Gender Pay Gap Analysis Guide for Employers

Purpose of this guide

This guide helps you conduct a gender pay gap (GPG) analysis so you can identify the drivers of your GPG and take targeted action to reduce it.

Who is this guide for?

• Business leaders
• HR leaders
• Diversity & Inclusion teams
• Payroll & finance teams
• Data & analytics teams

Contents

1. Understanding gender pay gap analysis
     – What is GPG & how it’s calculated
     – Median vs. average
     – Benchmarks
2. Conduct your GPG analysis
     1. Choose a snapshot date
     2. Collect the data
     3. Clean the data
     4. Analyse common drivers
     5. Summarise findings
3. Additional resources & tools

1. Understanding Gender Pay Gap Analysis

Purpose of this guide

This guide is to help you conduct a gender pay gap analysis so that you can identify the drivers of your gender pay gap. Through identifying the drivers, you can then take targeted action to address them and reduce your gender pay gap.

Who is this guide for?

• Business leaders
• Human Resources leaders
• Diversity and Inclusion leaders
• Payroll and finance teams
• Data teams

Why conduct a GPG analysis?

A gender pay gap analysis is the first critical step you should take to understand and reduce your gender pay gap. It uses payroll and demographic data to compare the rates of pay for women and men at different levels of an organisation and highlight inconsistencies in the data. Done effectively, a gender pay gap analysis will expose the drivers of your gender pay gap and pinpoint areas for action.

You should perform a gender pay gap analysis annually to measure your progress toward improving or eliminating your gender pay gaps, as well as to identify any emerging gender pay gaps.

What is the gender pay gap?

The gender pay gap is the difference between the average or median earnings of men and women in an organisation. It can be caused by a range of factors, including men dominating higher-paid leadership positions and female-dominated jobs attracting lower wages. It is expressed as a percentage of men’s earnings:

(Average/median remuneration of men – Average/median remuneration of women)
÷ Average/median remuneration of men × 100
        

Median vs. Average

• Average gap: sensitive to outliers; shows concentration of high earners.
• Median gap: shows the typical employee’s experience.

How does my GPG compare?

WGEA publishes median gender pay gaps for employers with 100+ employees. Gaps within ±5% are deemed neutral, allowing normal business fluctuations while showing focus on equality.

2. Conduct Your GPG Analysis

1. Choose a snapshot date

Pick a date that represents your typical workforce. Use the same date each year for consistency.

2. Collect the data

Gather demographic, job and pay data from your HRIS or payroll. For WGEA reporters, use the Workforce Profile and Management Statistics.

3. Clean the data

• Annualise all salaries to FTE.
• Convert foreign currencies at snapshot rates.

4. Compare your data with common drivers

Test each of these drivers:

• Unequal pay for equal/comparable work
• Imbalance in senior vs junior roles
• Segregation in higher- vs lower-paid jobs
• Unequal part-time participation
• Inequality in hiring, promotion and turnover

Example: Unequal pay within an occupation

Example: Senior vs Junior roles

Equal pay at each level, but more women in junior roles lowers their overall average.

Example: Occupational segregation

Example: Part-time work

Even if part-time pay is annualised, women’s over-representation in part-time roles can depress their overall average.

Example: Employee movements

Women managers had similar performance ratings but smaller pay increases:

3. Further Analysis & Summarise Findings

Further analysis

Drill deeper by breaking out pay gaps by:

• Division or location
• Age or other demographics (e.g. cultural diversity, disability)

Hint: Avoid reporting groups smaller than 5 people for statistical reliability.

Summarise your findings

Your summary should include:

• Overall average & median GPG (base & total remuneration)
• Key drivers identified
• Additional insights (e.g. regional variations)
• Recommended actions to close gaps

Suggested resources

• Employer Gender Pay Gap Technical Guide – WGEA
• Gender Strategy Toolkit – WGEA
• Closing your gender pay gap – UK Govt Equalities Office
• ILO’s Understanding the gender pay gap
• Behavioural Insights Team – Evidence-based actions

How WGEA Classifies Occupations

1. Underlying Taxonomy: ANZSCO

The Australian and New Zealand Standard Classification of Occupations (ANZSCO) is maintained by the Australian Bureau of Statistics and Statistics New Zealand. It mirrors the ILO’s ISCO framework but is tailored to local labour markets. Structure:

• Major groups (1-digit, 8 families): Managers; Professionals; Technicians & Trades; Community & Personal Service; Clerical & Admin; Sales; Machinery Operators & Drivers; Labourers.
• Sub-major, minor, unit groups (2–4 digits): progressively more detailed job families and roles.

2. WGEA “Occupational Category” Field

When employers submit their Workplace Profile, each record must include:

• ANZSCO code (4-digit “unit group”)
• Manager / non-manager flag
• Graduate / apprentice flag

3. Assignment Sources & Logic

Employer data: pulled from HRIS or manually mapped to ANZSCO; pay converted to FTE and local currency at snapshot date.
WGEA validation: ensures codes exist, flags outliers, and checks minimum group sizes.
Gender-neutral: based solely on tasks, skill levels and qualifications.

4. Why This Structure Works

• Consistency: One framework for all industries and employers.
• Objectivity: Publicly published definitions, no proprietary “points.”
• Scalability: Drill down to 4-digit codes or stay at 1-digit for simplicity.
• Flexibility: Manager and graduate flags add level within each category.

5. In Practice

1. Choose your snapshot date (e.g. 31 March).
2. Map each employee to ANZSCO + level flags in your HRIS.
3. Upload to WGEA; they roll up to 8 major categories automatically.
4. Download your benchmark report—pay gaps by category vs. peers.