Indonesia’s first doctoral-level assessment center research challenges assumptions long held to be true about how organizations choose their leaders. Dr. Maharani Syahratu Kertapati, Future of Work Group Head at Daya Dimensi Indonesia, completed her dissertation at the Faculty of Psychology, University of Indonesia, on 6 January 2026 after six years of research. Her key finding affirms that the clarity of the competency definition being measured matters far more to assessment accuracy than the complexity of the method used. The research also proves that an assessor’s first impression of a candidate can contaminate the objectivity of the assessment—an important warning for every HR practitioner who relies on this method for strategic talent decisions.
On 6 January 2026, in the examination room of the Faculty of Psychology at the University of Indonesia, a simple question finally received a scientific answer after six years of inquiry: can an assessor’s first impression of a candidate damage the objectivity of the assessment? According to Dr. Maharani Syahratu Kertapati, the answer is yes—and the impact is greater than many assume.
The dissertation, titled “The Influence of Assessor First Impressions on Assessment Accuracy in the Assessment Center Method Across Different Measurement Dimensions and Simulation Types,” is the first doctoral-level study in Indonesia to specifically dissect the assessment center method—a method used for decades to choose leaders in hundreds of companies and state institutions.
The research was conducted under the guidance of Prof. Dr. Guritnaningsih as promoter, with Dr. Dewi Maulina and Drs. R. Urip Purwono as co-promoters, at the PsyTrust laboratory, Faculty of Psychology, University of Indonesia. Maharani noted that worldwide there were only a handful of academic papers on the influence of first impressions in assessment centers, making this research a rare contribution globally.
An assessment center is an evaluation method that uses a variety of simulations and measurement dimensions to assess a person’s potential and competencies, particularly for leadership roles. The method is designed precisely to minimize bias by relying on behavioral observation rather than subjective impression alone.
Yet the greatest added value of an assessment center should be accountability—and according to Maharani, the highest accountability is the kind grounded in scientific evidence. This is what drove her to mine the rich assessment data that had until then been used only for practical needs, not scientific contribution.
If there is one thing Maharani wants to convey to HR practitioners in Indonesia, this is the core of it: the clarity of the competency definition being measured matters far more to assessment accuracy than the complexity of the method used. A clearly defined, well-structured dimension makes it easier for assessors to evaluate accurately, while an abstract dimension makes assessment quality drift.
The clearest example is integrity. Clients often ask for the integrity of a leadership candidate to be measured, yet measuring integrity from a three-hour assessment is an enormous leap. The fundamental problem is that integrity means something different in each person’s mind—if even the definition differs, accuracy is impossible to maintain.
The solution is not to avoid measuring abstract values but to break them down into specific, observable behaviors. Instead of measuring ‘integrity’ as one big label, the competency can be unpacked into compliance with rules, consistency between words and actions, and the courage to speak the truth in difficult situations.
With clear operationalization like this, assessors have a concrete benchmark—making the assessment center method produce far more reliable evaluations.
The second, equally important finding concerns the assessor’s first impression. In daily practice, many assessors read a candidate’s CV or profile before the session begins, hoping to be ‘better prepared.’ Maharani’s research shows the opposite.
A first impression formed before the formal assessment begins can contaminate the final evaluation. Assessors who already hold an image of a candidate tend to seek confirmation of that image rather than assess objectively based on the behavior displayed. The implication is clear: a procedure long considered helpful can actually undermine the validity of the results.
Maharani understands that academic findings are not always easy to apply. Although there are International Guidelines on Assessment Center Practice and a code of ethics for assessment center practice in Indonesia, field practice is often modified due to time or budget constraints.
One of the most frequently neglected is assessor training. Many assessors are hired without adequate training, relying only on experience without further verification. Yet international standards make clear that assessors must be trained for each new project, especially when the company context or the position being assessed differs from before.
This scientific approach does not negate the value of intuition. Maharani acknowledges the existence of tacit knowledge—knowledge that only a person holds because of years of experience—which is real and valuable. The problem, however, is that tacit knowledge is not reliable in an organizational sense: when that person leaves, their knowledge leaves with them and cannot be passed on.
The scientific approach offers something different: documentation, standardization, and the ability to be re-tested. This is what makes an assessment center run with scientific discipline accountable across time and teams.
Why does all this matter? Maharani answers with a counter-question: what is the cost an organization bears when it chooses the wrong leader? Assessment is not the sole basis for a decision, but it is often the consideration most widely accepted by various stakeholders, especially for strategic positions.
A mistake at the leadership level is no small error. When an organization chooses the wrong leader, its direction can go astray, and the effects are long-term and difficult to repair. The function of assessment here is to minimize risk—ensuring strategic decisions are based on evidence, not merely personal impression.
For Maharani, the journey is only just beginning. She pursued further study because she felt her previous knowledge was insufficient for future challenges, as clients’ assessment needs continue to change.
On whether assessment centers will be replaced by AI, she emphasizes the answer must be evidence-based. The question is not whether AI replaces humans, but which parts can be replaced and which cannot. Assumption alone is not enough—evidence is needed to answer it responsibly.
In closing, Maharani invites leaders to discuss the questions that often remain unanswered: should assessors read CVs before evaluating? Should simulations be as complex as possible? Is measuring more dimensions always better? Her invitation is for grounded discussion that can be scientifically accountable—not merely procedural.
Dr. Maharani Syahratu Kertapati is the Future of Work Group Head at Daya Dimensi Indonesia, leading the Applied Science and Imagination Center (ASIC)—the company’s internal research and development unit. Daya Dimensi Indonesia, part of Dayalima Group, is known as a pioneer of the assessment center method in Indonesia. This research reaffirms the company’s commitment to delivering talent practices grounded in scientific evidence, not mere tradition.
An evaluation method that uses a variety of simulations and measurement dimensions to assess a person’s potential and competencies—especially for leadership roles—relying on behavioral observation rather than subjective impression.
The clarity of the competency definition being measured matters far more to assessment accuracy than the complexity of the method used.
Because a first impression formed before the assessment begins can contaminate the evaluation—assessors tend to seek confirmation of their initial image rather than assess behavior objectively.
According to this research, the answer must be evidence-based: the question is not whether AI replaces humans, but which parts can be replaced and which cannot.
