What are factors and why do they matter?
When you go in for your annual physical and your doctor, as part of evaluating your overall health, wants to measure how much you weigh, are they more likely to get an accurate read by asking you directly, or by having you step on a scale? In most, if not all cases, the greatest precision would be achieved by placing someone on a scale. Many are either not comfortable revealing their weight, or they weighed themselves last week but can’t say for sure what today’s exact weight is. pymetrics functions similarly by giving recruiters a unique and comprehensive window into a person’s cognitive, social, and emotional attributes through behavioral measurement of nine broad factors: attention, decision-making, effort, emotion, fairness, focus, generosity, learning, and risk tolerance.
Relying on a resume to evaluate how attentive, fair, focused, or adventurous someone truly is will inevitably allow for self-presentation bias to creep into the evaluation process, and enables recruiters to make false assumptions about what is important for success in the role. For similar reasons that someone may not share accurate weight information, candidates want to show themselves in the most favorable or authentic light-- and who can blame them?
Moreover, for similar reasons that weight information may not be useful to evaluate specific health issues, employers want to index on what specific attributes to look at when making hiring decisions. It’s about being a good match, which requires comprehensive understanding of your candidates’ behavioral tendencies in addition to your current incumbents’ equally well, and matching them accordingly. As such, not only does pymetrics believe in and design our tools with objective measurement in mind, but in line with our vision of identifying the perfect job for everyone, our nine behavioral factors were developed to be bi-directional - measures where one can score on a spectrum with neither side assumed to be inherently “good” or “bad”.
How do we look at Factors?
pymetrics uses the same 12 exercises (also referred to as assessments or games) for both employees and candidates that gather behavioral measurements that feed into the nine cognitive, emotional, and social constructs we call factors. For example, during the game “Stop,” red and green circles are flashed and the player is asked to press the spacebar only when the red circle appears as quickly and accurately as possible. Those who are quick to hit the spacebar, even when a green circle appears, might fall on the more instinctive side of the decision-making factor spectrum, whereas those who hit the spacebar more slowly but accurately may fall on the more deliberative side of the spectrum. The aggregation of such behavioral patterns collected over the course of gameplay then informs the proprietary models we build of a company’s successful incumbents in a particular role. Such models are then used to evaluate fit-to-role based on the match between applicants’ behavioral attributes measured via gameplay and the behavioral success profile modeled from that of successful incumbents. All candidates and incumbents who play through the pymetrics exercises receive a multi-page, personalized profile report that summarizes what we learned about their attributes through our games with understandable, workplace-relevant, and actionable takeaways.
What do Factors measure?
Attention is conceptualized as an individual’s approach to managing incoming information and distractions. Individuals can range from being very methodical to very biased towards action. More methodical individuals tend to be thorough and restrained, preferring accuracy over speed in order to avoid mistakes. More action- focused individuals tend to be quick to react, not easily flustered by mistakes, and open to information outside of the focal task.
Decision making focuses on an individual’s approach to making decisions in terms of how much time and/or planning is involved. Individuals can range from being very deliberative to very instinctive. Individuals who are more deliberative tend to be thoughtful planners who reflect before reacting or making decisions. Individuals who are more instinctive tend to trust their intuition more and thus, can act more quickly and decisively.
Effort is measured in terms of how much effort an individual invests, based on the size of reward and probability of success. Individuals can range from being very hard-working to very outcome-driven. Hard-working individuals tend to work hard on all tasks, regardless of the reward. Outcome-driven individuals work more selectively, focusing their efforts on more high-reward tasks.
Fairness focuses on individuals’ perceptions of fairness in social situations. Individuals can range from being very accepting to very critical. More accepting individuals tend to be quick in judging most situations as fair, whereas more critical individuals tend to take their time when judging the fairness of social situations.
Focus is conceptualized as individuals’ concentration styles for one or more tasks. Individuals can range from being very focused to very adept at multitasking. More focused individuals are very effective at attending to a single task, even in the presence of distracting information. These individuals also tend to be focused and consistent in their work, with above-average memory. Individuals who tend to be stronger with multi- tasking are quick thinkers with shorter attention spans. They tend to be better at handling challenges in multiple tasks and adapting to dynamic circumstances with fast responses.
Generosity is measured in terms of individuals’ tendencies to prioritize the needs of others above their own in resource allocation and transactions. Individuals can range from very sharing to very frugal. More sharing individuals tend to trust the good intentions of others and balance their personal desires with others’ needs. More frugal or conservative individuals tend to invest their resources more cautiously, focusing on achieving their personal goals and being self-sufficient.
Learning focuses on individuals’ tendencies to change behavior based on new information. Individuals can range from being very adaptive to very consistent. Individuals who are more adaptive tend to recognize patterns in the environment, learn quickly from mistakes and can modify their behavior on immediate feedback. Individuals who are more consistent tend to take time to deliberate before changing their approach to a problem and they are not deterred by mistakes.
Risk tolerance is conceptualized as individuals’ comfort with risk-taking. Individuals can range from being very adventurous to very cautions. More adventurous individuals tend to respond quickly with less concern about negative outcomes whereas more cautious individuals tend to carefully test options and choose safer alternatives in order to avoid negative outcomes.
In addition to enabling fairer, more predictive talent selection, leveraging factor data can also enable you to uncover groundbreaking Workforce Insights. Workforce Insights answers key talent management questions and gives organizations insights to future-proof their workforce. It enables clients to:
- Understand their workforce DNA: explore inherent soft skills of their workforce, broken down by roles, regions, and tenures, to highlight where teams are different and similar.
- Benchmark teams: see how their employees compare to other top performers in the same role across other industries and verticals.
- Bring competencies to life: Break down each role and explore its alignment to company competencies and competencies of the future, like digital literacy, grit, etc.
- Optimize teamwork: Gain an understanding of how teams are similar and different, what this means for how teams work together, and implement strategies to improve collaboration using pymetrics frameworks.
If you would like to learn more about how to leverage pymetrics’ factor data for talent selection, workforce insights, and more, feel free to reach out to us here!