University of Western Australia

Gender Pay Gap

What they said.

Zest’s analysis gave us clear insight into the drivers of our gender pay gap and where to focus our efforts. It provided the evidence we needed to prioritise actions that address the gap in a meaningful and sustainable way.

Drew Williams

Chief People Officer

Mission Goals

The University of Western Australia engaged Zest to explore whether gender was influencing pay outcomes once other factors such as tenure, job function, agreement type and location were considered. They needed a rigorous, data-driven approach to move beyond surface-level averages and uncover the structural drivers of the gender pay gap.

The Solution

Zest built a series of regression models across multiple reference groups, agreements and control variables, including age, school, location and agreement level. This approach isolated the effect of gender on pay while accounting for other influential factors, giving the University a statistically robust view of where inequities existed and what was driving them.

Complex findings were translated into accessible, practical insights that guided decision-making and shaped the University’s pay equity strategy. The result was a clear and credible foundation for action, backed by data and aligned with organisational priorities.

Highlights

Statistical Strength
Regression models achieved strong explanatory power (R² > 0.5 in expanded models), giving confidence in the reliability of results.

Targeted Insights
Analysis revealed where gender had a statistically significant effect and where other structural factors, such as tenures or pay grades, were more influential.

Actionable Outcomes
Findings were paired with practical recommendations, identifying priority areas to address inequities and strengthen pay equity outcomes.

Challenges

Consolidating multiple datasets into one accurate, reliable source of truth.
Simplifying complex regression results for non-technical audiences.
Balancing statistical depth with practical, actionable insights.

Wins

Clarity and Confidence: Complex regression data was distilled into insights leaders could easily understand and act on, giving them confidence to discuss pay equity with evidence and clarity.
Strategic Credibility: The analysis established a robust, data-driven foundation for the University’s pay equity strategy, informing future policy and planning.
Meaningful Impact: The work identified where targeted action would have the greatest effect, helping leaders focus efforts and measure progress over time.

More Work.

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