Unstructured interviews remain widespread used in businesses despite consistently poor predictive performance. Such informal, conversational interviews are vulnerable to interviewer bias, halo effects, similarity attraction, confirmation bias, and overreliance on intuition.
Similarly, years of experience, while often useful as a screening criterion, are generally poor predictors of future performance when considered in isolation.
Experience alone does not guarantee adaptability, learning agility, interpersonal effectiveness, problem-solving capability or critical thinking, all of which are better predictors of future success.
In this article we will discuss a more evidence-based, scientific process that results in superior prediction of job performance, starting with defining what good looks like.
The success profile
No assessment process can deliver meaningful ROI if the organization does not know what successful performance actually looks like.
One of the most common mistakes in selection is treating assessments as isolated diagnostic tools detached from the realities of the role. Companies are to prepared to invest the necessary time and energy to critically review what critical constructs they are looking for in their applicants.
Problems frequently emerge when:
- End-users interpret results without deep role understanding
- Organizations derive ideal profiles by averaging scores of existing employees
- Generic potential profiles are used without clear behavioural relevance
A robust success profile should instead emerge from careful job analysis and consultation with high-performing incumbents, managers, and relevant specialists.
An effective success profile:
- Identifies the actual behaviours linked to success
- Clarifies what high performers consistently do differently
- Distinguishes essential from merely desirable competencies
- Connects assessment criteria directly to role requirements
Once this foundation exists, assessments become significantly more meaningful because organizations are measuring constructs that matter to performance.
Objective measures predict job performance
Unlike poor prediction methods such as unstructured interviews, structured and evidence-based selection methods consistently demonstrate strong predictive validity. These include:
- Cognitive ability assessments
- Personality questionnaires aligned to job requirements
- Situational Judgement Tests (SJTs)
- Structured, competency-based interviews
- Role simulations and work samples
Combinations of these methods commonly achieve validity coefficients around 0.35 – 0.51 and above.
While such figures may sound abstract, their practical implications are substantial. Even moderate increases in validity meaningfully improve the odds of selecting stronger performers and avoiding weaker ones.
Importantly, assessments should not be viewed as replacements for human judgment. Rather, they provide structured, objective evidence that complements and improves decision-making quality.
Assessment ROI tends to be strongest in two situations:
- High-volume selection environments
- High-impact roles where individual performance carries major organizational consequences
For example, when selecting 100 employees from a pool of 330 applicants, adding a scientifically valid assessment process may dramatically increase the number of eventual high performers selected:
- Without assessments, approximately 40 strong performers might emerge
- With a robust assessment battery, that figure could increase to around 61
That represents 21 additional strong performers from the same hiring volume.
Equally important, assessments can improve operational efficiency by:
- Reducing interviewer hours
- Narrowing candidate pools more effectively
- Shortening time-to-hire
- Improving recruiter focus
- Enhancing consistency across hiring decisions
Designing a better recruitment process
Assessment effectiveness depends not only on the tools used, but also on how they are integrated into the broader recruitment process.
A high-ROI recruitment process typically follows a step-by-step approach:
1. Initial screening
Although their predictive power is relatively low, basic qualification and eligibility filters remain necessary.
At this stage, so-called gross negative disqualifiers such as certification and physical minimums may be employed to filter candidates.
2. Screening assessments
Online cognitive tools, SJTs, or other scalable, cost-effective and highly predictive assessments are used early to narrow large candidate pools efficiently.
These methods ensure that the initial pool of candidates all display the foundational requirements for job success.
3. In-Depth assessments
Shortlisted candidates may complete more detailed personality measures, simulations, technical tests, or role-specific exercises.
These are more resource-intensive but applied to far fewer individuals. The goal at this stage is to provide in-depth data on how candidates match specific requirements for success in the job itself, rather than more general potential for job success across roles.
4. Final structured interviews
As a final hurdle, behavioral and competency-based interviews aligned to the success profile can provide integrative judgment and contextual interpretation.
One common organizational mistake is reversing this sequence by conducting extensive interviews first and assessments last. Many organizations will conduct interviews with several candidates and will only assess the final shortlisted candidate.
This approach creates several problems:
- Large amounts of managerial time are spent on weak predictors
- Emotional investment develops before objective data is available
- Confirmation bias becomes more likely
Placing data-rich methods earlier in the process improves efficiency and helps managers make better talent decisions.
Assessments beyond selection
The value of assessments extends well beyond initial hiring decisions. Many organizations feel that once candidates has been appointed the role of assessment information has fulfilled its purpose.
When implemented thoughtfully, assessment systems can support:
- Onboarding and development planning
- Leadership identification
- Succession planning
- Team composition
- Retention strategies
- Culture shaping
For example, assessment insights may help managers tailor development conversations or identify employees requiring additional support during onboarding.
Similarly, organizations that consistently select for attributes such as collaboration, adaptability, resilience, or curiosity may gradually reinforce those characteristics culturally over time.
One recent client example demonstrated the broader organizational impact of a more evidence-based assessment strategy:
- 48% reduction in first-year turnover in a call centre environment
- 5% uplift in performance ratings
- 65% reduction in time-to-hire
- Fewer performance improvement plans and disciplinary interventions
While no intervention operates in isolation, these outcomes illustrate how data-driven selection processes can influence broader organizational functioning.
Final thoughts
Organizations that implement evidence-based, robust processes when making talent decisions are likely to outpace their competitors in regard to better hires, as well as accelerated engagement and growth for existing employees.
Given the distinct advantages, the question for most talent professionals should not be “if” objective assessments are the way forward, but “when.”
This article was based on key themes from the TTS session, The ROI of Assessments: Linking Selection to Performance, presented at the recent Recruitment Conference.
If you would like to know more about designing assessment-centric talent processes, reach out to us at info@tts-talent.com.