Indicator 1 - Gender composition at all levels of the workforce

• In your employee dataset, use the ‘gender’ data provided for each employee.
• Record the percentage of employees who are women, men or people of self-described gender. The total should add up to 100%.

Looking at the gender mix of your workforce shows if some groups are over- or under-represented across your organisation. If most roles are held by one gender, it might point to issues with how people are hired, supported, or included. It can also raise safety and inclusion concerns, especially in spaces dominated by men.

A more balanced gender mix helps challenge stereotypes and brings fresh perspectives. It can be a foundation for a workplace where people feel safe and respected.

This measure also sets a baseline to compare with other measures like gender composition in leadership roles (Measure 1.3) or certain occupations (Measure 7.1).

Use these prompts to consider this measure alongside other relevant data.

Use the ‘level’ classification in your audit data and compare with your overall gender composition. You might consider grouping levels together to get a broader picture.

Are there differences in the gender composition at certain levels, compared to the overall workforce composition?

Look at the gender composition of employee type, such as ongoing, fixed term, or casual roles.

Are some genders overrepresented in certain employment types?

Compare the gender composition across different role types, like functional or support roles compared to operational roles.

Do you see certain genders over-represented within certain role types?

If you have the data, look at how gender intersects with other factors, like cultural identity or disability status.

Do you see different trends for groups facing intersecting inequalities?

Consider this measure alongside:

• Measure 1.2: Gender composition of part time workers in the duty holder organisation
• Measure 1.3: Gender composition of senior leaders in the duty holder organisation
• Measure 5.2: Gender composition of employees who were promoted
• Measure 7.1: Occupational gender segregation.

• In your employee dataset, use the ‘gender’ and ‘employment basis’ data provided for each employee.
• For each gender, record the percentage of employees who are part-time (either ‘part-time ongoing’ or ‘part-time fixed term’).

Part-time work can limit career progress, contribute to the gender pay gap, and reduce retirement savings. Knowing who works part-time in your organisation helps you identify potential barriers to gender equality and support career progression for all employees.

For example, if most part-time workers are women, it might point to a lack of support for men to work part-time and/or flexibly. Supporting men to work part-time or flexibly can help challenge uneven unpaid caring responsibilities at home and in the community.

Knowing the gender breakdown of part-time workers also helps you explore how to better help these employees to grow their careers and move to full-time if and when they want to.

Use these prompts to consider this measure alongside other relevant data.

Use the ‘level’ classification in your audit data to look at the gender composition of employees who work part-time at different levels. You might consider grouping levels together to get a broader picture.

Are there gendered patterns in part-time work at different levels?

Consider the gender composition of part-time employees on different types of contracts (such as ongoing, fixed term).

Are certain genders more likely to be in insecure, part-time work? If you have the data, look at how gender intersects with other factors, like cultural identity or disability status.

Do you see different trends for groups facing intersecting inequalities?

Consider this measure alongside:

• Measure 1.1: Gender composition of the duty holder organisation
• Measure 6.2: Uptake of flexible work, by gender.

• In your employee dataset, use the ‘gender’ and ‘employee type’ data provided for each employee.
• For the ‘senior leader’ employee type, record the percentage of senior leaders who are women, men or people of self-described gender. The total should add up to 100%.

Who’s at the decision-making table matters. When leadership teams reflect the people they lead (and the communities they serve) decisions are more likely to be fair, inclusive, and better for everyone. If women are under-represented in senior roles, it may mean decisions are being made without a full range of perspectives. It can also contribute to the gender pay gap, especially if women are well represented in the wider workforce but missing from the top.

These results can prompt important questions about whether your promotion pathways and recruitment practices are truly equitable.

Use these prompts to consider this measure alongside other relevant data.

Use your employment basis data in addition to your employee type data. Compare the gender composition of senior leaders who work part time with part-time work across your organisation.

Are senior leaders less likely to work part time compared to the overall workforce?

Are senior leaders of a particular gender more likely to work part time?

If you have the data, look at how gender intersects with other factors, like cultural identity or disability status.

Do you see different trends for groups facing intersecting inequalities?

Consider this measure alongside:

• Measure 1.1: Gender composition of the duty holder organisation
• Measure 1.2: Gender composition of part time workers in the duty holder organisation
• Measure 5.2: Gender composition of employees who were promoted.