

Rather than selecting specific examples, this article will summarise the key trends Perez finds in the implications of the gender data gap:

1.    The invisibility of the female body: When differences between male and female bodies are unaccounted for in the data, design is unable to accommodate the female body. This, Perez argues, is a routine occurrence, “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.”

2.    Male sexual violence against women: Failure to report and measure incidences of sexual violence and harassment, results in a lack of data upon which to design a world that is safe for women. The impacts of this can be seen across the design of transport, education, and workplace policies.

3.    Valuing unpaid care work: Perez argues that the trend that is having the most significant impact on women worldwide is the failure to value women’s unpaid work. By failing to value the unpaid work that women do as carers and in the home, the data that underpins the design of the modern workplace is flawed.

4.    Women are ‘too complicated’ to measure: When touching on the reasons why women are absent from the data, Perez found a common argument was that women are more complex, less homogenous and, as a result, more difficult to account for than men.


For organisations the implications of the research are substantial, argues Perez, “The world of work needs a wholesale redesign – of its regulations, of its equipment, of its culture – and this redesign must be led by data on female bodies and female lives.” Specifically, Perez recommends to:

·       Apply higher levels of accountability and transparency in people management: While technology and policies that enforce ‘blind recruitment’ may help overcome gender bias in recruitment, Perez argues that managing gender bias in promotions is more difficult. Based on Spanish research that found accountability to reduce gender pay inequality, Perez argues that organisations should introduce accountability to management decision-making and appoint a committee to monitor collected data (Castilla, 2015).

·       Start valuing women’s unpaid work and stop designing workplaces for the ‘unencumbered worker’: Perez argues that a failure to account for women’s unpaid care work has created a world where the traditional workplace is designed to suit the ‘unencumbered worker’ which is typically male. As Perez describes, “His life is simple and easily divided into two parts: work and leisure.” Perez recommends that organisations need to value unpaid work and design the workplace to accommodate for it. She provides examples of initiatives to account for hidden male bias, including Campbell Soup offering on-site after-school classes and summer programs, Ericsson and Evernote providing complimentary house cleaning and American Express paying for travelling women to ship their breastmilk home.

·       Increase representation of women at all levels: Central to Perez’s argument is the recommendation that, in order to start designing a world for women, women must be involved in the design process. As recommended by Deloitte in multiple reports, for organisations this means creating gender diversity at all levels – in particular leadership (Deloitte Global Center for Corporate Governance, 2015; Bourke and Dillon, 2018; Bourke et al., 2016). Drawing on a story of a woman, Daina Taimina, who found the solution for modelling a hyperbolic plane, Perez argues that the benefits of closing the gender data extends beyond women’s rights. Put simply, “When we exclude half of humanity from the production of knowledge we lose out on potentially transformative insights.” Such an argument is central to the thesis of Juliet Bourke’s research on diversity and inclusion, reflected in her book Which two heads are better than one? (2016).


Perez’s consolidation of data is extremely valuable and allows her book to act as a ‘go-to-guide’ for gender data bias and a tool for advocacy in a range of fields. For example, this month British Minister, Helen Goodman, referenced a statistic from the book in the House of Commons, she said, “Women who are in a car crash are 17% more likely to die than men, so will the Department consider a legal requirement on car manufacturers to have female dummies to test their cars?” (HC Deb, 12 June 2019, c646). Following this she thanked Perez via Twitter for highlighting this “important data gap” (Helen Goodman, 2019).

Such is the power of data: a statistic can inform the design of everything from laws and policies to job descriptions, strategies, products and project teams. Ultimately, gender equal outputs require gender equal inputs – gender inequality in, gender inequality out. An alternate ending to this story is – gender equality in, gender equality out.


Caroline Criado-Perez (2019) Invisible Women: Exposing Data Bias in a World Designed for Men, Vintage Publishing

References originally cited in Perez’s book, cited in this blog:

Boris Kingma and Wouter van Marken Lichtenbelt (2015) ‘Energy consumption in buildings and female thermal demand’ Nature Climate Change, vol. 5, pp. 1054 – 159. Available at:

Cecile Andrzejewski (2018) ‘The invisible risks facing working women in France’ The Equal Times, 13 February 2018. Available at:

Dembe Allard and Xiaoxi Yao (2016) ‘Chronic Disease Risks From Exposure to Long-Hour Work Schedules Over a 32-Year Period’, Journal of Occupational and Environmental Medicine, 58 (9), pp. 861 – 867. 

Sharan Burrow (2017) ‘Face it: We are all sickened by inequality at work’, Hazards Magazine, March 2017. Available at:

Emilio J. Castilla (2015) ‘Accounting for the Gap: A Firm Study Manipulating Organisational Accountability and Transparency in Pay Decisions’ Organisation Science, 26(2), pp. 311-33.

Additional references cited in this blog:

Deloitte Global Center for Corporate Governance (2015) Women in the boardroom: A global perspective 5th edition, Available at: 

Karen Boyle (2019) ‘Invisible Women: Exposing Data Bias in a World Designed for Men – a review’, The Conversation, March 23 2019. Available at:

Juliet Bourke and Bernadette Dillon (2018) ‘The Diversity and Inclusion Revolution: Eight Powerful Truths’ Deloitte Review, Issue 22, January 2018. Available at:

Juliet Bourke et al. (2016) Research Summary: Toward gender parity: Women on boards initiative, Deloitte. Available at: 

Juliet Bourke (2016) Which two heads are better than one? How diverse teams create breakthrough ideas and make smarter decisions, Australian Institute of Company Directors

HC Deb (12 June 2019) col. 646. Available at: Accessed 19 June 2016

Helen Goodman (2019) 12 June 2019. Available at:

Meet our author

Jessie Goldie

Jessie Goldie

Programme Quality Officer, Oxfam

Jessie was formerly a Senior Consultant in Deloitte Human Capital Consulting Practice and a member of the Diversity, Inclusion and Leadership Newsletter editorial team. In 2018, she headed to Myanmar to undertake an assignment under the Australian Volunteers for International Development program as an advisor to a not-for-profit organisation. She continues to work with NGOs in the country and remains connected to the Deloitte D&I and Leadership team, with a focus on issues relating to gender equality and LGBTI+ inclusion.