April 1, 2025 • 29 mins
The workplace is evolving rapidly, with one-third of job skills changing every three years. In this episode, host David Rice speaks with Cole Napper, VP of Research at Lightcast, about how AI, automation, and demographic shifts are reshaping the labor market. As blue-collar industries face worker shortages while knowledge jobs undergo disruption, organizations must rethink skills development and workforce strategies.
Cole shares insights on the future of work, from shifting career paths to the rising importance of critical thinking. With mastery giving way to adaptability, how can workers and businesses stay ahead? Tune in for a deep dive into the changing world of skills and employment.
Related Links:
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- Connect with Cole on LinkedIn and Substack
- Check out Lightcast
- Cole’s podcast - Directionally Correct
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Cole Napper (00:00):
Everyone who's building things with AI and
automation, for the most part,is spending their time on
how do you automate coding?
How do you automate all thedifferent creative tasks
that have primarily beendone by knowledge workers?
And so those skill setsare being pushed to
change very rapidly.
And the reality is, I thinkorganizations are working
on a hope and a prayer thatautomation will just fix
(00:23):
things quicker than theneed for skills to change
will be able to catch up.
David Rice (00:29):
Welcome to the People Managing People podcast.
We're on a mission to builda better world of work and to
help you create happy, healthy,and productive workplaces.
I'm your host, David Rice.
My guest today is Cole Napper.
He's the Vice President ofResearch, Innovation, and
Talent Insights at Lightcast.
He's also the host orco-host of the "Directionally
Correct" podcast.
(00:51):
We're going to be talkingabout skills, how they're
shifting, and how weunderstand them, and what it
all means for the workplace.
So Cole, welcome.
Cole Napper (00:58):
Yeah.
Thanks for having me, David.
David Rice (00:59):
No problem.
So we are talking about skillsand people analytics today.
I want to start by askingyou a sort of, it's a little
bit of a ridiculous question.
I guess I want to ask, howdo you define the way things
are changing around skillsand how we view them from
an analytics perspective?
So if you had to givethis period in labor
market intelligence anickname, what would it be?
Cole Napper (01:21):
I was thinking about this earlier.
This is probably not theperfect answer to the question,
but I thought it was clever.
Is with the real talentintelligence, please stand up
because I feel like everybodyis saying they do talent
intelligence nowadays andfrom an analytics perspective,
that can be frustrating.
Because in my mind, talentintelligence actually means
(01:42):
something and a lot of peoplewho say they're doing it aren't
doing the thing that I mean.
And so when I look at it, Ilook at is like, how can you
use labor market information,labor market insights internally
on your skills and the makeupand the composition of your
workforce to create realinsights to drive change
and value for organizations.
That's as simple of anexplanation as I can give
(02:04):
and If you're doing thosethings, you're doing it right.
If you're not doing thosethings, I don't know what
you're doing, but it'snot talent intelligence.
David Rice (02:12):
That's a good answer.
I like that one.
So with your work withLightcast, you've all
released a report recently.
It's called the Speedof Skill Change.
And I'm curious because in thatreport, I looked it over and
it's noted that the average jobhas seen one third of its skills
change in the last three years.
And that speed appears to begetting more intense, more fast.
(02:33):
So bit of an existentialquestion here, if this keeps
up, in your opinion, are we, dowe get to a place where mastery
of a skill is like never quiteachieved or even possible?
Like most skills due tothe pace of change, do they
exist long enough to master?
Cole Napper (02:49):
I would even flip the question of do
we even master skills thatwe have today or have we
mastered them in recent years?
And I would argue that theanswer is largely, we get to
a point of diminishing returnswhere it's good enough, but
we never really get to masteryanymore on most things.
And so to reference thatreport, so Lightcast had done
(03:10):
some research between 2019 and2022 that had shown, roughly
a third of the skills thatwere going to get disrupted
over that period of time.
And then we did some researchfrom 2022 through 2025 and
found that not only was itgetting disrupted, they were
getting disrupted faster thanbefore, which means that the
pace of change is accelerating.
(03:30):
And I'm sure we're goingto talk about AI at some
point today, but thatplays a role, but honestly,
these changes predated AI.
So we're already on thistreadmill right now.
And the question is,what do we do about it?
David Rice (03:42):
Yeah, that's a great question.
One that everybody'sthinking about, obviously.
I don't care whatfield you're in.
You all also developedlike a skills library.
It's got more than Ithink, 32,000 skills in it.
And I find this interestingbecause the positioning behind
it that I see on like thewebsite, and I leave, I even
looked at the API that youall have created, which is
(04:03):
a really interesting tool.
But it's that we all needa common language to speak
in order to understandskills and hiring needs.
Take me through the refinementand the development of that
common language at a high levelwhere your internal skills
language makes sense againstwhat's in the labor market.
Cole Napper (04:21):
It's an interesting concept.
So people throw around terms,and I'll be honest, a lot
of times I didn't even knowwhat they meant when they
were throwing it around,like skills taxonomies.
I was like, whatdoes that even mean?
And the reality is, how doyou group things together?
Think about the tree oflife from like, how all the
different animals are related.
That's just a fancy wayof saying a taxonomy.
(04:43):
The same thing exists inorganizations with skills.
So you have a particularskill, and then you roll
it up a level, and maybeyou call that a competency.
And then you roll it up anotherlevel, and you call that a
function like finance, right?
And you roll it upanother level, and
you've got an industry.
And so just a skill is just thefundamental unit of different
ways of rolling up informationabout your organization
(05:06):
and the talent place wherethey're in your organization.
When I think about thatopen skills library, what
that's meant to do is toposition Lightcast because
it's open source, it's free.
Anybody can go take it.
You mentioned the API calls.
Anybody can call thatAPI and put it into
your own organization.
What it's meant to do is tobe the universal translator.
What does that mean?
(05:27):
So let's say you've gota particular job title
or job posting at yourorganization, which has a
collection of skills in it.
But those, the terminology isdistinct to your organization.
So what do we do?
We take that terminology that'sdistinct to your organization.
We transfer it into ouruniversal language, right?
But guess what?
(05:48):
That's not good enoughbecause chances are
you use Workday or UKG.
They have their own language.
So you want your job titleto work with Workday.
If you put it through ouruniversal translator, we
already work with all ofthose vendors to translate
into their language.
And so fundamentally, our openskills philosophy is embedded
(06:10):
into basically almost allof the HR technology market.
A lot of our, let's call themfrenemies, our competitors,
they even use our openskills taxonomy because
it is so open source.
And so I would say weare the universal skills
language that's out there.
And that really positionsus to move from what people
call skills taxonomiesto skill ontologies.
(06:33):
So a skill ontology is thenext level is to say, what
are the emerging skills?
How are skills transforming?
What skills are diminishing?
How do those relate tothe whole body of work?
And I'm not going to getoverly technical today,
but that is the next foraythat we are getting into.
We're leading thepack in that space.
David Rice (06:50):
That's interesting you said that about the people
talk about skills taxonomy.
If you don't have a backgroundin information architecture
at all, taxonomy is oneof those words that I'm
I think people confuse itfor a list, essentially.
Cole Napper (07:03):
But it's not what it is, but that is
a common confusion, yeah.
David Rice (07:08):
Yeah, because it's one of those phrases people do
like to use, but I'm not exactlysure they know what it means.
Cole Napper (07:14):
Yeah, my grocery taxonomy, not my grocery list,
David Rice (07:17):
One of the things the report highlights, and I
think this is something thatfolks are starting to realize
more and more, is that A lot ofthe change that's coming in the
skills market, it's not goingto impact blue collar jobs a
great deal, but it is goingto really impact like white
collar jobs and STEM fields.
Those are going to be changingthe most over the next year
or two, and that's going tocreate a lot of disruption.
(07:39):
We've been talking aboutupskilling and reskilling
since before the pandemic.
As long as I've beencovering HR, we've been
talking about this, right?
But it seems like a lot oforgs haven't quite gotten
it right or never reallyinvested in it sufficiently.
How prepared do you feel thewhite collar workforce is to
shift with the changes thatare coming in the skills
market in the next year or two?
Cole Napper (08:00):
I'll even go upstream of that a little bit
because you talked about thespeed of skill change report.
We talk about a tale oftwo labor markets in that
report, and you talkedabout a little bit.
The two labor markets isessentially knowledge workers
versus people who do thingsin the physical world or what
people used to call blue collarversus white collar jobs.
It's not a perfect designation,but let's say that for
(08:21):
the sake of argument.
There's a reason why it'snot to say that the blue
collar jobs can't change.
They do see disruption.
Automation plays a role inblue collar jobs all the time.
It's just as a society,we just haven't chosen to
spend our investments there.
Right now, everyone who'sbuilding things with AI and
automation for the most part,is spending their time on
(08:42):
how do you automate coding?
How do you automate programming?
How do you automatevideo creation?
How do you automate all thedifferent creative tasks
that have primarily beendone by knowledge workers?
And so those skill setsare being pushed to
change very rapidly.
And the reality is, I thinkorganizations are working
on a hope and a prayer thatautomation will just fix
(09:04):
things quicker than the needfor skills to change will
be able to catch up, right?
That's just a interestingposition that we're in as a
society right now, and I knowwe're going to talk more about
some of the demographic shiftsthat are coming as a part of
this conversation, but really,it's going to be a forcing
function where we're going tobe coming into new territory
that we've never been before,and we don't have a playbook for
(09:26):
navigating, and so I don't thinkorganizations have a playbook
for navigating the skillschanges that are going on right
now, and I think they're justworking on hopes and prayers.
David Rice (09:35):
Yeah.
It's interesting, like reallyaround AI in particular, we
always talk about even onthis podcast, we've had guests
on and we talk about puttingin guardrails and, trying to
develop like a training aroundAI, but like this thing's
changing fast all the time.
It gets better with everyiteration or it gets
differently, at least.
Can do something new is it,there really is no playbook
(09:57):
that anybody has any experiencedeveloping around this.
This isn't like a social media.
Cole Napper (10:02):
It's an interesting point you made earlier about,
are we ever going to seemastery of skills again?
And then what were thetrends that were going on
in L&D over the last years?
It's all about likemicro learning and
giving people learning.
Do you really think you're goingto get to the point of mastery
through watching a few videos?
David Rice (10:18):
No, that's exactly it.
Cole Napper (10:19):
And so it's here's how to get to good
enough at a particularskill to be serviceable.
And now, I think the goal is,or the hope is that if you
can do it, if automation canplay a role, maybe it will
help you get to that pointof being good enough faster.
David Rice (10:35):
You mentioned there, when we were just talking
about the demographic shifts,I read another report that
Lightcast did, and listeners,they've got some good reports,
you should check these out.
I found it interesting to seethe data behind it and the
impact boomers leaving theworkforce is going to have.
And there's a lot ofthemes that we're familiar
with at play here, right?
Like for all the concernabout automation, this
(10:56):
kind of suggests that it'sgoing to be a while before
a real ability to replacepeople is in place, right?
And I think the data shows thevalue of a college education
may be fading and impact ofimmigration policy is massive.
So we're seeing all thesechanges, record levels of
prime age men not participatingin the workforce, right?
There's a lot going on hereand I'm curious, so forgive
(11:17):
this two part question, butWhat were some of the big sort
of takeaways from that reportfor you, and particularly in
terms of how demographics andskills intersect, but also
did any of it surprise you?
Cole Napper (11:29):
Yeah, well, there's so much surprising
information in that report.
It's called The Rising Storm,and I don't want to take
credit for it because thatgreat research was done before
I joined Lightcast by someof my colleagues like Ron
Hedrick, who's just amazing.
The thing that stands out themost to me is a saying that's
known in demography, whichis demographics is destiny.
And supply and demand do weirdthings in the labor market.
(11:54):
And let's go in the way backmachine, because a lot of that
report is talking about thedifferent generations and when
they entered the workforce.
So you've got the baby boomers,you've got Gen X, you've got
millennials, and then nowGen Z entering the workforce.
And one of the things thatyou find is, we've been
talking a lot about skills.
Skills, People do have theability to change, but it's
not very often you see a rocketscientist who becomes a doctor,
(12:17):
who becomes an airline pilot,who moves from a completely
different discipline to another.
You could say that most people'sdisciplines are relatively
stable throughout their career.
And if you look at that meansthat disciplines are destiny.
If demographics are destiny.
And so just take eachgeneration and say, okay, what
percentage of the baby boomergeneration was college educated
(12:39):
versus had blue collar jobs?
It was a much lower percentagethan the millennial generation.
And you could almost saythat those demographics
inverted where millennialshad a much higher degree of
college education than thebaby boomers before them.
So what does that mean?
That means is as the babyboomers exit the workforce
(13:00):
a little by little every dayand every year, their makeup
and their composition ofcollege educated versus non
college educated gets replacedby a completely different
makeup of individuals.
And what that does is now you'regetting to a point where you
have an oversupply of peoplewith college educations and
(13:20):
an under demand for thosetype of roles because of the
tale of the two labor marketsthat we mentioned earlier.
And When I was growingup, I'm sure the same
thing happened for you.
You were told like getting acollege education was like your
ticket to the middle class,your ticket to the American
dream, yada, yada, yada.
That was in a time where acollege degree was a minority
(13:43):
thing to be occurring and havinga non college degree, that
was the majority population.
That's actuallyinverting right now.
What you might find isover the next few years.
And we just released areport yesterday called
the workforce risk outlook.
So it is the next instantiationof the rising storm.
And what we did is weclassified all the fortune
(14:04):
1000 companies by their riskprofile of their industry,
by the occupations that theyhad, by the, they have the
markets in which they operate.
And the AI disruption that couldbe occurring to that particular
organization, and we scoredall of them on a risk index.
What did we find?
(14:24):
The top five industries thatare the most at risk are retail,
health care, constructionand manufacturing, right?
So you've got the top five.
Guess what are all ofthose industries are?
They're blue collar industries.
Which means that if you lookat the supply and demand
pressures going forward, youcould see the possibility.
(14:45):
I think we've already started tosee this in the last few years,
that you're going to see wagesrise in those professions and
potentially people with collegedegrees moving into those
professions because there's ahigh demand and a low supply.
David Rice (14:59):
I wonder if this will mean the end of tipping.
No, I'm just kidding.
Cole Napper (15:04):
I'll tell you something truly wild
about the workforce riskreport that came out.
Is if you truly see thelevel of shortages that
we are projecting, which Ithink you will see unless
You just see some miraculousgains in automation and
things like fast food.
I could see an instance inthe next few years where
fast food organizationsstart putting workers under
(15:24):
contract and giving themsigning bonuses, right?
Where they say, wow, youcome here, sign a three year
contract and we'll give youa 30,000 signing bonus today.
And what that will do is thatwill lock them in because
the one prescription that wefound, which came from the
rising storm, but we have justcontinued it with the workforce
risk is the organizations whoare creative and proactive will
(15:48):
be the winners because there aretruly some zero sum dynamics.
In a local market, if youhave an Amazon distribution
center and a McDonald's fastfood chain, they're sourcing
for the same talent, there'sno more talent to be had
in that particular market.
So if McDonald's wins,Amazon loses and vice versa,
whoever strikes first andis most proactive will be
(16:10):
the winners in these talent.
Talent war, we alwaystalked about the war for
talent that always appliedto the knowledge workers.
Now the war for talent isgoing to be inverting for
more of the retail, themanufacturing, the construction
industries and the like.
David Rice (16:24):
It's funny, it's what just came into my mind
just now is that old sayingplumbers rule the world.
It's just wait, they might.
Cole Napper (16:32):
Oh man.
I've been saying that since allthe AI started, stuff started
coming out, it's like The lastprofession to be automated
is going to be plumbing.
It really is.
David Rice (16:40):
Guaranteed.
One of the, with automationstaying on long that vein
is one of the things I tookfrom the report was, it
highlighted some key pointsaround how far automation is
from being able to close thegaps in terms of workforce
shortage that's coming.
There's a quote in there fromsome researchers at Goldman
Sachs and MIT, and they weresaying, there's nothing humans
do as a meaningful occupationthat generative AI can now do.
(17:04):
And I think about, customerfacing roles, there's this
sort of like disconnectbetween management's perception
of what AI can do and whatcustomers probably wanted to do.
So I'm curious from yourperspective, when we look
at AI and how it's beingintegrated into people's
work, how far it off it isin terms of replacing people
(17:26):
in a thoroughly satisfactoryway, we'll say, do you think
we've reached the point wherethe hype is going to start to
fade that old hype cycle graph?
Are we past the peak ofinflated expectation, no?
Cole Napper (17:37):
We're not in the trough of disillusionment
yet, but we have definitely,I think reached peak hype.
One of the things that Iwant to reframe and I think.
Anthropic actually earlierthis week released a
report about the impactof AI on different skills.
We're actually talking aboutpartnering with them on some
research because they usesome of our data through Onet.
(17:58):
So Lightcast supplies all thedata to Onet and they use Onet
data to do the classification.
So I was like, basicallythey're using Lightcast data,
which I thought was cool.
But one of the things thatyou find is AI doesn't
replace roles, but itdoes replace skills.
And so then if you realize it'slike how much of a particular
skill does a role complete?
(18:18):
And the question we have toask ourselves is, at what point
do the number of skills addup to a role being replaced?
Because as far as I can tell,other than the companies
that are trying to get, dopublicity stunts like Klarna
and Salesforce and Workday evento an extent are saying, we're
laying off people and replacingthem with AI, which, if you
(18:39):
read the fine print or if you doany level of digging, you find
out that's not actually true.
And I think from that Anthropicresearch, I think the role that
they found that had the mostskills that were being replaced
right now, it was only like 20%.
And I think it was a computerscientist, and most of them
were hanging around 6%, 5%.
And so the wholeconversation has been
(18:59):
replacement or augmentation.
Right now we're in theaugmentation phase.
Now that said, once weget through the trough of
disillusionment to the slopeof enlightenment, which is
what is coming in the nextfew years, you're going to
see a lot more skills beingreplaced by AI, which means
as a percentage, more andmore roles will be at risk.
(19:21):
And so it's our job as,forward thinking professionals
to say, what are theimplications of that?
How can we be proactive?
How can we use thisas an opportunity?
One of the things thatwe actually found in our
workforce risk report thatI just mentioned earlier,
is we actually, we thoughtabout AI disruption as a
positive, not a negative.
(19:43):
Because if you realize that youhave a human being shortage,
which is what is coming in thenext few years, you actually see
AI is giving you optionality.
Because you may be losinghuman beings through
immigration policy.
You may be losing humanbeings through not as
many people being born.
You may be losing humanbeings through the number of
(20:03):
retirements that are happening.
And all of those aredecreasing your optionality.
So AI actually gives youanother tool in your tool
chest to try to increaseyour optionality and decrease
your risk as a consequence.
David Rice (20:15):
When you start doing the math, I was
like, actually, this mightbalance out in some ways.
Cole Napper (20:19):
In some ways, yeah.
David Rice (20:21):
I listen to your podcast.
It's really good.
And I highly recommend it toall our listeners out there.
You should check it out.
Cole Napper (20:26):
It's a lot more funny than this
conversation, I promise.
David Rice (20:29):
Yeah.
You guys do a lotmore joking than I do.
Yeah.
I enjoyed the recentepisode with Mark Efron.
In it you ask him a question andI want to ask you that question.
There's a lot of hype aroundideas of skills based work
and deconstructing work wherewe strip away roles and we
all allocate our skills todifferent projects and jobs and
(20:50):
people apply a skill in thisrole and a skill in that role.
But Mark points outin the episode, right?
People don't want that.
They want stability.
In a lot of ways, HR folkshave been cooking this sauce
for a long time, right?
He brought up competency modelsand what's the sort of right
level of granularity here.
I'm curious, in your opinion,is the juice worth the
(21:11):
squeeze on skills based work?
And if so, how's my LinkedIngoing to capture all of that
in a way that makes senseto anybody looking at it?
Cole Napper (21:19):
The answer is your LinkedIn isn't going
to capture all of that.
And that's the reason whyyou've seen a lot of company
have fits and starts whenthey try to become skills
based organizations, right?
That's the reality.
Now, I don't personallysubscribe to this notion
that all work is going toget deconstructed and all
we are as human beings arecollections of skills and
(21:41):
that's all we'll ever be.
That's not my modus operandi andwe'll all be 1099 independent
contractors who kind of act likeUber drivers except where we
work, it'll just be like Uber.
I don't think that's thefuture of work, because
people have needs, and we dohave needs for continuity.
That said, even in a worldof disruption, there are
skills that are on thedownswing because they're
(22:03):
rife to be automated, butthere are skills that are
very much on the upswing.
The number one skill, okaywe've done some research
internally, we call it ourdisruptive skills matrix.
You know what the numberone skill on the upswing is?
Critical thinking, everyorganization should be trying
to talent hoard right now andbuild and create modes around
(22:25):
is developing critical thinkingin house because the people who
attain that level of skill incritical thinking are going to
be the disruptors of the future.
And so I always lookat it through, there's
really three lenses.
There's core skills.
There's skills that areexpanding and there's skills
that are diminishing, right?
If you're a skill basedorganization, a lot of the core
(22:48):
skills Are really unsatisfying.
And what I mean by that islet's say you're in marketing.
You know what a coreskill to marketing is?
Marketing.
Right?
No one thinks of a hugeskills transformation or
teaching marketing as askill to marketing people.
All right.
So really what, or all thefun happens at the tails.
It happens at what's diminishingand what's expanding.
(23:11):
What's expanding rightnow is critical thinking.
What's diminishing is thingslike Microsoft Word and
Microsoft Excel and all thethings that used to be a
core skill, but now can behighly automated through AI.
And so that's whatorganizations, why I think
it does become somewhatexistential to be a skills
based organization, becauseyou have to know What are
(23:34):
the skills that are growingand what are the skills that
are going away and makingthe adjustments accordingly?
David Rice (23:39):
Awesome.
Before we go, there's twothings that I always like to
do as we wrap up these shows.
First is, I want to giveyou a chance to tell people
about where they can connectwith you and find out more
about what you got going on.
Cole Napper (23:49):
Yeah man, I got so much stuff going on.
You can listen to my podcast,Directionally Correct, and
we have a newsletter onSubstack under the same name.
You can find me on LinkedIn.
I'm also writing a book rightnow on the usage of people
analytics, workforce planning,and talent intelligence with AI.
So that's very top of mind.
It'll be coming outlater this year.
And I'll be referencing a lotof the research that we talked
(24:11):
about today in that book.
You can check us out atLightcast with our research
reports on the speed ofskill change, the rising
storm, the workforce risk.
And yeah, just find me wherever.
David Rice (24:23):
The last thing, we have a tradition
here on the podcast.
You get to ask me a question.
So turn it over toyou, ask me anything.
Cole Napper (24:30):
I was like, David, isn't going to take it
easy on me today and ask mesome of the hard questions.
So I'm going to askhim the hard question.
And so it's a two parter.
What makes HR relevant in fiveyears and knowing what you know
now, what would make HR morerelevant in the C-suite today?
David Rice (24:47):
Oh, wow.
You weren't kidding.
Okay.
Cole Napper (24:49):
I know.
You made me explainwhat a taxonomy was, so.
David Rice (24:56):
Fair enough.
That's fair.
I think right now we're stillin that phase of like HR finding
its business footing all thetime and like being comfortable
being in the room when the big,the C-suite table essentially.
Cause I think for a longtime, HR was passed over
or it had this littlechip on its shoulder.
And a lot of folks aremoving into a space where
(25:16):
that's not the case anymore,but it's still getting
comfortable with your position.
I talked to a lot of leaderswho have had imposter
syndrome pretty hard.
They've learned a lotof lessons the hard way.
So I think we're still inlike this maturing phase
of HR is like a clearbusiness function and not
being like mushy about it.
(25:38):
In five years, I think, thething is I think that this
transition with the technologyfalls squarely into the HR
court more than any otherC-suite position, right?
It's essentially HR's job tonavigate how people are gonna be
working in five, ten years andwhat Like, what is our purpose?
(25:59):
Cause we will get to a placewhere I'm sure one day,
I'm hoping that I'm retiredby then, but one day it's
going to be smarter than us.
It's gonna be able to domost anything better than us.
And what is our purpose?
I think like navigating thatand all the other external
factors that are changing theway business gets done, the
way work gets done, HR sitting.
(26:20):
Basically in thequarterback spot.
Cole Napper (26:22):
Yeah.
So then the question Ihave is, are we ready
to be the quarterback?
Because some of the peoplethat are the quarterbacks
right now, they're going toretire in the next five years.
Do we have the benchthat's ready to be the
quarterback as well?
David Rice (26:36):
Yeah.
I'm actually a littleencouraged in that area.
I think there's a lot offorward thinking people right
now working in the HR space.
A lot of people who have,they haven't come from the
world where it was necessarilylike a compliance function.
You know what I mean?
Because you talked to a lotof older HR folks are like
the job before 2015 was likea completely different job.
(26:58):
And now.
If you've gotten into it andyou've become like a director
level or above in the lastcouple of years, that's a
completely different functionthan what somebody did.
And it's required you to bemore forward thinking and
more data centric and thinkingabout like people as a whole
human being, not just theeight hours that they're there.
So I think that the, allof that is going to serve
(27:20):
them well as they try tonavigate this transition.
Cole Napper (27:23):
I've been talking about this for years because I
have a background in analytics,so I've been an internal
analytics practitioner mostof my career in HR, and people
always talk about, how doyou build the capability in
people to be digitally nativeand to use data on the job?
And I say, it's agenerational problem.
The people who never hadto use it, they're going
to age out eventually.
The people who've used ittheir whole career, they're
(27:44):
moving more and more intoleadership every year.
And so actually I seeexactly what you see there,
which is you're going tohave people start to age in
to being digitally nativeat the leadership ranks.
David Rice (27:55):
Yeah, exactly.
I'm not too worriedabout it as a function.
Cole, thanks forcoming on today.
I really appreciate it.
This was a great chat.
I really enjoyed this.
Cole Napper (28:04):
Fantastic, man.
Thanks for having me.
David Rice (28:06):
All right listeners, until next time, be sure
to subscribe to the PeopleManaging People newsletter
if you haven't already.
You'll get all the latestinsights and podcast
interviews, articleswe're writing, everything
straight to your inbox.
It's a good newsletter.
Until next time.
Enjoy a sports game.
Just relax.
Cole Napper (28:23):
Yeah.
Take it easy.
David Rice (28:24):
Have a decaf.
Everyone who's building things with AI and
automation, for the most part,is spending their time on
how do you automate coding?
How do you automate all thedifferent creative tasks
that have primarily beendone by knowledge workers?
And so those skill setsare being pushed to
change very rapidly.
And the reality is, I thinkorganizations are working
on a hope and a prayer thatautomation will just fix
(00:23):
things quicker than theneed for skills to change
will be able to catch up.
David Rice (00:29):
Welcome to the People Managing People podcast.
We're on a mission to builda better world of work and to
help you create happy, healthy,and productive workplaces.
I'm your host, David Rice.
My guest today is Cole Napper.
He's the Vice President ofResearch, Innovation, and
Talent Insights at Lightcast.
He's also the host orco-host of the "Directionally
Correct" podcast.
(00:51):
We're going to be talkingabout skills, how they're
shifting, and how weunderstand them, and what it
all means for the workplace.
So Cole, welcome.
Cole Napper (00:58):
Yeah.
Thanks for having me, David.
David Rice (00:59):
No problem.
So we are talking about skillsand people analytics today.
I want to start by askingyou a sort of, it's a little
bit of a ridiculous question.
I guess I want to ask, howdo you define the way things
are changing around skillsand how we view them from
an analytics perspective?
So if you had to givethis period in labor
market intelligence anickname, what would it be?
Cole Napper (01:21):
I was thinking about this earlier.
This is probably not theperfect answer to the question,
but I thought it was clever.
Is with the real talentintelligence, please stand up
because I feel like everybodyis saying they do talent
intelligence nowadays andfrom an analytics perspective,
that can be frustrating.
Because in my mind, talentintelligence actually means
(01:42):
something and a lot of peoplewho say they're doing it aren't
doing the thing that I mean.
And so when I look at it, Ilook at is like, how can you
use labor market information,labor market insights internally
on your skills and the makeupand the composition of your
workforce to create realinsights to drive change
and value for organizations.
That's as simple of anexplanation as I can give
(02:04):
and If you're doing thosethings, you're doing it right.
If you're not doing thosethings, I don't know what
you're doing, but it'snot talent intelligence.
David Rice (02:12):
That's a good answer.
I like that one.
So with your work withLightcast, you've all
released a report recently.
It's called the Speedof Skill Change.
And I'm curious because in thatreport, I looked it over and
it's noted that the average jobhas seen one third of its skills
change in the last three years.
And that speed appears to begetting more intense, more fast.
(02:33):
So bit of an existentialquestion here, if this keeps
up, in your opinion, are we, dowe get to a place where mastery
of a skill is like never quiteachieved or even possible?
Like most skills due tothe pace of change, do they
exist long enough to master?
Cole Napper (02:49):
I would even flip the question of do
we even master skills thatwe have today or have we
mastered them in recent years?
And I would argue that theanswer is largely, we get to
a point of diminishing returnswhere it's good enough, but
we never really get to masteryanymore on most things.
And so to reference thatreport, so Lightcast had done
(03:10):
some research between 2019 and2022 that had shown, roughly
a third of the skills thatwere going to get disrupted
over that period of time.
And then we did some researchfrom 2022 through 2025 and
found that not only was itgetting disrupted, they were
getting disrupted faster thanbefore, which means that the
pace of change is accelerating.
(03:30):
And I'm sure we're goingto talk about AI at some
point today, but thatplays a role, but honestly,
these changes predated AI.
So we're already on thistreadmill right now.
And the question is,what do we do about it?
David Rice (03:42):
Yeah, that's a great question.
One that everybody'sthinking about, obviously.
I don't care whatfield you're in.
You all also developedlike a skills library.
It's got more than Ithink, 32,000 skills in it.
And I find this interestingbecause the positioning behind
it that I see on like thewebsite, and I leave, I even
looked at the API that youall have created, which is
(04:03):
a really interesting tool.
But it's that we all needa common language to speak
in order to understandskills and hiring needs.
Take me through the refinementand the development of that
common language at a high levelwhere your internal skills
language makes sense againstwhat's in the labor market.
Cole Napper (04:21):
It's an interesting concept.
So people throw around terms,and I'll be honest, a lot
of times I didn't even knowwhat they meant when they
were throwing it around,like skills taxonomies.
I was like, whatdoes that even mean?
And the reality is, how doyou group things together?
Think about the tree oflife from like, how all the
different animals are related.
That's just a fancy wayof saying a taxonomy.
(04:43):
The same thing exists inorganizations with skills.
So you have a particularskill, and then you roll
it up a level, and maybeyou call that a competency.
And then you roll it up anotherlevel, and you call that a
function like finance, right?
And you roll it upanother level, and
you've got an industry.
And so just a skill is just thefundamental unit of different
ways of rolling up informationabout your organization
(05:06):
and the talent place wherethey're in your organization.
When I think about thatopen skills library, what
that's meant to do is toposition Lightcast because
it's open source, it's free.
Anybody can go take it.
You mentioned the API calls.
Anybody can call thatAPI and put it into
your own organization.
What it's meant to do is tobe the universal translator.
What does that mean?
(05:27):
So let's say you've gota particular job title
or job posting at yourorganization, which has a
collection of skills in it.
But those, the terminology isdistinct to your organization.
So what do we do?
We take that terminology that'sdistinct to your organization.
We transfer it into ouruniversal language, right?
But guess what?
(05:48):
That's not good enoughbecause chances are
you use Workday or UKG.
They have their own language.
So you want your job titleto work with Workday.
If you put it through ouruniversal translator, we
already work with all ofthose vendors to translate
into their language.
And so fundamentally, our openskills philosophy is embedded
(06:10):
into basically almost allof the HR technology market.
A lot of our, let's call themfrenemies, our competitors,
they even use our openskills taxonomy because
it is so open source.
And so I would say weare the universal skills
language that's out there.
And that really positionsus to move from what people
call skills taxonomiesto skill ontologies.
(06:33):
So a skill ontology is thenext level is to say, what
are the emerging skills?
How are skills transforming?
What skills are diminishing?
How do those relate tothe whole body of work?
And I'm not going to getoverly technical today,
but that is the next foraythat we are getting into.
We're leading thepack in that space.
David Rice (06:50):
That's interesting you said that about the people
talk about skills taxonomy.
If you don't have a backgroundin information architecture
at all, taxonomy is oneof those words that I'm
I think people confuse itfor a list, essentially.
Cole Napper (07:03):
But it's not what it is, but that is
a common confusion, yeah.
David Rice (07:08):
Yeah, because it's one of those phrases people do
like to use, but I'm not exactlysure they know what it means.
Cole Napper (07:14):
Yeah, my grocery taxonomy, not my grocery list,
David Rice (07:17):
One of the things the report highlights, and I
think this is something thatfolks are starting to realize
more and more, is that A lot ofthe change that's coming in the
skills market, it's not goingto impact blue collar jobs a
great deal, but it is goingto really impact like white
collar jobs and STEM fields.
Those are going to be changingthe most over the next year
or two, and that's going tocreate a lot of disruption.
(07:39):
We've been talking aboutupskilling and reskilling
since before the pandemic.
As long as I've beencovering HR, we've been
talking about this, right?
But it seems like a lot oforgs haven't quite gotten
it right or never reallyinvested in it sufficiently.
How prepared do you feel thewhite collar workforce is to
shift with the changes thatare coming in the skills
market in the next year or two?
Cole Napper (08:00):
I'll even go upstream of that a little bit
because you talked about thespeed of skill change report.
We talk about a tale oftwo labor markets in that
report, and you talkedabout a little bit.
The two labor markets isessentially knowledge workers
versus people who do thingsin the physical world or what
people used to call blue collarversus white collar jobs.
It's not a perfect designation,but let's say that for
(08:21):
the sake of argument.
There's a reason why it'snot to say that the blue
collar jobs can't change.
They do see disruption.
Automation plays a role inblue collar jobs all the time.
It's just as a society,we just haven't chosen to
spend our investments there.
Right now, everyone who'sbuilding things with AI and
automation for the most part,is spending their time on
(08:42):
how do you automate coding?
How do you automate programming?
How do you automatevideo creation?
How do you automate all thedifferent creative tasks
that have primarily beendone by knowledge workers?
And so those skill setsare being pushed to
change very rapidly.
And the reality is, I thinkorganizations are working
on a hope and a prayer thatautomation will just fix
(09:04):
things quicker than the needfor skills to change will
be able to catch up, right?
That's just a interestingposition that we're in as a
society right now, and I knowwe're going to talk more about
some of the demographic shiftsthat are coming as a part of
this conversation, but really,it's going to be a forcing
function where we're going tobe coming into new territory
that we've never been before,and we don't have a playbook for
(09:26):
navigating, and so I don't thinkorganizations have a playbook
for navigating the skillschanges that are going on right
now, and I think they're justworking on hopes and prayers.
David Rice (09:35):
Yeah.
It's interesting, like reallyaround AI in particular, we
always talk about even onthis podcast, we've had guests
on and we talk about puttingin guardrails and, trying to
develop like a training aroundAI, but like this thing's
changing fast all the time.
It gets better with everyiteration or it gets
differently, at least.
Can do something new is it,there really is no playbook
(09:57):
that anybody has any experiencedeveloping around this.
This isn't like a social media.
Cole Napper (10:02):
It's an interesting point you made earlier about,
are we ever going to seemastery of skills again?
And then what were thetrends that were going on
in L&D over the last years?
It's all about likemicro learning and
giving people learning.
Do you really think you're goingto get to the point of mastery
through watching a few videos?
David Rice (10:18):
No, that's exactly it.
Cole Napper (10:19):
And so it's here's how to get to good
enough at a particularskill to be serviceable.
And now, I think the goal is,or the hope is that if you
can do it, if automation canplay a role, maybe it will
help you get to that pointof being good enough faster.
David Rice (10:35):
You mentioned there, when we were just talking
about the demographic shifts,I read another report that
Lightcast did, and listeners,they've got some good reports,
you should check these out.
I found it interesting to seethe data behind it and the
impact boomers leaving theworkforce is going to have.
And there's a lot ofthemes that we're familiar
with at play here, right?
Like for all the concernabout automation, this
(10:56):
kind of suggests that it'sgoing to be a while before
a real ability to replacepeople is in place, right?
And I think the data shows thevalue of a college education
may be fading and impact ofimmigration policy is massive.
So we're seeing all thesechanges, record levels of
prime age men not participatingin the workforce, right?
There's a lot going on hereand I'm curious, so forgive
(11:17):
this two part question, butWhat were some of the big sort
of takeaways from that reportfor you, and particularly in
terms of how demographics andskills intersect, but also
did any of it surprise you?
Cole Napper (11:29):
Yeah, well, there's so much surprising
information in that report.
It's called The Rising Storm,and I don't want to take
credit for it because thatgreat research was done before
I joined Lightcast by someof my colleagues like Ron
Hedrick, who's just amazing.
The thing that stands out themost to me is a saying that's
known in demography, whichis demographics is destiny.
And supply and demand do weirdthings in the labor market.
(11:54):
And let's go in the way backmachine, because a lot of that
report is talking about thedifferent generations and when
they entered the workforce.
So you've got the baby boomers,you've got Gen X, you've got
millennials, and then nowGen Z entering the workforce.
And one of the things thatyou find is, we've been
talking a lot about skills.
Skills, People do have theability to change, but it's
not very often you see a rocketscientist who becomes a doctor,
(12:17):
who becomes an airline pilot,who moves from a completely
different discipline to another.
You could say that most people'sdisciplines are relatively
stable throughout their career.
And if you look at that meansthat disciplines are destiny.
If demographics are destiny.
And so just take eachgeneration and say, okay, what
percentage of the baby boomergeneration was college educated
(12:39):
versus had blue collar jobs?
It was a much lower percentagethan the millennial generation.
And you could almost saythat those demographics
inverted where millennialshad a much higher degree of
college education than thebaby boomers before them.
So what does that mean?
That means is as the babyboomers exit the workforce
(13:00):
a little by little every dayand every year, their makeup
and their composition ofcollege educated versus non
college educated gets replacedby a completely different
makeup of individuals.
And what that does is now you'regetting to a point where you
have an oversupply of peoplewith college educations and
(13:20):
an under demand for thosetype of roles because of the
tale of the two labor marketsthat we mentioned earlier.
And When I was growingup, I'm sure the same
thing happened for you.
You were told like getting acollege education was like your
ticket to the middle class,your ticket to the American
dream, yada, yada, yada.
That was in a time where acollege degree was a minority
(13:43):
thing to be occurring and havinga non college degree, that
was the majority population.
That's actuallyinverting right now.
What you might find isover the next few years.
And we just released areport yesterday called
the workforce risk outlook.
So it is the next instantiationof the rising storm.
And what we did is weclassified all the fortune
(14:04):
1000 companies by their riskprofile of their industry,
by the occupations that theyhad, by the, they have the
markets in which they operate.
And the AI disruption that couldbe occurring to that particular
organization, and we scoredall of them on a risk index.
What did we find?
(14:24):
The top five industries thatare the most at risk are retail,
health care, constructionand manufacturing, right?
So you've got the top five.
Guess what are all ofthose industries are?
They're blue collar industries.
Which means that if you lookat the supply and demand
pressures going forward, youcould see the possibility.
(14:45):
I think we've already started tosee this in the last few years,
that you're going to see wagesrise in those professions and
potentially people with collegedegrees moving into those
professions because there's ahigh demand and a low supply.
David Rice (14:59):
I wonder if this will mean the end of tipping.
No, I'm just kidding.
Cole Napper (15:04):
I'll tell you something truly wild
about the workforce riskreport that came out.
Is if you truly see thelevel of shortages that
we are projecting, which Ithink you will see unless
You just see some miraculousgains in automation and
things like fast food.
I could see an instance inthe next few years where
fast food organizationsstart putting workers under
(15:24):
contract and giving themsigning bonuses, right?
Where they say, wow, youcome here, sign a three year
contract and we'll give youa 30,000 signing bonus today.
And what that will do is thatwill lock them in because
the one prescription that wefound, which came from the
rising storm, but we have justcontinued it with the workforce
risk is the organizations whoare creative and proactive will
(15:48):
be the winners because there aretruly some zero sum dynamics.
In a local market, if youhave an Amazon distribution
center and a McDonald's fastfood chain, they're sourcing
for the same talent, there'sno more talent to be had
in that particular market.
So if McDonald's wins,Amazon loses and vice versa,
whoever strikes first andis most proactive will be
(16:10):
the winners in these talent.
Talent war, we alwaystalked about the war for
talent that always appliedto the knowledge workers.
Now the war for talent isgoing to be inverting for
more of the retail, themanufacturing, the construction
industries and the like.
David Rice (16:24):
It's funny, it's what just came into my mind
just now is that old sayingplumbers rule the world.
It's just wait, they might.
Cole Napper (16:32):
Oh man.
I've been saying that since allthe AI started, stuff started
coming out, it's like The lastprofession to be automated
is going to be plumbing.
It really is.
David Rice (16:40):
Guaranteed.
One of the, with automationstaying on long that vein
is one of the things I tookfrom the report was, it
highlighted some key pointsaround how far automation is
from being able to close thegaps in terms of workforce
shortage that's coming.
There's a quote in there fromsome researchers at Goldman
Sachs and MIT, and they weresaying, there's nothing humans
do as a meaningful occupationthat generative AI can now do.
(17:04):
And I think about, customerfacing roles, there's this
sort of like disconnectbetween management's perception
of what AI can do and whatcustomers probably wanted to do.
So I'm curious from yourperspective, when we look
at AI and how it's beingintegrated into people's
work, how far it off it isin terms of replacing people
(17:26):
in a thoroughly satisfactoryway, we'll say, do you think
we've reached the point wherethe hype is going to start to
fade that old hype cycle graph?
Are we past the peak ofinflated expectation, no?
Cole Napper (17:37):
We're not in the trough of disillusionment
yet, but we have definitely,I think reached peak hype.
One of the things that Iwant to reframe and I think.
Anthropic actually earlierthis week released a
report about the impactof AI on different skills.
We're actually talking aboutpartnering with them on some
research because they usesome of our data through Onet.
(17:58):
So Lightcast supplies all thedata to Onet and they use Onet
data to do the classification.
So I was like, basicallythey're using Lightcast data,
which I thought was cool.
But one of the things thatyou find is AI doesn't
replace roles, but itdoes replace skills.
And so then if you realize it'slike how much of a particular
skill does a role complete?
(18:18):
And the question we have toask ourselves is, at what point
do the number of skills addup to a role being replaced?
Because as far as I can tell,other than the companies
that are trying to get, dopublicity stunts like Klarna
and Salesforce and Workday evento an extent are saying, we're
laying off people and replacingthem with AI, which, if you
(18:39):
read the fine print or if you doany level of digging, you find
out that's not actually true.
And I think from that Anthropicresearch, I think the role that
they found that had the mostskills that were being replaced
right now, it was only like 20%.
And I think it was a computerscientist, and most of them
were hanging around 6%, 5%.
And so the wholeconversation has been
(18:59):
replacement or augmentation.
Right now we're in theaugmentation phase.
Now that said, once weget through the trough of
disillusionment to the slopeof enlightenment, which is
what is coming in the nextfew years, you're going to
see a lot more skills beingreplaced by AI, which means
as a percentage, more andmore roles will be at risk.
(19:21):
And so it's our job as,forward thinking professionals
to say, what are theimplications of that?
How can we be proactive?
How can we use thisas an opportunity?
One of the things thatwe actually found in our
workforce risk report thatI just mentioned earlier,
is we actually, we thoughtabout AI disruption as a
positive, not a negative.
(19:43):
Because if you realize that youhave a human being shortage,
which is what is coming in thenext few years, you actually see
AI is giving you optionality.
Because you may be losinghuman beings through
immigration policy.
You may be losing humanbeings through not as
many people being born.
You may be losing humanbeings through the number of
(20:03):
retirements that are happening.
And all of those aredecreasing your optionality.
So AI actually gives youanother tool in your tool
chest to try to increaseyour optionality and decrease
your risk as a consequence.
David Rice (20:15):
When you start doing the math, I was
like, actually, this mightbalance out in some ways.
Cole Napper (20:19):
In some ways, yeah.
David Rice (20:21):
I listen to your podcast.
It's really good.
And I highly recommend it toall our listeners out there.
You should check it out.
Cole Napper (20:26):
It's a lot more funny than this
conversation, I promise.
David Rice (20:29):
Yeah.
You guys do a lotmore joking than I do.
Yeah.
I enjoyed the recentepisode with Mark Efron.
In it you ask him a question andI want to ask you that question.
There's a lot of hype aroundideas of skills based work
and deconstructing work wherewe strip away roles and we
all allocate our skills todifferent projects and jobs and
(20:50):
people apply a skill in thisrole and a skill in that role.
But Mark points outin the episode, right?
People don't want that.
They want stability.
In a lot of ways, HR folkshave been cooking this sauce
for a long time, right?
He brought up competency modelsand what's the sort of right
level of granularity here.
I'm curious, in your opinion,is the juice worth the
(21:11):
squeeze on skills based work?
And if so, how's my LinkedIngoing to capture all of that
in a way that makes senseto anybody looking at it?
Cole Napper (21:19):
The answer is your LinkedIn isn't going
to capture all of that.
And that's the reason whyyou've seen a lot of company
have fits and starts whenthey try to become skills
based organizations, right?
That's the reality.
Now, I don't personallysubscribe to this notion
that all work is going toget deconstructed and all
we are as human beings arecollections of skills and
(21:41):
that's all we'll ever be.
That's not my modus operandi andwe'll all be 1099 independent
contractors who kind of act likeUber drivers except where we
work, it'll just be like Uber.
I don't think that's thefuture of work, because
people have needs, and we dohave needs for continuity.
That said, even in a worldof disruption, there are
skills that are on thedownswing because they're
(22:03):
rife to be automated, butthere are skills that are
very much on the upswing.
The number one skill, okaywe've done some research
internally, we call it ourdisruptive skills matrix.
You know what the numberone skill on the upswing is?
Critical thinking, everyorganization should be trying
to talent hoard right now andbuild and create modes around
(22:25):
is developing critical thinkingin house because the people who
attain that level of skill incritical thinking are going to
be the disruptors of the future.
And so I always lookat it through, there's
really three lenses.
There's core skills.
There's skills that areexpanding and there's skills
that are diminishing, right?
If you're a skill basedorganization, a lot of the core
(22:48):
skills Are really unsatisfying.
And what I mean by that islet's say you're in marketing.
You know what a coreskill to marketing is?
Marketing.
Right?
No one thinks of a hugeskills transformation or
teaching marketing as askill to marketing people.
All right.
So really what, or all thefun happens at the tails.
It happens at what's diminishingand what's expanding.
(23:11):
What's expanding rightnow is critical thinking.
What's diminishing is thingslike Microsoft Word and
Microsoft Excel and all thethings that used to be a
core skill, but now can behighly automated through AI.
And so that's whatorganizations, why I think
it does become somewhatexistential to be a skills
based organization, becauseyou have to know What are
(23:34):
the skills that are growingand what are the skills that
are going away and makingthe adjustments accordingly?
David Rice (23:39):
Awesome.
Before we go, there's twothings that I always like to
do as we wrap up these shows.
First is, I want to giveyou a chance to tell people
about where they can connectwith you and find out more
about what you got going on.
Cole Napper (23:49):
Yeah man, I got so much stuff going on.
You can listen to my podcast,Directionally Correct, and
we have a newsletter onSubstack under the same name.
You can find me on LinkedIn.
I'm also writing a book rightnow on the usage of people
analytics, workforce planning,and talent intelligence with AI.
So that's very top of mind.
It'll be coming outlater this year.
And I'll be referencing a lotof the research that we talked
(24:11):
about today in that book.
You can check us out atLightcast with our research
reports on the speed ofskill change, the rising
storm, the workforce risk.
And yeah, just find me wherever.
David Rice (24:23):
The last thing, we have a tradition
here on the podcast.
You get to ask me a question.
So turn it over toyou, ask me anything.
Cole Napper (24:30):
I was like, David, isn't going to take it
easy on me today and ask mesome of the hard questions.
So I'm going to askhim the hard question.
And so it's a two parter.
What makes HR relevant in fiveyears and knowing what you know
now, what would make HR morerelevant in the C-suite today?
David Rice (24:47):
Oh, wow.
You weren't kidding.
Okay.
Cole Napper (24:49):
I know.
You made me explainwhat a taxonomy was, so.
David Rice (24:56):
Fair enough.
That's fair.
I think right now we're stillin that phase of like HR finding
its business footing all thetime and like being comfortable
being in the room when the big,the C-suite table essentially.
Cause I think for a longtime, HR was passed over
or it had this littlechip on its shoulder.
And a lot of folks aremoving into a space where
(25:16):
that's not the case anymore,but it's still getting
comfortable with your position.
I talked to a lot of leaderswho have had imposter
syndrome pretty hard.
They've learned a lotof lessons the hard way.
So I think we're still inlike this maturing phase
of HR is like a clearbusiness function and not
being like mushy about it.
(25:38):
In five years, I think, thething is I think that this
transition with the technologyfalls squarely into the HR
court more than any otherC-suite position, right?
It's essentially HR's job tonavigate how people are gonna be
working in five, ten years andwhat Like, what is our purpose?
(25:59):
Cause we will get to a placewhere I'm sure one day,
I'm hoping that I'm retiredby then, but one day it's
going to be smarter than us.
It's gonna be able to domost anything better than us.
And what is our purpose?
I think like navigating thatand all the other external
factors that are changing theway business gets done, the
way work gets done, HR sitting.
(26:20):
Basically in thequarterback spot.
Cole Napper (26:22):
Yeah.
So then the question Ihave is, are we ready
to be the quarterback?
Because some of the peoplethat are the quarterbacks
right now, they're going toretire in the next five years.
Do we have the benchthat's ready to be the
quarterback as well?
David Rice (26:36):
Yeah.
I'm actually a littleencouraged in that area.
I think there's a lot offorward thinking people right
now working in the HR space.
A lot of people who have,they haven't come from the
world where it was necessarilylike a compliance function.
You know what I mean?
Because you talked to a lotof older HR folks are like
the job before 2015 was likea completely different job.
(26:58):
And now.
If you've gotten into it andyou've become like a director
level or above in the lastcouple of years, that's a
completely different functionthan what somebody did.
And it's required you to bemore forward thinking and
more data centric and thinkingabout like people as a whole
human being, not just theeight hours that they're there.
So I think that the, allof that is going to serve
(27:20):
them well as they try tonavigate this transition.
Cole Napper (27:23):
I've been talking about this for years because I
have a background in analytics,so I've been an internal
analytics practitioner mostof my career in HR, and people
always talk about, how doyou build the capability in
people to be digitally nativeand to use data on the job?
And I say, it's agenerational problem.
The people who never hadto use it, they're going
to age out eventually.
The people who've used ittheir whole career, they're
(27:44):
moving more and more intoleadership every year.
And so actually I seeexactly what you see there,
which is you're going tohave people start to age in
to being digitally nativeat the leadership ranks.
David Rice (27:55):
Yeah, exactly.
I'm not too worriedabout it as a function.
Cole, thanks forcoming on today.
I really appreciate it.
This was a great chat.
I really enjoyed this.
Cole Napper (28:04):
Fantastic, man.
Thanks for having me.
David Rice (28:06):
All right listeners, until next time, be sure
to subscribe to the PeopleManaging People newsletter
if you haven't already.
You'll get all the latestinsights and podcast
interviews, articleswe're writing, everything
straight to your inbox.
It's a good newsletter.
Until next time.
Enjoy a sports game.
Just relax.
Cole Napper (28:23):
Yeah.
Take it easy.
David Rice (28:24):
Have a decaf.
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