Michael Priddis, CEO of Faethm, shares the opportunities for companies that adopt a data-enabled and human-first approach to workforce transformation, in response to automation, COVID and recession, to rapidly upskill and reskill their workforces to transition to the jobs of tomorrow.
After several years of diving deep into the future workforce needs of successful companies, Mike Priddis, CEO of Faethm, has come to a bold conclusion. He speaks to the LHH team about the new skills economy.
The “knowledge economy” is dead. Long live the “skills economy.”
“We are definitely seeing that the knowledge economy is becoming the skills economy,” said Priddis, whose company uses AI to predict the impact of forces such as automation, robotics, and the pandemic on current and future jobs.
“Today, knowledge and access to knowledge is easy. Google is on any device we’ve got. Applying that knowledge is different. We are entering a period where learning skills will be critical.”
Priddis said many business organizations are struggling to embrace this rapid transition from knowledge to skills-based economies. That is, he said, due in part to the fact that economic disruption from the COVID-19 pandemic has changed the pace and magnitude of all forms of transformation.
Priddis calls this “the slingshot to 2023” what once used to take years to design, plan and put into action must now be brought to fruition in a matter of months.
“Prior to January of this year, most organizations were preparing for a transformation of some sort. Now, the pace of transformation has accelerated at an alarming pace to ensure that companies survive. We call that the slingshot effect.”
Unfortunately, Priddis said, current approaches to education and workforce management do not match up well with the slingshot phenomenon. Most post-secondary institutions still focus heavily on traditional approaches to education, where knowledge is acquired over a period of years in an academic vacuum but never applied in the real world. Employers, meanwhile, remain wedded to buying talent or hiring people with new skills, rather than reskilling existing workers to meet new business demands.
“The best boss I ever had said ‘the half-life of learning is 30 minutes unless you get to apply it,’” Priddis said. “What that implies is that we need to have action-based learning, taking place in context. We need to be giving people not just the information but a chance for people to practice that skill.”
If you apply those principles in a real-world example—like a company forced to transform to address the impact of a global pandemic—the emphasis very quickly shifts to identifying those jobs that are vulnerable to automation, or cannot be performed effectively in a remote environment and those that have longer-term future viability.
Priddis said Faethm works with clients to analyze the impact of external trends on current workforces and the skills required to be future-ready. This analysis is predictive, he said, identifying portions of jobs that might be replaced by technology (automation), jobs that might evolve with technology (augmentation) and the new and emerging jobs that will need to be filled to support deployment of these technologies (addition).
“It’s cheaper to retrain and redeploy than to make redundant and rehire.”
This analysis should help companies to not only meet future skills needs but identify people within an existing workforce that can transition from vulnerable to emerging roles.
“Our biggest contribution has been to show companies that the people they are going to need in the future, they already have,” Priddis said. “It’s a pretty simple equation. It’s cheaper to retrain and redeploy than to make redundant and rehire.”
Even though almost everyone wants to take a “humanistic approach,” where the well-being of individual employees is not sacrificed to a bottom-line objective, not every organization can see the value in retraining and redeploying, Priddis said.
“We all want to do right by people,” Priddis said. “But most companies also know that it’s the lens of dollars and cents that drives decisions at the executive table. The problem is that if everybody sheds staff, they don’t need with no thought about what they’re going to do next, it creates chaos.”
Thankfully, Priddis said an increasing number of companies are starting to see that the humanistic approach may also be the most cost-effective approach.
From accountant to cyber security analyst
That was certainly the experience with one Faethm client who was facing a pressing need to reduce its workforce of accountants. Few jobs have been more impacted than accountancy, Priddis said, which involves a range of skills that are easily performed by AI applications. However, a predictive analysis of other remaining and emerging jobs within the same organization revealed opportunities for the accountants to be retrained.
Specifically, Faethm was able to determine that an accountant’s skill set was very similar to that of a cyber security analyst—a high-demand job in organizations all over the world.
“The only gap we could see was the specific cyber-security knowledge and that was a trainable gap,” Priddis said. “It didn’t make any sense for this company to shed their accounting staff, spending all that money on redundancy and then hiring new cyber security people. They could teach those accountants to be cyber analysts.”
Priddis said predictive analytics can function as a data-driven “GPS” that can help employers anticipate future workforce scenarios and inform decision making.
That means organizations need to acquire the capacity to transform their workforces in a more rapid and agile fashion as new and potentially seismic technologies arrive.
“It always struck me as slightly ambitious and perhaps slightly naïve to think that we are in a position to determine exactly where we’re transitioning to,” Priddis said. “I think most organizations, rather than trying to figure out where they are going, should be building capabilities to continuously experience these sorts of changes. The ability to change, and to have a dynamic workforce that can adjust as the context changes, is probably the single biggest muscle that organizations need to build.”