Why this matters to Australian employers today
Gender pay equity is now a material governance, compliance and reputation issue. The Workplace Gender Equality Act 2012 (WGEA Act) requires relevant employers to report gender equality data, while the Workplace Gender Equality Amendment (Closing the Gender Pay Gap) Act 2023 expanded public transparency through WGEA publication of employer gender pay gap information. The Fair Work Act 2009, as amended, also reinforces pay equity expectations, including prohibitions on pay secrecy terms and strengthened gender equality and equal-remuneration settings.
For boards and executives, a WGEA gender pay gap figure is an important signal, not a complete diagnosis. Regression analysis can provide a more refined view by testing whether gender remains associated with remuneration after accounting for legitimate, job-related factors. It is a valuable internal analytical tool, but it is not a legal conclusion, an excuse for inaction, or a substitute for examining the structural causes of inequality.
The stakes are visible. WGEA can publicly name non-compliant employers, and non-compliance may affect eligibility for certain Commonwealth procurement opportunities. National media coverage of published employer pay gaps and compliance failures can quickly shape employee, candidate, investor and customer perceptions. Internationally, UK gender pay gap reporting enforcement and the EU Pay Transparency Directive’s penalty framework demonstrate a clear global direction: transparency obligations are becoming more consequential and more closely scrutinised.
Key compliance and strategic insights
1. Define the question before building the model
A regression model is only as useful as the business question, data scope and assumptions behind it. Its purpose should be clearly documented: for example, to identify whether a gender-related pay difference exists within comparable roles after accounting for relevant remuneration drivers.
- Set the population carefully, including employees, relevant casuals and executives where appropriate, and document inclusions, exclusions and the effective date.
- Analyse total remuneration as well as components such as base salary, allowances, bonuses, incentives, commissions, superannuation and equity or long-term incentives where material.
- Use defensible explanatory variables: job level, occupation, function, location, tenure, employment type, performance measures where consistently applied, and scarce-skills premiums where evidenced.
- Avoid using variables that may conceal historic disadvantage, such as prior salary, discretionary manager ratings without calibration, or career interruptions, unless their use is justified and separately tested.
Model specification should align with the employer’s remuneration architecture. A single enterprise-wide model may be less meaningful than models by business unit, job family or level where pay-setting practices differ.
2. Treat regression results as evidence to investigate, not a verdict
A statistically significant gender coefficient can indicate an unexplained difference after the included factors are controlled for. It does not, by itself, establish unlawful discrimination or prove causation. Equally, a non-significant result does not establish that the organisation has achieved gender pay equity.
- Report the estimated gap, confidence interval, statistical significance, sample size and practical significance—not simply a “pass” or “fail” outcome.
- Review outliers and small cohorts manually. Small sample sizes, particularly at senior levels, can produce unstable or misleading results.
- Compare adjusted findings with WGEA-style median and mean gender pay gap measures. Both perspectives matter: adjusted analysis explores comparable pay; overall gaps reveal workforce composition, occupational segregation and progression barriers.
- Undertake sensitivity testing by changing reasonable model assumptions and checking whether conclusions remain stable.
Executive reporting should plainly explain what the model can and cannot answer. This protects against false assurance and supports informed board oversight.
3. Address the drivers that regression cannot “control away”
Many of the most significant gender equity issues sit upstream of individual pay decisions. Women may be underrepresented in higher-paid roles, concentrated in lower-paid occupations, less likely to receive discretionary incentives, or excluded from advancement pathways. These are strategic workforce issues, not statistical noise.
- Examine recruitment shortlists, starting-pay decisions, promotion rates, acting opportunities and succession pipelines by gender.
- Audit bonus and performance-calibration processes for consistency, transparency and manager discretion.
- Assess flexible work access, parental leave outcomes, return-to-work progression and part-time career pathways.
- Where data permits and privacy can be protected, assess intersectional patterns involving gender, age, cultural background, disability and First Nations status.
Regression should therefore sit within a broader pay equity assessment and action plan, rather than being used to narrow the conversation to individual salary adjustments alone.
4. Build robust governance, privacy and legal controls
Pay data is sensitive and analysis can create legal, employee-relations and reputational risk if poorly managed. Establish clear ownership across HR, remuneration, finance, legal and data teams, with board or remuneration committee visibility.
- Create a documented methodology, data dictionary, model rationale, quality checks and approval process.
- Restrict access to identifiable remuneration data and suppress reporting for small groups to protect privacy.
- Seek legal advice early where findings may indicate potential contraventions of equal-remuneration, discrimination or employment obligations; advice can assist in structuring investigations and remediation appropriately.
- Develop a disciplined communication plan that is accurate, transparent and aligned with WGEA reporting, employee consultation and external messaging.
Practical checklist for HR and board leadership
- Confirm WGEA reporting status, compliance timetable and accountable executive.
- Reconcile payroll, HRIS, incentive and job architecture data before analysis.
- Approve a documented regression methodology and independent quality review.
- Assess both adjusted pay differences and overall workforce gender pay gaps.
- Investigate material findings at cohort, manager, role and process level.
- Prioritise remediation, assign owners, set timeframes and cost the actions.
- Monitor outcomes at least annually and after major remuneration, restructuring or acquisition events.
- Provide the board with a concise dashboard covering risk, findings, actions and progress.
Conclusion and next steps
Responsible regression analysis helps employers move beyond headline figures to make better decisions about pay, progression and accountability. Its value lies not in producing a defensible number, but in prompting rigorous investigation and sustained action. In a transparent regulatory environment, organisations that combine sound analytics with fair systems and credible governance will be best placed to meet WGEA expectations and build workforce trust.
For a seamless path from diagnosis to compliance and strategic execution, Diversity Australia’s WGEA Readiness Tool and Consulting Services provide practical support for data readiness, pay equity assessment, governance, reporting and action planning. Explore the recommended solution at Diversity Australia’s WGEA Readiness and Gender Equality services.