How to hire without resumes (3-step-guide)
In this article I will explain:
- How to hire for potential instead of experience;
- The role of Predictive Analytics and Machine Learning in this process;
- The pros of gamification in recruitment.
Resumes are dead. Or it least that’s what’s going to happen. The war for talent is heavier than it has ever been before. The result: hiring policies should change radically. My advice: start hiring for potential.
Predictive analytics and Machine Learning
When willing to hire for potential, predictive analytics and Machine Learning are key. A short explanation of these concepts:
Predictive analytics means analyzing historical data to predict future outcomes. In other words: find a pattern in the past to predict the next step in the future.
Machine Learning algorithms can learn from data without relying on rules-based programming. In other words: letting an algorithm learn and improve itself based on collected data.
Why are these two concepts so important? Well, simply because the combination of these two concepts results in the possibility to hire for potential instead of just hiring for experience.
Hiring for potential: how it works
Hiring for potential is an HR-concept that is interpreted in several ways. This is my definition of hiring for potential:
Hiring for potential means gathering candidate information that predicts a candidate’s capabilities for the future instead of information that focusses on a candidate’s past. In other words: base your job successfulness prediction on ability to learn and personality instead of experience so far.
Now that you know more about my perception of hiring for potential, let’s figure out a step-by-step guide how to do so.
Step 1. Create assumptions.
Every analysis starts with creating assumptions. In other words: try to find out what’s likely to be true. This is the part where Predictive Analytics are key. By analyzing historical data, we can create a first prediction of future outcomes: an assumption.
An example: research into Business Developers (BD) has shown that 86% of all successful BDs has a high logical reasoning ability. Based on this analysis, we can assume that a high logical reasoning ability is required in order to be successful on this job.
Most of these assumptions will be based on particular professional skills, cognitive skills and personality traits.
Step 2. Find a way to assess the components of your assumptions.
As mentioned above, many assumptions in job successfulness are based on a candidate’s personality traits and cognitive traits. In practice you’ll often experience that personality traits predict company fit and cognitive traits predict job fit.
The most reliable and innovative method to analyze these traits is gamification — and that’s because of the following reasons:
- There’s no room for social desirability (in other words: you can’t manipulate the outcomes);
- Gamification stimulates a candidate’s subconscious behaviour. This behaviour is the type of behaviour that we’re not aware of — our daily habits, how we interact with others and how we’re experienced by others. This behaviour tells us everything we need to know about personality and cognitive traits.
Are you searching for ways to gamify your hiring process? Just request an Equalture demo.
Step 3. Create a feedback loop.
Finally, assumptions need to be constantly evaluated and adjusted. In other words: you need to create a feedback loop to see whether your assumptions have indeed provided you with the best candidate. This is the part where Machine Learning is key.
At Equalture, we’ve created a self-learning algorithm through Machine Learning. This algorithm continuously improves itself based on feedback from the system. Once a candidate is hired for a job, we ask the company to provide us with feedback so that we know whether a candidate is successful on the job. In other words: we compare our job successfulness prediction with the real successfulness rate.
Et voilà. By following these three steps, you should be able to hire a candidate without a resume. Two preconditions:
- You need a game provider;
- You need a tool that provides you with a self-learning matching algorithm — including assumptions.
If this is what you’re searching for, Equalture might be the perfect solution for you.