Published 06. Apr. 2017
Automatic Recruitment Edge with Predictive Analytics
Either "specialists" and "high potentials" are in shorter supply or the competition has gotten a lot better. Either way, recruitment is having a tougher time finding and keeping talents using the old HR ways. avantum consult AG says it's time to switch to predictive analytics.
Using checklists and interview guidelines are one of the most common ways of sifting through applicants. But for avantum consult AG, this method is not only time-consuming, it also requires the involvement of several HR representatives and specialists. And then in the end, they would still have missed the “lateral thinkers” or those with out-of-the-box approach to application. These days, it’s from this particular pool of talents that innovative and creative thinkers come from — which are what organizations that wish to stay relevant and ahead badly need.
What could HR do?
Invest in Predictive Analytics
avantum consult AG advocates for predictive analytics, as it can do so much more than just filter a specific type from a flood of applicants. It can also ensure that certain targets actually apply for the job — and they can all be done automatically. Here’s how:
- Selection – The application processes is simplified and optimized using state-of-the-art analysis systems that work with machine-learning techniques. These systems treat all applications uniformly, objectively, independently, and with great attention to detail.
- Classification and Segmentation – The algorithms analyze precisely whether the job profile and the available applicant information fit with one another and to what extent. It can even predict whether a qualified candidate will reach contract signing or not.
- Evaluation – Based on the information obtained, candidates are evaluated and compared. In order to determine a manageable number of suitable candidates, the characteristics of all applicants are compared against the relevant job profile.
Two Major Benefits
Objective Findings Over Arbitrary Selection – Needless to say, machine analysis and selection will never replace the actual job interview. But it can make the selection process a lot easier and more objective. It also guarantees a high fit among the selected candidates.
All in all, it means that more time can be used for the important recruitment process of getting to know the applicants in person. This gives a far greater likelihood of not only finding the best candidate from a technical perspective, but also one who will actually sign the contract and stay with the company for a long time.
Here, the more information collected beforehand, the better the algorithms can recognize patterns and provide suitable recommendations.
First in Finding Top Candidates – This can also be used for conducting a proactive search for interesting candidates on relevant online platforms such as LinkedIn or Xing. Thanks to free and accessible data online, finding candidates for managerial and IT specialists positions has never been easier.
Recruiters who use predictive systems today can make a play for “high potentials” as soon as their online activities increase, for example, or if they edit their online profiles. This way, they don’t have to wait for the prospects to make clear statements such as “I want to change jobs” or “I’m looking for a new challenge.”
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They will also be at the following events in Germany,
- IndustryForum Retail, 26th April 2017
- IndustryForum Insurance, 19th September 2017
- 600Minutes CFO, 14th November 2017
- Business Analytics, 27th September 2017