Quantifying Quality: Best Practices for Measuring Quality of Hire

By SIOP Members Julia Walsh, Kristen Cooper, and Amy Wester

Quality of Hire (QoH) is one of the most frequently discussed yet least standardized metrics in talent management. It has emerged as a critical measure linking recruitment practices to long-term business outcomes. Research shows that hiring decisions carry enduring implications for productivity, retention, and culture (Schmidt & Hunter, 1998), yet debate continues over how best to define, measure, and apply QoH (Breaugh & Starke, 2000; Keller, 2017; Zottoli & Wanous, 2000). At the 2025 SIOP Annual Conference in Denver, the session Quantifying Quality: Best Practices for Measuring Quality of Hire brought together experts from across industries to share practical approaches, examine challenges, and explore opportunities for more consistent and meaningful measurement. Building on that discussion, this article reviews what the research literature identifies as best practices for measuring QoH and offers reflections on future directions for research and practice.

Why Quality of Hire Matters

Hiring the right people is fundamental to organizational effectiveness. Decades of research demonstrate that valid selection systems improve both individual and organizational outcomes (Schmidt & Hunter, 1998).

QoH is particularly important because it connects hiring practices to downstream outcomes. Poor hires are costly not only in terms of direct replacement but also in lost productivity, turnover, and potential cultural misalignment (Breaugh & Starke, 2000). Conversely, high-quality hires accelerate innovation, strengthen teams, and contribute to organizational resilience (Schmidt & Hunter, 1998; Sackett & Lievens, 2008).

The Challenge of Defining and Measuring QoH

Despite its importance, QoH lacks a universally accepted definition. Some organizations use short-term measures such as new-hire performance ratings or probationary completion, while others adopt broader, longitudinal views incorporating promotion rates, engagement, or retention at one- and two-year marks (Zottoli & Wanous, 2000). This lack of consistency makes benchmarking difficult and complicates cross-organizational comparisons.

Workforce shifts add complexity. Remote and hybrid work arrangements blur traditional performance metrics, while the rise of gig and contract work demands new ways of assessing contribution.

Technological advances add both promise and complexity. Advanced analytics, AI-based selection tools, and integrated people data systems can provide more nuanced QoH insights (Murphy, 2016). Yet these tools must be implemented responsibly, with attention to data privacy, transparency, and fairness (Chamorro-Premuzic, Winsborough, Sherman, & Hogan, 2016).

Emerging Best Practices

Although no single formula captures QoH perfectly, several best practices are gaining traction:

1. Use a multi-metric approach.
   Relying on a single indicator oversimplifies a complex construct. Combining early managerial feedback, performance ratings, retention data, and even cultural fit indicators provides a more holistic view (Keller, 2017; Murphy, 2016).
2. Focus on longitudinal outcomes.
   Short-term success does not always predict long-term effectiveness. Measures should capture both immediate productivity and sustained contribution over time (Sackett & Lievens, 2008; Zottoli & Wanous, 2000).
3. Integrate across data systems.
   Breaking down silos and integrating recruitment, performance, and engagement systems can yield more valid and actionable insights into QoH (Yoon, 2024).
4. Account for context.
   QoH is shaped by job type, organizational culture, and labor market conditions. Practitioners should adapt metrics to reflect unique organizational realities while maintaining comparability where possible.
5. Check for fairness.
   QoH measures should be examined for subgroup differences and aligned with broader organizational commitments to equity and inclusion (Aguinis, Gottfredson, & Culpepper, 2013).

Insights From Practice

Panelists in the SIOP 2025 session brought diverse experiences implementing QoH strategies across industries:

• Reed Bramble (Uber) emphasized holding hiring managers accountable by linking QoH outcomes to recruiter and interviewer practices.
• Kristen Cooper (SHL) brought a consultant’s lens, highlighting tradeoffs between in-house and external approaches.
• Zach Reburn (Meta) integrated early manager feedback with performance data to evaluate the health of recruiting pipelines sooner.
• Evan Theys (Palo Alto Networks) underscored aligning advanced data strategies with organizational readiness to ensure adoption.
• Julia Walsh (General Mills) demonstrated how QoH can be measured across all levels, from frontline production roles to senior executives, despite technological and data hurdles.
• Amy Wester (Palo Alto Networks) highlighted equitable, scalable assessment strategies in cybersecurity and beyond.

Together, these perspectives illustrate both the diversity of approaches and the common challenges practitioners face.

Looking Ahead

For I-O psychologists, QoH measurement is not just a technical exercise but a strategic opportunity. By grounding measurement in established principles of reliability, validity, and fairness, the field can help organizations move beyond operational efficiency metrics toward outcomes that reflect true talent quality.

Future research and practice should continue to explore:

• Standardization vs. customization: How to balance the need for common benchmarks with organizational context.
• Technology and AI: Leveraging advanced analytics while ensuring ethical safeguards.
• Global application: Adapting QoH metrics across diverse cultural and legal environments.
• Continuous improvement: Embedding QoH into broader talent management and organizational learning cycles.

Moving forward, progress will depend on I-O professionals sharing best practices and lessons learned with one another and finding ways to incorporate technology to measure Quality of Hire more efficiently and effectively.

Quality of Hire remains one of the most pressing yet elusive measures in human capital management. By integrating multi-metric approaches, longitudinal perspectives, and ethical and legal considerations, and by fostering greater collaboration across the I-O community, organizations can move closer to a comprehensive, meaningful standard.

References

• Aguinis, H., Gottfredson, R. K., & Culpepper, S. A. (2013). Best-practice recommendations for estimating cross-level interaction effects using multilevel modeling. Journal of Management, 39(6), 1490–1528. https://doi.org/10.1177/0149206313478188
• Breaugh, J. A., & Starke, M. (2000). Research on employee recruitment: So many studies, so many remaining questions. Journal of Management, 26(3), 405–434. https://doi.org/10.1177/014920630002600303
• Chamorro-Premuzic, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New talent signals: Shiny new objects or a brave new world? Industrial and Organizational Psychology, 9(3), 621–640. https://doi.org/10.1017/iop.2016.6
• Keller, J. (2017). Posting and slotting: How hiring processes shape the quality of hire and compensation in internal labor markets. Administrative Science Quarterly, 63(4), 848–878. https://doi.org/10.1177/0001839217736045
• Murphy, J. P. (2016). Quality of hire: Data makes the difference. Employment Relations Today, 43(2), 5–15. https://doi.org/10.1002/ert.21562
• Sackett, P. R., & Lievens, F. (2008). Personnel selection. Annual Review of Psychology, 59, 419–450. https://doi.org/10.1146/annurev.psych.59.103006.093716
• Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262–274. https://doi.org/10.1037/0033-2909.124.2.262
• Yoon, S. W. (2024). People Analytics and Human Resource Development. SAGE Open, 14(3). https://doi.org/10.1177/15344843231209362
• Zottoli, M. A., & Wanous, J. P. (2000). Recruitment source research: Current status and future directions. Human Resource Management Review, 10(4), 353–382. https://doi.org/10.1016/S1053-4822(00)00032-2