Even as algorithms continue to beat human judgment when it comes to hiring, people still prefer to rely on their gut feelings instead of going with algorithms. It is this aversion that is holding humans back from using analytics for informed decision making. Analytics provide solid insights into HR operations but they are still highly undervalued when it comes to taking data-driven hiring decisions. Despite being aware of the tremendous power of predictive algorithms for driving recruitment efficiency and reducing the attrition rate, people still suffer from what the researchers call, “algorithm aversion” and this can have very real costs in a wide range of contexts.
This means that trusting the gut can result in extra work and increased cost which no company wants. Hiring is an important decision that takes time, effort and also involves cost. So should recruiters base their decisions on their gut feeling or simply follow their intuition? While trusting your gut may work often, it can also lead you astray from the bigger picture. There are so many variables that recruiters need to consider in the hiring process beyond their instincts. Is a prospective candidate a culture fit? Does he/she have the required qualifications? Will he be able to perform? And the questions can go on.
It is not advisable to go with your gut instincts when it comes to hiring because it needs an objective point of view that takes into account:
However, there are exceptions to the rule and one example of this is when your inner voice is practically screaming, “This person is not right” because listening carefully to this warning can pay off. Another good example is when a recruiter is required to fill a single vacancy and has two equally amazing candidates vying for it. In this scenario, you can trust your gut on the final decision but at the end of the day, analytics will always make the smarter choice so try and avoid trusting your instincts. This is because the associated costs of conducting interviews, traveling, hotel stays, meals, relocation costs, onboarding, orientation, training, termination and repeating the entire cycle for every bad hire are hard to quantify.
Algorithms make better assessments in various contexts because they occasionally make a mistake and completely eliminate the human bias. Algorithms employ a strictly scientific approach that is based on evidence and previous trends to produce better hiring results. For consistent hiring success, recruiters can leverage the accuracy of algorithms to narrow the talent pool and then tap human judgment to weigh in on the final decision. This approach is quick, easy, intuitive, and uses data to identify candidates who are most likely to stay and be more productive. It offers more reliable and balanced assessments than gray matter can when it comes to finding the right fit while ensuring diversity. When you are hiring for a lot of positions over a relatively shorter timeframe, it is important to have the science behind algorithms while you continue to use your human element.
The current talent acquisition practices are neither adequate nor accurate and also biased and this explains why the man-machine collaboration is slowly gaining ground. Artificial intelligence is now enabling the new breed of HR to create a richer talent pool. AI brings an integrated approach to recruitment by automating the repetitive steps of the recruitment process and accelerating the screening process with smart filter intelligence. With the entry of AI into HR, recruiters are now leveraging the insights of accurate reports for performance and process optimization. With accurate reports that track every activity from sourcing to onboarding, recruiters can easily avoid the implications of wrong hiring decisions and add to the bottom-line of the business.