Beyond Good Intentions: Making Work Fair
Disclaimer: The summaries and interpretations provided on this page are unofficial and have not been reviewed, endorsed, or approved by the Canada School of Public Service (CSPS).
Summary
- The speaker introduces Siri Chelazi, a Harvard researcher and expert in advancing women and promoting gender equity in organizations through evidence-based approaches
- The presentation begins with the story of Astred Linder, a Swedish engineer who created the world’s first female crash test dummy to address the safety gap where women are more likely to be injured in car accidents despite being in fewer accidents overall
- Car safety regulations worldwide only require testing on crash test dummies modeled after the average male body, which explains why women face higher injury rates in accidents
- Linder’s creation of a female crash test dummy has inspired other researchers and car companies to develop more diverse testing models, making traffic safer for everyone
- Making work fair is not about special programs or events, but about embedding fairness into everyday work processes like emails, meetings, feedback, performance reviews, hiring, and promotion decisions
- Fairness is defined using a running race analogy where all competitors should start at the same starting line with equal resources and conditions, rather than some runners being disadvantaged by having to run barefoot, on grass, or from a position further back
- The Broward County school district example demonstrates how system changes can reveal hidden talent by switching from a referral model to universal screening for identifying high-potential students
- Under the referral system, parents or teachers could nominate first and second graders for IQ testing, but this led to underrepresentation of talented students of color
- When Broward County implemented universal screening where all first graders automatically took the same IQ test, participation of Black students in the high IQ program increased by 80% and Hispanic students by 130%
- The European Central Bank case study shows how setting a voluntary goal of 30% women in management roles led to promoting higher-performing women who had previously been overlooked in favor of mediocre men
- Women promoted during the goal period had higher salary trajectories than their male peers, indicating the bank had been missing top female talent before implementing the systematic approach
- Without fairness, true meritocracy cannot exist because it requires accurately identifying people’s skills and giving equally skilled people equal opportunities to develop and contribute
- The framework for making work fair consists of three components: making fairness count, making fairness stick, and making fairness normal
- Making fairness count means treating fairness with the same seriousness and tools used for core business functions, including data collection, goal setting, incentives, transparency, and accountability
- The example of Roz Atkins at BBC News illustrates how he started collecting data on guest representation during his nightly news show by spending two minutes after each broadcast counting and categorizing the people featured on air
Actionable Advice
- Apply the same systematic tools to fairness that you use for core business functions including data collection, goal setting, incentives, transparency, and accountability
- Collect data on the things you care about regarding fairness and representation in your organization
- Set specific, measurable goals for fairness outcomes rather than relying on good intentions
- Implement universal screening or assessment processes rather than relying on referral systems that may introduce bias
- Track and transparently share outcomes of fairness efforts to determine if you're making progress
- Create methods of accountability where positive consequences follow good fairness outcomes and negative consequences follow poor outcomes
- Focus on changing everyday work processes like hiring, promotion decisions, task assignments, and performance reviews rather than just implementing special programs
- Question whether your current systems are inadvertently creating unequal starting points or resources for different groups
- Look for simple design changes in existing processes that can level the playing field
- Spend time manually collecting data on representation if automated systems aren't available
- Examine whether high-potential individuals are being missed due to flawed identification systems
- Consider implementing organizational goals or targets as interventions to help identify previously overlooked talent