Our goal is to see a FAIR SHARE of women leaders in the civil society sector by 2030, and the FAIR SHARE Monitor is a data-based tool tracking progress towards that goal.
We use it to collect and publish data on the proportion of women in staff and leadership of civil society organisations, which in turn encourages transparency and accountability. We began collecting this data in 2019 and will continue to do so until 2030, in line with Goal 5 of the United Nations Sustainable Development agenda. Read more about why we built the Monitor on our blog.
Based on the data collected, we rank organisations according to how close they are to a FAIR SHARE of women in their leadership (see the bottom of the page for our definition of a FAIR SHARE). The Monitor can therefore be used by both individual organisations and the sector in general to set benchmarks and measure progress.
About the FAIR SHARE Monitor
The annual data collection for the FAIR SHARE Monitor takes place in Q4 or Q1. International social impact organisations are called upon to participate by sharing their figures via an online survey. Organisations we do not directly invite could also volunteer to participate by contacting us.
When organisations do not share their data with us, we research it for them through their websites, then give them the opportunity to confirm the figures we find. Once the data is in, we begin data analysis and publish the results in April.
For the FAIR SHARE Monitor 2023, 82 organisations were invited to participate. About 48% actively supported us in collecting data, either submitting figures on their own or confirming data researched by us. Take a look at the results of the FAIR SHARE Monitor 2023 here.
We collect organisations' data through an online questionnaire. Organisations invited to participate in the FAIR SHARE Monitor receive a link to the questionnaire to submit their data. You can see the full FAIR SHARE Monitor 2024 questionnaire here.
Initially, the FAIR SHARE Monitor only collected data about the number of women and men in staff and leadership. Since 2021, we also ask for data on Black, Brown, Indigenous women and women of colour (BIWoC). Read more on that here.
In 2023, we also started collecting data on non-binary staff in the social impact sector. This comes after consultation with members of the non-binary community and thorough reflections on how to collect and communicate this data in a way that wouldn’t jeopardize the integrity and privacy of individuals who entrust us with such sensitive information. Read more here.
In summary, we currently collect data in the following categories:
We also ask more general questions to understand the internal structure of participating organisations.
We recognise that diversity encompasses significantly more dimensions than just gender and race/ethnicity. We see collecting data on BIWoC as a first step towards making the Monitor more intersectional, but by no means an exhaustive one. Through our other work, such as advocating for Feminist Leadership, we aim to contribute to wider cultural change and help create the conditions for a truly equitable and inclusive sector.
To date, over 70 international social impact organisations have been part of the FAIR SHARE Monitor. This selection is expanded annually by FAIR SHARE and we welcome additional international social impact organisations that would like to be included in the FAIR SHARE Monitor on their own initiative. If you are interested, please contact us at monitor@fairsharewl.org.
The FAIR SHARE Index shows how well or poorly women are represented in leadership based on our criteria for a FAIR SHARE (see FAQ). It takes into account:
If there are at least 50% of women on all organisational levels (the average representation gap, across overall staffing, senior management and Boards) and if there is a difference between the share of women in the total workforce and women in leadership (the FAIR SHARE Gap).
Both gaps are added to calculate the FAIR SHARE Index.
The lower the index, the more fairly women are represented in leadership. The perfect Index would be “0” but to acknowledge fluctuations in staff, we defined an index below 15 as a desirable FAIR SHARE.
However, calculating the index as described above meant organisations with more women leaders than the share of women staff received a negative score, and the higher the proportion of women leaders, the worse this score would be. For example, an organisation made up of 40% women staff and 60% women leaders would be penalised for this gap, even though it actually indicates a positive shift from the norm and a willingness to go beyond the minimum benchmark of 50/50.
In 2021 we therefore adjusted the formula to ensure that a FAIR SHARE gap in favour of women (more women leaders than their share of staff) would not be penalised in the same way as a FAIR SHARE gap in favour of men (more male leaders than their share of staff). We do this by applying a 50% correction to the score of such organisations.
Our vision is not that eventually all organisations are fully led by women. However, given that for so long the norm has been that men dominate the ranks at all levels, we understand gender dynamics skewed towards women as part of the process towards gender equality.
We answer further questions about our work in our FAQ.
The FAIR SHARE Monitor is an exciting project with enormous potential and added value for our sector – and at the same time a complex challenge in terms of data analysis, technical design, implementation and further development. We are therefore grateful to have knowledgeable and energetic supporters at our side, with whom we can realise the FAIR SHARE Monitor.
Allen Gunn is Executive Director of Aspiration in San Francisco, USA, and works to help NGOs, activists, foundations and technologists make more effective use of technology for social change.
Gunner has worked in numerous technology environments from NGO to Silicon Valley start-up to college faculty to large corporation, serving in senior management, engineering, teaching and volunteer roles. He is an experienced strategist, mentor and facilitator with a passion for designing collaborative open learning processes, and he believes in melding hard work with serious fun.
Garret O’Connell is a data scientist from Ireland interested in applying data analytic methods (e.g. causal inference, forecasting, ML) to problems in the civil society and non-profit sectors. He volunteers with CorrelAid, a non-partisan, non-profit network that enables data scientists to use their skills for the common good and helps social organisations increase their impact on society through pro bono (Data4Good) projects.
Jay Goulden is a consultant on program strategy and innovation based in the UK. Since 2017 he has served as Head of Knowledge Management & Learning for the CARE International Secretariat’s Programs team, where he is responsible for coordinating the collection, aggregation and sense-making of CARE’s global impact evidence. Prior to working in CARE, Jay worked for several international and local NGOs in the UK and Central America, including Oxfam, Christian Aid, and International Alert.