How Data Analytics is a Key Element of the Modern Recruiting Process
Analytics and its role in the Recruitment Process
Big Data Analytics is used by many global companies to understand people’s behaviors; Amazon and Ebay are notable examples. Through web attitudes and habits, these e-commerce driven businesses are able to obtain information on what people search online. For example following a search for a product on Google, you might find the same product appearing magically on your Amazon homepage later. This is not magic however; it is personalized target marketing through Big Data Analytics.
So, can Recruitment agencies leverage Analytics to align talented candidates with suitable job opportunities?
Recruiters deal with vast amounts of personal data each day. The skills, experience and background of candidates is often difficult to analyze, separate and ultimately act upon. Analytics from LinkedIn uses algorithms and filters to classify candidates into groups based on their skillsets and job preferences. Recruiters must be able to quickly detect these skills and behaviors of candidates before their competitors.
Using more than analytics – The skills of the recruiter
At a conference, recently attended, a speaker described recruitment using the metaphor of fish and a pond. The fish (candidates) swim in the pond (a recruiter’s database). The problem is that outside there’s a lake where a wide variety of talented fish also swim.
The recruiter’s ability is assessed as he or she expands their network, bringing external fish from the lake into their pond. Gathering information about existing fish in their pond can allow them to target what fish they need to catch in the lake. This is where analytics can play a key part. Patterns can be found within skillsets, job titles and other clearly defined variables among existing fish. This information and data can then be utilized by searching for these terms on LinkedIn or other job boards. Useful data could also be the salary levels, locations or personal interests of candidates.
However, the skill of the recruiter goes deeper than this. For example, recruiters can gain referrals from existing fish in their pond to gain access to fish in the outside lakes. This involves maximizing existing data to reach more people and expand networks, using more than just analytics.
So, the goal that a good recruiter should have is: use the existing data to reach similar people. In this way, he or she can avoid wasting time and gain greater results more efficiently.
Data analytics could also be an effective way to initiate the first contact with a potential candidate. People look for a personalized experience: recruiters should use the data to woo their target candidates. We are not talking about stalking someone here, but rather showing that you know a bit about him or her, their interests, experiences and attitudes. This is a far more compelling way to get the candidate’s attention and consideration. This is what will make the difference between success and failure. Predictive analytics can be a powerful tool for this.
Recruiting is a business driven by human behaviors. Recruitment is about relationships. No amount of automation or data analytics could take away the need for human interaction in the recruitment process. But there is no doubt that it now plays a key part in enabling us to reach and connect with the right people for your business.