The evidence on structured interviewing is consistent. Here’s what the research shows, and why it matters to the integrity of your team during the interview process.
In 2022, Sackett et al. published a large-scale analysis in the Journal of Applied Psychology.
The research showed that the structured interview validity coefficient is .42, which is more than double the .20 associated with unstructured interviews. Since validity coefficients measure how well tools predict real job performance, this is meaningful information for hiring teams.
Put simply, structured interviews are a better predictor of on-the-job success than years of experience, cognitive tests, and unstructured conversations. These findings are consistent across research and have clear implications for how recruiters should spend their time.
The term “structured interview” isn’t as complex as it sounds.
In practice, it means three things: Every candidate is asked the same competency interview questions, every answer is scored against predefined criteria with behavioural anchors, and every question is mapped to a specific competency identified before the process began.
As mentioned above, the advantages of a structured interview are compelling. Organisations that use them are able to predict future job performance with greater accuracy. Also, candidates receive a better experience, which could help improve your employer brand.
Keep in mind, structure isn’t about rigidity. It is about giving the interviewer a consistent lens through which they can assess candidates who apply for current roles.
When candidates go through the same process, answer the same competency questions, and get scored on the same criteria, the conditions that allow for bias disappear.
Bias in hiring usually comes from inconsistency, not bad intentions. If you ask one candidate about a challenging project and another about their career ambitions, you end up making decisions based on comfort, familiarity, or an overall impression rather than evidence. A structured approach closes the gap so hiring teams can better assess candidates.
Worth mentioning, a well-designed competency interview still allows for follow-up questions and genuine conversation, while removing unwanted variability.
Do you know what success looks like in the role you’re hiring for? If you don’t, you can’t write effective interview questions because you haven’t performed a satisfactory job analysis.
Research by Campion et al. in 2011 shows that job analysis, combined with competency modeling, bridges the gap between academic methodology and realistic implementation. As such, it gets executive attention in a way that traditional job analysis language rarely does.
When you describe the key competencies a brilliant hire needs to demonstrate, rather than listing duties from a job description, stakeholders engage in a different way.
Skipping job analysis has consequences. Without a clear definition of success, hiring managers focus on different things, interviews become inconsistent, and feedback conflicts. Worse, when a hire doesn’t work out, it’s almost impossible to know why. Because of this, companies use the same informal briefs and gut feelings during the next hiring cycle, which leads to more failure.
Not all interview questions are equal. The format of a question shapes the quality of the insight it generates. The research is clear about which formats produce the best results.
Behavioural competency questions ask candidates to describe past experiences.
Specific examples include: “Tell me about a time you had to manage competing priorities under pressure,” and “Talk me through a project where you had to influence people.“
The reasoning is simple: Past behaviour is the most reliable predictor of future performance. When a candidate explains a real situation, including the context, the task, the actions they took, and the outcome they achieved, the interviewer gets a window into the candidate’s mind.
This is especially true when using the STAR approach, which gives candidates a structured way to respond and gives interviewers a consistent framework to assess answers.
Situational questions take a different angle. Rather than asking candidates to draw on past experience, they present a specific scenario and ask how they would respond. “How would you approach a team situation where two colleagues disagree and the deadline is imminent?“
This format is particularly useful for early-career candidates who can’t prepare examples of past performance. It also tests problem-solving and decision-making skills in context, which helps interviewers understand how candidates think under pressure.
A well-designed competency interview uses a mix of behavioural and situational questions.
Different question types reveal different information: Individual contributions, leadership in a team setting, how someone handles competing priorities, and how they adapt to adverse scenarios.
Using both behavioural and situational questions will give you a full and fair picture of each candidate. That way, you can evaluate their ability to achieve success in a role.
Per the research, structured, competency-based interviews predict business performance better than almost every other method. Still, many hiring managers aren’t prepared to run interviews and thus ask inconsistent questions that lead to false assumptions about candidates.
Why does this happen? Because structured interviews are hard to build. They require a clear job analysis, well-designed competency questions, a scoring rubric with behavioural anchors, and alignment across the entire organisation. Most organisations don’t have access to I/O psychologists or external consultants—the professionals who excel at this kind of work.
Fortunately, organisations don’t need access to these professionals anymore. Thanks to AI tools, they can run a job analysis, design competency-based interview questions, and score every candidate against the same criteria in less time. The result? A process that’s twice as predictive, leading to more successful recruitment workflows.
Sapia.ai gives every volume hiring team access to science-backed hiring tools.
Our Job Analysis Studio defines skill sets for each role by translating job description inputs into a weighted competency model that reflects real-world success.
The AI Chat Interview tool then drives a structured AI chat interview, where every candidate responds to the same competency-based questions and gets scored against the same criteria.
With Sapia.ai, you can build a hiring process that’s supported by scientific research: Define the role, ask consistent questions, and use evidence-based scoring. Just as important, you can build it without an expensive I/O psychologist—in minutes, not hours.
Book a demo of Sapia.ai today to see our industry-leading recruitment platform in action!
A competency-based interview is a structured approach to hiring where every candidate answers the same predefined questions, scored against consistent criteria. Rooted in evidence-based hiring research, it’s one of the best predictive hiring assessments.
Competency-based interview questions ask candidates to describe specific situations in which they demonstrated a particular skill or behaviour. They typically begin with “Tell me about a time when…” or “Give an example of…” and reveal how candidates work.
STAR stands for Situation, Task, Action, Result. This method gives candidates a structured way to respond to competency questions by walking through the context of a situation, what they were responsible for, what they did, and what the outcome was. For interviewers, it also provides a consistent framework with which to score responses.
The most common competencies include problem solving, leadership, decision making, teamwork, and communication skills, as well as the ability to manage competing priorities. The specific competencies you test for, however, should be determined by a thorough job analysis.
Traditional interviews are unstructured. As such, questions vary by candidate, and scoring is largely subjective. Competency-based interviews ask every candidate the same set of questions, which have been mapped to predefined criteria. This consistency is what makes competency-based interviews more predictive of job performance, and thus a better tool.
Start with a job analysis to identify key competencies. Then craft behavioural and situational questions that give candidates the opportunity to demonstrate related skills. Finally, use an anchored scoring rubric to hold every candidate to the same standard. While this approach may sound complicated, tools like Sapia.ai use modern technology to simplify the process.