The Evolution of Talent Assessment
The Evolution of Talent Assessment
by Avinash Pakhre, Consumer and Retail Head
RGF Professional Recruitment, India
"Hire people who are better than you are, then leave them to get on with it. Look for people who will aim for the remarkable, who will not settle for the routine."— David Ogilvy
Innovation and excellence have bred an unprecedented level of competition in the business world. The earlier measures of organization performance (revenue, market share, brand image, EPS) have been rendered ineffective. Widespread need for more holistic parameters is evident. Talent Management has become a crucial parameter to assess organizational performance. The ability to attract talent, develop and deploy at various roles, engage and retain the high potentials, are the subsets of talent management which eventually determine the performance of an organization vis-a-vis its competitors. Valuable and rare talent provides a sustainable competitive advantage and ensures that an organization stays ahead of its competitors and excels in what it does.
The war for talent as predicted by McKinsey is witnessing perhaps the most intensive phase in its history where organizations have taken quantum leaps to ensure the brightest of the talent join them, perform exceptionally and stay long. “The cost of a bad hire to an organization is five times the bad hire's annual salary," -SHRM. The constantly increasing cost burden and pressure to cut down time to hire the right candidate organizations have taken a slew of measures. Organizations have realized the significance of comprehensive and accurate assessment methods to select the right and the best fit.
Talent Assessment in hiring has evolved over multiple phases-
The earliest phase is characterized by human judgments. Assumptions and experiences prevailed over any data or information. Instinct-based decision was considered to be the best gauge to the candidate’s competencies and potential. The applicant pool was limited, jobs were easy and simple to perform, and the competition was negligible. Human Judgement/intuition or mental synthesis of information was the chief decision-making methods. Scientific hiring assessment was neither known nor was conceptualized in this phase. Nevertheless, it surely paved the way for more accurate and precise methods for assessment.
Then comes the era of psychometric assessment- As organizations evolved, tangible change interventions were made some were appreciated, some created ripples and led to high management turnover, hence the need for a more sustained workforce was felt. Hawthorne study was a landmark research in industrial psychology and served as an impetus to much notable organizational behavior studies. Subsequently, tools were designed to gauge the behavioral traits, like, leadership, team building, agreeableness etc. Fit with the team and the organization became the major yardsticks for assessments.
The phase witnessed paradigmatic shifts in operational processes, technology, competition, and workforce demographics. These transformations warranted organizations to change the way they hire and manage their talent. Industrial psychologists, the proponents of psychometric assessment underscored the significance of behavioral assessment in conjunction with technical knowledge and skills evaluation. The efficacy of these methods was validated to statistically significant levels. However, the process failed to elude the manager's judgment and biases. The phase has contributed immensely in providing valuable data and insights into our hiring decisions vis-a-vis assessment of candidates’ performance and potential.
A group of researchers — Nathan R. Kuncel, Deniz S. Ones, and David M. Klieger — analyzed 17 studies of job applicant evaluations and found that a simple algorithm outperforms human decision-making by at least 25%.
The rise of algorithmic assessment- cost of hire, time to hire, have become the secondary indicators to assessment results. The business performance of a new hire is the new acid test. 39% respondents underscored the importance of quality of hire as the most important metric, in LinkedIn’s Global Recruiting Trends.
The complexity of assessment has increased multi folds. In recent years big data has become the most used business term. It’s been stated that organizations have stored tones of data but aren’t capable of bringing it to meaningful use. Effective use of data analytics in talent assessments is an exception though. Tremendous advancement has been made by organizations in using data to improvise the efficiency and effectiveness of assessment methods and processes. From using data just for reporting purposes, to predict and prescribe the likelihood of an assessment outcome, organizations have leveraged on it to enhance their talent assessment techniques. Data from social networking profiles of candidates are used to generate a better understanding of their behavioral aspects
Disruptive technologies have changed the way assessments used to be performed. From in-person interviews to video-based interviews from pen-paper time-consuming assessments to online quick and convenient assessments, technology has immensely aided the assessment process. Oracle, IBM, and SAP are the unicorns of technology provider while Talview and Pymetrics have come to prominence by offering the innovative ways to make assessment convenient and quick. The consumer giant Unilever has partnered with digital HR service providers Pymetrics and HireVue to completely digitize the first steps of the process. The hiring process overhaul has been implemented in 68 countries and was conducted in 15 languages, and involved a total of 250,000 applicants which resulted in increase in job application by 2 times, reduction in hiring biases with most diverse batch hiring, sharp decline in time to hire from average four month to four weeks, and recruiters’ time spent decreased by 75%.
The advent of AI & Machine Learning has started showing business results by impacting the various aspects of the assessment value chain. Ideal uses AI to screen and shortlist candidates by analysing rich candidate information such as resumes, assessments, conversations and performance data. Chatbots can add more information in resumes and talk to candidates, answering their basic questions. Advanced chatbots like Mya not only talk to candidates but also analyse their responses using Natural Language Processing, which allows them to see if a person demonstrates certain skills.
PiQube and HackerRank are the one stop shop for all- where organizations can get ready to deploy the candidate for technical jobs. Cocubes India’s leading assessment and hiring platform, now under Aon Hewitt, helps its clients in assessing entry and lateral level talent. A host of new assessment methods are being used for comprehensive assessment of candidates- BEI, job sample test, psychometric test, simulation exercises, case-based interviews. The application of these tools is based on the job content, and competencies required.
Hiring assessment in today’s environment is well structured, advanced, and relatively less time-consuming. However, it has become more complex as the factors in play have significantly increased. Big data, different hiring methods, sophisticated tools and technology, and judgment have developed an interdependent relationship with each other.
C-Suite hiring is the most challenging and critical for any organization. Surveys suggest that when assessing individuals, 85% to 97% of professionals rely to some degree on intuition or a mental synthesis of information. Human judgment is ineluctable in assessments. Tools provide data that needs to be analyzed and interpreted. It is the human judgment that decides what inferences to be drawn, what interpretation to be made and how to use them. Over-reliance on data can result in unexpected undesirable outcomes. Particularly in situations where social interaction of C -Suite executives is considered pivotal, the decision based on personal observations of candidates in a variety of social settings may reduce the chances of hiring a candidate with poor social skills.