It's time to break the legacy cycle and get smarter about how candidates are recruited, onboarded and nurtured.
One of the most vital aspects of any company looking to win the war for talent is finding candidates who have the ability and drive to reinvent themselves.
Candidates who excel at unlearning and learning are always seeking out new learning challenges that fuel self-reinvention. They are willing to let go of old concepts and frameworks, replacing them with new and more relevant ones.
Unlearning and learning fuels career growth
Any professional over 30 needs to put a strong effort into excelling at these skills of unlearning and learning to succeed at reinventing themselves and staying marketable.
“Those who reinvent themselves have a higher probability of success.”
As one Chief Human Resource Officer (CHRO) from a leading Silicon Valley-based tech firm says: ”I see too many engineers who stop learning at 30, reducing their marketability by not keeping their technical skills current.”
The CHRO went on to say that those who have the unique ability to unlearn and learn new knowledge have an inside edge at reinventing themselves and being a good fit for new positions. Employees who embrace these traits have a much higher probability of being picked for internal mobility, assigned to strategic projects and earmarked as future leaders in their current company.
She and other CHROs say that the need for quality talent is so great that those who excel at unlearning, learning and reinventing themselves are more likely to overcome common biases, including race, gender, age and academic background.
Finding employees and candidates who have the ability and initiative to constantly reinvent themselves is the goal of every company today, though it isn’t easy.
The role of machine learning
Talent management is at an inflection point, specifically in recruiting and internal mobility. Machine learning and artificial intelligence (AI)-based applications capable of pinpointing exactly the right candidate for each open position based on their abilities, not just skills on their resume, is gaining momentum.
“Talent management is at an inflection point, specifically in recruiting and internal mobility.”
Manual approaches to recruiting such as looking through thousands of resumes or using legacy technologies like Applicant Tracking Systems (ATS) introduce conscious and unconscious biases into hiring decisions.
Many companies have separate organizations that cater to recruiting and career needs of internal employees – inevitably ending up with little synergies, wasting money on hiring and retaining employees and not learning from each other.
It’s time to break the legacy cycle and get smarter about how candidates are recruited, onboarded and nurtured. Defining the attributes, experience, innate skills and strengths of ideal candidates crystallizes the most qualified candidates for recruiters and hiring managers.
The bottom line
Machine learning is redefining every aspect of talent management. In recruiting, machine learning is bringing greater personalization at scale by finding those applicants who most resemble known high achievers that excel at reinventing themselves and make great contributions to the future growth of companies hiring them.
This article originally appeared on the U.S. Chamber of Commerce Foundation blog and was republished with permission.
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