Predictive analysis – a friend to each Recruiter or Hiring Manager



If you are a Hiring Manager or a Recruiter, for you, a recruitment process is always in the pipeline. And recruiting means beautiful moments when you smile in front of a resume shouting out „Evrika!” or when you scream out with pain when you find no one. You rejoice after recruiting the best person who, after 3 months, tells you it is the job he wanted. Despair comes knocking when the recruitment deadline is overdue and you did not find a single candidate with all the skills required in your team after recruiters have already introduced you to 5 people. You ask yourself the question: Am I the problem? Are my requirements not on the market? But you quickly get over yourself and say: I won’t give up! And you start again, more determined than ever. Also see the recruiters’ determination, do not forget about that.

There are a few tools that can help us. If you shared a glass of wine with STATISTICS, no matter if that was in college, as a mandatory subject, or simply because you loved it, it comes to bring us some helpful tools.

There are 3 types of analyses through which STATISTICS becomes our friend:

  1. Descriptive analysis uses data processing to pinpoint an image of the past by addressing AAEAAQAAAAAAAAiFAAAAJDUyOWViNzVkLTg4ODYtNGFjZS05MmI1LTMxMTFlODExYjE1MQthe question: How did it happen?
  2. Predictive analysis uses statistical modelling to understand the future and answer the question: What might happen?
  3. Prescriptive analysis uses optimization algorithms and simulations to create scripts on possible outcomes and to address the question: What should we do?

We are all familiar with predictive analysis. It uses past data analysis to make predictions about future tendencies. It is used in many industries. For instance, Amazon uses predictive analysis for suggesting various other products which might be of interest for you thus encouraging your possible future purchases by comparing them with those of other similar buyers. The autocorrect feature that comes with our phones would be another example for the use of predictive analysis.

You have definitely used predictive analysis if you purchased something online or if you used music apps that make further recommendations based on your taste in music, which are based on songs you have previously listened to. In the same way, predictive analysis uses the data of your analyses in the stage of identifying candidates, hiring decisions, but also the numbers that show employee retention. It is clear: predictive analysis-based recruitment can increase the employee retention rate.

For a position requiring higher education the average number of analysed resumes is between 140 and 200. This is only the first stage, but 52% of recruiters consider identifying the candidates as the most important stage. Machine learning can help us make better and better decisions in such analyses and move forward to choosing candidates who offer us the added value we need in the organisation. It is clear, predictive analysis must have a good friend, artificial intelligence, which helps us in automating this process.


Prescriptive analysis, defined above, suggests decisions based on the results of predictive analysis. In other words, prescriptive analysis can guide you towards the hiring decision that is more likely to be successful. The same support you get regarding the decision to post announcements on certain channels by taking into consideration the past success of the resumes received through all the analysed channels. Once the applicants are in the pipeline, prescriptive analysis can identify those who are best suited to be included in the interview stage. It makes that ranking of resumes for you.

Of course these prescriptive analyses are also based on the scores given by recruiters. All these scores offer a good starting point for the predictive analysis of data. But, let us not forget, the hiring/rejecting decision is the recruiter’s or the manager’s. Artificial intelligence helps us, but does not replace us, we are lucky. In turn, we are more efficient and accurate in the decisions we make.predictive analytics

In the United States, 54% of organisations use predictive and prescriptive analyses in their decisions. Probably our turn will come as well, but we must know what to ask. Recruitment is only a part of what an organisation means. We are capable of identifying the sources and tools that can make our work more efficient, no matter the department we are working in.

Kind regards,




Vreau sa stiu mai multe despre recrutare

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