Industrial-Organizational Psychology is a subfield of psychology that focuses on understanding how people think, feel, and behave in the workplace. It emphasizes the practical application of psychological theories to improve people’s relationship with their work environment. Selection and assessment, a key area of research within Industrial-Organizational psychology, aims to identify methods for measuring individual characteristics related to employment outcomes such as job performance.
The Importance of Employee Fit
Research consistently shows that when there is a good match between an applicant’s characteristics and the work environment, it benefits both the organization and the employee. For organizations, having employees that fit the work environment can increase overall worker productivity, job satisfaction, and commitment to the organization. On the other hand, low levels of fit can have negative consequences for an individual’s health and well-being, resulting in a range of psychological and physical issues due to increased levels of stress at work. Employees who don’t fit into the work environment perform poorly on the job, have worse health outcomes, and are more likely to leave their job. Misfit is simply bad for business.
Assessing for Fit Pre-Hire
Ideally, organizations should assess applicant fit before hiring to maximize the chances of finding a good match. Interviews are commonly used to assess applicant fit, and highly structured interviews are the strongest predictor of job performance compared to other popular methods to assess applicant fit. Unfortunately, they are time-consuming and cost-intensive, which prevents organizations from using them with more than a small subset of applicants. Applicants are generally screened out using subpar methods like resume screening. However, advances in technology and artificial intelligence are beginning to challenge traditional screening methods. Specifically, advances in natural language processing provide opportunities to deploy interviews at scale means that automated interview scoring is now possible. Knockri is at the forefront of this technological advancement and working with leading researchers in automated interviews to support the validity and use of automatically scored interviews.
Presenting Research at SIOP
Every year, the Society for Industrial-Organizational (I-O) Psychologists brings together over 10,000 members to network, present interesting research, and discuss the practical application of psychological theory within the workplace. This year, Knockri was invited to present a study conducted in collaboration with Louis Hickman, an Assistant Professor in Psychology at Virginia Tech. The study tested Knockri’s patented approach to the automation of interview scoring, which is designed to identify samples of work-related behaviors within an applicant’s response to an interview question and use the behavioral data to measure a range of applicant characteristics.
About the Study
The study involved 842 participants who completed a mock, 6-question asynchronous interview intended to assess various individual characteristics predictive of performance across a wide range of occupations. Trained raters provided assessments of personality traits in response to viewing the interviews along with overall perceptions of whether they would hire the applicant. Independently, transcripts of the interviews were scored using Knockri’s proprietary automated interview scoring algorithm. The relationships between scores derived from the algorithm and recruiter ratings were examined.
The results of the study showed meaningful relationships between the automated interview scores and interview ratings of applicant characteristics. Behavioral samples identified in an applicant’s response were meaningfully correlated with personality traits such as openness, conscientiousness, and intellect. In addition, the behavioral samples also displayed meaningful relationships with cognitive ability, interviewees’ college GPA, and perceptions of Hireability.
Future of Selection with Knockri
According to Professor Louis Hickman, “focusing on samples of job-relevant behavior appears to be a promising new approach to the automated scoring of employment interviews”. Knockri’s Chief Scientist, Dr. Dave Mayers, is continuing to work with Louis Hickman to further explore the capabilities of this novel interview approach. He is also collaborating with businesses and researchers worldwide to address measurement and validation, demographic differences, applicant experience, hiring manager decision-making, and explainable AI.
References
Kristof-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences of individual’s fit at work: A meta-analysis of person-job, person-organization, person-group, and person-supervisor fit. Personnel Psychology, 58(2), 281-342.
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.
