This is how not to act on data in order to objectify your scaleup’s hiring practices

This is how not to act on data in order to objectify your scaleup’s hiring practices

Building a scaleup team that’s capable of actually scaling your company is tough enough, let alone building a diverse team to do so. Cause let’s be honest, ensuring a certain level of demographic and neurodiversity in your team is still the largest challenge for every recruiter, hiring manager, and founding/management team. 

Ironically enough, diversifying your team is not only the largest challenge but also serves an enormous commercial imperative – as diverse teams have proven to be more successful. In fact, diverse scaleup teams generate 19% more revenue than non-diverse scaleup teams.

Most discussions about building diverse teams go hand in hand with the questions: ‘’How to objectify our hiring practices?’’ Because after all, a lack of diversity is in most cases the consequence of subjective (read: biased) hiring decisions. And finally, objectifying goes hand in hand with data. If you do it the right way. 

Data as a means to objectify hiring

When talking about objective hiring, what we are actually talking about is eliminating our initial bias and adjusting our frame of reference when reviewing candidates – because our own biased views on candidates are by definition subjective rather than objective. 

Data therefore has the potential of being the perfect solution here. Collecting for instance ten additional data points for all candidates not only provides you with a more detailed overview of your candidates, but moreover enables you to review your candidates based on equal information. 

A great example of data in hiring is the use of (the right!) assessments. Assessments are a way to learn more about your candidates’ soft skills, personalities or cognitive abilities. Our product, Equalture, has for instance integrated gamified assessments. 

Why we chose gamified assessments rather than traditional assessments in order to ensure unbiased insights.

How using data the wrong way can stimulate hiring bias even more

Let’s, for now, stick to the assessment example, since I think that this is the most tangible example of using data in your hiring process. 

Like I mentioned in the introduction of this blog, objectifying hiring goes hand in hand with data usage. If you do it the right way. And unfortunately, most companies don’t. Here’s why many companies don’t use data the right way, leading to even more bias and less diversity. 

What to look for vs. who fits best

When having the ambition to hire a new team member, you always have two important decisions to make – and one that’s slightly less important. These are the questions, where the first one is the least important one:

  • What will be the job title;
  • What are the criteria that we are going to look for; 
  • Who fits our criteria best. 

The first and last decisions are the ones that everyone is making – the middle one, however, is actually the most important one (since it heavily impacts your third decision), but also the one that most companies forget about. What to actually look for in a next hire. 

And if you skip this decisive moment in your hiring process, data will become a danger rather than a helping hand. Here’s why.

Imagine you’re looking for a new team member in your Sales Team. Since you’re a B2B SaaS company, you will likely choose between Sales Executive, Sales Development Representative, or Business Developer. 

If you also use an assessment, your assessment tool will likely choose a set of assessments and the most suitable outcome based on your job title – because most assessment tools standardise their assessment library on job titles. 

So here you are, using data to assess whether your candidates fit the needs for the job. The only problem here: these needs are likely based on a database, while the circumstances in your team aren’t taken into consideration. As a result of that, you will look for the exact same person when opening the same vacancy again. Bye diversity. 

Finding out what it actually is that you should be looking for in the next hire should be as much of an assessment as your candidate evaluation. It’s not a data set you can just pick from a library, because this library doesn’t take into consideration your company culture or current team composition. And it certainly won’t provide you with other recommendations when you are looking for another team member on that same function. 

If you want data to actually objectify your hiring practices, you should leverage it to not only review your candidates, but also your hiring needs.

How Equalture collects unbiased insights in both your team and your candidates

Visualised overview of one of the Equalture test results, portraying the game score that relates to teh traits of stress-resistance and self-prioritising. It shows a score of 85% benchmarked against a 53% for the average applicants and a 66% industry benchmark score.

Our software helps scaling companies objectify their hiring practices to build the best possible team. And this won’t be a surprise: we do so by enabling those companies to act data rather than gut feeling. 

How that works is that we help companies collect unbiased insights in both their teams and their candidates:

  • Team insights: We assess your current team in order to reveal its strengths, weaknesses and cultural traits. These insights, together with our Industry Benchmark (which provides us with industry-wide insights into certain job groups), accurately determine what you should be looking for in a next hire. 
  • Candidate insights: Consequently, we use the same assessment (our neuroscience games) for your candidates to be able to calculate who fits your hiring needs best.

And by doing it this way, we make sure that they act on data throughout the entire hiring process, not only the final step – resulting in much better hiring decisions. 

Cheers, Charlotte

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