Interactive resources for incubators and accelerators
Interactive resources for incubators and accelerators
Gender data can be analysed using your standard analytical methods. That being said, you will want to design your analysis to compare information about different genders, and where possible, about different categories for each gender (e.g. ethnicity, age, sexual orientation, ability, etc.). Comparing these will reveal any inequalities and gaps that exist, that are likely to affect women, men, and other genders’ access, inclusion, participation, etc.
Collecting the data is only half the battle. To make the most of the data you collect, it needs to be regularly reviewed. Set aside time to review data after each program, each quarter or at the end of each year to inform end of year reporting and guide strategy for the new year. If data has been collected electronically, or through online tools like SurveyMonkey or Jotform, there are built-in data analysis features that will generate graphs and reports from your data for you. If you’ve captured it manually, you can use Word or Excel to create your own graphs and tables to present and analyse your data.
Ideally you want to compare the data against previous periods to identify key trends and patterns or to answer key questions you have about the effectiveness of your strategies.
At an organisational level, you may see that your retention rates for women and men differ and women are more likely to leave the organisation than your male employees. Uncovering insights like this, can prompt you and your team to dig deeper and identify any cultural issues that may be inhibiting a sense of inclusion for women.
At a programmatic level, you may find that while you are targeting more of your marketing to women, you are still seeing similar levels of female applicants. This insight may mean that women just aren’t seeing as much value in the program or that there are other barriers to their ability or interest in participating. You may need to look at other incentives for women founded teams like more female mentors, a more female-friendly delivery format or curriculum that addresses key challenges they face.
We are assuming that most small teams won’t have the capacity to be measuring the outcomes of efforts to influence the ecosystem through your work towards gender equality. Therefore the insights you can gain here will be relatively limited to trends or patterns in your own engagement with the ecosystem. However, they may still highlight interesting learnings or opportunities for you when compared to other organisational data you may collect. For example, when analysing the trends within your ecosystem engagement and your revenue or funding sources, you may realise that as your ecosystem engagement has grown over the years, you’ve been able to attract significantly more funding for your work. Or if one of your strategies is focused on investor education, you may be able to collect data around the number of gender-lens investments they have made after engagement with your organisation.
The insights you gain from this analysis should help you assess the effectiveness of current gender equity strategies and highlight where new strategies may be necessary. You should aim to build a habit around encouraging your team to back up decisions with data. This can be achieved simply by requiring any proposed strategies or approaches to cite the data that supports this new direction or decision. Data-driven decisions can guard against the unconscious biases that may otherwise influence the choices we make.
In analysing the data you collect on your recruitment processes, you may realise that very few women have applied for recent management positions. This insight may drive the decision to target your recruitment efforts where women network or look for work. This might be local women’s organisations or employment websites, all-women colleges/universities or women’s groups on social media. You may also decide to review your job ads to ensure the language and culture you are promoting is appealing to women.
Your program data may reveal that very few women founders in your cohorts are attending evening webinars and a recent survey confirmed that 50% of women found the timing difficult if they had young children at home. These insights indicate a change to the format of the program is needed in order to ensure it is inclusive of all participants.
If one of your insights is the increased funding you’ve been able to attract since becoming more vocal about your efforts to advance gender equality, your programs team can use this data to support the decision to, for example, launch a women-focused program due to both the need for a program like this and the perceived interest from funders in this kind of program.
If one of your insights is the increased investments that apply a gender lens after your investor education efforts, your team may decide that this is an area of your work that is seeing great impact and that deserves more of your resources and attention.
