Effective talent sourcing is not just about filling open positions quickly — it's about matching workforce planning to business strategy and using selection methods proven to predict actual job performance, rather than interviewer gut feeling alone.
Workforce planning and sourcing strategy
HRM5060 begins with workforce planning: forecasting future talent needs based on business growth, turnover trends, and skills gaps, then building a sourcing strategy that matches — employee referrals, campus recruiting, passive-candidate sourcing, and internal mobility programs each fit different talent needs and cost structures differently.
Structured interviewing and selection validity
The course emphasizes structured interviewing (consistent, job-related questions scored against a defined rubric) over unstructured interviewing, citing the substantial research showing structured interviews have significantly higher predictive validity for job performance and lower vulnerability to interviewer bias. Students learn to build behavioral and situational interview questions tied directly to a job analysis, and to evaluate selection methods (interviews, work samples, cognitive ability tests, assessment centers) by their validity and adverse-impact risk.
Key topics in HRM5060
- Workforce planning: forecasting talent needs from business strategy and turnover data
- Sourcing channels: referrals, campus recruiting, passive sourcing, internal mobility
- Job analysis as the foundation for accurate job descriptions and selection criteria
- Structured vs. unstructured interviewing and predictive validity research
- Behavioral and situational interview question design
- Selection methods and adverse impact: avoiding discriminatory (even if unintentional) selection criteria
Working on a workforce-planning analysis or a structured-interview design project?
Our business experts build HRM5060-level coursework with genuine talent-acquisition rigor.
Worked example: converting an unstructured interview to a structured one
- Unstructured approach: Each interviewer asks whatever questions come to mind, with no shared rubric — low predictive validity, high bias risk
- Job analysis: Identifies the top 5 competencies critical to success in the role (e.g., stakeholder communication, prioritization under ambiguity)
- Structured questions: Each competency gets a behavioral question ("Tell me about a time you had to reprioritize under a tight deadline") scored on a defined 1-5 rubric
- Outcome: All candidates are asked the same questions and scored the same way, improving both fairness and predictive accuracy
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Workforce-planning and structured-interview design assignments.
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Frequently asked questions
Decades of industrial-organizational psychology research consistently show that structured interviews — where every candidate is asked the same job-relevant questions and scored against a predetermined, defined rubric — predict future job performance substantially better than unstructured interviews, where interviewers ask whatever comes to mind and form a holistic, often intuitive judgment. The reason is that structure removes several sources of error: it ensures interview content is actually tied to job-relevant competencies (rather than rapport or shared interests, which don't predict performance), it reduces the influence of unconscious bias since every candidate faces the same standard, and it improves inter-rater reliability since scoring against a defined rubric is more consistent across different interviewers. HRM5060 teaches structured interviewing as an evidence-based practice specifically because the intuitive confidence many hiring managers feel in unstructured interviews is not actually correlated with how well those interviews predict on-the-job success.
Adverse impact occurs when a facially neutral selection procedure (a test, an interview question, a physical requirement) results in a substantially different selection rate for members of a protected class compared to others — commonly assessed using the "four-fifths rule," where a selection rate for a protected group below 80% of the rate for the highest-scoring group signals potential adverse impact. It matters regardless of intent because U.S. employment law (under disparate impact theory) can hold an employer liable for a selection practice that produces adverse impact even if there was no intent to discriminate, unless the employer can demonstrate the practice is genuinely job-related and consistent with business necessity. HRM5060 teaches students to proactively analyze selection data for adverse impact patterns — for example, checking whether a cognitive ability test disproportionately screens out certain groups — before relying on a selection method at scale, rather than discovering the problem only after a legal challenge.