Hiring and retaining top talent keeps getting harder. Bad hires, however, are easy to make and they impact businesses at many levels, from productivity decrease to reputation damage and high turnover rates, companies have a lot more to lose besides money.
Also very often, hiring managers end up looking bad in the picture due to the impact bad hires have on the organisation. As such, it is crucial to stop using traditional, gut feeling-based recruiting and selection methods which leave hiring decisions up to chance.
When it comes to getting the right talent in the right roles, traditional hiring methods are not good enough, anymore. Hiring managers and recruiters need to push further, and using a data-driven hiring strategy can definitely improve decision making and help onboard the best talent in a faster and more efficient way.
As bringing in a new hire is always a risk, any tool that helps identify a better hiring decision is essential, and predictive hiring technology offers the best approach to improve and boost talent acquisition.
Predictive hiring is a recruiting technology that uses data and analytics to improve recruitment outcomes by recommending best-fit candidates to recruiters and hiring managers.
While traditional hiring practices are often based on brief resume screenings and the recruiter's gut-feeling during interviews, predictive analytics for hiring leverages historical data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future. Meaning, allowing to make predictions about candidates and improve the talent acquisition process through data-driven decision making.
It is common knowledge that screening resumes fast and efficiently is especially hard for recruiters. Recruiters often manage more than one job opening at a time and job application statistics indicate that around 250 candidates apply when a position opens up in a large corporation.
Unfortunately, most candidates don’t meet the basic job requirements, which goes to show the smashing amount of time recruiters waste manually sifting through unfitted CVs. This is precisely one of the aspects that predictive analytics can improve making the hiring process more efficient.
However, there are other key benefits of using predictive hiring in your talent acquisition:
Talent acquisition is extremely important for any organisation, as finding and hiring the right people is essential for business success. Without skilled, experienced and motivated employees, any business is likely to struggle and lose its competitive advantage.
Incorporating predictive hiring in your talent acquisition strategy is key to help you build amazing teams that move your company forward.
Here are some of the challenges that predictive hiring can help you with:
A predictive hiring process incorporates the factors that are the most predictive of job outcomes. We can call it evidence-based hiring given that it uses the evidence compiled from extensive research in industrial organisational psychology as a basis to determine scientifically which factors are more likely to predict job performance than others.
By building a hiring process that incorporates more predictive factors and weights them more heavily, organisations can improve their hiring outcomes. Over time, this should improve the entire makeup of the company. For this reason, evidence-based hiring has solidified itself as a best-in-class practice for Fortune 500s and beyond.
Yet, when it comes to recruitment, past work experience keeps being the most used criteria to assess whether a candidate is suitable or not for a position. Recruiters usually look for candidates with some degree of experience in regard to the number of years in the workplace, the role seniority, the type of companies they worked for and the schools they attended.
However, job experience has been deemed a poor predictor of future performance. According to research, years of experience can only predict 3% of the differences in performance between the best and worst hires.
Predictive Assessments
A study from 2016 by Frank L. Schmidt, which explores practical and theoretical implications of 100 years of research findings regarding selection methods in personnel psychology, found that job experience alone only allows to predict job performance with 16% accuracy, whereas the combination of cognitive ability with personality allows 78% accuracy in future performance prediction. Meaning, there are other criteria which can better determine a candidate’s ability to successfully perform in a role.
What this research by Schmidt shows clearly is that experience alone is not a strong performance predictor, however, if combined with cognitive ability and personality traits assessments, then it can portrait a candidate’s job knowledge and help predict future job success with more accuracy.
Hence, there are stronger performance predictors that recruiters should focus on:
Reasoning ability - the general intelligence factor is the variable that best explains and illustrates a collaborator’s performance at work, especially in roles with highly complex tasks, allowing recruiters to learn how candidates think and make decisions.
Personality - personality questionnaires based on the scientifically proven "Big Five" theoretical model, for instance, provide insightful information about the candidates’ personality and about how it will impact their workplace behaviour allowing recruiters to understand how candidates relate to others, how they approach and solve problems and how they manage their emotions.
Motivation - a motivation assessment helps recruiters identify the things that motivate candidates on a daily basis, evaluating the candidates’ fit with activities, leadership styles and workplace culture. It allows recruiters to understand the types of activities and contexts that make candidates want to invest themselves in their work.
Given the weak correlation between previous work experience and future job performance, hiring managers should recognise and harness the power of data in the selection process through a predictive hiring approach. Predictive hiring uses data and analytics to make better informed hiring decisions instead of relying on intuition or gut feeling which most often ends up leading to a poorly skilled and not so diverse workforce.
An important aspect of this approach is candidate assessment. Using the right type of pre-employment assessments is crucial to accurately screen candidates and identify the right person for the job. Like research has shown, past experience is less relevant when it comes to predicting future job performance. On the contrary, soft skills and personality are what makes people thrive in a role.
Previous experience alone won’t tell hiring managers how well a candidate will perform on the job; how the candidate will behave in the workplace; or what drives the candidate? Hence, assessing your candidates’ personality, motivation and cognitive ability is essential to determine whether they’ll succeed and thrive in a position and find the right person for the job.
Read the full ebook to know more and to discover how you can succeed in predictive hiring.
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