Hiring with Predictive Analysis: Using Data to Target Perfect Candidates

By Mike Alaimo

TeroVesalainen / Pixabay

What if you could predict the job performance and longevity of your next tech hire? The signs are there if you know what to look for. Enough data exists in your organization and through public and private resources to transform your candidate searches from gut reactions to repeatable formulas.

At best, only 15% of hiring managers prioritize hiring with predictive analytics in their recruitment strategies. That short-term approach prevents them from gaining a renewable search criterion that improves overall employee performance and cuts down attrition levels. Fortunately, there are a number of solutions to improve the regularity of high quality hires across positions.

Eliminating Useless Search Criteria

What does your perfect employee look like? The prototype probably already exists in your organization. Yet what limits candidate searches from getting dependable results is they’ve relied too heavily on intuition and assumptions. Accurate measures are muddied when placed alongside unproven bias. So, the whole process needs to start by separating what’s verifiable from what’s unsubstantiated by the facts.

What technical skills and interpersonal competencies matter? Test everything. Google applied their passion for data to their People Analytics division (formerly HR) and examined which assumptions held up. In the process, they found that their beloved brainteasers did little to identify exceptional future Googlers. So, they accepted the evidence and cut those questions from their interviews.

Assessments need to be reevaluated regularly. Unreliable data sets can be just as bad as no data at all. Consider employee engagement assessments. Personal benchmarks and perspectives vary between employees, making it difficult to compare responses without a healthy margin for error. Tracing backward from satisfaction to the goals and personality that make employees happy in your company assumes consistent responses. Even then, anonymous surveys still tend to lean toward more positive comments (to protect candidates if their identities are found out).

Leveraging Data-Driven Resources

Certain tests clearly are not a good gauge of a candidate’s future performance, but there are tests that help to distill candidate performance into the right search criteria. Data-driven platforms and services are providing better results for predictive analysis.

Want to use your top performer as a measuring point? Companies like Pairin evaluate their employees’ soft skills and mentality, which among other things can be used to predict which candidates will be a strong fit. Part of their goal is to make hiring easier by identifying what is important in a specific job role and the overall organization. With claims that they can increase employee retention by 67%, their behavioral tests and data analysis has a strong potential to improve your workforce.

Trusting the Right Recruiting Metrics

Hiring with predictive analytics requires a look at recruiting metrics just as much as performance metrics. Does any recruiting data indicate where to find exceptional future employees? Is there a candidate goldmine out there? Are you even targeting perfect candidates in the right way? Combining your findings and those of your IT staffing firm (we’re meticulous about data gathering) creates a better understanding of the answer.

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Source:: Business 2 Community

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