Recruitment strategy Find & Engage The art and science of successful recruitment
Finding the right candidates in 2017 is more and more a mix of human work and the power of digital technology and data science. To remain successful in recruitment, Hays developed a new recruitment strategy: Find & Engage. A recruitment model that brings the best of both aspects together.
Find & Engage identifies the right talents, makes and maintains contact with them, and enthuses them for a new job... even if the candidate is not yet actively looking for a new challenge.
Advertise & Apply – the traditional model of recruitment
The traditional model of recruitment, which we call Advertise & Apply, is a long-established process of employers or agencies advertising a vacancy, to which only those individuals actively interested in a new role would apply.
Due to the advances in technology, advertise & apply is no longer as relevant as it was once deemed to be.
Why we don't recommend advertise & apply
Eventhough this model remains prevalent across the industry today, we don't recommend advertise & apply. Why?
Firstly, this model results in huge volumes of applications, significantly decreasing the likelihood of finding the best candidate.
And secondly, it risks losing the established personal relationships between candidate and recruiter.
Find & Engage – the new recruitment strategy
We have developed a new and improved model, one which we call Find & Engage.
Thanks to new technologies, organisations can now use a personalized recruitment strategy on a scale that was previously impossible.
Recruitment nowadays means the smart use of large volumes of data, complex recruitment tools and advanced content platforms.
With the emergence of Find & Engage, we play more than ever a crucial part in your search for the perfect candidate. You are now able to go for the best talent in the market, rather than for a candidate who happens to be available and shows an active interest.
This approach puts the relationship back at the heart of recruitment, but uses digital technology, machine learning and data science to operate on a massive scale that has not previously been possible.
