August 24, 2023 • 24 mins
Ever wondered how AI can turbocharge your hiring process? Are you curious to know how a deep understanding of individual skills can revolutionize recruitment? Then buckle up, as Adam Wray from AstrumU joins us for a riveting conversation, shedding light on the potential of an AI data platform in skill-based hiring. He delves into how this technology identifies and measures skills. Moreover, he emphasizes its potential to bridge the gap between industry, education, and individuals - creating a clearer path for job seekers, employers, and educators alike.
As we journey through this discussion with Adam, we explore the value of non-traditional degrees and how they aid in nurturing critical thinking skills. We're breaking down biases and challenging the status quo. It's about appreciating the lifelong value of critical thinking, and how AI can quantify it. We also discuss the shelf life of skills and the importance of understanding an individual's unique skill set. Notably, Adam shares how AstrumU uses AI to assess and map these skills to suitable roles, aiding job seekers in making informed career decisions.
In the final leg of our chat, we take a deeper look at AI's role in identifying individual skills and how this can shape recommendations for learning or work. Here's a thought - what if we could use philanthropic dollars to fund training companies connected to HRIS systems, reducing the cost of upskilling individuals? We ponder this innovative idea, and discuss the potential benefits for organizations like the Texas Workforce Commission in understanding how military skills translate to the corporate world. So, join us for this enlightening conversation and get ready to rethink hiring, education, and skill development through the lens of AI.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Welcome to Recruiting Daly's Use Case Podcast, a show
dedicated to the storytellingthat happens or should happen
when practitioners purchasetechnology.
Each episode is designed toinspire new ways and ideas to
make your business better as wespeak with the brightest minds
in recruitment and HR tech.
That's what we do.
Here's your host, WilliamTincup.
Speaker 2 (00:26):
This is William Tincup and you're listening to
the Use Case Podcast.
Today we have Adam on fromAstrumU and we'll be learning
about the business case, so theuse case for why, as prospects
and customers choose AstrumU.
Let's do some introductions.
Adam, would you do us a favorand introduce yourself and
AstrumU?
Speaker 3 (00:44):
Yeah, no, I'd love to .
It's great to be here, and AdamRay, based out of Seattle,
we'll see you on the corner ofAstrumU.
We're an AI data platformcompany that focuses on
understanding and extractingskills of individuals so that
they can understand better whatpathways are available to them
through learning or working toget advancement and opportunity.
Speaker 2 (01:05):
That's nice.
So the skills you're helpingemployees, not necessarily
candidates, right?
Speaker 3 (01:11):
Yeah, so really it's fundamentally, if you look at
the problem statement we'retrying to solve, is there's this
gap between industry andeducation on what's really
created outcomes.
The problem is that theeducators have one point of view
, the HR and the hiring managershave another and the individual
has a third and nobody talksthe same language and leaving
(01:32):
everybody behind, right, and soyou get a lot of inefficiency, a
lot of waste, and so what wewant to do is create, through
data, transparency around thatso that people can start to
understand and ask a simplequestion what education short
form, medium form, long form,etc.
And I leverage to get thenecessary skills to be
successful on this opportunityin front of me, and that could
(01:54):
be a person looking for a newjob, is in workforce training to
traditional degrees, or thatcould be a person within an
employer's environment who's?
sitting here and going.
I want to upscale to the nextopportunity and pathway, and so
we have a data platform that is,a set of API services that
people can build, lego blocksolutions to take on these
(02:16):
problems and ultimately we'realways extracting different
skills so we can measure wherethe individual is and then we're
matching that ultimately to anoutcome through education, to an
ultimate job or role.
And for us, the uniqueness iswhen we focus not on the large
cohorts, like everybody thatlooks isn't the same.
We focus on the individual andwe're after verified data such
(02:40):
as their transcripts, hrinformation, etc.
We can help to build a richprofile of the distances they've
uniquely traveled so they canunderstand their skills.
Speaker 2 (02:50):
And so we're looking at skills where we're looking at
skills three dimensionally, orwe're looking at micro skills,
transferable skills, tangentialskills.
The way that people talk aboutskills is fascinating to me,
especially in this era, rightnow, the last year or two of our
skills based hiring.
So we've seen in our world.
We've seen everything andhiring get flipped on its head
(03:11):
and say we don't care anything,we just care about skills.
It's okay, how do you measureskills?
I had I hand coded HTML and 95.
Do I still have that skill?
Speaker 3 (03:24):
You're an excellent developer.
Still to this day, right HTMLhasn't changed at all.
Speaker 2 (03:30):
No, not at all right.
It's like when the WYSIWYG camealong for HTML.
I'm like I don't know what thisthing is.
This is crazy.
It's crazy All these colors andthings that kind of show me no,
I just need to hand code it.
Speaker 3 (03:44):
But you know what my point is?
Yeah, I was here when you weregoing.
I think that the challenge herereally is everybody says they
want to do skills-based hiringand nobody out knows how to do
it, it's because A.
Nobody really has a common wayin which they look at skills.
Everybody has their own skillsrubric, their own way of
defining.
We think this is the next newchallenge because if we're
(04:06):
really going to continue to growas a country and society and
also create more opportunity forpeople, especially for
marginalized communities, we'regoing to have to figure out a
way to start capturing skillsthat go beyond the pedigree
we're going to need to get tothe people who have other things
that they bring to the tableare highly valued by employers
but they can't be trusted.
(04:27):
So I'll give you a use caseexample Veterans.
Veterans come out, they gothrough an immense amount of
training that is captured inwhat's called the JST, a joint
service transcript, and otherdocuments that are military
transcripts.
But the employers have no wayof understanding.
They have no way ofunderstanding the training they
might have gone through, theexperiences they might have gone
through, and what those skillsmean to that particular role and
(04:49):
opportunity.
So we started a pilot with theArmy at Fort Riley in Kansas and
a Transition Assistance ProgramTAP basically to start breaking
down soldiers JSTs and theirother transcripts that are from
the military, such as ERBs orORBs that capture an Army, all
these things that they do andlearn along the way, which the
(05:11):
world doesn't know what it meansto them, but they're real
valuable skills communication,leadership, logical allocation,
cognitive, analytical skillsetfrom the durable to a technical.
And then we compile those allinto a profile after we actually
extrapolate out the transcriptsthemselves, what their skills
are, and then map itautomatically to a role and
(05:32):
opportunity, so that the soldiercan know two things One, what's
the top three roles I'mavailable for right now in the
civilian world that I didn'trealize my skills were
applicable?
And two, what are the top threeroles I could get to?
That there's a skills gap thateducation could specifically be
recommended to go address, andso that's how we hope to enable
(05:54):
more people to transition backinto civilian workforce, to have
opportunity to scale and grow,because they bring a lot of
value.
But right now society just hasa hard time understanding the
package.
Speaker 2 (06:05):
So, inside of a corporate environment, what is
actually a you?
What is it connected to?
Is it connected, is it thoughtof or connected to the learning
and development?
Is it internal mobility, like Iknow the audience is going to
wonder?
Okay, sounds great, totally getit needed, because it's where
it's the future, of course.
Now, where does it get datafrom and inside of that
(06:28):
environment, the HR platform,etc.
All of the technology that HRhas, and recruiting to the
sub-degree what does it need tobe tied to for folks?
Speaker 3 (06:37):
Yeah, no, that's a great question.
So, obviously, thinking back tothe fact that we're putting
together a data platform with alot of API services that use
cases can be built on, and someof those use cases are
repeatable ones that we'rescaling out, others can be- an
employer or a university doingsomething specific to their
needs, just with different APIs.
What we've been doinghistorically is we've done some
(06:58):
point projects with CERNR andT-Mobile doing an analysis on
skills, building the profiles,feeding them back in, and
they've used that typically intheir HRIS system.
We've actually got experiencethrough that process translating
, breaking down HRIS records,ats records and corporate
learning management systemsrecords, feeding it back in a
scalable, systematized way.
(07:19):
We haven't done yet, and so oneof the things we just announced
less than a month ago was astrategic partnership with CERNR
, which I'm sure you'll knowvery well.
We're working with the CEO andhis number two over there, nick
Schach, specifically on aproject that we're teaming up
the systematized workforcetraining, and what we mean by
(07:39):
that is we want to index all ofthe workforce training type
content based on skills and theindividuals coming out of those
programs and line them up in away automatically to the
opportunity and the role thatthe company has and then feed
those individuals directly intothe HRIS system, and so that
could be a work day or an Oracleover time.
(08:00):
So this is work we're going togo forth and do and we're
actually putting a lot of greatgroundwork right now.
But the goal here is thatcompanies want, if they're going
to do work skills-based hiring,they're going to need to be
able to understandnon-traditional paths where
people are picking up theseskills and working to break that
down form so that they can thenenable.
(08:20):
And then CERN wants to be in aposition to help hiring managers
and HR begin to understand howto do skills-based hiring at
scale.
So you could think, if you playthat over time, I'd expect we'll
see things like certificatesaround skills-based hiring and
skills-based knowledge, so thatpeople can start to say, hey,
the degree is important, butguess what?
(08:41):
It's just part of a journey.
People might bring a lot ofexperience and workforce.
It doesn't directly translate,but if we can break those skills
down through verified and thenwe have a way to process it into
our HR system, then we have away to hire these people and
take advantage of thatopportunity.
Speaker 2 (08:58):
Yeah, I think also in the traditional sense it also
as we dig in we learn what weprobably don't know about those
things.
So you got a degree incommunications.
One would assume you have theskill of writing, but that's
just an assumption.
Speaker 3 (09:14):
Yes, there's some.
I've met a lot ofcommunications majors, yeah.
And I'm not talking about myniece right now, by the way OK,
Sorry, I didn't realize when Iwas getting you right and drove
up the family.
Speaker 2 (09:28):
That's all right.
But, like when you say thenon-traditional, I really love
that because, again, it unlocksa bunch of things where people
didn't take a college route.
Ok, great, there's all kinds ofcool stuff that they've done.
They've garnered these skills.
We can test them.
I have an understanding of whatthey have, what they don't,
what's close to them.
I love the living.
(09:49):
People talk about contiguousskills.
It's like you have this skill,but really you have this skill
over here they just call itsomething different.
Oh, ok, all right, that's cool.
But when you mentioned thetraditional sense, I thought to
myself you know what?
Especially, the further you goaway from a degree, the further
one drifts away from the degreeone way or another.
(10:10):
When I went to the Universityof Alabama, my career services
person told me she said, listen,one in four, this is 91.
So one in four graduate workingtheir major.
And I'm like say that again,25%.
I'm like 25%.
And she goes yeah, and soreally it's about getting a
(10:31):
degree that you like, that youthink that you're going to
thrive in, and then somethingthat's interesting to you.
I'm like OK.
So I picked art history and ofcourse all my family was really
very upset with me for a longtime.
What are you doing?
Why are you going to college?
Why are you spending this moneyon this?
But yeah.
Speaker 3 (10:47):
The Renaissance education.
Speaker 2 (10:49):
It was Ironically enough.
Speaker 3 (10:51):
It served you well.
It served you well, I just put.
Speaker 2 (10:55):
Most of my conversations, especially
business conversations, will bemore creative than they are
about when I was in my MBA, moreabout formulas and platforms,
rubrics and things like that.
So it's actually funny, butanyhow, the traditional stuff.
I'm assuming that we test outof these things and make sure
that they the person with acommunications degree actually
(11:18):
can write.
Speaker 3 (11:19):
So there's.
So I'm gonna answer a question,but I will digress back to your
earlier comment on the Degreein your liberal arts background.
Look, I run an AI company.
I've been, I've been in cloudservices, ai, distributed data
and he's managing and leadingengineering teams and data
science teams.
I've been in this stuff for thelast 20 years, since before
(11:39):
that wasn't an AI, was cloudservices, then it was yeah, asp,
let's go way back.
Speaker 2 (11:49):
Software developed over the end and delivered over
the internet.
What that can't?
Speaker 3 (11:53):
be done.
Speaker 2 (11:54):
Yeah.
Speaker 3 (11:56):
Followed by degree which I had to work two jobs.
To go through school again Isan English degree with a minor
in German and history.
Speaker 2 (12:07):
The humanities.
The irony of the humanitiesdegree is people look down on it
, but it's the.
It's actually the degrees thatmake you think.
Speaker 3 (12:15):
No, I agree I agree.
Speaker 2 (12:16):
Preach critical thinking is.
What else do you need?
You do, yeah, you need a lot ofthings, but critical thinking.
They don't teach that infinance, it's another tactical
skill.
Speaker 3 (12:27):
The biggest example is it's a.
They're teaching you durableskills, yes, that have a period
and the compounding valueproposition as you you walk into
more, whereas when you gofinance or you go become an
engineer, they're teaching youhard skills, but they have a
shelf life.
That's right that shelf lifeexpires quicker and quicker the
(12:49):
farther we go along Going on,whereas durable skills never
expire.
Yeah, it's like more valuable.
Speaker 2 (12:56):
It's like Moore's law applied to skills.
Yeah.
You know saying it's just apace Today.
It's just happening so rapidlythat those skills that you
learned last year they're notout of date but you're just not
being used, especially indevelopment languages.
I found that you find somebodythat's just they've learned,
(13:18):
let's say, python.
They learned Python, got deepinto it, did a bunch of projects
, are really great at it and allof a sudden they're almost out
of work.
Speaker 3 (13:26):
Yeah, many people moved on to something else
couple that up with what islarge language models and
generating To developers, Ithink you're gonna see a lot of
entry-level roles, trinket sizeand options hundred percent.
Speaker 2 (13:39):
I'm sure it's gonna be.
It's gonna be more of aarchitectural type of job where
people again, if I can codeusing generative AI, why do I
need to learn the language?
Yeah, that's actually quitefascinating you.
Speaker 3 (13:58):
I think, like general AI is we.
As soon as some of the stuffwas available, we were all over
it for automation andstreamlining.
But in answer to your earlier,question in regards to how we're
understanding proficiency level.
We have a lot of things we doto get at proficiency.
And we think of this as anever-ending journey of us
continuing to find new ways toparse out data that we can then
(14:21):
extrapolate skills so that wecan then make a matching
learning or workingrecommendation.
And so, underneath that concept, the traditional thought
process is most proficienciesunderstood through direct
assessments Right.
Whereas everything in ourengine is in direct assessment,
we're using the inference-basedengine.
Speaker 2 (14:42):
Oh, interesting, so it can run behind and to the
side of them.
They don't have to do stuff.
Speaker 3 (14:48):
Yeah, exactly.
So, we're trying to use theexperiences they bring,
normalized against otherverified data we can find, to
get a sense of what level ofproficiency first, what skill
they have Right, then over time,what level of proficiency can
we actually ascertain so that wecan then say, hey, this person
really does bring with astatistically relevant signal,
(15:11):
this percentage of probabilityof skills for confidence.
So we are always trying to getit down to a confidence score,
which really is this what weknow of you so far?
Yeah, so, based on the data isand your alignment to this
opportunity, and based on theskills they need, but that we
can see in real time in theindustry.
This is our confidence score.
(15:32):
You're aligned in match.
Speaker 2 (15:33):
When individuals first see their astromuze scores
, are they shocked.
And what's there?
I didn't know I had that skill,or we might know that I should
have more of those skills.
Is there anything that's offthere?
Speaker 3 (15:46):
Yeah, yeah, so it's really been fun with soldiers
because we're starting to reallyhelp them understand.
I can't answer you.
They've been surprised, I think, with a lot of people in
traditional.
We'll probably find over timebut it will vary, but I really
were.
I think we help over time.
It's especially going afteranswering your question
(16:06):
indirectly but, yes, shocked.
My best example of shocked wasthe amount of options available
to Lieutenant Colonel, who ismanaging an entire Army base and
he did not realize just howmany different things he could
do.
He was actually aligned andsuccessful for it because he was
getting ready to matriculateout and he was actually
(16:27):
incredibly concerned that he'sgoing to only be able to flip
burgers.
And this man is running a baseof a billion dollar budget and
I'm like I admit you canactually do a little bit more
than that.
Yeah.
Speaker 2 (16:41):
In fact, we have a job opening.
So a couple of tactical thingsIndustry is there any particular
industry that we care about?
Market in terms of enterprise,global enterprise, mid caps,
small and medium, SMB, etc.
And my dreaded softwarecategory.
I despise software categoriesat them, but I also know that a
(17:01):
lot of these budgets are builtin Excel.
And so the budgets got to comefrom somewhere being called
something.
So let's start with.
Is there any industry wherewe're playing first?
Speaker 3 (17:12):
Yeah, so the industry playing first.
We are focusing when it comesto the HR and corporate side of
the world.
We're focusing heavily onworkforce training.
So this is a real workforcedevelopment challenge in
Conundrum, that the companiesare trying to understand these
people that are coming throughnon-traditional pathways.
How am I going to understandtheir skills, alignments, my
opportunity, and how am I goingto understand which workforce
(17:34):
training program, when everybodysays they're the same great
stuff, which one actually is theright one, aligned to me, based
on quantitative data?
So that's our area of focus,that budgetary work.
This is just being verytransparent back when we think
we've been seeing companies takethe HR teams, take these out of
analytics.
Speaker 2 (17:52):
Yeah.
Speaker 3 (17:53):
But?
But we've also seen anintriguing trend where we're in
some of the conversations we'rehaving with chief people
officers, as well as even theirCEOs, where they're looking at,
because we have a lot ofnonprofit partners that we work
with like, for example, who's alarge profit partner and they
have a lot of foundation there'sactually a discussion around
(18:15):
hey, this stuff is needed atscale.
Maybe we should be fundingthrough the workforce training
companies to buy your asset andconnect it into us, because then
they can tap into theirphilanthropic budgets that
they're already giving forupscaling individuals and
training as well as economicdevelopments in their region.
We're looking at that templateof either how much of it has to
(18:38):
be HR versus how much can it betied back to putting ROI into
philanthropy and they can fundthese training companies to
connect directly into the HRISsystem and the bulk of the cost
actually will go throughphilanthropic dollars.
Speaker 2 (18:54):
Well, no one likes to resell to government or NGOs
things like that.
But I'm thinking about I livein Texas the Texas Workforce
Commission who helps people getjobs.
They help people that areunemployed.
I've interacted with them on alot of different things.
If they could actuallyunderstand, especially those
translatable skills from themilitary to the corporate world,
(19:16):
I think the good that theycould do is exponential.
Speaker 3 (19:20):
I think there is a lot of dollars desperate to be
able to crack these codes.
If we put ROI behind thosedollars, they tie back to not
only the mission components ofhow do we help more people find
the economic mobility, but theimpact in the region, which is
an economic development story ofhow do companies get people
(19:44):
from their backyard.
They have the skills necessaryto do the role so we can grow.
It's a powerful statement.
Speaker 2 (19:49):
If someone's never bought, I might ask you some buy
side questions real quick, yeah, no, love it.
If someone's never boughtsomething like Astramu before,
what are the questions that theyshould be asking of you?
Speaker 3 (20:01):
Yeah.
So the questions they should beasking of me is okay.
Why are you unique inunderstanding these skills to be
able to make theserecommendations versus, say, a
labor market analytics typefirms or firms we've used to
have.
AI, such as an eight-fold AI.
The question always comes downto the simple.
Our approach to this balance isvery unique and you should want
(20:24):
to understand that we'reverifying an individual skill at
a micro level versus the macro.
You truly understand the skillsthey bring to table, match to
your particular role andopportunity, and our objective
is to systematize that over timeso you can ingest that into
your hiring process andultimately even apply it to your
upskilling internal process.
(20:44):
But we aren't doing that yet,but we have aims for it.
Speaker 2 (20:48):
All right, I see a lot of the internal mobility
plays.
They approach skills from atesting perspective.
So they go to the individual.
They test that person, whetheror not it's on a scale of one to
ten, whatever, which is great,but they're not really unpacking
all the other stuff that'saround that Also.
I think that test just my ownopinion.
I think that test has the shelflife.
Speaker 3 (21:09):
Oh, agree, I agree with Laura and I would also be.
It's terrible that,unfortunately, for example, so
we've been some bad economicchallenges in the last year or
two, right, and so the what isthe first thing?
Every company cuts theirtraining budget.
Speaker 2 (21:25):
Yeah, so they immediately slash that because
they consider that extra.
Speaker 3 (21:29):
I think we need to get to a point, based on the
rapid change in technology,where companies are going to
need to understand thatinvesting in their own employees
for upskilling is not an extra.
It is an ROI differentiatorthat is critical to the success
and longevity of your company.
Speaker 2 (21:48):
So when you get, so go finish your thought.
Speaker 3 (21:51):
Yeah, I'm just going to say so.
Speaker 2 (21:52):
We want to put a number to that Vigil so that
they can do targeted it's almostin real time too, so that they
understand, like a market index,that they can see where they're
at with their skills.
But they can also see theyhaven't done something in that
skill.
It's diminished, it's over timethat degrades.
(22:13):
I guess is a better way ofthinking about it is skills can
excel and they can degrade.
And knowing where you are as anindividual, where you are with
those particular skills, is, Ithink, first of all, it's useful
to understand the value youbring, because that could affect
negotiations, compensation,internal mobility, going after a
different job.
So I think it's helpful for theperson to understand that, hey,
(22:35):
I haven't done that particularskill in a long time and it's
degrading.
That's not necessarily a badthing.
You did it at a certain point.
You're great at it at a certainpoint.
You don't need to be great atit now.
The last question is when youget to show, people Ask from you
for the first time what's yourfavorite part of the demo?
Speaker 3 (22:55):
So the favorite part of the demo is just showing them
how we're extrapolating outthings that they never even
realized had value someplaceelse.
If you go to our website, itstarts right off with a video of
Skill Set, which is our appthat actually allows individuals
to upload verified data sources, like transcripts, and
immediately start to get a senseof where their skill base is
(23:17):
and what options are in front ofthem.
And I just get a kick out ofthat because I think people just
don't realize how much theirvalue they're really creating
through their journey of lifeand they don't have a clue of
how to apply it.
We need to turn that into aquantitative discussion if we're
going to really open up moreopportunity for everybody.
Speaker 2 (23:36):
Jobs.
Mike walks off stage.
Adam, thank you so much forcoming on the podcast.
It's been great.
Speaker 3 (23:41):
Hey, I really enjoyed it, William.
It was a great conversation.
Thanks for having me.
Speaker 2 (23:45):
Absolutely, and thanks everyone for listening.
Until next time.
Welcome to Recruiting Daly's Use Case Podcast, a show
dedicated to the storytellingthat happens or should happen
when practitioners purchasetechnology.
Each episode is designed toinspire new ways and ideas to
make your business better as wespeak with the brightest minds
in recruitment and HR tech.
That's what we do.
Here's your host, WilliamTincup.
Speaker 2 (00:26):
This is William Tincup and you're listening to
the Use Case Podcast.
Today we have Adam on fromAstrumU and we'll be learning
about the business case, so theuse case for why, as prospects
and customers choose AstrumU.
Let's do some introductions.
Adam, would you do us a favorand introduce yourself and
AstrumU?
Speaker 3 (00:44):
Yeah, no, I'd love to .
It's great to be here, and AdamRay, based out of Seattle,
we'll see you on the corner ofAstrumU.
We're an AI data platformcompany that focuses on
understanding and extractingskills of individuals so that
they can understand better whatpathways are available to them
through learning or working toget advancement and opportunity.
Speaker 2 (01:05):
That's nice.
So the skills you're helpingemployees, not necessarily
candidates, right?
Speaker 3 (01:11):
Yeah, so really it's fundamentally, if you look at
the problem statement we'retrying to solve, is there's this
gap between industry andeducation on what's really
created outcomes.
The problem is that theeducators have one point of view
, the HR and the hiring managershave another and the individual
has a third and nobody talksthe same language and leaving
(01:32):
everybody behind, right, and soyou get a lot of inefficiency, a
lot of waste, and so what wewant to do is create, through
data, transparency around thatso that people can start to
understand and ask a simplequestion what education short
form, medium form, long form,etc.
And I leverage to get thenecessary skills to be
successful on this opportunityin front of me, and that could
(01:54):
be a person looking for a newjob, is in workforce training to
traditional degrees, or thatcould be a person within an
employer's environment who's?
sitting here and going.
I want to upscale to the nextopportunity and pathway, and so
we have a data platform that is,a set of API services that
people can build, lego blocksolutions to take on these
(02:16):
problems and ultimately we'realways extracting different
skills so we can measure wherethe individual is and then we're
matching that ultimately to anoutcome through education, to an
ultimate job or role.
And for us, the uniqueness iswhen we focus not on the large
cohorts, like everybody thatlooks isn't the same.
We focus on the individual andwe're after verified data such
(02:40):
as their transcripts, hrinformation, etc.
We can help to build a richprofile of the distances they've
uniquely traveled so they canunderstand their skills.
Speaker 2 (02:50):
And so we're looking at skills where we're looking at
skills three dimensionally, orwe're looking at micro skills,
transferable skills, tangentialskills.
The way that people talk aboutskills is fascinating to me,
especially in this era, rightnow, the last year or two of our
skills based hiring.
So we've seen in our world.
We've seen everything andhiring get flipped on its head
(03:11):
and say we don't care anything,we just care about skills.
It's okay, how do you measureskills?
I had I hand coded HTML and 95.
Do I still have that skill?
Speaker 3 (03:24):
You're an excellent developer.
Still to this day, right HTMLhasn't changed at all.
Speaker 2 (03:30):
No, not at all right.
It's like when the WYSIWYG camealong for HTML.
I'm like I don't know what thisthing is.
This is crazy.
It's crazy All these colors andthings that kind of show me no,
I just need to hand code it.
Speaker 3 (03:44):
But you know what my point is?
Yeah, I was here when you weregoing.
I think that the challenge herereally is everybody says they
want to do skills-based hiringand nobody out knows how to do
it, it's because A.
Nobody really has a common wayin which they look at skills.
Everybody has their own skillsrubric, their own way of
defining.
We think this is the next newchallenge because if we're
(04:06):
really going to continue to growas a country and society and
also create more opportunity forpeople, especially for
marginalized communities, we'regoing to have to figure out a
way to start capturing skillsthat go beyond the pedigree
we're going to need to get tothe people who have other things
that they bring to the tableare highly valued by employers
but they can't be trusted.
(04:27):
So I'll give you a use caseexample Veterans.
Veterans come out, they gothrough an immense amount of
training that is captured inwhat's called the JST, a joint
service transcript, and otherdocuments that are military
transcripts.
But the employers have no wayof understanding.
They have no way ofunderstanding the training they
might have gone through, theexperiences they might have gone
through, and what those skillsmean to that particular role and
(04:49):
opportunity.
So we started a pilot with theArmy at Fort Riley in Kansas and
a Transition Assistance ProgramTAP basically to start breaking
down soldiers JSTs and theirother transcripts that are from
the military, such as ERBs orORBs that capture an Army, all
these things that they do andlearn along the way, which the
(05:11):
world doesn't know what it meansto them, but they're real
valuable skills communication,leadership, logical allocation,
cognitive, analytical skillsetfrom the durable to a technical.
And then we compile those allinto a profile after we actually
extrapolate out the transcriptsthemselves, what their skills
are, and then map itautomatically to a role and
(05:32):
opportunity, so that the soldiercan know two things One, what's
the top three roles I'mavailable for right now in the
civilian world that I didn'trealize my skills were
applicable?
And two, what are the top threeroles I could get to?
That there's a skills gap thateducation could specifically be
recommended to go address, andso that's how we hope to enable
(05:54):
more people to transition backinto civilian workforce, to have
opportunity to scale and grow,because they bring a lot of
value.
But right now society just hasa hard time understanding the
package.
Speaker 2 (06:05):
So, inside of a corporate environment, what is
actually a you?
What is it connected to?
Is it connected, is it thoughtof or connected to the learning
and development?
Is it internal mobility, like Iknow the audience is going to
wonder?
Okay, sounds great, totally getit needed, because it's where
it's the future, of course.
Now, where does it get datafrom and inside of that
(06:28):
environment, the HR platform,etc.
All of the technology that HRhas, and recruiting to the
sub-degree what does it need tobe tied to for folks?
Speaker 3 (06:37):
Yeah, no, that's a great question.
So, obviously, thinking back tothe fact that we're putting
together a data platform with alot of API services that use
cases can be built on, and someof those use cases are
repeatable ones that we'rescaling out, others can be- an
employer or a university doingsomething specific to their
needs, just with different APIs.
What we've been doinghistorically is we've done some
(06:58):
point projects with CERNR andT-Mobile doing an analysis on
skills, building the profiles,feeding them back in, and
they've used that typically intheir HRIS system.
We've actually got experiencethrough that process translating
, breaking down HRIS records,ats records and corporate
learning management systemsrecords, feeding it back in a
scalable, systematized way.
(07:19):
We haven't done yet, and so oneof the things we just announced
less than a month ago was astrategic partnership with CERNR
, which I'm sure you'll knowvery well.
We're working with the CEO andhis number two over there, nick
Schach, specifically on aproject that we're teaming up
the systematized workforcetraining, and what we mean by
(07:39):
that is we want to index all ofthe workforce training type
content based on skills and theindividuals coming out of those
programs and line them up in away automatically to the
opportunity and the role thatthe company has and then feed
those individuals directly intothe HRIS system, and so that
could be a work day or an Oracleover time.
(08:00):
So this is work we're going togo forth and do and we're
actually putting a lot of greatgroundwork right now.
But the goal here is thatcompanies want, if they're going
to do work skills-based hiring,they're going to need to be
able to understandnon-traditional paths where
people are picking up theseskills and working to break that
down form so that they can thenenable.
(08:20):
And then CERN wants to be in aposition to help hiring managers
and HR begin to understand howto do skills-based hiring at
scale.
So you could think, if you playthat over time, I'd expect we'll
see things like certificatesaround skills-based hiring and
skills-based knowledge, so thatpeople can start to say, hey,
the degree is important, butguess what?
(08:41):
It's just part of a journey.
People might bring a lot ofexperience and workforce.
It doesn't directly translate,but if we can break those skills
down through verified and thenwe have a way to process it into
our HR system, then we have away to hire these people and
take advantage of thatopportunity.
Speaker 2 (08:58):
Yeah, I think also in the traditional sense it also
as we dig in we learn what weprobably don't know about those
things.
So you got a degree incommunications.
One would assume you have theskill of writing, but that's
just an assumption.
Speaker 3 (09:14):
Yes, there's some.
I've met a lot ofcommunications majors, yeah.
And I'm not talking about myniece right now, by the way OK,
Sorry, I didn't realize when Iwas getting you right and drove
up the family.
Speaker 2 (09:28):
That's all right.
But, like when you say thenon-traditional, I really love
that because, again, it unlocksa bunch of things where people
didn't take a college route.
Ok, great, there's all kinds ofcool stuff that they've done.
They've garnered these skills.
We can test them.
I have an understanding of whatthey have, what they don't,
what's close to them.
I love the living.
(09:49):
People talk about contiguousskills.
It's like you have this skill,but really you have this skill
over here they just call itsomething different.
Oh, ok, all right, that's cool.
But when you mentioned thetraditional sense, I thought to
myself you know what?
Especially, the further you goaway from a degree, the further
one drifts away from the degreeone way or another.
(10:10):
When I went to the Universityof Alabama, my career services
person told me she said, listen,one in four, this is 91.
So one in four graduate workingtheir major.
And I'm like say that again,25%.
I'm like 25%.
And she goes yeah, and soreally it's about getting a
(10:31):
degree that you like, that youthink that you're going to
thrive in, and then somethingthat's interesting to you.
I'm like OK.
So I picked art history and ofcourse all my family was really
very upset with me for a longtime.
What are you doing?
Why are you going to college?
Why are you spending this moneyon this?
But yeah.
Speaker 3 (10:47):
The Renaissance education.
Speaker 2 (10:49):
It was Ironically enough.
Speaker 3 (10:51):
It served you well.
It served you well, I just put.
Speaker 2 (10:55):
Most of my conversations, especially
business conversations, will bemore creative than they are
about when I was in my MBA, moreabout formulas and platforms,
rubrics and things like that.
So it's actually funny, butanyhow, the traditional stuff.
I'm assuming that we test outof these things and make sure
that they the person with acommunications degree actually
(11:18):
can write.
Speaker 3 (11:19):
So there's.
So I'm gonna answer a question,but I will digress back to your
earlier comment on the Degreein your liberal arts background.
Look, I run an AI company.
I've been, I've been in cloudservices, ai, distributed data
and he's managing and leadingengineering teams and data
science teams.
I've been in this stuff for thelast 20 years, since before
(11:39):
that wasn't an AI, was cloudservices, then it was yeah, asp,
let's go way back.
Speaker 2 (11:49):
Software developed over the end and delivered over
the internet.
What that can't?
Speaker 3 (11:53):
be done.
Speaker 2 (11:54):
Yeah.
Speaker 3 (11:56):
Followed by degree which I had to work two jobs.
To go through school again Isan English degree with a minor
in German and history.
Speaker 2 (12:07):
The humanities.
The irony of the humanitiesdegree is people look down on it
, but it's the.
It's actually the degrees thatmake you think.
Speaker 3 (12:15):
No, I agree I agree.
Speaker 2 (12:16):
Preach critical thinking is.
What else do you need?
You do, yeah, you need a lot ofthings, but critical thinking.
They don't teach that infinance, it's another tactical
skill.
Speaker 3 (12:27):
The biggest example is it's a.
They're teaching you durableskills, yes, that have a period
and the compounding valueproposition as you you walk into
more, whereas when you gofinance or you go become an
engineer, they're teaching youhard skills, but they have a
shelf life.
That's right that shelf lifeexpires quicker and quicker the
(12:49):
farther we go along Going on,whereas durable skills never
expire.
Yeah, it's like more valuable.
Speaker 2 (12:56):
It's like Moore's law applied to skills.
Yeah.
You know saying it's just apace Today.
It's just happening so rapidlythat those skills that you
learned last year they're notout of date but you're just not
being used, especially indevelopment languages.
I found that you find somebodythat's just they've learned,
(13:18):
let's say, python.
They learned Python, got deepinto it, did a bunch of projects
, are really great at it and allof a sudden they're almost out
of work.
Speaker 3 (13:26):
Yeah, many people moved on to something else
couple that up with what islarge language models and
generating To developers, Ithink you're gonna see a lot of
entry-level roles, trinket sizeand options hundred percent.
Speaker 2 (13:39):
I'm sure it's gonna be.
It's gonna be more of aarchitectural type of job where
people again, if I can codeusing generative AI, why do I
need to learn the language?
Yeah, that's actually quitefascinating you.
Speaker 3 (13:58):
I think, like general AI is we.
As soon as some of the stuffwas available, we were all over
it for automation andstreamlining.
But in answer to your earlier,question in regards to how we're
understanding proficiency level.
We have a lot of things we doto get at proficiency.
And we think of this as anever-ending journey of us
continuing to find new ways toparse out data that we can then
(14:21):
extrapolate skills so that wecan then make a matching
learning or workingrecommendation.
And so, underneath that concept, the traditional thought
process is most proficienciesunderstood through direct
assessments Right.
Whereas everything in ourengine is in direct assessment,
we're using the inference-basedengine.
Speaker 2 (14:42):
Oh, interesting, so it can run behind and to the
side of them.
They don't have to do stuff.
Speaker 3 (14:48):
Yeah, exactly.
So, we're trying to use theexperiences they bring,
normalized against otherverified data we can find, to
get a sense of what level ofproficiency first, what skill
they have Right, then over time,what level of proficiency can
we actually ascertain so that wecan then say, hey, this person
really does bring with astatistically relevant signal,
(15:11):
this percentage of probabilityof skills for confidence.
So we are always trying to getit down to a confidence score,
which really is this what weknow of you so far?
Yeah, so, based on the data isand your alignment to this
opportunity, and based on theskills they need, but that we
can see in real time in theindustry.
This is our confidence score.
(15:32):
You're aligned in match.
Speaker 2 (15:33):
When individuals first see their astromuze scores
, are they shocked.
And what's there?
I didn't know I had that skill,or we might know that I should
have more of those skills.
Is there anything that's offthere?
Speaker 3 (15:46):
Yeah, yeah, so it's really been fun with soldiers
because we're starting to reallyhelp them understand.
I can't answer you.
They've been surprised, I think, with a lot of people in
traditional.
We'll probably find over timebut it will vary, but I really
were.
I think we help over time.
It's especially going afteranswering your question
(16:06):
indirectly but, yes, shocked.
My best example of shocked wasthe amount of options available
to Lieutenant Colonel, who ismanaging an entire Army base and
he did not realize just howmany different things he could
do.
He was actually aligned andsuccessful for it because he was
getting ready to matriculateout and he was actually
(16:27):
incredibly concerned that he'sgoing to only be able to flip
burgers.
And this man is running a baseof a billion dollar budget and
I'm like I admit you canactually do a little bit more
than that.
Yeah.
Speaker 2 (16:41):
In fact, we have a job opening.
So a couple of tactical thingsIndustry is there any particular
industry that we care about?
Market in terms of enterprise,global enterprise, mid caps,
small and medium, SMB, etc.
And my dreaded softwarecategory.
I despise software categoriesat them, but I also know that a
(17:01):
lot of these budgets are builtin Excel.
And so the budgets got to comefrom somewhere being called
something.
So let's start with.
Is there any industry wherewe're playing first?
Speaker 3 (17:12):
Yeah, so the industry playing first.
We are focusing when it comesto the HR and corporate side of
the world.
We're focusing heavily onworkforce training.
So this is a real workforcedevelopment challenge in
Conundrum, that the companiesare trying to understand these
people that are coming throughnon-traditional pathways.
How am I going to understandtheir skills, alignments, my
opportunity, and how am I goingto understand which workforce
(17:34):
training program, when everybodysays they're the same great
stuff, which one actually is theright one, aligned to me, based
on quantitative data?
So that's our area of focus,that budgetary work.
This is just being verytransparent back when we think
we've been seeing companies takethe HR teams, take these out of
analytics.
Speaker 2 (17:52):
Yeah.
Speaker 3 (17:53):
But?
But we've also seen anintriguing trend where we're in
some of the conversations we'rehaving with chief people
officers, as well as even theirCEOs, where they're looking at,
because we have a lot ofnonprofit partners that we work
with like, for example, who's alarge profit partner and they
have a lot of foundation there'sactually a discussion around
(18:15):
hey, this stuff is needed atscale.
Maybe we should be fundingthrough the workforce training
companies to buy your asset andconnect it into us, because then
they can tap into theirphilanthropic budgets that
they're already giving forupscaling individuals and
training as well as economicdevelopments in their region.
We're looking at that templateof either how much of it has to
(18:38):
be HR versus how much can it betied back to putting ROI into
philanthropy and they can fundthese training companies to
connect directly into the HRISsystem and the bulk of the cost
actually will go throughphilanthropic dollars.
Speaker 2 (18:54):
Well, no one likes to resell to government or NGOs
things like that.
But I'm thinking about I livein Texas the Texas Workforce
Commission who helps people getjobs.
They help people that areunemployed.
I've interacted with them on alot of different things.
If they could actuallyunderstand, especially those
translatable skills from themilitary to the corporate world,
(19:16):
I think the good that theycould do is exponential.
Speaker 3 (19:20):
I think there is a lot of dollars desperate to be
able to crack these codes.
If we put ROI behind thosedollars, they tie back to not
only the mission components ofhow do we help more people find
the economic mobility, but theimpact in the region, which is
an economic development story ofhow do companies get people
(19:44):
from their backyard.
They have the skills necessaryto do the role so we can grow.
It's a powerful statement.
Speaker 2 (19:49):
If someone's never bought, I might ask you some buy
side questions real quick, yeah, no, love it.
If someone's never boughtsomething like Astramu before,
what are the questions that theyshould be asking of you?
Speaker 3 (20:01):
Yeah.
So the questions they should beasking of me is okay.
Why are you unique inunderstanding these skills to be
able to make theserecommendations versus, say, a
labor market analytics typefirms or firms we've used to
have.
AI, such as an eight-fold AI.
The question always comes downto the simple.
Our approach to this balance isvery unique and you should want
(20:24):
to understand that we'reverifying an individual skill at
a micro level versus the macro.
You truly understand the skillsthey bring to table, match to
your particular role andopportunity, and our objective
is to systematize that over timeso you can ingest that into
your hiring process andultimately even apply it to your
upskilling internal process.
(20:44):
But we aren't doing that yet,but we have aims for it.
Speaker 2 (20:48):
All right, I see a lot of the internal mobility
plays.
They approach skills from atesting perspective.
So they go to the individual.
They test that person, whetheror not it's on a scale of one to
ten, whatever, which is great,but they're not really unpacking
all the other stuff that'saround that Also.
I think that test just my ownopinion.
I think that test has the shelflife.
Speaker 3 (21:09):
Oh, agree, I agree with Laura and I would also be.
It's terrible that,unfortunately, for example, so
we've been some bad economicchallenges in the last year or
two, right, and so the what isthe first thing?
Every company cuts theirtraining budget.
Speaker 2 (21:25):
Yeah, so they immediately slash that because
they consider that extra.
Speaker 3 (21:29):
I think we need to get to a point, based on the
rapid change in technology,where companies are going to
need to understand thatinvesting in their own employees
for upskilling is not an extra.
It is an ROI differentiatorthat is critical to the success
and longevity of your company.
Speaker 2 (21:48):
So when you get, so go finish your thought.
Speaker 3 (21:51):
Yeah, I'm just going to say so.
Speaker 2 (21:52):
We want to put a number to that Vigil so that
they can do targeted it's almostin real time too, so that they
understand, like a market index,that they can see where they're
at with their skills.
But they can also see theyhaven't done something in that
skill.
It's diminished, it's over timethat degrades.
(22:13):
I guess is a better way ofthinking about it is skills can
excel and they can degrade.
And knowing where you are as anindividual, where you are with
those particular skills, is, Ithink, first of all, it's useful
to understand the value youbring, because that could affect
negotiations, compensation,internal mobility, going after a
different job.
So I think it's helpful for theperson to understand that, hey,
(22:35):
I haven't done that particularskill in a long time and it's
degrading.
That's not necessarily a badthing.
You did it at a certain point.
You're great at it at a certainpoint.
You don't need to be great atit now.
The last question is when youget to show, people Ask from you
for the first time what's yourfavorite part of the demo?
Speaker 3 (22:55):
So the favorite part of the demo is just showing them
how we're extrapolating outthings that they never even
realized had value someplaceelse.
If you go to our website, itstarts right off with a video of
Skill Set, which is our appthat actually allows individuals
to upload verified data sources, like transcripts, and
immediately start to get a senseof where their skill base is
(23:17):
and what options are in front ofthem.
And I just get a kick out ofthat because I think people just
don't realize how much theirvalue they're really creating
through their journey of lifeand they don't have a clue of
how to apply it.
We need to turn that into aquantitative discussion if we're
going to really open up moreopportunity for everybody.
Speaker 2 (23:36):
Jobs.
Mike walks off stage.
Adam, thank you so much forcoming on the podcast.
It's been great.
Speaker 3 (23:41):
Hey, I really enjoyed it, William.
It was a great conversation.
Thanks for having me.
Speaker 2 (23:45):
Absolutely, and thanks everyone for listening.
Until next time.
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