Better than Vague: Why Data is a Better Hiring Tool than Psychometric Testing

Suppose you’re responsible for hiring at your company, a fast-growing organisation that is causing ripples across the industry, but is not known for making waves yet: if you’re a Tier II company, or a fast-growth start-up, you need to hire the very best talent out there, right?

Wrong.

Hunting for the ‘best talent out there’ doesn’t really help your firm. What you should be looking for is the best talent for your organisation, your situation, and your business aspirations.

So how does one achieve this?

The first step is to stop relying solely on psychometric testing and look at the data instead. Here’s how:

Suppose you’re hunting for talent – before you begin chasing the hottest leads in the market, spend some time identifying the superstars and rock stars you already have – who are the existing members of your company that have out-performed the pack, and who have leadership potential? Who do you think will lead the charge in the next phase of the company’s growth, and who has been tapped by management as being on a promotion track?

There are over 150 data points that one can track in relation to each individual, and once you’ve managed to harness these and subject them to rigorous analysis, you will be able to derive a fairly explicit pattern that shows you exactly the sort of person who will thrive in your organisation – and who will help your organisation thrive.

But why is this a better approach? Psychometric testing relies on the method of creating an assessment pattern that can help you identify a person who fits a particular model – one that is pre-defined, along terms as vague as ‘company culture’. But who defines this ‘culture’? Probably only one or two members of senior management, who, inevitably, will let subjective biases creep into their definitions of ‘culture’. So while psychometric testing may well help you find people who fit your model, the idea of creating a model in such a subjective manner is, essentially, flawed. With data, you have a far more sharply defined set of criteria that has been objectively defined, and on which you can reliably depend when making hiring decisions.

Data-driven hiring decisions go even further – with the use of these approaches, you can determine not only who will be a better performer in your organisation, you may also be able to determine who is more likely to stick around longer, thereby contributing to the continuing progress of whatever project or business objective they work on. Once again, this is possible if you are able to derive a set of criteria based on a deep analysis of the data you’ve gathered about the people in your organisation with the longest tenures. This way, you avoid wasting precious time and money hiring seemingly great talent that is just waiting around for a better opportunity, and will leave your organisation at the first available chance…

…and the applications you can extend from here are simply unlimited: for example, you could find out that someone who takes an off day every alternate Monday morning does so because they are likely to be appearing for job interviews then. This tells you to watch out for similar behaviour in other employees, and take pre-emptive steps that could help you retain your best talent.

Here at IDfy, we’re developing a suite of solutions that leverages the power of big data and analytics to achieve results and insights like the ones I’ve talked about in this post – and I’ve got to say: the results are exciting – and way more accurate than anything we’ve ever seen before!

 

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