How states are grappling with a tight labor market, accessing new pools of talent
Using micro-credentials and skills-based hiring in Amanda’s work
The role of degrees and skills in the future of work and learning
Using data as a proof point for skills-based hiring and more
The metrics to measure the effectiveness of pathway programs
The rundown on learning employment records
Finding inspiration in Arkansas’ Chief Data Officer
Amanda's final thoughts
Welcome to The Skill Shift, a podcast for organizations that want to future ready their workforces, brought to you by D2L. I’m your host, Malika Asthana, senior strategy and public affairs manager. Each episode will speak with guests from some of the most innovative businesses around the world about their unique approaches to learning and development. They’ll share specific actionable insights into how they’re preparing their workforces for the future and the ways they’re addressing skills gaps in their industries. You are listening to The Skill Shift.
Organizations of every size industry and across nearly every state are facing unprecedented challenges trying to find skilled workers to fill open roles as they navigate a tight labor market and changing skills needs due to technological advancements. The nation’s governors are key players in this conversation. That’s why I’m so excited to share that our guest for today’s episode is Amanda Winters, program director for Postsecondary Education at the National Governor’s Association Center for Best Practices. If you’re not familiar, NGA is the non-partisan membership organization whose mission is to support leaders from 55 states, territories and commonwealths in identifying challenges, considering best practices for state policymaking, and providing resources to take collective action.
Amanda’s team at the NGA advises state officials on post-secondary and workforce policies. With a focus on equity and measurable outcomes, her current portfolio spans economic mobility, skills-based education and hiring pathways, work-based learning and more. Amanda, welcome. I’m really looking forward to this conversation.
First of all, it’s great to be here. I’m excited to be able to talk through some of these issues and how states are grappling with some of the same things their private sector partners are grappling with when it comes to a tight labor market and trying to access new pools of talent to meet a lot of their needs. So governors are approaching this in a couple different ways. First of all, they’re thinking about their own talent pipelines for public sector work. There’s a lot of needs and a lot of gaps that they’re trying to fill in a talent space, but also they’re trying to think about economic growth and attracting businesses and thinking about how their workforce in their state can meet the emerging needs of industry so that they can continue to keep their economies vibrant.
So NGA and the Center for Best Practices is currently thinking about projects that support both ends of that spectrum, helping governors really think about how to attract businesses and to support economic vitality while at the same time positioning themselves as employers and how can they think about the talent that could flow into public sector roles. People who are drawn to public sector roles, from the research you see, it’s not just money it’s the mission, it’s the work, it’s the feeling like they’re doing elements of public service and speaking to a higher mission in their state.
We’ll start kicking off some work the beginning of next year to hopefully help some states come together and have those conversations together about how they’re trying to change the talent marketplace for the public sector, while at the same time thinking about the way that skills as a pathway, skilled pathways rather than just seat time… more degrees… in addition to degrees, how that’s sort of filling out the picture of talent within their state.
Absolutely. No, that’s great. As we try to address some of these challenges, there’s been considerable excitement about the prospect of micro-credentials to enable rapid up-skilling and skills-based hiring to get people skilled through alternative routes into open jobs. In short, there’s a lot of hope being put into these ideas. How do you see this playing out in the work that you’re doing at NGA?
I used to work in a state, I worked in the State of Illinois at the Board of Higher Ed for several years before I moved to a national role. So I come at a lot of this conversation with sort of a systems understanding, like how are we actually going to make some of this happen? And what I’m seeing now that I have the privilege of sitting at a national organization and looking at activity in the states, I think there’s a lot of energy around micro-credentials from the education side, and there’s a real disconnect as to what employers are not only looking for, but also just in the very basic sense ingesting into their own HR systems. So there’s some research out of Northeastern University last year that highlighted the fact that many of the large HR systems don’t have any mechanisms to ingest digital credentials, and digital credentials being those issued with that metadata embedded into them about skills that they’ve learned or the experience that is memorialized through this digital credential.
So it feels like sometimes, especially in the policy space, that we’re creating a lot of supply in hopes that it will generate demand on the employer side. And it does not feel like those conversations are being connected in a way that’s really meaningful, like employers are like, “Yes, these micro-credentials mean things to me.” It feels like a lot of modularization, almost an administrative exercise, on the part of education to say, “Look, we have these on-ramps and off-ramps,” which I think is a good idea. I’m not saying that the concept is bad. I’m just saying that the outcomes for these micro-credentials, we’re not really mapping those or gathering data on those in a way that’s really building a large scale case for these types of credentials.
And then there is a disconnect, I think, in what employers understand about them and how they actually use them in any sort of hiring process. So for me, I get the energy around the micro-credentials but I do feel like there’s several missing pieces to make them really have real outcomes for learners and workers and for our systems to better understand where they should invest and what micro-credentials are meaningful and which are meaningless.
Right. Yeah, I think even in our own research at D2L we found a very similar thing where there’s so much excitement around it, but even in the education space, a lot of leaders are finding that they’re at the very initial stages of thinking through exactly what you were talking about, about how to communicate value and ensure that there’s rigor around assessing the quality of those micro-credentials, even the ones that they’re creating in states. So we heard some really great examples from a couple institutions out in Australia that were saying it has to serve some kind of student need and there has to be a connection to employer-based outcomes. So I think there’s a lot of potential there, but it does feel like we’re at the very, very beginning of so much of this process, and it’s not necessarily a slam dunk as it were yet, we’re still building the foundation for it.
At the same time, I think we’re finding that in some of the writing around this shift to skills-based hiring people are sort of saying, “Well, we’re going to do away with degrees. Degrees don’t matter anymore. Post-secondary education is over.” I note that there’s new research out from the Georgetown Center on Education in the workforce that said by 2031 72% of jobs in the US will require post-secondary education and/or training. So in other words degrees aren’t going away and it sort of depends on the type of degrees. I wonder if you’ve got a reaction to that as it comes to your hope and your skepticism about skills-based hiring?
Yeah, I will state upfront, I’m a firm believer in the power of post-secondary education. While my work explores multiple pathways, and I think that there’s lots of ways in which we should be building paths into economic mobility for families, there is lots of evidence that degrees are still a great path to that. We need to talk about value really broadly for personal and economic value of the things that we’re providing to residents of our state. And also understanding that building a vibrant workforce is about giving people skills to continue to learn, continue to grow, and to be able to adapt to a changing industry, sector or marketplace, and not just to be prepared for one job and to be deemed worthy to get this one job with the skills that you have, but instead to be able to see the array of opportunities available to you based on the skills that you’ve developed.
You reminded me of something that another one of our guests, Chike Aguh, former chief innovation officer at the US Department of Labor, shared with us, which is this idea that skills-based hiring should be a drawbridge, but it shouldn’t be the only bridge, right? So we’re not doing away with education. We’re recognizing how it brought so many of us forward and into this work and trying to make sure that people have an opportunity to compete and to learn, and that there are multiple pathways to learning, but that education still has value. And I think what we’re all trying to do is make sure that more people have access to education and that we are thinking about employment opportunities in terms of advancement and creating that opportunity. So I really appreciate that.
I want to talk about something that you just mentioned a few times, which is this idea of, it’s almost this idea of data. So I know that one of your passion areas is state longitudinal data systems, so we’re taken with all these hopeful ideas, we’ve got some anecdotes, but it doesn’t feel like we’ve always got the evidence to back up claims that skills-based hiring is really going to lead to economic mobility for people and their families. I wonder if you could just tell us a little bit about what you’re doing with data at NGA and how you think about that side of the conversation.
Yeah. It’s sometimes not the most exciting part of education that people want to talk about, but it’s so critical. I would say that every governor would say they want to be data-driven or their initiatives based in sound data, but that takes a lot of work. And we need to build up at the same time we’re having these conversations about innovative pathways, we need to have a mirrored investment in our data systems in order to actually track and see if these things are doing the things that we say we think they can do. And for skills-based hiring especially, I think there’s a real need to be intentional about developing the metrics and systems to measure whether or not the people that we’re sending through these pathways are getting the outcomes that we say they will. Because right now there’s a lot of promise in this space, and there’s a lot of rhetoric around how if we move to skills-based hiring then we will have a more equitable workforce. And it’s all in the implementation.
And that’s why we’re really excited to work with states to figure out what public sector skills-based hiring looks like so that we get to those outcomes that governors are envisioning. Governors across the political spectrum have removed degree requirements for public sector roles where they’re not necessary. So let’s get the data in place or the metrics and the measurement in place so that as hiring shifts we’re able to see is this opening up doors? Is this creating new opportunities for different talent pools or is it a different process for somebody who was already moving into that job, like a pathway for people who already had pathways? That’s what we want to avoid. And the only way we can know that our work is really having the impact that we want it to have is by setting up the structures of data collection and measurement. I mentioned it back when we were talking about the micro-credentials.
There are some states that are really starting to think about how to collect better data on some of their shorter term credentials. We’ve been pleased to work alongside the State of Virginia as they’re collecting more data on their credentials connected to their workforce grants. And it’s exciting to see some of that data start to be compiled and start to get insights about who the students are who are moving through these pathways, what kind of employment outcomes they can expect, and it helps to inform state investment and state development of further pathways, it helps to inform how they can connect with industry partners, having a better outreach to disconnected communities and communicate the value of some of these innovative pathways. But we can’t just say because it’s new and different or we’re trying something new that it’s somehow going to magically change outcomes. And then five, 10 years down the road, we haven’t measured anything, so we really have no idea of the impact.
So I think it’s great that states are getting innovative about the ways in which they’re thinking about their data because it’s so necessary in this space to be intentional and make sure that we’re getting the equitable outcomes that we’re looking for so that we can then say, “Yes, this is a best practice. This has achieved our goals.” So we’ve got to set those goals and then we’ve got to measure to them so that then we can start to say, “Okay, this is how we scale it,” or “This is what we recommend other states consider as they’re thinking about these same types of strategies,” because we can see that it’s working. And until then, it’s really just a conversation about what do you want to try and let’s see what innovation comes out of some of these pilots or these efforts in states. And as long as we’re measuring it, in a couple years we’ll have some great data about these strategies really got us to where we need to go.
But that investment in data at the state level, and I think certainly alignment with any investments in data that come down from the federal space, need to be connecting on how do we better shift our data investments towards thinking about some of these shorter term pathways and skilled pathways alongside the data we gather about our degrees so that we can understand the whole ecosystem of opportunity and we can see how they might mesh together into different pathways for learners and workers, or how we can see different spaces that are really getting the ROI and outcomes for learners to balance the investment from the state and federal side.
Yes, that’s so important, and it reminds me of other conversations we’ve had even with measuring the ROI of learning and development investments within a singular company. So when you think about the complexity of doing it at the state or the multi-state or the federal level, I mean, it just goes bananas. So I think we’re looking at, just to recap some of what you’re saying, you’re looking at the outcomes associated with multiple pathways from high school into work and making sure that people are having access to economic mobility, certain increased wages, advancement opportunities. What else should we be looking for in terms of metrics?
One of the things I’ve always been frustrated with, and I’ve seen pockets of some of this work, but we lay out a lot of pathways on paper for students and we’re not that great. And when I say we, it’s just like the royal we of state systems. We’re not really great at measuring who’s moving through those pathways. If we lay out a LPN, like a CNA, LPN to RN pathway saying, okay, we’ve connected our dots on our side so that you can transfer from this program to this program to this program in order to move up.
To get you to a registered nurse.
To get you to a registered nurse. We’re not really measuring in most of our programs, are people using that pathway, and if so, how long does it take them? What are the demographics of the people moving through there? Are there barriers to continuing your education after you get each of these steps, these stackable pathways? I feel like we’re really good at putting things down, mapping things out the way we think they should work, and then just being like it is there for you to access and then just trusting that people move through those pathways. Transfer is still super messy and hard, and even within your own institution moving from program to program might be in different spaces within your educational institution, and so we expect students to just move through these and we don’t measure whether they are.
And the handful of places where I’ve seen some analysis, there’s a handful that they have successful pathways laid out, and I’m sure it’s because there’s student supports and advising at crucial points to get people through those. But most of them, they’re not moving. They’re moving like this through pathways. They’re not moving straight ahead the way we laid it out on a nice neat path for them. Student paths can go in a lot of different ways, and so we should be more responsive after analyzing our data to some of the paths that students are taking to move through occupational spaces. So I think that’s a place where we need a lot more analysis too. If we’re breaking things down into these incremental pieces, then we need to follow with the data. Are these steps being taken or are there ways in which we can better support movement through some of these pathways or follow the direction that the students are taking and maybe build better pathways this way.
And I think it’s such an interesting thing because right now there doesn’t even, to your earlier point, there doesn’t even seem to be a space for data collection, centralized data collection, on some of this stuff. We don’t always know what people have done before moving into their next job. Maybe if they’ve included it in their job profile and resumes or on LinkedIn or something like that, you might be able to graph some. But part of the issue is we lack a common language to describe the skills we’re gaining through credentials, and we lack a common place for individuals to store them. So that brings me to my question about learner employment records, which I know you’re very passionate about. I wonder if you could tell our audience what they are, why you’re excited about them, and what kind of work you’re seeing progressing that movement forward.
So learning employment records, LERs, I’ll shorten it, that’ll be my little parenthetical acronym that I’m going to use now, they are essentially the digital way that learners and workers can move their credentials around. So this can be anything from a transcript to badges to just skills assessments, and it can be employment related training and records as well. So the E in LERs. So this is essentially a digital representation of the earning of skills and credentials by an individual. So this is sort of the technological layer on the top of the skills conversation. NGA has been working on an exploration of learning and employment record systems and issues over the past about two years. It’s been exciting to sit alongside states to think about how they might leverage their data and technology systems or work with vendors in order to try to envision spaces where people could house those things and more easily move them around in order to access other educational training or employment opportunities.
So LERs will many times, how I envision it, and I’m not a technology expert, so I talk to a lot of technology experts who help to answer the deep questions for me, but they’ll be housed in a digital wallet. So the easiest way for a layperson to think about it is like your Apple Wallet. So if you click on that, you see lots of different things and they come from a lot of different places and you have a lot of apps that’ll be like do you want to move this to your Apple Wallet? Yes, I would. It’s because that data is interoperable with Apple Wallet. So even if it’s coming from, say, your American Airlines app, it is structured in a way that’s interoperable with the structure of the Apple Wallet so the data can then move and you can see that representation of your airline ticket in the space that also holds all these other things.
So the conversation around learning employment records is really sort of how can we structure data that’s coming from a lot of different spaces of employment and learning in order that it could be pulled into digital wallets of this type so that it can be represented in a lot of different ways. So we’ve seen a lot of pilots over the last couple of years. There’s a brand new effort that just got announced this last week called Skills Forward, the thing is being released which is like five or six different large grants to some states and regions that are trying to accelerate and launch end-to-end learning employment record system, meaning you have a learner worker who gets these credentials issued to them and then they can hold them in a digital wallet and then they cannot transfer them to employers and education providers. You can have users interacting with this system.
That’s been something we’ve been kind of missing is the user experience. We’ve been thinking a lot about the technology layers leading up to that and the data structures, but there hasn’t been a lot of user interaction with learning employment record systems yet. So I’m very excited to see the outcomes of some of those programs that are being funded. And some of them are states, Alabama, Colorado, Montana and Connecticut, I think are going to be moving forward with some exploration of that end-to-end LER system. Now, some things I will throw in here about LERs from a personal perspective. I spent the last two years learning about them. When we first started this project I really had no idea what they were, and so had to spend some time learning what would be the impact on our education training systems, how would states play a role in thinking about this kind of strategy?
It’s not a strategy that I brought to states as like, “Hey, you guys need to try this.” I essentially put out a call and said, “Are people interested in this? Do you want to talk about it together?” And 11 states were like, “Yeah, we’re thinking about something related to that so we’d love to just talk through this with our colleagues.” And what I think was really important about the community of practice that we held with those 11 states was I tried very hard to create an environment that was separate from vendors. And there’s a lot of great vendors out there and I’ve certainly gotten to know some of the platforms that are being developed and are doing some really interesting things, but LER conversations are very led by technology and technology vendors, and not really talking about the policy and what’s the background to all of this? What do we have to know before we can launch a technology platform?
You don’t just want to dive in head first to this thing that it’s promising to create a more equitable workforce for you, but the fact is these platforms are only as good as the information that flows into them that can be then utilized. And so if we’re not talking about how to get our data ready or the goals that we’re trying to reach with any sort of technology platform, then it’s a meaningless exercise. And I honestly think you can do skills-based hiring well without learning employment records. If we can do the process, if we can figure out everything that goes into it and figure out the process, that’s a win. And then technology can enable that to scale and be faster and be more efficient. But if we can’t figure out what we’re even trying to do without the technology, then it really, I think, can be a barrier to some of these conversations and be a distraction.
It’s kind of a shiny thing. And how I put it with folks that I’ve been working with is, I think the skills-based hiring conversation is a combination of a lot of issues we’ve been talking about for years. Competency-based education, multiple pathways, work-based learning and skill development, and we’ve just put a technology hat on it and pretended like it’s some new issue now. Like, oh, well, learning employment records, okay, well, they’re no good if we can’t figure out these other things. So I feel like my duty in this space is to uphold the policy conversations and data conversations that have to be held in order to help a skills-based hiring, say in a state who’s trying to really think about how to leverage all of their assets to build a skills-based hiring public sector space. I want to be there to help them leverage those assets in a way that’s really meaningful and then think about more efficiency through technology.
And the critical thing we can’t ignore is right now employers are not clamoring for this. So again, going back to the micro-credentials thing where I said I feel like there’s a disconnect, I really also think in the LER space there’s a disconnect right now between all the things that are being tried and the strategies that we’re trying to jump into and whether or not employers want this and whether or not they will use it in the way that we imagine for their hiring processes and for their advancement processes. I was at a meeting recently where I was with LinkedIn who is a partner of the National Governor’s Association, and they have so much data around how people are moving through pathways, and we’re talking specifically about the cybersecurity sector when we’re talking about jobs, which is a critical area of need for public and private sector.
So we were exploring this together and some of the insights they had indicated that while there is a move to hire more people without degrees into some of these cybersecurity jobs, that those jobs that had the degree removed from them paid significantly less. And so there’s that consideration too, as we have the skills and degree conversation, we have to make sure that we’re not creating two tracks for the degreed workers and then the skilled workers who are coming alongside them and making sure that we don’t set up systems that gives less value to the skilled workers and more to the degree because of that proxy that there right now is more trust from employers in the degree.
So I think that’s just something I would flag about learning employment records. I feel like if we put a lot of the people who have a grouping of skills that we think will move them better into the marketplace, there could be a differentiation between those that come with an LER and those that just come with a degree. So avoiding that, I think, is a critical piece of the early stages of this work too, to make sure if we’re shifting to framing experience and skills as sort of the core of how we’re talking about each of these learners and workers, then it has to be universal. It can’t just be skills for these people, everybody else keep doing the regular degree pathways and we’ll create that separation.
Exactly. No, I couldn’t agree more. And we’ve talked on this podcast before about how breaking down some of those barriers to employment and quality jobs isn’t just about removing the degree requirement, which you’ve just talked about, but it’s also culture change and talent development. I think you mentioned some really interesting work that Arkansas is doing a few times. One of the things that I also wanted to call out you shared in our preparatory call is that they’ve got a new state chief data officer that is implementing a no-wrong-door approach to public services. I wonder if you could just speak a little bit to that and what they’re thinking in terms of wraparound supports and connecting some of that data?
Yeah, and Arkansas sounds like my favorite child right now. I’m mentioning them a lot. They have an amazing chief data officer. His name is Robert Magoo, and he is leading his office to bring together the governor’s workforce cabinet and talk about the data that intersects across all of these agencies. Higher ed, education, corrections, human services, public health, they’re thinking about workforce economic development, all the different spaces where they might be able to connect to people who need services, but also people who are looking for jobs and training and figuring out how they can set up a portal, so using technology to implement their vision. So the vision setting coming first. I was lucky enough to be in some of the rooms where the workforce cabinet was really talking through what their vision is for this. And what was exciting about that for me was one of the strongest voices in the room was their new corrections lead in the state of Arkansas.
And when he had the opportunity to share a little bit with the larger group about his role, that was pretty new at the time, and his goals for that agency, he was like, “I want the vision of my agency to be hope.” And I was like, “I’m sold. This is amazing. I love that.” And so through that, he’s thinking about how do we connect people to services before they reenter their communities? How can we prepare them with workforce skills? How can we get them educational opportunities? How do we make sure they have proper medical care that can transition them back into their community as well? How can we get people reconnected to their families? And it created a picture of all of the dots that need to be connected in order for people to have that support system as they move from corrections back in into their communities.
And that was exciting to me as a conversation around how digital records, so thinking about them beyond just a degree or a badge or I had this work experience, but really sort of their digital identity. A lot of people transitioning back into communities need a state ID in order to confirm access to medical services or to housing or to new employment opportunities. So states, Arkansas, but also Illinois and Oklahoma and Indiana, thinking about how do you get driver’s licenses or state IDs to the people who are in these incarcerated settings right before they get out so they have that in hand? Because the biggest delay in getting them connected to services, is just proving who they are. And technology connections can make those, and that is a digital credential, your confirmation of who you are. And so you can take that then to all these other places to get access to services.
So as they’re thinking about how technology can be leveraged to support people, they’re thinking about, okay, before I can even get them to the job or the learning opportunity, how do we make sure they have those bridges from the space that they are, maybe transitioning back into a community, maybe somebody who’s been unemployed for a long time, maybe someone who has low literacy or digital literacy skills, how would we get them bridged to these opportunities by better leveraging our technology in order to get them what they need? So it’s exciting that they’re thinking even beyond just the learning space as they’re thinking about credentialing individuals and they’re thinking about what’s necessary in order to get people to that space where they can access opportunities that get them economic mobility opportunities.
So I think it’s really exciting and it’s great to see the governor bringing all of these people together so that they can discuss and align some of the visions of these different agencies towards human centered design activities that help them build a plan together. And it was great to see that change coming from agency leads, that culture change you mentioned, that’s necessary to spur a lot of these things and it’s great to see that coming from the governor’s cabinet because that’s where I think we’ll see some really transformative uses of data and applications of technology.
Absolutely. This has been such an interesting conversation and so unique from the other ones that I have with stakeholders in this space, so I appreciate your candor and sharing so many practical examples of work that’s underway. I just want to repeat a few things back to you because I think there’s so many great nuggets that I want to leave our listeners with. This whole idea that we tend to operate in silos about, well, I think we already know that when it comes to education and workforce, but this whole idea of conversations that may seem to have momentum in one space, whether it’s education or workforce, not necessarily translating into the realities that employers are facing.
This idea that we need to be evidence informed and evidence informed starts with data collection, data connection, data cleaning, and really collaboration. There’s also an idea that you need sort of willpower of a leader, whether it’s a governor or someone else to put attention on this and bring people together. And I think there’s also an idea that we need to be careful about recognizing things as silver bullet solutions without thinking about them on a long, long-term timescape, 10 to 15 years out. The goal is to give people opportunities for economic mobility and advancement, and I think that’s something we really need to take away. So we’re coming to the end of our time. I want to give you a platform to say where can listeners find you and what would you like for them to take away from our conversation today?
Yeah, I’m super easy to find. You can go to nga.org, my emails listed there. Feel free to reach out. I think I always come to this space particularly, but all of my work, with a sense of learning and curiosity. I know that I’m never going to be the expert on all of these things, but I do feel like I’m pretty much an expert on how states are approaching some of these issues and how to bridge the innovation conversation with the implementation conversation. But I’m continually learning, so I don’t pretend to know all the things. All the stuff I shared is really just from my work over the last two years on this topic. And it’s always evolving. I start to learn more about different parts of it and get excited. I start out cynical most of the time just because I’ve got very much a prove it to me before I take it to states or if you can’t convince me I can’t convince states kind of mentality.
But I think if people want to reach out and share their excitement or share my cynicism or be able to talk about how they might want to contribute to a conversation around public sector skills-based hiring, which is our next step in our work, we’d be more than happy to partner with them. As I mentioned, we’re partnering closely with Opportunity@Work in this space, but we’re also thinking about lots of other partners who are thinking about implementation, who are thinking about data and research, and we really want to be able to curate this space for state offices so that they can come to us as their trusted association and be able to say, “Who knows this stuff? Who’s doing this stuff? Who can help us do this stuff?” It’s rarely ever us when it comes to that deep implementation, but we can certainly say we know some people who are doing exciting things, and we want to know more of those people.
So I fully encourage everybody to reach out and learn a bit more about our work or share what they’re doing in their work and see how we might be able to connect what you’re doing or what you’re learning to folks in the states. And if you want to change my mind about some stuff, I’m open to that as well. So it’s a continual evolution, and I want my cynicism to be proved wrong in most every case. I feel like I sometimes need to balance the sort of this is the new shiny thing with the opinion of we always have a lot of shiny things in education and workforce. Some of them don’t work out, most of them don’t work out, and I think we should learn from that and say, “Hey, what can we do to make this effort work because the promise is there.”
And it’s exciting to be focused on something that’s trying to be more inclusive and to bring in more people who may have been disconnected from our labor force or who haven’t had access to some of these types of jobs and opening up those doors is a great goal, and I’m right there with everyone. I just want to make sure that we do it in a way that is sustainable and really has the learner worker in mind, but connects to the reality of our state systems and our employer needs, which the employers, including the public sector, and how they might be better able to serve these folks and get them to really enhance the diversity of their talent pool to build the workforce of the future.
That’s great. Amanda Winters, thank you so much.
Yeah, thank you. I really had fun. Talk to you soon.
Thanks for listening to The Skill Shift. This episode was produced by D2L, a global learning innovation company, helping organizations reshape the future of education and work. You can find links to the resources we discussed in this episode on our website, d2l.com. There you’ll also find the video version of this podcast, related content, and more. You can also find other episodes on Spotify, Apple Podcasts, Google Podcasts, or wherever you listen to your favorite podcasts. Thank you for joining us.
Resources Discussed in the Episode
- Enabling Learning for Life: New Realities for Work and Education, D2L
- Georgetown University Center on Education and the Workforce
- Creating Accessible Pathways Between Workers and Open Jobs | Chike Aguh, The Skill Shift
- Why the ROI of Corporate Learning is Hard to Measure—And What To Do About It, The Skill Shift
- Robert McGough, Chief Data Officer