BUS 6553 Module 2 Hiring Process Bias Analysis Example

Referrals, Résumé Hunches and the Beer Test: Where Bias Enters the Hiring Funnel at a Charlotte Engineering Firm

Student Name

American College of Education

BUS6553: Leveling the Playing Field in Talent Management

Module 2 Assignment

Instructor Name

January 28, 2030

Introduction

My earlier review traced unfair outcomes to moments when decision makers have wide latitude and can see who a candidate is. This paper applies that conclusion to one hiring process. Piedmont Civil Group is a composite firm; its details combine several engineering companies and have been altered. Based in Charlotte, North Carolina, it employs about 900 people and hires roughly 60 entry-level project engineers a year. Its leaders are concerned that, although engineering graduates are increasingly diverse, its new hires are not. The analysis maps the hiring process, measures where candidates from different groups drop out and explains the gaps with research.

The Hiring Process

Hiring for project engineers moves through five stages. Candidates are sourced through employee referrals, career fairs at four regional universities and online postings. Recruiters screen résumés without a written rubric, looking for relevant internships and, in practice, familiar schools. Candidates who pass have a phone screen with a recruiter. Those who advance meet a panel of two or three engineers for an unstructured interview, after which the panel discusses each candidate and votes, often citing whether the person would fit the team. Offers are made by the hiring manager, with salary set within a band.

Method

Applicant tracking data for 2027 and 2028 covered about 2,400 applicants, of whom self-reported gender was available for 88 percent and race and ethnicity for 79 percent. For each stage, the pass-through rate was calculated by group: the share of candidates entering a stage who advanced to the next. Interviews with six recruiters and eight frequent panelists explored how decisions were made. Comparing pass-through rates, rather than final hires alone, shows where in the process differences arise.

Data Quality

The analysis also examined data quality. Self-reported demographic data were missing for about one applicant in eight, and missing data were somewhat more common among applicants who withdrew early. To test whether this affected the findings, pass-through rates were recalculated under the assumption that all missing applicants belonged to the group with the lowest rate; the gaps narrowed slightly but remained. The firm will need better data collection to monitor any changes it makes.

Where the Gaps Open

The data show three points where gaps open. At sourcing, 46 percent of hires came through referrals, and referred applicants were less diverse than the graduating classes of the firm's target universities. At résumé screening, women advanced at 34 percent compared with 41 percent for men, and Black and Hispanic applicants at 29 percent compared with 40 percent for white applicants, even among graduates of the same programs. At the panel interview, Black and Hispanic candidates advanced at 38 percent compared with 52 percent for white candidates. Phone screens and offer acceptance showed small differences.

What Recruiters and Panelists Said

Interviews added context the numbers could not. Recruiters said they screened quickly, often spending less than a minute per résumé during peak season, and that familiar school names offered a fast signal. Panelists said they valued candidates who seemed confident and easy to talk to, and several admitted that their questions varied from one candidate to the next. None described intentionally favoring any group. Their accounts show how time pressure and unstructured discretion, rather than intent, produce the patterns in the data.

Sourcing Through Referrals

Referrals are attractive because they are cheap and referred hires often stay longer. Fernandez et al. (2000) studied hiring at a phone center and found that referrals produced economic returns for the employer through richer applicant pools and better-matched hires. But referrals draw on employees' networks, which tend to resemble the employees themselves. When the current workforce is not diverse, heavy reliance on referrals reproduces its composition. At Piedmont, the referral bonus program, which pays $2,000 per hire, rewards this pattern without any check on who is referred.

Résumé Screening Without Criteria

Screening without a written rubric gives recruiters wide discretion and exposes identity cues in names, schools and activities. The field experiments reviewed earlier show that such cues affect callbacks among equally qualified candidates. Recruiters at Piedmont described relying on a sense of who looked promising, often favoring schools they knew and activities they recognized. These preferences are not intended to exclude, but they convert familiarity into opportunity, and familiarity is unevenly distributed.

Panel Interviews and the Search for Fit

Panelists described asking open-ended questions and discussing candidates afterward, sometimes applying what one called the beer test: whether they would enjoy spending time with the person. Rivera (2012) studied hiring at elite professional service firms and found that evaluators often sought candidates similar to themselves in leisure pursuits, experiences and self-presentation, treating cultural similarity as a sign of quality. Unstructured interviews make such matching easy. Levashina et al. (2014) reviewed research on structured interviews, which ask all candidates the same job-related questions and rate answers against defined standards, and concluded that structure improves reliability and validity and can reduce the influence of irrelevant factors.

What the Firm Loses

The gaps are not only a fairness problem. Unstructured screening and fit-based interviews are weak predictors of job performance. Schmidt and Hunter (1998) summarized decades of research showing that structured interviews and work sample tests predict performance substantially better than unstructured interviews. Sackett et al. (2022) revisited the validity estimates, concluding that some earlier figures were inflated, but structured interviews remained among the strongest predictors. By relying on unstructured judgments, Piedmont not only narrows its pool unfairly but also selects less accurately, losing capable engineers who would have performed well.

Legal and Ethical Distinctions

It is important to separate legal and ethical questions. The analysis does not show intentional discrimination, and pass-through differences alone do not establish legal liability, which depends on facts and legal standards that counsel must assess. Ethically, however, a process that disadvantages qualified candidates because of familiarity, networks or similarity to evaluators fails the principle that people should be judged on job-relevant merit. The firm's leaders can act on the ethical case and on the business case for better selection without waiting for a legal finding.

Rival Explanations

Two alternatives were considered. One is that the groups differ in qualifications. Comparing candidates from the same university programs with similar grades and internship experience reduced but did not eliminate the screening gaps. The other is that candidates from some groups withdraw more often. Withdrawal rates were similar across groups at every stage except offer acceptance, where differences were small. The remaining gaps are most consistent with the discretion and cues identified above.

Conclusion

At Piedmont Civil Group, gaps in hiring open at three points: referral-heavy sourcing that reproduces the current workforce, résumé screening without criteria that turns familiarity into opportunity and unstructured panel interviews that reward cultural similarity. Research on networks, cultural matching and structured interviews explains each gap, and research on selection validity shows the same practices also weaken prediction of performance. These findings will inform the design of fairer, more accurate practices in the final module, after promotion and succession are examined.

References

Fernandez, R. M., Castilla, E. J., & Moore, P. (2000). Social capital at work: Networks and employment at a phone center. American Journal of Sociology, 105(5), 1288-1356. https://doi.org/10.1086/210432

Levashina, J., Hartwell, C. J., Morgeson, F. P., & Campion, M. A. (2014). The structured employment interview: Narrative and quantitative review of the research literature. Personnel Psychology, 67(1), 241-293. https://doi.org/10.1111/peps.12052

Rivera, L. A. (2012). Hiring as cultural matching: The case of elite professional service firms. American Sociological Review, 77(6), 999-1022. https://doi.org/10.1177/0003122412463213

Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection: Addressing systematic overcorrection for restriction of range. Journal of Applied Psychology, 107(11), 2040-2068. https://doi.org/10.1037/apl0000994

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