Selection procedures refer to any measure or method or a combination of measures or methods used as a basis for an employment decision. Selection procedures include a range of assessment techniques from traditional paper and pencil tests, work samples and other skills-based tests, psychometric tests such as personality or aptitude tests, probationary periods, educational and work experience requirements, and interviews.

Selection methods vary concerning their propensity for bias to influence candidate assessment. Although the most common selection procedure, a vast body of research shows that informal unstructured interviewing is the least objective selection method(1). In the majority of cases, candidate interviews add zero credibility to the hiring decision(2). In the best cases, unstructured interviews add only 10% validity to the process. 

Bias in Selection

Cognitive neuroscience research shows us that most decisions we make, particularly about people, are contaminated by biases that operate under the scope of human consciousness. Unconscious bias in selection has profound implications—when assessing a candidate’s suitability for a role, we add our own subliminal and emotional criteria to that decision. Criteria we might not even be aware of and which may have no basis in facts. Bias can also be institutionalised in the form of assessment practices that systematically favour some groups over others.

The Case for Objective Selection

Selecting the best candidates not only drives higher performance—but it also reduces costs. Harvard Business Review report that 80% of turnover is due to bad hiring decisions(3). Research from the Society for Human Resource Management concludes that a poor hire can cost a company up to five times the amount of the hire’s salary when one considers the original cost of hiring the employee, the cost of lost productivity, the cost of training the poor hire, and the cost of hiring and training a replacement, among other factors(4).

If you have biases which are impacting recruitment decisions you are likely not choosing the best person for the job. Also, you are likely to end up with a relatively homogenous workplace, missing out on the competitive potential of a diverse workforce.

Strategies for Objective Selection

Although 81% of employers recognise the potential for unconscious bias to influence selection, 42% of employers do not use any strategies to reduce bias in selection(5). Eliminating bias from selection involves techniques and practices that:

  • Encourage the assessor to focus on matching demonstrable applicant capabilities to well-defined job criteria
  • Limit the potential for information about the candidate that is not relevant to job performance but that might influence how the assessor personally feels about or perceives the candidate to impact decision-making
  • Level the playing field for diverse candidates

Matching capabilities to job criteria

Many hiring decisions are made on instinct or assumptions about the type of person who will succeed in the role rather than demonstrable skills and abilities that are valid predictors of job performance. When thinking about the ideal candidate, recruiters and hiring managers often look to the sorts of people who have held the role in the past. Anchoring hiring decisions on past hires means that equally qualified candidates with diverse backgrounds that can make an additive contribution to the team are overlooked. A focus on past candidates also perpetuates bias and limits the recruitment of top talent—were past hires objectively the best candidate or did bias influence selection?

Improving objectivity in hiring requires attention to the following steps:

  • Identify tasks critical for job performance: Define success in the role by asking what tasks are most critical for job performance?
  • Define required capabilities: What knowledge, skills and abilities are needed to perform critical job tasks? Consider hard and soft skills. Be careful to specify knowledge, skills, traits, qualifications, and experience that map to the role requirements, not to the type of person you think would be successful in that role. Consider also performance risks for the role—where do employees come ‘unstuck’ in the role? What causes underperformance? (e.g. poor time management, weak conflict resolution skills). Include compensating competencies as job criteria.
  • Rank and weight criteria: Mark selection criteria as ‘non-negotiable’, ‘desired’, or ‘can be developed’ to encourage consideration of a broader pool of candidates. Rank and weight your top five criteria.
  • Review selection criteria for bias: Are your selection criteria valid predictors of job performance or do they describe the type of person assumed to be successful in the role? Are you recruiting for performance or potential? What assumptions are you making about skill from qualifications? What proof do you have that a criterion predicts job performance? Does any criterion reference a trait commonly associated with gender, age, cultural or other stereotypes?
  • Hire to include: Include diversity as a selection criterion, where relevant, For example, recognise the value of cultural and linguistic skills for customer-facing roles. Consider capability gaps across a team rather than an individual-level approach when setting criteria. Taking an additive approach encourages recruiters and hiring managers to look beyond cultural fit for candidates with different experiences that complement existing team capabilities. Be careful not to focus on one-dimensional characteristics. Don’t determine you need a woman, for example, to balance out the team. Diversity for diversity’s sake leads others to make negative assumptions about your people decisions and those you hire or promote. Instead, look at how people can add to the total portfolio of mindsets, skills, and experiences on the team.
  • Skills-based testing: Give a work sample test that mimics the kinds of tasks the candidate will be performing on the job. Research shows that work samples are the best indicators of future job performance and outperform interviews, unstructured and structured. Whenever possible, ask for samples or examples of work and review them before you meet with the candidate to diffuse the impact of biased first impressions.
  • Behavioural-based interviewing: Behavioural-based interviewing allows candidates an opportunity to demonstrate their competencies by describing how they achieved examples of success in their current or past roles, how they managed challenges, or by explaining how they would approach a hypothetical situation

Reduce the potential for bias

  • Structured application forms: Using structured application forms that tap specific skills and experience rather than inviting CV’s where gender, background, and education are often visible decreases the likelihood that identity information will influence selection decisions.
  • Remove identifying information: In a similar vein, employers can remove identity information from CVs, a technique known as the blind CV. De-identification is not appropriate, however, when under-represented groups make up a small proportion of applicants. In these circumstances, CV de-identification should be implemented along with other interventions like targeted recruitment strategies. Technology, such as Gap Jumpers can automate blind recruitment processes.
  • Phone screening: Candidate screening by phone helps to minimise bias by decreasing the visibility of some diversity dimensions that are not relevant for job performance but might influence the assessor’s evaluation of a candidate unconsciously. Phone screens are a way of making interviews ‘blind’ and encourage the assessor to focus in the first instance on skills, abilities, and knowledge relevant to the role rather than other characteristics of the candidate that can unconsciously influence assessment. While phone interviews minimise the influence of visual first impressions, however, they do not eliminate accent or linguistic bias. If you want to make the interview even more blind, you can go so far as to use a voice modulation app for technical interviews.
  • Automated shortlisting: Automated shortlisting that matches candidate skills reported on CV or application forms to job criteria can be useful so long as the criteria and the matching algorithm are not biased. In 2017, the Illinois attorney general opened an investigation into several hiring platforms after complaints that a résumé tool excluded older applicants because a drop-down menu prevented applicants from listing any qualification of experience before 1980. Similarly, a 2016 class-action lawsuit alleged that Facebook tools enabled discrimination. Facebook’s Lookalike Audiences feature allowed employers to choose only users demographically identical to their existing workers to see job ads, thus replicating racial or gender disparities at their companies.
  • Structured interviews: Standardising the interview process, interviewers focus on data rather than instincts when assessing candidates. Data-based hiring methods outperform our instincts by at least 25 percent(6). Structured interviews have a predictive validity of 62 percent (7). Structured interviews also ensure that no illegal criteria enter the hiring process, In a 2015 review, Jennifer Yugo, who holds a PhD in industrial and organisational psychology, reported half of the unstructured interviews challenged in court had been found to be discriminatory, whereas only 13 percent of structured interviews were found to be discriminatory. Structured interviews minimise bias in selection because they force the interviewer to focus on factors that directly impact role performance. To undertake a structured interview, the recruiter must develop a set of questions that are strictly focused on the role and requirements of the job and selection criteria, ask all candidates the same questions, in the same manner, in the same order, in the same time period. This ensures that each candidate receives the same interview experience. Without standardising interviews, employers do not have a common baseline for comparing and ranking candidates.
  • Use a rating scale: The predictive validity of interviews can be improved by employing a rating system for scoring candidate answers to the questions asked by the interviewer. To reduce inconsistency in ratings across different interviewers and candidates, the rating system should describe in as much detail as possible how to score a candidate’s answer. 
  • Take notes during the interview: Studies show a recall bias for vivid examples such as stories and also for answers that are most recent. Waiting until the end of the interview to rate answers increases the risk of forgetting an early or less-vivid, but high-quality answer, or favouring candidates whose speaking style involves storytelling or whose latter responses are particularly strong. Taking notes also helps to counter our tendency for confirmation bias—paying greater attention to and recalling information congruent with our preferences.
  • Engage a panel but rate candidates independently: By involving others who ideally represent the diversity that the employer is striving to achieve, recruiters are exposed to different perceptions and opinions about the candidate. They are challenged to justify their assessment of a candidate with objective data. This helps to decrease the potential for emotion-driven or instinctive decision-making. Panel members should always score candidates individually first and save their discussion until the end of the interview process. Independent ratings guard against conformity bias. Conformity bias is a tendency to be influenced by the ideas and behaviours of others rather than exercising our independent judgment. Reference checks are another data point for the hiring process, but it is important to remember that referee assessments can be biased. Asking referees for examples of achievements on the job that demonstrate behaviours required in the role as well as probing for any red-flags can improve the objectivity of referee data. Ideally, the reference checks should be conducted by an individual who did not interview the candidate. This avoids the person conducting the reference check being influenced by confirmation bias.
  • Use validated assessment tools: Validated assessment tools such as tests of emotional intelligence, cultural intelligence (for performance in diverse cultural settings), general cognitive ability (IQ), personality assessments and other psychometric tools control for unconscious bias and improve objectivity in candidate assessment, which in turn drives greater diversity. A study of 150 companies found that those that used a personality assessment in their hiring had more racially diverse workforces(8).
  • Employ multiple assessment methods: Using various assessment methods offers multiple data points and decreases the risk of bias. Supplement structured interviews with work samples, validated psychometric tools, panels, and reference checks.
  • Challenge your own and others biases: Unconscious bias is universal—we all have bias in some shape or form. However, although bias is inevitable, acting on it isn’t. When we are motivated to be fair and unprejudiced because of either a strong internalised belief that it is morally correct to treat others fairly or because of strong social norms and legal restrictions against expressed prejudice and discrimination, we can engage controlled mental processes to override biased automatic responses.
  • Develop hiring to include capability: Assist recruiters and hiring managers in understanding their implicit assumptions and prejudgments with formal training that transfers skills for objective assessment, including developing their ability to monitor and manage their own and other’s bias.

Level the playing field

  • Video interviews: Video interviews make the selection process more flexible and accessible and address some of the barriers facing individuals with non-traditional work schedules, candidates that are geographically dispersed, candidates with mobility restrictions or other disabilities, and candidates who are unable to take time off from their existing employment to attend interviews. Candidates have the opportunity to record themselves at home, on their own time. If multiple interviewers are involved in the process, each interviewer can watch the candidate’s pre-recorded interview on their schedule.
  • Flexible scheduling and location: Similar to video interviews, offering flexibility in when and where the assessment process is conducted addresses some of the barriers facing non-traditional talent pools. 
  • Accessible assessment practices: Offering and granting accommodations to candidates with a disability helps to level the playing field. Examples include providing materials in alternative formats or granting additional time and ensuring assessment centres are accessible.
  • Interpreter support: Providing translation services for candidates from a non-English speaking background can support assessment performance when high levels of English proficiency is not a job criterion.
  • Gender-neutral addressing: Addressing candidates by name (as recorded on their application form unless otherwise advised by them) and confirming pronoun use conveys respect for transgender, transitioning and gender non-binary candidates. 
  • Seek to reduce candidate anxiety: Candidates from non-traditional backgrounds may experience higher levels of anxiety that could potentially impact assessment outcomes. Recruiters and hiring managers can support candidates by providing transparency about assessment methods, candidate guides/information, sufficient time to allow candidates to prepare, pre-interview office tours, and conducting interviews in a warm and friendly tone.
  • Offer a candidate grievance channel: Respond in a timely and transparent manner to any complaints raised.

After the interview

  • Make introductions: Allow candidates to chat with current members of the workforce. This is particularly important for women and minorities who may be uncertain of how welcoming and supportive the wider organisation is to difference. Introduce diverse candidates to diversity champions, role models or representatives from Employee Affinity Groups.
  • Provide feedback: For unsuccessful candidates, always give objective interview feedback. This helps to minimise any concerns that the candidate might have regarding the role of bias in selection.
  • Seek to understand the candidate experience: Survey all shortlisted candidates and conduct employee focus groups and exit interviews to tap perceptions of fairness of the talent management process. Act on the information gathered to drive inclusive recruitment and improve the experience of diverse candidate and employees.
  • Track success: Diversity metrics for tracking bias risk areas include candidates shortlisted, performance at interview, selection, candidate retention. Equality monitoring forms must be kept separate from the assessment process.

Citations

  1. 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. http://dx.doi.org/10.1037/0033-2909.124.2.262
  2. RemarkAble HR. (nd). Problems regarding subjective interview techniques. Downloaded from https://cdn.ymaws.com/www.southpalmbeachbar.org/resource/resmgr/imported/PROBLEMS%20REGARDING%20SUBJECTIVE%20INTERVIEW%20TECHNIQUES.pdf
  3. Bassi & McMurrer. (2007). Maximising Your Return on People. Downloaded from Harvard Business Review website: https://hbr.org/2007/03/maximizing-your-return-on-people
  4. Frye. (2017).The Cost of a Bad Hire Can Be Astronomical. Downloaded from SHRM website: https://www.shrm.org/resourcesandtools/hr-topics/employee-relations/pages/cost-of-bad-hires.aspx
  5. Robert Walters. (2017). Diversity and Recruitment Whitepaper. Downloaded from Robert Walters website: https://www.robertwalters.co.uk/content/dam/robert-walters/country/united-kingdom/files/whitepapers/Diversity-In-Recruitment-Whitepaper-web.pdf
  6. Kuncel, Ones, & Klieger. (2014). In Hiring, Algorithms Beat Instinct. Downloaded from Harvard Business Review website: https://hbr.org/2014/05/in-hiring-algorithms-beat-instinct
  7. Beardwell, I., Holden, L. and Claydon, T.(ed.), (2004), Human Resource Management A Contemporary Approach, 4th edition.
  8. Ng & Sears. (2010). The effect if adverse impact in selection practices on organisational diversity: a field study. https://doi.org/10.1080/09585192.2010.488448