Interactive resources for incubators and accelerators
Interactive resources for incubators and accelerators
Interactive resources for incubators and accelerators

GLIA Toolkit

Collecting Data

Collecting Gender Data

Gender data refers to facts, such as measurements, observations and numbers, that are collected and presented by sex as a primary and overall classification; reflect gender issues; are based on concepts and definitions that adequately reflect the diversity of women and men and capture all aspects of their lives; and are developed through collection methods that take into account stereotypes and social and cultural factors that may induce gender bias in the data (this is the definition of gender statistics used by the United Nations Statistics Division). We extend this definition to all genders, other than women and men.

It is important to try and collect unbiased gender data so that you can gain an accurate understanding of whether the strategies you have put in place, whether that be a policy, program or other intervention, are advancing gender equality. If you are not collecting the right type of data and/or ensuring your data collection methods minimise bias, it won’t matter what analysis you perform, as you won’t be getting an accurate picture of what is happening.

Below we guide you through what you should consider when collecting gender data.

Determine your collection methods

Once you have your indicators determined, as well as the gender data you wish to collect, you need to establish how and when you will collect this data. You may use pre and post program surveys, focus groups, employee satisfaction surveys, interviews, your customer relationship management system or other program registers. Data may be collected annually, before and after each program, or on a monthly or quarterly basis. The important thing, as mentioned above, is to try and select data collection methods that will minimise bias. To do this, you will want to consider the stereotypes, social and cultural factors that may introduce bias into your data. For example, if you are conducting an interview (data collection method) with one of your women entrepreneurs to try and understand why they are unable to participate in certain workshops, and you have their husbands or parents present in the room whilst they answer, they may not feel psychologically safe to disclose the real reason why they cannot attend and participate. Without knowing the real reason behind their inability to participate, you won’t have an accurate understanding of the problem and therefore be able to find a suitable solution.

When selection a data collection method, consider the following questions: 

What format will allow you to best collect the insights you are after? Will an interview be more appropriate? Is an anonymous survey best?

Who is the most appropriate person to conduct the interview? Who has a trusted relationship with the interviewee and how can you encourage a safe space for honest feedback? What power dynamics am I introducing?

What technology is available to you and those you are collecting data from? Is a phone call more suitable than an online survey in your context? 

What kind of data collection is safest and most effective within your local context? 

What capacity do you have to collect the data? Is there enough time or resources to conduct in-person interviews, or is it more feasible to send out a survey or have a chat over the phone?

How often will you collect this data? 

How could gender impact your collection methods?  e.g. will any particular gender be more or less likely to complete an online survey compared to a phone interview? What times will be most convenient for all genders to be contacted or to participate in interviews and focus groups?

How will you share back the data that you collect, so that respondents/interviewees will also have a record of the information they shared with you, and also see how their data is used?

 

Explore a range of different data collection methods here.

  • Organisation

    To monitor your progress against the gender diversity in your board make-up, recruitment process, or around things like retention, promotion and pay, you will likely have organisational registers to track the gender split in these areas. To measure your employee engagement, their sense of belonging/inclusion or their satisfaction with the company culture, a survey is likely to be more appropriate where answers can ideally be provided anonymously.

  • Program

    Your pre and post program surveys are likely to be your biggest tools in capturing data against your program indicators. Interviews may also be useful in capturing some of the qualitative data like ‘most significant change’ stories or more in-depth case studies of how founders have benefited from your programs.

  • Ecosystem

    In measuring your own contribution to the ecosystem, you may also utilise a company register that records your ecosystem engagements like the number of resources developed, conferences spoken at, gender lens projects collaborated on, etc.

Collect a baseline

To measure meaningful change, we need to understand the current status of gender equality across your organisation, programs and ecosystem before you begin implementing your strategies. To do that we collect what we call a ‘baseline’ that we then use to compare the data we collect after a period of implementing our strategies to see if we have seen a significant change.

  • Organisation

    For example, if you are measuring the proportion of women in managerial positions within your organisation, you will want to record where that sits now and then again after implementing quotas or adapting your recruitment and promotion processes for 6-12 months. 

     

  • Program

    If you are measuring the extent to which the delivery of your program was suitable to all participants, you would record participant responses now and then again after implementing changes to your program design like for example, amending the timing or format to cater for women with children.

  • Ecosystem

     If you were looking at the long term impact of your influence on the ecosystem, you could do some initial research into the number of gender lens projects undertaken or public articles or reports shared that discuss the application of a gender lens over for example the last 6 months.  You could then engage in your own advocacy activities to influence the ecosystem and encourage more accelerators and incubators to incorporate a gender lens to their work. After a year or two of that advocacy work, you would then measure once again, the number of projects applying a gender lens or public articles and reports published over the previous 6 months and see if there had been an increase. 

    A note on attribution: In this case, we may not necessarily be able to prove that the increase was due to our advocacy work, as there are likely other factors at play that led to that increase, however we could make a connection between our efforts and the result and make a case for the role we played in achieving that result.

Set some targets

Once you know what you will measure, how you will measure it, and your baseline data, you may also want to work with your team to set some KPI’s. If you have historical data available, this is a good starting point to consider what your KPI’s might be. For example, if your organisation currently has a 30% gender split, you may want to set a stretch KPI of 40% in the next two years. You may also want to do some research on any standards or benchmarks that may exist, for example GALI has gathered some benchmarks for ventures that have participated in accelerators against those who have not, and some of their data can be filtered down to gender. Determine what is realistic and achievable for you and your team against each of your indicators and commit to those targets. Remember, these targets need not only be around quotas and representation but can also be around changes to things like confidence levels, a sense of belonging/inclusion, or a sense of empowerment.

  • Organisation

    You may want to have an equal gender split on your board within 3 years. You may want to have a 0% gender wage gap between men and women doing the same job in your organisation. Or you may aim for 100% of your staff to feel empowered to contribute to organisational decision making.

  • Program

    Perhaps you want to have at least 30% of each gender represented in each of your cohorts, you want to ensure you have an equal split of female and male mentors available, or you want to see an increase in confidence of at least 80% of participants.

  • Ecosystem

    Your team may set a goal of undertaking two specific projects that apply a gender lens this year. Or you may aim to produce three publicly shared reports focused on advancing gender equality in the ecosystem.

Utilise best practice strategies

Collecting data, particularly post-program data, can be challenging. Ensure you and your team understand and utilise these best practice strategies when it comes to gathering data:

Strategies you can try

  • 1.

    Explain the importance of the data. In the context of both your staff and your ventures, you will be more likely to get survey responses if the respondents understand why the data matters, how it will be used and how the data respondents provide will be shared back with them When it comes to your ventures, it can also be helpful to stress the value this data has for them when it comes to attracting funding/investment or reporting their progress to current funders, partners, customers or other stakeholders. 

  • 2.

    Integrate training on data collection into your programs in order to ensure that ventures have the skills and knowledge necessary to collect accurate data. 

  • 3.

    Keep surveys concise. Your team, founders and partners are no doubt very busy and will be unlikely to complete a lengthy survey! Focus on the core information you need to capture, be clear on why you need each piece of data and formulate your questions in a concise and direct manner.

  • 4.

    Aim for anonymity. Particularly when measuring organisational impact on gender through things like belonging and inclusion, it is important to collect anonymous data to encourage honest answers. For small teams, we acknowledge that this can be a challenge, however by building trust and transparency with your team, and communicating your commitment to ensuring their positive experience, you can encourage genuine responses.

  • 5.

    Develop strong alumni programs or follow-on support to improve engagement and survey completion.

  • 6.

    Consider offering incentives for completion. You could incentivise survey completion with a chance to win a small monetary award or access to additional networking or training opportunities.

  • 7.

    Explore alternative sources of post-program outcomes when survey responses are low.  For example, you can keep an eye on industry news, including press releases from investors or ventures themselves which can even be automated through news alerts like Google Alerts.

Next:

Analysing Data