Storytelling About AstrumU With Adam Wray

William Tincup: [00:00:00] This is William Tincup and you’re listening to the Use Case Podcast. Today we have Adam Wray from AstrumU and we’ll be learning about the business case, so the use case for why prospects and customers choose AstrumU. Let’s do some introductions. Adam, would you do us a favor and introduce yourself and AstrumU?

Adam Wray: Yeah, no, I’d love to. William. It’s great to be here. And Adam Wray based outta Seattle c e o and founder of AstrumU. We’re an AI data platform company that focuses on understanding, extracting skills of individuals so that they can understand better what [00:01:00] pathways are available to them through learning or working to get advancement and opportunity.

William Tincup: That’s nice. So the skills you’re helping employees, not necessarily candidates, right? Yeah, so

Adam Wray: really it’s, fundamentally, if you look at the problem statement we’re trying to solve is there’s this gap between industry and education on what’s going to really create outcomes.

And the problem is that the educators have one point of view, the HR and hiring managers have another, and the individual has a third, and nobody talks the same language. And leaving everybody behind, right? And so you get a lot of inefficiency, a lot of waste, and so what we want to do is create through data transparency around that.

So that people can start to understand and ask the simple question, what education, short form, medium form, long form, et cetera, can I leverage to get the necessary skills to be successful on this opportunity in front of me? And that could be a person looking for a net new job. Is it workforce training to traditional degrees?[00:02:00]

Or that could be a person within an employer’s environment who’s sitting there and going, hey, I want to upskill to the next opportunity and pathway. And so we have a data platform that is a set of API services that people can build Lego block solutions to take them on these problems. And ultimately we’re always extracting different skills so we can measure where the individual is.

And then we’re matching that ultimately to an outcome through education to an ultimate job or role. And for us, the uniqueness is, when we focus not on the large cohorts, like everybody that looks, lives in the zip codes the same. We focus on the individual, and we’re after verified data, such as their transcripts, HR information, etc.

We can help to build a rich profile of the distances they’ve uniquely traveled so they can understand their skills.

William Tincup: And so we’re looking at skills where we look in at skills three dimensionally or we look at micro skills, transferable skills, tangential skills. The way that [00:03:00] people talk about skills is fascinating to me especially in this era right now, the last year or two of our own skills based hiring.

So we’ve seen. In our world, we’ve seen everything in hiring get flipped on its head and say, we don’t care anything about, we just care about skills. It’s okay how do you measure skills? I had, I hand coded HTML in 95. Do I still have that skill? You’re

Adam Wray: an excellent developer still to this day,

William Tincup: right?

Adam Wray: HTML

William Tincup: hasn’t changed at all. No, not at all, right? It’s like when the WYSIWYG came along for HTML, I’m like, I don’t know what this thing is. This is crazy. This is crazy. All these colors and things that kind of show me. No, I just need to hand code it. Yeah, you know what my point is. Yeah, I

Adam Wray: see where you’re going.

Yeah, no, I just said I think that the challenge here really is everybody says they want to do skills based hiring and nobody else knows how to do it. It’s your point, it’s because, A, nobody really has a common way in which they look at skills. Everybody has their own [00:04:00] skills rubric, their own way of defining.

And and we think this is the next new challenge because If we’re really going to continue to grow as a country and society and also create more opportunity for people, especially for marginalized communities, we’re going to have to figure out a way to start capturing skills that go beyond the pedigree.

We’re going to need to get to the, people who have other things that they bring to the table are highly valued by employers, but they can’t be trusted. So I’ll give you a use case example. Veterans. Veterans come out they go through an immense amount of training that is captured in their, what’s called the JST, a Joint Service Transcript, and other documents that are military transcripts, but the employers have no way of understanding.

They have no way of understanding the training they might have gone through, the experiences they might have gone through, and what those skills mean to that particular role and opportunity. So we started a pilot with the Army at Fort Riley in Kansas and Transition Assistance Program, TAP, basically to start breaking [00:05:00] down soldiers JSTs and their other transcripts that are from the military, such as ERBs or ORBs that capture an Army.

All these things that they do and learn along the way, which the world doesn’t know what it means to them, but they’re real valuable skills. Communication, leadership, logical, allocation, cognitive analytical skill sets from a durable to a technical. And then we compile those all into a profile after we actually extrapolate out of the transcripts themselves what their skills are, and then map it automatically to a role and opportunity so that the soldier can know two things.

One… What’s the top three roles I’m available for right now in the civilian world that I didn’t realize my skills were applicable? And two, what are the top three roles I could get to, but there’s a skills gap that education could specifically be recommended to go address? And so that’s how we hope to enable more people to transition back into civilian workforce.

They have opportunity to scale and [00:06:00] grow because they bring a lot to value, but right now society just has a hard time understanding the package.

William Tincup: So inside of a corporate environment, what is Astrum you, what is it connected to? Is it connected? Is it thought of or connected to the learning and development?

Is it internal mobility? Like I know the audience is going to wonder okay, sounds great. Totally get it. Need it. Because it’s where the, it’s the future, of course. Now, what is it where does it get data from? And inside of that environment the HR platform, et cetera, all of the technology that HR has and recruiting to some degree.

What does it need to be tied to for folks?

Adam Wray: Yeah, no, that is a great question. So obviously, thinking back to the fact that we’re putting together a data platform with a lot of API services that use cases can be built on, and some of those use cases are repeatable ones that we’re scaling out. Others can be An employer or a university doing something specific to their need just with different APIs.

What we’ve been doing historically is we’ve done some point projects with [00:07:00] Cerner and T Mobile doing analysis on skills, building the profiles, feeding them back in, and then they’ve used that typically in their HRIS system. We’ve actually got experience through that process, translating and breaking down HRIS records, ATS records, and corporate learning management systems records.

Feeding it back in a scalable, systematized way we haven’t done yet. And so one of the things we just announced less than a month ago was a strategic partnership with SHRM which I’m sure and, you let us know very well. We’re working with the CEO and his number two over there, Nick Schock.

Specifically on a project that we’re teeing up to systematized workforce training. And what we mean by that is we want to index all of the workforce training type content based on skills and the individuals coming out of those programs and line them up in a way automatically to the opportunity and the role that the company has and then feed those individuals directly into the HRIS system.

And that could be a workday or an [00:08:00] oracle over time. So this is work we’re going to go forth and doing. We’re actually putting a lot of green groundwork right now. But the goal here is that, companies want, if they’re going to do work skills based hiring, they’re going to need to be able to understand non traditional paths.

Where people are picking up these skills and break that down for them so that they can then enable and then SHRM wants to be in a position to help hiring managers and HR begin to understand how to do skills based hiring at scale. So you can think if you play that over time, I’d expect we’ll see things like certificates around skills based hiring and skills based knowledge that people can start to say, hey, the degree is important, but guess what?

It’s just part of the journey. People might bring a lot of experience and workforce that doesn’t directly translate, but if we can break those skills down through Verify, and then we have a way to process it into our HR system, then we have a way to hire these people and take advantage of that opportunity.

Yeah,

William Tincup: I think you also in the [00:09:00] traditional sense, it also as we dig in, we learn what we probably don’t know about those things. So you got a degree in communications. One would assume you have the skill of writing, but that’s just a, that’s just an assumption. Is there

Adam Wray: something? I’ve met a lot of communications majors.

William Tincup: And I’m not talking about my niece. I’m not talking right now, by the way.

Adam Wray: Oh, okay. I’m sorry. I didn’t realize William I was getting you right in trouble with the family.

William Tincup: But, like when you said the non traditional, I really love that because again, it unlocks a bunch of things that where people, didn’t take the, didn’t take a college Great.

There’s all kinds of cool stuff that they’ve done. They’ve garnered these skills. We can test them have an understanding of what they have, what they don’t, what’s close to them. I love the, when people talk about contiguous skills, it’s like you have this skill, but really you have this skill over here.

They just call it something different. It’s Oh, okay. All right. That’s cool. [00:10:00] But when you mentioned the traditional sense I thought to myself, you know what? Especially the further you go away from a degree, the further, one drifts away from the degree one way or another.

When I went to the University of Alabama, my career services person told me, she said listen, one in four, this is 91. So one in four graduate work in their major. And I’m like, say that again, 25%, I’m like 25% and she goes, yeah. And so really it’s about getting a degree that you like, that you think that you’re going to thrive in.

And that’s something that’s interesting to you. And I’m like, okay. So I picked art history. And of course, all my family was really very upset with me for a long time. It’s what are you doing? Why are you going to college? Why are you spending this money on this? But yeah. It’s a renaissance education.

It was. Ironically enough. It served you well. It just. I know more. Yeah. Most of my conversations, especially business conversations, will be more [00:11:00] creative than they are about when I was in my MBA, more about formulas and platforms and rubrics and things like that. So it’s actually funny, but anyhow, the traditional stuff I’m assuming that we test that, test out of these things and make sure that they are the person with a communications degree.

Actually can write.

Adam Wray: So there’s a, so I’m going to answer that question, but I will digress back to your earlier comment on the degree and your liberal arts background. Look, I run an AI company. I’ve been I’ve been in cloud services, AI, distributed data, and these, managing and leading engineering teams and data science teams.

I’ve been in this stuff for the last 20 years since before. I wasn’t an AI, it was cloud services. Oh

William Tincup: yeah. ASP. Yes, oh

Adam Wray: yeah, let’s

William Tincup: go way back. Oh, you’re software developed over the, and delivered over the internet. What? That can’t be done. Yeah.

Adam Wray: Crazy world. All I’m going to say is my degree which I had to work two [00:12:00] jobs to go through school to get is an English degree with a minor in German and history.

A hundred percent.

William Tincup: The humanities, the irony of the humanities degree is people look down on it, but it’s the, it’s actually the degrees that make you think. Oh, I agree. I agree. Preach critical thinking. And it’s what else do you need? You need, yeah, you need a lot of things, but critical thinking, they don’t teach that in finance.

Adam Wray: Those are tactical skills. The biggest example is it’s a, they’re teaching you durable skills that have a period, have a compounding value proposition as you, you walk into more, whereas when you go finance or you go become an engineer They’re teaching you hard skills, but they have a shelf life.

That’s right. That shelf life expires quicker and quicker the farther we go along and more movement is going on, whereas durable skills never expire. Yeah, it’s like it’s

William Tincup: more valuable. It’s like Moore’s law applied to skills. [00:13:00] Yeah, you know what I’m saying? It’s just at a pace, especially today. It’s just happening so rapidly that those skills that you learned, last year, they’re, they’re not out of date, but you’re just not being used, especially in development languages.

I found that, you find somebody that’s just, they’ve learned, let’s say Python. They learned Python, got deep into it, did a bunch of projects. They’re really great at it. And then all of a sudden they’re almost out of work. Yeah. Maybe people have moved on to something else.

Adam Wray: Couple that up with what is large language models and generative AI going to do to developers? I think you’re going to see a lot of entry level roles shrink in size and options.

William Tincup: 100%. 100%. It’s going to be, it’s going to be more of a architectural type of job where people, again, if I can code using generative AI, why do I need to learn the language?

Adam Wray: Yeah,

William Tincup: That’s actually quite fascinating.

Adam Wray: I think, look, generative AI is, [00:14:00] we, as soon as some of the stuff was available, we were all for automation and streamlining. But in answer to your earlier question, in regards to, how we’re understanding proficiency level.

We have a lot of things we do to get at proficiency. And it’s we think of this as a never ending journey of us continuing to find new ways to parse out data that we can then extrapolate skills so that we can then make a matching learning or working recommendation. And so underneath that concept, you.

The traditional thought process is most proficiency is understood through direct assessments whereas everything in our engine is an indirect assessment. We’re using the inference based engine. Oh,

William Tincup: so it can run behind and and to the side of them, they don’t have to do

Adam Wray: stuff.

Yeah, exactly. So we’re trying to use the experiences they bring, normalized against other verified data we can find, to get a sense of what level of proficiency, first what skill [00:15:00] they have, then over time, what level of proficiency can we actually ascertain. So that we can then say, Hey, this person really does bring with a statistically relevant signal, this percentage of probability of skills for confidence.

So our goal, we are always trying to get it down to a confidence score, which really is this, what we know of you so far, based on the data is, and your alignment to this opportunity and based on the skills they need, but that we can see in real time in the industry. This is our confidence score, you’re aligned and matched.

William Tincup: When individuals first see their ASTRO MUSE scores, do they, are they shocked at what’s there? I didn’t know I had that skill or, wait a minute, no, that I should have more of those skills? Is there any, anything that’s off there? Yeah,

Adam Wray: yeah, so it’s really been fun with soldiers because we’re starting to really help them understand, I can’t answer an answer.

They’ve been surprised. I think with a lot of people in traditional, we’ll probably find over time, it will vary, [00:16:00] but I really were, I think we help over time. It’s especially going after, answering your question indirectly, but yes, shock. My best example of shock was the amount of options available to a lieutenant colonel who is managing an entire army base, and he did not realize just how many different things he could do, he was actually aligned and successful for, because he was getting ready to matriculate out, and he was actually incredibly concerned that, he’s going to only be able to flip burgers, and this man is running a base of, I had a billion dollar budget, And I’m like, I miss you, you can actually do a little bit more than that.

Yeah.

William Tincup: In fact we have a job opening. Yeah, exactly. So a couple kind of tactical things. Industry, is there any particular industry that we care about? Market, in terms of… Enterprise, global enterprise, mid cap, small to mid, SMB, et cetera. And my dreaded software category. I despise [00:17:00] software categories, Adam, but I also know that a lot of these budgets are built in Excel.

So the budget’s got to come from somewhere being called something. So let’s start with, is there any industry where we’re playing first?

Adam Wray: Yeah, so the industry playing first. We’re focusing when it comes to the HR and corporate side of the world, we’re focusing heavily on workforce training. So this is a real workforce development challenge and conundrum that the companies are trying to understand these people that are coming through nontraditional pathways, how am I going to understand their skills alignment to my opportunity?

And how am I going to understand which workforce training program? When everybody says they’re the same, great stuff. Which one actually is the right one aligned to me, based on quantitative data? So that’s our area of focus that budgetary, we’re, this is just being very transparent back William we think, we’ve been seeing companies take, HR teams take these out of analytics, CEOs.[00:18:00]

Where they’re looking at, because we have a lot of nonprofit partners that we work with, right? Like for example, who’s a large profit partner. And they have a lot of foundation. There’s actually a discussion around, Hey, this stuff is needed at scale. Maybe we should be funding through the workforce training companies to buy your asset.

And then to connect it into us. ’cause then they can tap into their philanthropic budgets. That they’re already giving for, upskilling individuals in training as well as economic developments in their region. So we’re a, we’re looking at that template of either how much has to be HR versus how much can be tied back to putting ROI into philanthropy.

And they can fund these training companies to connect directly into the HRIS system and the bulk of the cost actually will go through philanthropic

William Tincup: dollars. And, you NGOs, things like that, but. They, I’m thinking about, I [00:19:00] live in Texas, the Texas Workforce Commission who helps people get jobs, right?

Yep. They help people that are unemployed. I’ve interacted with them on a lot of different things. If they could actually understand, especially those translatable skills from the military to the corporate world, I think they could, the good that they could do is exponential.

I think

Adam Wray: there is a lot of dollars desperate to be able to crack these codes, and if we put ROI behind those dollars, that tie back to not only the mission components of how do we help more people find economic mobility, but the impact in the region, which is an economic development story, of how do our companies get people from their backyard and they’ve got the skills necessary to do the role so we can grow?

I, it’s a powerful statement.

William Tincup: If someone’s never bought, I’m going to ask you some by side questions real quick. Yeah, no, love it. If someone’s never bought something like AstroMU before, what are the questions that they should be [00:20:00] asking of you? Yeah,

Adam Wray: so the questions they should be asking of me is, okay, why?

Why are you unique in understanding these skills to be able to make these recommendations versus, say, a labor market analytics type firms or, firms we’ve used to have AI such as an 8 fold AI and so the question always comes down to the simple. Our approach to this balance is very unique.

And you should want to understand that we’re verifying an individual skill at a micro level versus the macro. So that you truly understand the skills they bring to table match to your particular role and opportunity. And our objective is to systematize that over, over time. So you can ingest that into your hiring process and ultimately even apply it to your upskilling internal process.

But we aren’t doing that yet, but we’ve, we have aims for

William Tincup: it. All right, I see a lot of the internal mobility plays they approach skills from a testing perspective. So they go to the individual, they test that person whether or not it’s on a scale of one to 10, whatever, and which is great, but [00:21:00] they’re not really unpacking all the other stuff that’s around that.

And also, I think that test, just my own opinion, I think that test has a shelf life. Oh,

Adam Wray: agreed. Agreed. And I would also, the… It’s terrible that, unfortunately for example, so we’ve been some bad economic challenges in, the last year or two, right? And so the, what is the first thing every company cuts?

Their training budget. So they immediately slashed that because they consider that, extra. I think we need to get to a point based on the rapid change in technology where companies are going to need to understand that investing in their own employees for upskilling is not a extra. It is an ROI differentiator that is critical to the success and longevity of your company.

William Tincup: So when you get, go ahead, finish your thought.

Adam Wray: Yeah, I’m just going to say, so we want to put a number to that, individuals so that they can do targeted.

William Tincup: It’s almost in real time too, so that [00:22:00] they understand it’s like a market index that you can see where they’re at with their skills, but they can also see, if they haven’t done something in that skill, it’s it’s diminished, it’s over, over time that it degrades, I guess is a better way of thinking about it is skills can excel and they can degrade.

And knowing where you are as an individual, where you are with those particular skills is I think first of all, it’s useful to understand the value you bring, because that could affect negotiations, compensation, internal mobility, going after different jobs. So I think it’s helpful for the person to understand, Hey, I haven’t done that particular skill in a long time and it’s degrading and that’s not necessarily a bad thing.

You did it at a certain point. You’re great at it at a certain point. You don’t need to be great at it now. Last question is, when you get to show people SHRMU for the first time, what’s your favorite part of the demo?

Adam Wray: So the favorite part of the demo is just, showing them how we’re extrapolating out things that [00:23:00] they never even realized had value.

someplace else. If you go to our website it starts right off with a video of Skillset, which is our app that actually allows individuals to upload verified data sources, like transcripts, and immediately start to get a sense of where their skill base is and what options are in front of them.

And I just get a kick out of that because I think people just don’t realize, how much, their, how much their value they’re really creating through their journey of life. And they don’t have a clue of how to apply it. And we need to turn that into a quantitative discussion. If we’re going to really open up more opportunity for everybody.

William Tincup: Drops mic, walks off stage. Adam, thank you so much for coming on the podcast. It’s been great. Hey, I really

Adam Wray: enjoyed it, William. It was a great conversation. Thanks for

William Tincup: having me. Absolutely. And thanks everyone for listening until next time. [00:24:00]