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Reimagining Talent Evaluation & Selection for the Future of Work – by Frida Polli, Ph.D

The nature of jobs, companies, workers, and society has transformed in innumerable ways over the past few decades. Four key considerations have emerged as critical for talent evaluation and selection in the new economy:

  1. Job fit: Modern employers view job fit as critical to reducing employee turnover, due to the increased competitiveness of labor markets.
  2. Soft skills: Today’s employers have fewer needs for skills like rote memorization or task repetition due to automation and the widespread adoption of computers, and instead emphasize soft skills.
  3. Fairness: Legal requirements force organizations to consider the fairness of their hiring strategies, and they are socially pressured to prioritize demographic diversity.
  4. Flexibility: As technology to both creates and eliminates new types of jobs, modern employers seek more flexible approaches to evaluating talent than their predecessors.

Entirely new areas of science dedicated to studying human brains, behaviors, and thought processes – fields like cognitive science, neuropsychology, cognitive psychology, and behavioral neuroscience – have emerged since employment selection first became a research discipline. These advancements enable the evaluation of job candidates to be individualized, nuanced, equitable, and dynamic, resulting in the efficiency of employers, the well-being of employees, and the cohesion of society.

Limitations of Traditional Approaches to Talent Evaluation & Selection
Traditional employment tools, which may include resume reviews, personality inventories, and intelligence tests (e.g., IQ, general mental ability [GMA], or cognitive assessments) have shortcomings that do not meet modern employers’ considerations for evaluating and selecting their workforce, as follows:

Job fit: People who are in roles that align with their personality, preferences, and skills are more satisfied – and more successful. Happy employees are more likely to demonstrate work ethic and remain with the organization, reducing costs due to turnover. Surveys also have shown that workers are often willing to take pay cuts to accept jobs that they believe better suit them. So, today’s employers have come to view matching people to their best-fit roles as a crucial part hiring.

Traditional hiring assessments assume employers simply had to identify the “best” candidates to perform the work productively. In this context, certain traits, like intelligence and conscientiousness, are deemed universally preferable and assumed to drive job performance across all contexts. Today, the idea that human potential should be evaluated with a multi-faceted approach is captured by the concept of neurodiversity, or the idea that variations in mental functions – like sociability, learning, attention, and mood – are adaptive and non-pathological.

Soft Skills: Inherent cognitive and non-cognitive characteristics that are not exclusively tied to a particular context are considered soft skills. Competencies like communication, teamwork, and people skills are generally accepted as crucial for a successful workforce. Such competencies are growing in importance: between 1980 and 2012, “social-skill intensive” occupations grew by nearly 12 percentage points as a share of all U.S. jobs and wages grew more rapidly for these occupations than any others over the same period.

Soft skills are closely related to the idea of job fit – people with a certain personality type or cognitive style will naturally flourish in certain environments more than others. These underlying traits are largely not accounted for in traditional hiring assessments that seek to place all job candidates on a single spectrum of employability, like GMA or IQ tests, where a higher score is almost always deemed preferable than a lower score.

Fairness: Fairness in modern hiring comprises the legal requirement to not discriminate against job candidates and the societal desire to promote diversity in the workforce. Researchers have demonstrated that diversity and inclusion in the workplace can drive business outcomes like revenue, innovation, and profit. However, as GMA tests grew in popularity, so too did evidence indicating that scores were strongly correlated with demographic features, like educational attainment and socioeconomic status. According to one estimate, a GMA test that selects 50% of white candidates will only select 16% of black candidates from the same applicant pool.

Formal assessments are not the only part that yields discrimination against demographic groups: With the average resume review lasting only 7 seconds, human recruiters rely heavily on intuition, including personal prejudices and social stereotypes, to make rapid judgments about candidates.

Flexibility: Flexibility is how a workforce adapts to changing dynamics in the environment and organizes their talent to meet new business needs. Historically, the public sector would reskill displaced workers with the skills for a generic “modern” employer, and declare success if trainees found a job after and made equivalent wages to their previous role. The traditional approach to workforce flexibility is ineffective because the strategy ignores the uniqueness of each worker and the specific needs of employers. The World Economic Forum estimates that 65% of today’s preschoolers will eventually be working in roles that do not currently exist, so modern employers need tools that can help them craft their workforce in the face of ambiguity.

Reimagining Talent Evaluation & Selection
Rethinking how we evaluate and select talent for the workforce of the future is based on better understanding and measuring behaviors and thought processes that align people to opportunities that suit them well. Much of this is drawn from practical applications of cognitive science, neuropsychology, and neuroscience. The objective is not only to increase the efficiency and productivity of organizations, but also to disrupt patterns of bias and discrimination in the allocation of job opportunities.

The approach assumes that individuals vary on a spectrum, and their cognitive, social, and emotional traits can be measured by their parts or in their synergy. It then supports the four critical needs of modern employers in the following ways:

Link to Soft Skills: Using technology, researchers have amassed large data sets on people as they complete real-world tasks that helps understand the cognitive and personality spectrums of humanity. By comparison, self-report surveys limit the ability to accurately assess a candidate’s innate aptitudes and overall fit for a particular job because of biases that emerge in a high-stakes process like a job application. For example, humans tend to present themselves in a positive manner to others, but this tendency is mitigated in contexts where the respondent cannot tell what a test is meant to measure.

Link to Job Fit: Decades of cognitive science research have produced tasks to measure cognitive, social, and emotional attributes ranging from planning ability , to motivation for rewards. This range of validated tools that codify job-relevant traits are now deployable in the context of employment selection.

Link to Fairness: Certain demographic groups perform systematically worse on traditional GMAs, in part because a person’s educational background can significantly affect scores. Behavioral assessments avoid such problems by measuring traits in a manner that does not require reference to a particular context, like educational or cultural knowledge.

Link to Flexibility: With behavioral assessments, workers can be evaluated in terms of their innate aptitudes, providing the opportunity to optimize the alignment of trainees to reskilling initiatives. Additionally, as new types of jobs emerge, behavioral assessments allow for a more granular evaluation of the cognitive, social, and emotional traits that may position a person to perform well in the role.

 

Conclusion
Given the disruption due to COVID-19, companies are in a unique position to radically rethink nearly every aspect of their business and talent evaluation & selection is no exception. But yesterday’s approaches are no longer effective in building the workforce of the future; fortunately, behavioral assessments provide a ready option to help evaluate job candidates in an individualized, nuanced, equitable, and dynamic way, while delivering efficiency, fairness, and diversity to employers.

About the Author

Frida Polli Ph.D is an award-winning Harvard and MIT trained neuroscientist turned AI-startup CEO. She is the founder and CEO of pymetrics, a talent matching platform that uses behavioral science and AI to help companies match external and internal talent with their ideal jobs predictively and fairly. While an academic, Frida was an NIH fellow, a NARSAD Young Investigator, an MIT 100K winner, and a Life Science Fellow at Harvard Business School (where she earned an MBA). She has been featured on CNN, the Wall Street Journal, the New York Times, Fast Company, and Inc.

About pymetrics
pymetrics is a talent matching platform that makes workforce decisions more efficient, accurate, and fair. We use behavioral science-backed games to measure the cognitive, social, and emotional attributes of individuals and a data-driven approach to match them with the right opportunity – based on their potential, not their pedigree. Our ethical and audited AI-powered insights and recommendations equip employers with accurate and actionable information to manage the entire talent lifecycle, from hiring to internal mobility and beyond.

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