Today’s Talent Management: Unlearn, Learn, and Re-Invent Yourself
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.
The Path Of 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.
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.” She continued, “Anytime someone does not take responsibility for reinventing themselves, by the time they’re 50 they’re unemployable.”
The CHRO went on to say that finding and nurturing 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.
“We’re after those that can unlearn, learn, and define their learning roadmaps that lead to reinventing their skills, strengths, and marketability.”
She and other CHROs say that the need for quality talent is so great that those who excel at unlearning, learning, and reinventing themselves have a higher probability of success for overcoming 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.
How Machine Learning Helps Find Learning Employees
Talent management is at an inflection point, specifically in the area of 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.
Manual approaches to recruiting including looking through thousands of resumes or using legacy technologies including Applicant Tracking Systems (ATS) introduce conscious and unconscious biases into hiring decisions. It’s no wonder even with ATS systems only 30% of new hires are successful.
Most 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, recruiters and hiring managers can have an application provide a list of the most qualified candidates.
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 who excel at reinventing themselves and can make great contributions to the future growth of companies who hire them.