New talent development approaches are driving the thinking around hiring vs. retraining to respond to rapidly evolving technology, a global skills shortage, and the cost of continuously hiring new talent. As employers grapple with their talent demands, a conversation around reskilling must occur among managers, corporate leaders, HR, and chief learning officers (CLOs).
Recruiting practices over the last few decades have typically been driven by a decision to hire new talent instead of retraining existing talent. This “buy vs. build” approach rests on the premise that hiring people who already have the right skills and can be productive from day one is easier and/or quicker than the “unknown” of how long it would take to retrain existing employees and get them up to speed—or whether they would even be capable of making the change.
Whether the logic underpinning this choice was ever true is debatable, but there’s no question that today’s economy calls for a re-evaluation. The “buy vs. build” approach might best be described by what Daniel Kahneman describes in bestselling book Thinking, Fast and Slow as System 1 thinking: fast, intuitive, and emotion-driven. System 1 lets us make decisions quickly, whereas System 2 is slower, more deliberate, and requires more effort.
Without the speed of System 1 thinking we would be unable to function effectively in many situations. But System 1 thinking can become dangerous when the environment changes and the System 1 shortcuts no longer apply.
“System 2” Thinking in Talent Management
Today, several factors are combining to create a reality in which managers must think more deliberately (i.e., adopt more System 2 thinking) about the talent question. First, it is very costly to lay off workers, and there are legal considerations that complicate matters. Second, technology evolves so quickly, there is a near-constant need to acquire new skills. Third, there is a significant shortage of skilled people, and it’s not likely to moderate any time soon. According to research from Korn Ferry, a leading talent and organizational consulting firm, the global talent deficit is projected to reach 85.2 million skilled workers, a number that exceeds the current total population of Germany. In developed economies, this shortage is expected to cost approximately $2 trillion in lost productivity and opportunity as early as 2020; by 2030, that loss is projected at $8.5 trillion.
It is no surprise that a recent survey of staffing and recruiting agencies found that nearly three-quarters of them ranked the skills shortage as a top challenge. The solution is to put more emphasis on reskilling and upskilling. The same thinking was evidenced in the Made for the Future report from HSBC, based on a survey of business decision-makers in 14 markets: more than 52% of companies surveyed will increase their spending on skills and training; of those companies, 64% will increase spending by 5% or more.
Reskilling Gains Ground
There have always been industries that favored reskilling of talent. When an airline brings a new aircraft into the fleet, for example, pilots get retrained, not laid off and replaced. Experienced pilots are very valuable and often act as mentors to the next generation.
Now reskilling is gaining ground across the business landscape. Amazon recently announced a $700 million “Upskilling 2025” program for one-third of its workforce. Its plan is to retrain 100,000 workers being impacted by technology, preparing them for positions that they otherwise would be ineligible for—even if those opportunities are outside the company.
General Electric has said it plans to retrain 150,000 employees to better equip them for digital transformation. Similarly, Siemens, Lockheed Martin, and AT&T are investing in their existing workforce as well as developing future talent. This shift is accelerating as new personalized approaches to education dramatically change the cost-benefit equation on reskilling, which helps produce a wider and deeper internal pool of candidates.
Learning Agility: A Key Ingredient
It stands to reason that employees who possess a robust set of capabilities and traits should be retrained. That is especially true with employees who possess learning agility. Learning agility speaks to an individual’s capacity to apply past experiences in taking on first-time experiences and new challenges. In fact, as retraining and reskilling increasingly become the norm, learning agility may become an even more important criteria in selecting talent.
This is not a new idea, but certainly one that is gaining popularity. Several years ago, my friend Mike Barger, then a vice president and CLO at JetBlue, emphasized that a fundamental tenet of the airline was to “recruit for attitude, and train for aptitude.” Today, as executive director of the Office of Strategy and Academic Innovation at the Steven M. Ross School of Business at the University of Michigan, Barger continues to emphasize the importance of learning agility to help people gain comfort around making decisions with imperfect data and some degree of uncertainty. As he has told business students, “Get to the problem. Get the data that you need. Don’t wait for the problem to come to you.”
The desire to learn and upgrade skills can be found at every level of an organization. Recent research by Professor Joseph Fuller of Harvard Business School found that many workers, including those at risk of losing their jobs to automation, are excited to discover how technology could make their jobs more interesting. When workers are motivated to upgrade their skills, this engagement can be leveraged to improve productivity. Using advanced technologies, training can reinforce that engagement.
Adaptive Learning for Workforce Development
As more organizations adopt the retraining mindset as part of their business models, it begs the question of how best to reskill employees efficiently and effectively. This speaks not only to job-specific technical skills, but also to those skills that are key to success in the 21st century workplace: creativity, collaboration, communication, and critical thinking. Such skills elevate the role of the human, particularly to take on more complex jobs as automation and robotics make continued in-roads, including to eliminate many jobs completely.
As we know from the research of Benjamin Bloom, personalized learning such as the classic tutor-and-student approach is highly effective, but tutoring is not a scalable solution. Computer-based adaptive learning, however, combines the latest in computer science with cognitive research to replicate the tutor experience and deliver personalized learning at scale across a population of learners.
With adaptive learning, worker retraining and reskilling becomes more efficient; as we have seen in many organizations, competency can be reached in half the time compared to traditional learning approaches. Most important for workers facing a significant job change, personalized learning improves median performance and reduces performance variation. In other words, everyone has a greater opportunity to become more proficient in a new role, increasing everyone’s chance of success with a much wider range of job opportunities.
In summary, we need to examine the received wisdom of buy vs. build and shift the emphasis from hiring new talent to more reskilling and retraining of existing workers. With new educational approaches such as adaptive learning, greater possibilities emerge for rethinking talent strategies.