As a recruiter, you dread this situation: After the first month on the job, the new hire turns out not to be the strong candidate they exhibited in the talent acquisition process. You hope that, perhaps, they only need additional time to adjust. Still, when the hiring manager tells you that the new hire doesn’t seem competent for the role, your stomach drops.
Indeed, something went wrong. Like with other positions you recruit for, you work with the information the hiring manager gives you – what are the required skills and experience, what is the budget, where the person will work, and to whom they will report. You depend on what the hiring manager tells you and prepare a job posting from this input. When it comes to data analytics roles, however, without having a background in the field itself, it is a challenge for most recruiters and HR departments to discover why the people you hire turn out not to be strong in the competencies required for the job.
In the data specialist space, two types of bad hires sneak through. First, some hires end up not having the skills they claimed to have during the hiring process.
And second, there are the new hires who were hired based on a poor job description, which originated with the information provided by the hiring manager.
Addressing these two concerns can help you improve recruiting for and, more importantly, hiring for competence.
Resume inflation is enemy number one. “Outright lying…is only 15 percent to 25 percent, but exaggerating skills or making job titles sound more appealing…happens 50 percent to 60 percent of the time,” says former human resources director Amy White. With so many people misrepresenting their abilities, it is no wonder that you, as a recruiter, get caught in the middle. The data sciences have so many programs, languages, and business applications, it would be impossible for someone not working in the field daily to keep up, let alone be able to evaluate in an interview the level of competency.
This is aggravated by hiring managers who, themselves, probably are not experts in the various software and tools themselves. They may know the outcomes required, but not necessarily the subtleties within the rapidly evolving field of data analytics. As a result, they may not appreciate the crossover of skills they may be requesting. For example, a data wrangler and a data visualization person will likely not be the same professional…yet both (and more) sets of skills are listed as required.
What can you do?
With the pressure on, you need to make sure you recruit competent data specialists. By partnering with a company that pre-screens candidates for you, you can match proficient applicants with your company’s needs. Also, you will save time assessing the criteria of capable analysts.
This will shorten your hiring lead time and impress hiring managers with an improved level of competency of future candidates brought in for interviews. It will help you avoid wasting time interviewing people who don’t actually have the skills, as well as broaden your pool of applicants, being provided recommendations of candidates with transferable skills or requiring minimal upskilling.
Chisel Analytics can help you improve your recruiting for competence. Chisel vets top talent with our proprietary skill assessments across 6 key elements to ensure you hire the most qualified analyst for your critical needs – from project-based needs to full-time roles. We ensure that the addition is seamless, giving your company the competency and reliability you need from your workforce.
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