Shaping the Workforce for the Lifelong Learner

Updated: Aug 18

As higher ed is moving towards serving the lifelong learner, it’s important for both higher ed and the workforce to come together to provide solutions that will meet the needs of these learners.


An interview between Michael Palmer and Michelle Weise originally publised on The Evolllution





Mike Palmer (MP): Can you talk about what drove you to put the book together?


Michelle Weise (MW): It’s a play on lifelong learning. And to me, it’s important because I’ve been in a space straddling higher education and the workforce. People loved talking about lifelong learning, but I wasn’t necessarily seeing that translate into action. So, I thought a new mental model might be helpful.


One of the most useful prodding mechanisms to push us into action has been this thought that, “Oh my goodness, what are we going to do if we actually have to navigate a longer and more turbulent work life?” Because many of the different forecasts and prognostications are indicating not only a longer lifespan but ultimately a longer work life. So, as we think about lifelong learning, it suddenly makes clear all the different changes and moves we need to make in order to better connect the future of education and the future of work.


MP: Even with a great undergraduate experience, it can be hard to apply lessons learned to your professional life. As someone who looked at disruption with Clayton Christiansen, and how it relates to higher education, what are your thoughts on that?


MW: There are many different kinds of innovations. Not all of them are necessarily disruptive innovations but things that we need to pay attention to and think about scaling or building out more. When I was at Clayton Christensen’s think tank, we would get hundreds of inbound requests. People wanted us to look at what they were building to ultimately write about them as disruptors, but they also just wanted to see whether we knew of anything similar on the market.


It’s been fascinating to see the span of innovations and the incredible burgeoning of solutions out there. At the same time, it’s also been hard to see so much reinvention of the wheel, duplicated efforts, or just siloed activity. All of these amazing innovators are building parallel to one another, not realizing how their solutions overlap and might actually be more effective if brought together.


MP: Can you talk about the type of skills that people should be thinking about to stay job-relevant in that long life and prepare for jobs that don’t even exist yet?


MW: We’ve already seen, just over the last decade, jobs that previously didn’t exist emerging as the hot jobs of today. The purpose of the book is not to identify the specific jobs that will be in demand in the future but the kinds of skills and problem-solvers we need to become in order to meet that very uncertain world of work ahead. As we think about better preparing ourselves for this turbulent future, we have to realize first that there are certain skills that humans can leverage better than robots. But there are certain skills that we have to relinquish to machine learning and AI just because they’re always going to do it better, faster, and without any mistakes.


Also, workforce competencies around collaboration and teamwork, and exercising judgment, systems thinking, creativity, curiosity—all those kinds of things are going to be core skills needed in the future.


We also have to realize that in order to be someone truly marketable in the future, we have to have enough technical or domain expertise in order to also assess our own work or intervene at the right times when we’re seeing how it plays with artificial intelligence or these different kinds of rapid technological advancements.


MP: As the demographic in the workforce changes, how does that change the way we engage with learners?


MW: It’s fascinating because even today people are staying in the workforce for decades longer than we had anticipated. They’re well into their sixties and seventies before they think about retiring. So as a mature learner, how do you evaluate and surface the different kinds of skills and experiences you’ve accumulated along the way that have never been formally recognized? There is so much richness in what you’ve learned, and the labor market has no idea how to make sense of it.


When people think about reskilling and upskilling, they immediately think of the technical skills needed to remain relevant as technology advances. But often it’s those more human skills that we really need to work on. And for older learners, what kind of learning experience allows them to broaden those skills?


We tend to always situate that kind of learning in a two- or four-year degree. We associate it with a liberal arts experience. A 55-year-old learner needs something in short bursts, that is more affordable and more relevant to the skills that they want to build but also enables that broadening of human skills.


This pushes us to think about how we engage with learners differently than ever before. Even if you look at some of the open-access mega online universities that cater to 30-year-old-plus learners, they still aren’t meeting learners where they are. It’s still not quite flexible enough for people to integrate into their busy lives. We need to break down this monolithic category of adult learners and identify the different stages and phases for adult learners based on what their needs are.


MP: How do you stay optimistic about the future of higher ed?


MW: Being in this space of the future of work can feel daunting and paralyzing if you focus on the jobs that are going to be automated by technology. But once you shift away from that, you start to see how you can adopt a more positive and hopeful vision of the future.


My worldview was shaped by Clayton Christiansen. His theories of disruptive innovation have always offered me this very constructive lens through which I can look at a whole slew of innovations.


Hope comes from all the innovation that I see. We can’t just be in this mode of constant activity; it has to be geared toward a common agenda. That’s where the language of an ecosystem is critical. We cannot continue to have a K-12 system siloed from our higher ed system, which is in turn siloed from our workforce training system. We’ve done that for far too long.


MP: Can you expand on the idea of creating that ecosystem?


MW: If you think about an ecosystem like a forest, we tend to look at what’s above ground. What we fail to notice are the incredible workings underneath, and underneath is where this amazing communication network occurs. A near-intelligence emerges.


That ecosystem is what we need to aspire to have. When we think about the incredible data across all of those systems that we have—K-12, post-secondary, workforce—it is difficult today to understand the learner outcomes. We have no ability to stitch together wage earnings and outcomes data, so, we need to figure out how we pull all of these different strands together to make this data make sense. Once it makes sense, we can prioritize what to build and how to allocate resources.


MP: How do we get this new learning ecosystem to operate in a way that is not unfair and isn’t perceived as rigged?


MW: We have to be transparent about skills. How do we help folks actually translate what they can do into language the labor market can understand? That communication breakdown stymies learners from graduation throughout their work lives.


Part of this phenomenon has been this concept of skills-based hiring, which is an attempt to move away from thinking about pedigree or a degree from a prestigious institution—to rather get very granular about the kinds of skills needed in the workforce. There’s an assumption that if we can get transparent, there will be less friction in the labor market.


Right now, we’re flooded with the credential engine—there are over 730,000 different kinds of credentials out there. It’s impossible for a hiring manager sift through that. So, we have to figure out how to make the process fairer and be very clear about the skills we need.


It also goes back to learners who may have experience in the workforce but no degree. How do we capture those skills? A lot of the innovations that I point to in the book are showing different ways of acquiring this marriage of in-demand skills and those in supply. That can come in the form of different kinds of skills compasses, which I point to from places like SkyHive, MD, and Future Fit. There are different assessments that try to democratize the process and help us understand what skills someone possesses and compare them to what we need.


There are different, emerging innovations that are trying to reduce that friction between higher ed and the workforce. Even though this concept of skills-based hiring is trending, and employers are open to moving in this direction, we haven’t actually seen meaningful data from it yet. We haven’t actually seen this tremendous shift towards skills-based hiring. We have quite a bit of work to do there.


MP: Is there anything new and exciting that we haven’t talked about so far?


MW: I would say the concept of a skills compass. There are different kinds of AI-powered platforms out there that are trying to do a better job of helping us surface our competencies and helping employers understand the skills of their existing workforce.


It’s fascinating how poorly employers understand their own people. They often are struggling to figure out what to do with names and titles. They don’t actually know the granular skills that they have, or whether they should be skilling up some portion of their existing workforce for the jobs that they anticipate in the future.


One company in the skills compass family is Future Fit. They’ve gotten into the business of out-skilling—helping learners navigate a layoff. A lot of employers are now realizing that in the future they will have to maybe lay off a thousand workers. The optics of that are terrible.

And how do they do better for their people?


Now, some of these companies are bringing in a group like Future Fit to get clarity on skills and help some of these learners draw maps to better jobs elsewhere. They’re actually helping those workers understand their competencies and skills, and then helping them identify different pathways forward, as well as the education providers in their area that can help them fill their skills gaps. These are the kinds of things that, even if they’re more nascent innovations today, give me great hope for the future.


Read more here:

https://evolllution.com/revenue-streams/extending_lifelong_learning/shaping-the-workforce-for-the-lifelong-learner/

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