November 4, 2025 • 26 mins
We’ve reached the point where “AI in HR” isn’t just a buzzword—it’s a mandate. But with every vendor promising a smarter, faster, more predictive future, it’s getting harder to tell the difference between innovation and smoke and mirrors. In this episode, Alana Fallis and I go deep on how to navigate the noise: What should you actually invest in? How do you build real AI readiness, not just compliance theater? And how do you make sure your “data-driven” decisions don’t quietly erode employee trust?
We also tackle the people-and-technology dilemmas that HR leaders are facing right now. From scaling culture without losing soul, to drawing red lines on surveillance and privacy, to the sheer absurdity of AI-generated workplace flirtation—we’re not short on material. These aren’t hypotheticals. They’re real, messy, and urgent. Let’s get into it.
Related Links:
- Join the People Managing People community forum
- Subscribe to the newsletter to get our latest articles and podcasts
- Connect with Alana on LinkedIn
- Check out Quantum Metric
- Talk HR to Me
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
David Rice (00:00):
How can I cut through the hype and make
strategic decisions aboutwhere AI can genuinely add
value to our people strategy?
Alana Fallis (00:08):
Focusing on what the tenants of
your people strategy are.
What are you tryingto solve for?
Making sure that you'resolving real problems and not
just like getting distractedby the net's splashy thing.
David Rice (00:18):
I've been asked to develop AI readiness training.
Should I be focusing onre-skilling for specific
tools or is there a morefundamental shift in how we
think about human capabilities?
Alana Fallis (00:29):
We don't know what jobs are gonna be available
in five years, but we know thethings that AI can't replace.
Human connection andtrust and coaching and
empathy and compassion.
David Rice (00:39):
We're collecting productivity metrics, sentiment
analysis, even biometric data.
How do I protect employeeprivacy and trust?
Alana Fallis (00:47):
My friend, I know you did right into this column
to tell us so that we could tellyou to quit your job, and I'm
not gonna do that, but yikes.
David Rice (00:55):
If this were a relationship, you'd bail.
If they start going throughyour phone, you start to think
is the time for me to go?
Welcome to The People ManagingPeople Podcast — a show
where we help leaders keepwork human in the era of AI.
I'm your host, David Rice.
And today I'm once againjoined by Alana Fallis.
She is the head of people atQuantum Metric and the author of
(01:18):
our recurring series Talk HR toMe that we might just be turning
into a recurring podcast.
Because last time we didthis, you all responded with
a ton of questions and we'vegot more today and we're
both looking forward to it.
Alana, welcome!
Alana Fallis (01:32):
Thank you.
I'm so happy to be back.
Yeah, it was so fun to seethe questions pour in last
time, so keep 'em coming.
We love people problemsolving together.
Let's get into it.
Yeah, I'm excited.
David Rice (01:41):
Absolutely.
These are great.
Our first question wasaround AI, says there are
countless vendors promisingeverything from AI powered
recruiting to predictiveanalytics for retention.
How can I cut through the hypeand make strategic decisions
about where AI can genuinelyadd value to our people
strategy without wastingtime or budget on flashy
(02:03):
tools that don't deliver?
Alana Fallis (02:05):
Yeah.
I feel like a lot ofpeople feel this way.
And it's also interestingthat you and I are in seats
answering these questions'cause I, I feel like the
voice that I answered the roomaround AI and HR is like maybe
a little bit more sort of likeskeptical and slow roles and
a lot of my peers who havelike indexed all the way in.
So I feel like I'm alwayslikely to add a little bit of
(02:26):
skepticism to the conversation.
But in any event, so I thinka lot of people feel this way.
There's so much hype aroundAI right now and so much sort
of directive to incorporateit and make it forefront of
your work and solve all ofyour manual administration
problems and all that.
But okay, so the things thatI think about when not wasting
time or budget on flashytools and like really making
a meaningful investment is.
(02:47):
Really focusing in onwhat the tenants of your
people strategy are.
What are you tryingto solve for?
What are you actually tryingto leverage these tools to do?
And I think about itlike, what are your
competitive differentiators?
And any AI that you investin or lean into should either
leverage something thatyou already do well because
it's something like it's acompetitive differentiator for
your company, or fills in agap that you're not doing well.
(03:09):
I don't know.
Just make sure that you're beingthoughtful, making sure that
you're solving real problems andnot just like getting distracted
by the next splashy thing.
I'll say for myself, whenI'm evaluating tools, I'm
not willing to pay or paymy company's money for
a tool that's in beta.
I'll try it for you.
I'll pilot it for you andwe'll see if it's proven.
But definitely some of thesetools have big promises
(03:29):
and under-delivering, sodon't invest in something
that's not proven.
That's my sort offirst thoughts.
What do you think?
David Rice (03:36):
I agree.
We hear this allthe time, right?
Like I go out, I talk to,you know, chief people,
officers, CHROs, whatever.
Everybody's kindasaying the same thing.
It's like, first of all,a lot of the tools are
marketing a solution thatthey don't even need.
You know what I mean?
Like that happens a lot.
Alana Fallis (03:50):
Totally.
Yeah, yeah.
David Rice (03:51):
It's like I just need like practical uses.
I was talking to one womanand she said, you know what?
Why don't you just makesomething that pulls all these
data sources into one placeand does some insight analysis?
You know what I mean?
Alana Fallis (04:01):
Yeah.
Oh my goodness.
That's such a point.
Yeah.
David Rice (04:04):
But I, I think it highlights the bigger questions.
It's not necessarily whichtools should you buy, but
like what business problem amI actually trying to solve?
Like if retention is the corechallenge, then start there.
Don't start with a toolthat like looks amazing.
Right?
And I think the other thing islike you gotta build in some
kind of decision framework.
Things like, all right, yeah,what's the cost to implement it?
(04:26):
What data do we already haveand what does this require?
Who's gonna own this tool?
And like what are we looking forthe outcome to be in six months?
Because just like you didn'tneed 20 different types of
software and you ended upcutting your tech stack down,
you're not gonna need all thesedifferent AI tools in reality
in the long term especially.
Alana Fallis (04:45):
Yeah.
Oh, that resonates.
Yeah.
Yeah.
David Rice (04:47):
I think if you can find one or two that like
integrate with your existingstuff pretty well and you
have a process to experiment,evaluate, essentially retire
the stuff that doesn't deliver,then I think you're gonna,
you're on the right trackfor where we are right now.
Alana Fallis (05:01):
I think that's such a great point.
And the tech stack fatigue.
The building andbuilding and building.
If your AI tool does notintegrate with my current
tool, I don't want it.
I don't wanna just addthings to the menu, right?
So either what can you letgo of that's not serving
the organization andwhat can you make better?
But being really thoughtfulabout not just these like
sort of single use ideas.
But yeah, I feel likeI get pitched a lot of
(05:21):
these products like.
You know, in my role, andso many of them are not
relevant or useful, like ithas to integrate with what
we're already doing for sure.
David Rice (05:28):
So it's a common experience from what I can tell.
Alana Fallis (05:31):
Totally.
Totally.
Yeah.
David Rice (05:34):
Let's go to our next question.
It says, I've been askedto develop AI readiness
training for our workforce,but honestly, I'm not sure
what that means or how toprepare people for jobs that
might not exist in five years.
Our L&D budget is limited.
Should I be focusing onre-skilling for specific tools?
Or is there a more fundamentalshift in how we think
(05:54):
about human capabilities?
Alana Fallis (05:56):
What does AI readiness really mean?
I feel like there's like asort of buzzwordy component to
AI readiness, but if I thinkabout what it means to me, I
think it means adaptabilityspecifically in a technology
driven environment andthe ability to take on new
things and learn new skills.
So I think AI readiness isnot about one specific tool.
I think it's about resilienceand receptivity and
(06:17):
adaptability as technologycontinues to change.
So, I mean, it's a big ask.
Are we rethinkinghuman capability?
I think kind of like howtechnology's going to support
us in doing the work moreeffectively, making sure
that we know how to evaluatetechnology, making sure that
we're choosing the right tools.
The thing that was interestingabout this question is that we
don't know what jobs are gonnabe available in five years.
(06:38):
It's a really scaryand important call out.
We don't know what jobs aregonna be available or not
available in five years,but we know the things
that AI can't replace,which is human connection
and trust and coaching andempathy and compassion.
And so I think there'salso a space to lean into
those skills, like thosecoaching skills and those
relationship building skills.
But overall, I think it'sless about sitting seat
(06:58):
and thinking about whatwill and won't be available
in five years, but just.
Building a workforce withreadiness to be able to
adapt and leverage intothe human part of HR.
David Rice (07:07):
Yeah, I mean that resonates.
'cause I think the adaptabilitypart is the key, right?
Like even ChatGPT nowversus when it first came
out, it's like not even thesame tool hardly anymore.
You know?
You could do like so muchmore with it than you could
then, and so you're gonna.
That is the thing, likebuilding that adaptability
muscle is the key.
That's what's gonna keepfolks somewhat relevant.
(07:28):
I mean, the tools are gonnachange, the prompt design,
data literacy, all of that.
Those don't necessarily get old.
They have longershelf lives, Anyways.
Critical thinking never expires.
So you should probably.
Alana Fallis (07:40):
Yeah, problem solving.
Yeah.
Yeah, exactly.
David Rice (07:42):
Lead into that.
And then like in terms of thebudget part, you know, I'd focus
on transferable capabilities,you know, like how to work
alongside automation, how tointerpret AI outputs critically.
Again, that goes backto the critical thinking
piece, but like how tocollaborate in hybrid teams.
You know, like thesethings probably will
(08:03):
exist in five years.
It's worth hyperfocusing in those areas.
Alana Fallis (08:07):
Also, I think there's something to be said
for if you're working with yourspecific team, you know, the
advice I always give my team isto think about what makes them
different as an HR practitioner.
'cause those are the thingsthat are gonna be what
makes them hireable andmakes them promotable.
So leaning into the skillsthat your team is already
good at and just gettingreally good at them.
You know what I mean?
What be that executivepresence or communication
(08:28):
or you know, facilitation.
There's a lot of room andspace for a human in the
workplace still, and I thinkwe should keep that top of
mind and try to keep it topof mind for our leaders too.
David Rice (08:36):
Agreed.
Next question is, ourcompany has grown from 50
to 200 employees in twoyears, and I feel like we're
losing the family culturethat made us special.
Leadership wants to scaleeverything from policies to
processes and benefits, butour surveys are telling me
people feel like numbers Now.
How do I preserve ourhumanity while building
(08:57):
the structure we need?
Alana Fallis (08:59):
That's such an interesting question.
I deal with this a lot as aperson who's always historically
worked at startups that likewith scale up comes more
process and structure, but alsocomes less like platitude and
flexibility and the ability tofunction like a team of best
friends, like doing the work.
I think I would say can youget a sort of focus group of
long tenured employees going,or a culture committee of some
(09:21):
kind, going meet with peoplewho have been there for the
long time and are willingto share these concerns and
openly discuss these concerns.
And sort of get to the bottom ofwhat exactly the pain point is.
Like they're feeling likenumbers, how like they're
feeling like they're in themethod of communication from
the company and the way thatprocesses are structured.
Like what exactly is sortof going wrong for them?
What are they missing?
Are they missing more events?
Are they missing more culture?
(09:42):
Are they missing moreopportunities to connect?
So I would try to see whois willing to share that
information with you andrespond specifically to that.
But I also think thereis an element of change
management here because.
A company that is implementingmore process and structure
is a company that isgetting ready to scale.
And something that this questioneven asked was more benefits
like More benefits is great.
That's actuallygreat news, right?
(10:03):
So like a company that'sgrowing is a company that
is winning and is a companythat is being successful.
And so maybe there's an elementof change management here
for these teams about, yeah.
So some of thesethings are different.
I used to work for a companythat for a while posted
its company financials atall hands, and then over
time stopped doing that.
People are like, well,where's the transparency?
But it's like, well now we'rehundreds of people, right?
So it's like, here's theinformation you need, here's
(10:25):
how we can continue to createthat feeling of community
but also growth is good.
David Rice (10:30):
And I'd say enjoy this challenge while you can.
Right.
Because we see a lot, we see alot of companies, you mentioned
change management there.
We see a lot of companieshaving to manage change
in the other direction.
Alana Fallis (10:39):
Yeah.
David Rice (10:40):
You know, where they're having to
win down the numbers.
So yeah, this is a good problemto have at the end of the day.
Alana Fallis (10:46):
Yeah.
David Rice (10:46):
But you do hit that inflection point.
I know.
I've been a part of orgs wherelike, yeah, we were like 25
people and then it was, youcould kind of experiment and
we had like this move fastbreak things sort of culture
and then you get up to likea hundred people and yeah,
there's layers of approval andor bureaucracy that kind of
form in a larger organization.
And then it just kindof, it is part of the
(11:09):
process of growing, right?
You're not gonna becomea bigger, more successful
higher revenue generatingorg without adding some
people, and it's just.
I don't think processis the enemy of culture.
You know what I mean?
It's how you design it.
Alana Fallis (11:22):
Yeah.
You know that's, no,that's a good quote.
Quote.
I like it.
It's true.
Right?
David Rice (11:26):
Blow that one up, put it on your wall.
Alana Fallis (11:28):
Yeah, exactly.
Take it in the office.
Yeah.
David Rice (11:30):
But I mean, you scale, for example,
like onboarding, butyou keep storytelling.
You pair new hires withculture ambassadors.
You use AI tools to sort ofcapture and share institutional
knowledge in different ways.
And so I think there's waysto do this, and I think that
the technology is going tofacilitate us doing this in so
many different kinds of ways.
But I mean, it's justpart of the challenge.
(11:52):
Right.
Alana Fallis (11:53):
Well also throwback too.
So the last question is like,make sure that your team, HR
team, I'm assuming an HR personwrote this question, but I
actually could be wrong, butmake sure that your people,
leaders, HR or otherwiseare front facing as like a
cultural ambassador and achange ambassador for these
different programs because.
That's like a really keypoint is like the community
building, the relationshipbuilding and the storytelling
(12:15):
and that culture generation.
So make sure that thehumans and people, leaders
are front and center too.
So let's see AI do that.
Okay.
Let's see AI.
David Rice (12:21):
No, exactly.
You just said it like, whenleaders live the culture that
they want, it will scale.
If they look at HR particularly,and all they see is
essentially policies and notlike people doing the thing.
Then, yeah, you're gonnafeel the erosion pretty
quickly, you know?
Alana Fallis (12:37):
Yeah, for sure.
For sure.
David Rice (12:39):
Let's see here.
What do we got next?
We got, we're collectingproductivity metrics from AI
monitoring tools, sentimentanalysis from internal
communications, even biometricdata from workplace apps.
Oh boy.
Well, like we'reboth already like.
Alana Fallis (12:55):
Me too.
Yeah.
Yikes.
Yikes.
Yeah.
David Rice (12:57):
But yeah, I'm uncomfortable with the
surveillance, but leadershipsays it's necessary for
data-driven decisions.
How do I protect employeeprivacy and trust while
meeting demands forAI powered analytics?
Alana Fallis (13:10):
Ooh, my friend, I know you did write into
this column to tell us sothat we could tell you to
quit your job, and I'm notgonna do that, but yikes.
This wouldn't work for meas a leader in the business,
and I would've a really hardtime going along with this,
as I'm sure you are, which iswhy you wrote in for advice.
I guess what I would do here isreally push onto leadership to
describe what behaviors we'reactually trying to incentivize.
(13:34):
What behaviors arewe looking to drive?
What are we actuallylooking to reward?
What are we trying to changehere, and get really focused
and dialed in on those things.
I think there are harmoniousways to target behaviors.
I don't think there is areally easy or a way that I
personally feel comfortablewith to monitor productivity.
I think we canmonitor behaviors.
I think we can't really monitorproductivity in a way that feels
(13:56):
good to the employee population.
If it is something thatyou ultimately have to go
ahead with, you should bereally transparent with your
team, really transparentabout the why and what
you're hoping to achieve.
And may I even suggesttrialing it and then retiring
it when we feel that thingshave reached a better place.
But I don't think I wouldfeel comfortable doing this.
I'm sorry to tell you.
(14:16):
Sorry to tell you.
Yeah.
David Rice (14:18):
Yeah.
No, I mean, this isthe definition of a
trust issue, right?
So yeah.
If this were arelationship, you'd bail,
Alana Fallis (14:25):
totally.
No.
That's right.
That's right.
Yeah.
David Rice (14:27):
Like they start going through your phone you
start to think about like, asa time for me to go, right?
So like, I think you have totalk about this as a trust
issue and it's, this isn't.
This isn't evenabout data, right?
Like we're necessarilywhat you're collecting.
Like I think employeestolerate just like the general
population, we tend to toleratea level of data collection if
we believe that it's eitherethical or it's transparent.
(14:49):
It's genuinely in our interest.
Right?
If it is in our interest,people kind of don't care.
They'll be like, of courseI wanna see ads that,
I mean, that's the oneeverybody hates, right?
But.
Alana Fallis (14:57):
Yeah.
Right.
Serious for sure.
David Rice (14:58):
But still like, and I think you've gotta get
the governance layer in there.
And what I would sayis, is like try creating
like a data ethics group.
That is both leadershipand employees together,
co-designing whateverybody's comfortable with.
This way you're at leastclear about what you're
collecting, why you wantit, what's off limits.
The employees have a chance tosay what's off limits to them.
(15:21):
Like, and maybe that can kindof turn it from surveillance
into sort of like a co-designedintelligence system essentially.
Right?
But honestly if leadershipthinks productivity is built on
this surveillance I mean that'sa cultural red flag, right?
So, measure outcomes.
Alana Fallis (15:38):
Yeah, measure outcomes.
No, and to the extent thatyou're able like influenced
a very focused approach hereand a very specific approach.
But that was a really good pointbecause we know that, right?
Like companies have a rightto look at what employees
are doing with theirequipment and machine, right?
We know that it's usuallysigned some point within your
employment agreement process.
There is certainly a concernhere around data privacy because
there is a variety of statelaws around like what personal
(16:00):
information can be collectedor has to be reported on.
And so I'm not an expert,I'm not an attorney, but I
would also make sure thatthis is like up to speed
with, you know, your legalteam and your security team.
So there may be otherlegal implications that
I'll just call that out.
But yeah, I, there isa cultural problem.
If this is what we'veresorted to for sure.
David Rice (16:20):
It's like one of those where it kinda gives
you the willies, right?
Like for me personally,like I, I leave my laptop
on and then it's like themicrophone's always on.
So like, is it hearing ustalk about like, you know,
you know me talking tomy son about whatever was
talking to my girlfriendabout what, like it's.
Alana Fallis (16:34):
Yeah.
I don't like it.
I don't like it.
That's what I'd say.
David Rice (16:37):
That data's in there, you know?
Alana Fallis (16:39):
Yeah, for sure.
For sure.
David Rice (16:41):
We had having the phone around and
it's always listening.
I think I, it was the otherday as we were talking about
something and the first ad onInstagram was exactly that.
I was like.
Alana Fallis (16:52):
I know.
How is it doing it?
I know it's crazy if a friendrecommends me something, that
thing appears on my Facebookads the next day, like.
Whatever it is, what it is atthis point, but we have some
agency and autonomy and therelationships, to your point
that we choose to cultivate, andthat would not be a relationship
that I feel comfortablewith for my employer.
I'd feel weird about that.
David Rice (17:11):
And I think people are wanting more control over
how their data's used andwhat, how it's collected.
Yes.
So like, yeah.
Yeah.
I think that's why I, youknow, I feel like because
people are invested in that,this is the time to have that
conversation to co-design thatwith them, because there's a
lot of people with opinionsabout this stuff, and.
You can actually probablyhave a pretty interesting
(17:31):
conversation about whatpeople are willing to put up
with and what they're not.
I think that's worth having.
Alana Fallis (17:36):
Yeah, I think so too.
David Rice (17:37):
Alright, the next question.
We discovered that one of ouremployees built a custom beat
GPT to coach him on how toflirt with coworkers, and he's
been workshopping and sendingromantic messages on Slack.
HR is manually combingthrough spreads to find
out how many AI generatedpickup lines there are.
(17:59):
And whether anyone actuallyreplied how and where do
I even add this to policy?
Alana Fallis (18:06):
Oh my God.
I was gooped by this question.
I was absolutely goopedby this question.
What?
What?
David Rice (18:12):
I was like, wow.
I mean, you know, innovation.
He's an innovative spirit.
He's an innovator.
Alana Fallis (18:20):
He's an innovator.
Oh my God.
Okay.
Well, to answer the, firstly,this is crazy town bananas,
but to answer the que thequestion at hand, I mean you
can't have your AI policy,I think account for every
single crazy fringe use casethat people do in Cook Up.
I think your policy shouldnot speak to every crazy thing
people can actually do, butshould instead speak to like.
(18:41):
Best practices, usageof the technology, and
then examples of misuse.
So like it's intended for this.
Examples of inappropriate usewould be X, Y, and Z. But I
don't even think that you needto put this into your policy
because it's common sense and itcan absolutely rise to the level
of harassment if it's pervasive.
So from a policy perspective,outline the intended use and
(19:02):
then maybe one or two or threeexamples of things that are.
Prohibited under the policy, butin this case, you just have to
talk directly to this person.
You should absolutely bewriting up this person.
I wanna know ifany of it worked.
I have so many.
Can you follow up reader?
If this was you, I needto know what happened.
David Rice (19:17):
I mean, this is one where like I don't
env HR people sometimes.
'cause I you, you seethis guy, so it's like
this is hysterical to me.
Like on the surface this isgenuinely funny, but it's
also pretty serious, right?
It's like as the HR person, no,it could really my problems.
Yeah.
You have to address this.
We're entering this likeweird gray zone, right, where
like AI can supercharge somepretty terrible behaviors,
(19:39):
things HR policies were neverdesigned to mitigate for or
you would've never anticipated.
But I think you're right,like you can't list
every possible misuse.
Policies essentiallyshould focus on principles,
respect, consent,professionalism, boundaries.
Whether it's AI, augmentedor not, it still violates
those and it's a problem.
Alana Fallis (19:59):
Totally.
And I would also be willingto bet that this probably
falls under some kind ofharassment policy that you have
elsewhere in your handbooksand employee documents.
So I think this is notlike a specific to how
to use this tool policy.
It's just like a generalprinciple that you probably
have covered in manyplaces throughout like
your handbook and stuff.
But yeah, I wanna knowwhat happened, let us know.
David Rice (20:19):
If you're one of the recipients of one of
these messages, I'm curious,was it a decent pickup line?
Alana Fallis (20:26):
Did it work?
Did it work?
Yeah.
Were you more interested after?
No.
Yeah.
People find new and creativeways to do crazy things
in the workplace, man.
So AI is no exception.
So, wow.
David Rice (20:38):
That was a wild one.
I was like, I saw that onecome in and I was like, oh,
I can't wait for that start.
Alana Fallis (20:43):
I know.
Oh man.
Oh man.
Yeah.
David Rice (20:46):
Alright.
Final question.
I'm struggling with a disconnectbetween what our leadership
says about work-life balanceand what they actually expect.
We promote flexibility,but managers still schedule
last minute Friday eveningmeetings and expect
weekend email responses.
How do I address this gapwithout seeming like I'm not
supporting business needs?
Alana Fallis (21:06):
Oh, this is a tough one because burnout
is just so pervasive.
Like I work in the tech industryand I think burnout is like
a thing that we hear almostevery survey we do, almost
every employee listening, likethere's always this balance
between driving exceptionalbusiness results and being able
to have your team members havea relationship to work that is
sustainable and comfortable.
I think it's about implementingsome kind of framework, or
(21:29):
especially some written guidanceabout defining what's important,
defining working parameters.
Here are the circumstancesor the occasional seasons in
which we may expect you tohave to go above and beyond,
like if you work for any.
Software company, likesupporting for a retail brand,
for example, black Friday is,oh, like people have to be
on, even though it's a dayoff for many other companies.
Right?
So some kind of like bestpractices framework or working
(21:52):
guidelines framework oflike, you know, we promote
a culture of flexibility.
We promote a culture of workingwhen works best for you.
There are times that we needall hands on deck and those
times are these examples,in which case some late
nights may be expected.
As a matter of course, as amatter of day-to-day working
course weekend, email responsesshould not be expected.
So in that case,that's something that
(22:12):
you need to address.
But maybe with partnershipwith your managers, you
can define when we reallyneed it, what's most
important, and when we don't.
But if your managers, I think,run amuck and just like continue
to create a culture wherepeople have to be on 24 7,
they'll start to lose people.
And that's what youwanna get ahead of.
David Rice (22:30):
I would agree.
I've been seeing all kindsof crazy stuff lately.
The 9, 9, 6 thing that'sgoing around, it just
sounds like a nightmare.
And then you've got, I saw onethe other day, this lady said
she's been doing four days of,I think it was like 14 hour
days followed by three days off.
So she's like, oh, I gota four day work week.
I'm like, yeah, and this isa recipe of you're getting
(22:52):
addicted to drugs or something.
Like, what are you gonna keep?
Alana Fallis (22:55):
Yeah, right.
My God.
David Rice (22:56):
I mean, first of all, the word quality is gonna
suffer, so this is already abad business idea in my opinion.
Then, yeah, you're justgonna burn yourself out.
I think from the perspectiveof this question though,
when employees hear onething, they see another.
You don't just losegoodwill, right?
You lose credibility oncewe're all sitting around
having this trust conversation.
But you're eroding credibility,so you've got to weigh
(23:19):
up, like what's gonna makeevery initiative harder?
Well, this is one ofthose things, when we
don't live this value.
This is gonna makeeverything harder.
And people are looking outand they're seeing some
terrible behaviors, like I'mtalking about going around the
professional world right now.
And they're like, listen,if they, I gotta draw
the line somewhere.
So it starts to becomesort of like combative
and that is not where youwant your people to be.
(23:40):
So it's, I think it's, youwanna align leadership intent
with management practice.
Alana Fallis (23:47):
Yeah.
Yeah, that's agreat way to put it.
David Rice (23:49):
That might mean manager training clear
guardrails, you know, holdingleaders accountable to
the same balance that theyexpect employees to have.
Those are all things thathave to happen and I think
you can kind of put a positivespin when you fix this gap.
'cause you don't justimprove work-life balance.
Right?
You actually sort of, basicallyyou're unlocking productivity
'cause you're ensuring peoplearen't running on fumes.
(24:11):
So it's like really focus there.
This is how we'reavoiding burnout.
This is how we're maintainingproductivity, and this is
how we're keeping the culturewhere we want it to be.
It's really attractive to peoplewith the skills that we need.
Alana Fallis (24:23):
There's a real communication and
teaching here around a forestfor the tree situation.
Like you may meet X deadline,but your top talent will
eventually burn out andleave, or may have to
go on a medical leave.
Do you know what I'm saying?
Like you'll see people whoreally start to suffer, but it
always does come from the top.
So like the people who reallyneed to model this behavior
as the executive team.
Who needs to manage thoseexpectations are the executive
(24:44):
team, because some managers,maybe they don't, maybe
either the executive team isnot aware or they're pushing
you know, an unfeasible orunsustainable work culture.
But it's probably the former.
I mean, in my experience, Ifind that it's the former.
David Rice (24:56):
I agree.
All right.
Well, this was a goodround of questions.
Alana Fallis (24:59):
We got some questions answered today.
We knocked a coupleoff our list.
But yeah, keep 'em coming.
Give us your updates.
If you wrote any of these, likelet us know how things resolve.
We'd love to know.
David Rice (25:09):
Yeah, love an update.
Keep 'em coming.
We'll keep posting the linkto the question form, but
feel free to, it's out there.
It's called Talk HR to Me.
You can find thequestion form me.
You can find it on ourwebsite on Alana's articles.
So please do keep 'em coming.
We look forward to it.
Until next time, signup for the newsletter
if you haven't already.
Some really coolstuff is going on.
(25:31):
And until next time, pleasekeep your AI generated pickup
lines out of the workplace.
Alana Fallis (25:37):
Keep 'em to yourself.
Keep 'em to yourself.
How can I cut through the hype and make
strategic decisions aboutwhere AI can genuinely add
value to our people strategy?
Alana Fallis (00:08):
Focusing on what the tenants of
your people strategy are.
What are you tryingto solve for?
Making sure that you'resolving real problems and not
just like getting distractedby the net's splashy thing.
David Rice (00:18):
I've been asked to develop AI readiness training.
Should I be focusing onre-skilling for specific
tools or is there a morefundamental shift in how we
think about human capabilities?
Alana Fallis (00:29):
We don't know what jobs are gonna be available
in five years, but we know thethings that AI can't replace.
Human connection andtrust and coaching and
empathy and compassion.
David Rice (00:39):
We're collecting productivity metrics, sentiment
analysis, even biometric data.
How do I protect employeeprivacy and trust?
Alana Fallis (00:47):
My friend, I know you did right into this column
to tell us so that we could tellyou to quit your job, and I'm
not gonna do that, but yikes.
David Rice (00:55):
If this were a relationship, you'd bail.
If they start going throughyour phone, you start to think
is the time for me to go?
Welcome to The People ManagingPeople Podcast — a show
where we help leaders keepwork human in the era of AI.
I'm your host, David Rice.
And today I'm once againjoined by Alana Fallis.
She is the head of people atQuantum Metric and the author of
(01:18):
our recurring series Talk HR toMe that we might just be turning
into a recurring podcast.
Because last time we didthis, you all responded with
a ton of questions and we'vegot more today and we're
both looking forward to it.
Alana, welcome!
Alana Fallis (01:32):
Thank you.
I'm so happy to be back.
Yeah, it was so fun to seethe questions pour in last
time, so keep 'em coming.
We love people problemsolving together.
Let's get into it.
Yeah, I'm excited.
David Rice (01:41):
Absolutely.
These are great.
Our first question wasaround AI, says there are
countless vendors promisingeverything from AI powered
recruiting to predictiveanalytics for retention.
How can I cut through the hypeand make strategic decisions
about where AI can genuinelyadd value to our people
strategy without wastingtime or budget on flashy
(02:03):
tools that don't deliver?
Alana Fallis (02:05):
Yeah.
I feel like a lot ofpeople feel this way.
And it's also interestingthat you and I are in seats
answering these questions'cause I, I feel like the
voice that I answered the roomaround AI and HR is like maybe
a little bit more sort of likeskeptical and slow roles and
a lot of my peers who havelike indexed all the way in.
So I feel like I'm alwayslikely to add a little bit of
(02:26):
skepticism to the conversation.
But in any event, so I thinka lot of people feel this way.
There's so much hype aroundAI right now and so much sort
of directive to incorporateit and make it forefront of
your work and solve all ofyour manual administration
problems and all that.
But okay, so the things thatI think about when not wasting
time or budget on flashytools and like really making
a meaningful investment is.
(02:47):
Really focusing in onwhat the tenants of your
people strategy are.
What are you tryingto solve for?
What are you actually tryingto leverage these tools to do?
And I think about itlike, what are your
competitive differentiators?
And any AI that you investin or lean into should either
leverage something thatyou already do well because
it's something like it's acompetitive differentiator for
your company, or fills in agap that you're not doing well.
(03:09):
I don't know.
Just make sure that you're beingthoughtful, making sure that
you're solving real problems andnot just like getting distracted
by the next splashy thing.
I'll say for myself, whenI'm evaluating tools, I'm
not willing to pay or paymy company's money for
a tool that's in beta.
I'll try it for you.
I'll pilot it for you andwe'll see if it's proven.
But definitely some of thesetools have big promises
(03:29):
and under-delivering, sodon't invest in something
that's not proven.
That's my sort offirst thoughts.
What do you think?
David Rice (03:36):
I agree.
We hear this allthe time, right?
Like I go out, I talk to,you know, chief people,
officers, CHROs, whatever.
Everybody's kindasaying the same thing.
It's like, first of all,a lot of the tools are
marketing a solution thatthey don't even need.
You know what I mean?
Like that happens a lot.
Alana Fallis (03:50):
Totally.
Yeah, yeah.
David Rice (03:51):
It's like I just need like practical uses.
I was talking to one womanand she said, you know what?
Why don't you just makesomething that pulls all these
data sources into one placeand does some insight analysis?
You know what I mean?
Alana Fallis (04:01):
Yeah.
Oh my goodness.
That's such a point.
Yeah.
David Rice (04:04):
But I, I think it highlights the bigger questions.
It's not necessarily whichtools should you buy, but
like what business problem amI actually trying to solve?
Like if retention is the corechallenge, then start there.
Don't start with a toolthat like looks amazing.
Right?
And I think the other thing islike you gotta build in some
kind of decision framework.
Things like, all right, yeah,what's the cost to implement it?
(04:26):
What data do we already haveand what does this require?
Who's gonna own this tool?
And like what are we looking forthe outcome to be in six months?
Because just like you didn'tneed 20 different types of
software and you ended upcutting your tech stack down,
you're not gonna need all thesedifferent AI tools in reality
in the long term especially.
Alana Fallis (04:45):
Yeah.
Oh, that resonates.
Yeah.
Yeah.
David Rice (04:47):
I think if you can find one or two that like
integrate with your existingstuff pretty well and you
have a process to experiment,evaluate, essentially retire
the stuff that doesn't deliver,then I think you're gonna,
you're on the right trackfor where we are right now.
Alana Fallis (05:01):
I think that's such a great point.
And the tech stack fatigue.
The building andbuilding and building.
If your AI tool does notintegrate with my current
tool, I don't want it.
I don't wanna just addthings to the menu, right?
So either what can you letgo of that's not serving
the organization andwhat can you make better?
But being really thoughtfulabout not just these like
sort of single use ideas.
But yeah, I feel likeI get pitched a lot of
(05:21):
these products like.
You know, in my role, andso many of them are not
relevant or useful, like ithas to integrate with what
we're already doing for sure.
David Rice (05:28):
So it's a common experience from what I can tell.
Alana Fallis (05:31):
Totally.
Totally.
Yeah.
David Rice (05:34):
Let's go to our next question.
It says, I've been askedto develop AI readiness
training for our workforce,but honestly, I'm not sure
what that means or how toprepare people for jobs that
might not exist in five years.
Our L&D budget is limited.
Should I be focusing onre-skilling for specific tools?
Or is there a more fundamentalshift in how we think
(05:54):
about human capabilities?
Alana Fallis (05:56):
What does AI readiness really mean?
I feel like there's like asort of buzzwordy component to
AI readiness, but if I thinkabout what it means to me, I
think it means adaptabilityspecifically in a technology
driven environment andthe ability to take on new
things and learn new skills.
So I think AI readiness isnot about one specific tool.
I think it's about resilienceand receptivity and
(06:17):
adaptability as technologycontinues to change.
So, I mean, it's a big ask.
Are we rethinkinghuman capability?
I think kind of like howtechnology's going to support
us in doing the work moreeffectively, making sure
that we know how to evaluatetechnology, making sure that
we're choosing the right tools.
The thing that was interestingabout this question is that we
don't know what jobs are gonnabe available in five years.
(06:38):
It's a really scaryand important call out.
We don't know what jobs aregonna be available or not
available in five years,but we know the things
that AI can't replace,which is human connection
and trust and coaching andempathy and compassion.
And so I think there'salso a space to lean into
those skills, like thosecoaching skills and those
relationship building skills.
But overall, I think it'sless about sitting seat
(06:58):
and thinking about whatwill and won't be available
in five years, but just.
Building a workforce withreadiness to be able to
adapt and leverage intothe human part of HR.
David Rice (07:07):
Yeah, I mean that resonates.
'cause I think the adaptabilitypart is the key, right?
Like even ChatGPT nowversus when it first came
out, it's like not even thesame tool hardly anymore.
You know?
You could do like so muchmore with it than you could
then, and so you're gonna.
That is the thing, likebuilding that adaptability
muscle is the key.
That's what's gonna keepfolks somewhat relevant.
(07:28):
I mean, the tools are gonnachange, the prompt design,
data literacy, all of that.
Those don't necessarily get old.
They have longershelf lives, Anyways.
Critical thinking never expires.
So you should probably.
Alana Fallis (07:40):
Yeah, problem solving.
Yeah.
Yeah, exactly.
David Rice (07:42):
Lead into that.
And then like in terms of thebudget part, you know, I'd focus
on transferable capabilities,you know, like how to work
alongside automation, how tointerpret AI outputs critically.
Again, that goes backto the critical thinking
piece, but like how tocollaborate in hybrid teams.
You know, like thesethings probably will
(08:03):
exist in five years.
It's worth hyperfocusing in those areas.
Alana Fallis (08:07):
Also, I think there's something to be said
for if you're working with yourspecific team, you know, the
advice I always give my team isto think about what makes them
different as an HR practitioner.
'cause those are the thingsthat are gonna be what
makes them hireable andmakes them promotable.
So leaning into the skillsthat your team is already
good at and just gettingreally good at them.
You know what I mean?
What be that executivepresence or communication
(08:28):
or you know, facilitation.
There's a lot of room andspace for a human in the
workplace still, and I thinkwe should keep that top of
mind and try to keep it topof mind for our leaders too.
David Rice (08:36):
Agreed.
Next question is, ourcompany has grown from 50
to 200 employees in twoyears, and I feel like we're
losing the family culturethat made us special.
Leadership wants to scaleeverything from policies to
processes and benefits, butour surveys are telling me
people feel like numbers Now.
How do I preserve ourhumanity while building
(08:57):
the structure we need?
Alana Fallis (08:59):
That's such an interesting question.
I deal with this a lot as aperson who's always historically
worked at startups that likewith scale up comes more
process and structure, but alsocomes less like platitude and
flexibility and the ability tofunction like a team of best
friends, like doing the work.
I think I would say can youget a sort of focus group of
long tenured employees going,or a culture committee of some
(09:21):
kind, going meet with peoplewho have been there for the
long time and are willingto share these concerns and
openly discuss these concerns.
And sort of get to the bottom ofwhat exactly the pain point is.
Like they're feeling likenumbers, how like they're
feeling like they're in themethod of communication from
the company and the way thatprocesses are structured.
Like what exactly is sortof going wrong for them?
What are they missing?
Are they missing more events?
Are they missing more culture?
(09:42):
Are they missing moreopportunities to connect?
So I would try to see whois willing to share that
information with you andrespond specifically to that.
But I also think thereis an element of change
management here because.
A company that is implementingmore process and structure
is a company that isgetting ready to scale.
And something that this questioneven asked was more benefits
like More benefits is great.
That's actuallygreat news, right?
(10:03):
So like a company that'sgrowing is a company that
is winning and is a companythat is being successful.
And so maybe there's an elementof change management here
for these teams about, yeah.
So some of thesethings are different.
I used to work for a companythat for a while posted
its company financials atall hands, and then over
time stopped doing that.
People are like, well,where's the transparency?
But it's like, well now we'rehundreds of people, right?
So it's like, here's theinformation you need, here's
(10:25):
how we can continue to createthat feeling of community
but also growth is good.
David Rice (10:30):
And I'd say enjoy this challenge while you can.
Right.
Because we see a lot, we see alot of companies, you mentioned
change management there.
We see a lot of companieshaving to manage change
in the other direction.
Alana Fallis (10:39):
Yeah.
David Rice (10:40):
You know, where they're having to
win down the numbers.
So yeah, this is a good problemto have at the end of the day.
Alana Fallis (10:46):
Yeah.
David Rice (10:46):
But you do hit that inflection point.
I know.
I've been a part of orgs wherelike, yeah, we were like 25
people and then it was, youcould kind of experiment and
we had like this move fastbreak things sort of culture
and then you get up to likea hundred people and yeah,
there's layers of approval andor bureaucracy that kind of
form in a larger organization.
And then it just kindof, it is part of the
(11:09):
process of growing, right?
You're not gonna becomea bigger, more successful
higher revenue generatingorg without adding some
people, and it's just.
I don't think processis the enemy of culture.
You know what I mean?
It's how you design it.
Alana Fallis (11:22):
Yeah.
You know that's, no,that's a good quote.
Quote.
I like it.
It's true.
Right?
David Rice (11:26):
Blow that one up, put it on your wall.
Alana Fallis (11:28):
Yeah, exactly.
Take it in the office.
Yeah.
David Rice (11:30):
But I mean, you scale, for example,
like onboarding, butyou keep storytelling.
You pair new hires withculture ambassadors.
You use AI tools to sort ofcapture and share institutional
knowledge in different ways.
And so I think there's waysto do this, and I think that
the technology is going tofacilitate us doing this in so
many different kinds of ways.
But I mean, it's justpart of the challenge.
(11:52):
Right.
Alana Fallis (11:53):
Well also throwback too.
So the last question is like,make sure that your team, HR
team, I'm assuming an HR personwrote this question, but I
actually could be wrong, butmake sure that your people,
leaders, HR or otherwiseare front facing as like a
cultural ambassador and achange ambassador for these
different programs because.
That's like a really keypoint is like the community
building, the relationshipbuilding and the storytelling
(12:15):
and that culture generation.
So make sure that thehumans and people, leaders
are front and center too.
So let's see AI do that.
Okay.
Let's see AI.
David Rice (12:21):
No, exactly.
You just said it like, whenleaders live the culture that
they want, it will scale.
If they look at HR particularly,and all they see is
essentially policies and notlike people doing the thing.
Then, yeah, you're gonnafeel the erosion pretty
quickly, you know?
Alana Fallis (12:37):
Yeah, for sure.
For sure.
David Rice (12:39):
Let's see here.
What do we got next?
We got, we're collectingproductivity metrics from AI
monitoring tools, sentimentanalysis from internal
communications, even biometricdata from workplace apps.
Oh boy.
Well, like we'reboth already like.
Alana Fallis (12:55):
Me too.
Yeah.
Yikes.
Yikes.
Yeah.
David Rice (12:57):
But yeah, I'm uncomfortable with the
surveillance, but leadershipsays it's necessary for
data-driven decisions.
How do I protect employeeprivacy and trust while
meeting demands forAI powered analytics?
Alana Fallis (13:10):
Ooh, my friend, I know you did write into
this column to tell us sothat we could tell you to
quit your job, and I'm notgonna do that, but yikes.
This wouldn't work for meas a leader in the business,
and I would've a really hardtime going along with this,
as I'm sure you are, which iswhy you wrote in for advice.
I guess what I would do here isreally push onto leadership to
describe what behaviors we'reactually trying to incentivize.
(13:34):
What behaviors arewe looking to drive?
What are we actuallylooking to reward?
What are we trying to changehere, and get really focused
and dialed in on those things.
I think there are harmoniousways to target behaviors.
I don't think there is areally easy or a way that I
personally feel comfortablewith to monitor productivity.
I think we canmonitor behaviors.
I think we can't really monitorproductivity in a way that feels
(13:56):
good to the employee population.
If it is something thatyou ultimately have to go
ahead with, you should bereally transparent with your
team, really transparentabout the why and what
you're hoping to achieve.
And may I even suggesttrialing it and then retiring
it when we feel that thingshave reached a better place.
But I don't think I wouldfeel comfortable doing this.
I'm sorry to tell you.
(14:16):
Sorry to tell you.
Yeah.
David Rice (14:18):
Yeah.
No, I mean, this isthe definition of a
trust issue, right?
So yeah.
If this were arelationship, you'd bail,
Alana Fallis (14:25):
totally.
No.
That's right.
That's right.
Yeah.
David Rice (14:27):
Like they start going through your phone you
start to think about like, asa time for me to go, right?
So like, I think you have totalk about this as a trust
issue and it's, this isn't.
This isn't evenabout data, right?
Like we're necessarilywhat you're collecting.
Like I think employeestolerate just like the general
population, we tend to toleratea level of data collection if
we believe that it's eitherethical or it's transparent.
(14:49):
It's genuinely in our interest.
Right?
If it is in our interest,people kind of don't care.
They'll be like, of courseI wanna see ads that,
I mean, that's the oneeverybody hates, right?
But.
Alana Fallis (14:57):
Yeah.
Right.
Serious for sure.
David Rice (14:58):
But still like, and I think you've gotta get
the governance layer in there.
And what I would sayis, is like try creating
like a data ethics group.
That is both leadershipand employees together,
co-designing whateverybody's comfortable with.
This way you're at leastclear about what you're
collecting, why you wantit, what's off limits.
The employees have a chance tosay what's off limits to them.
(15:21):
Like, and maybe that can kindof turn it from surveillance
into sort of like a co-designedintelligence system essentially.
Right?
But honestly if leadershipthinks productivity is built on
this surveillance I mean that'sa cultural red flag, right?
So, measure outcomes.
Alana Fallis (15:38):
Yeah, measure outcomes.
No, and to the extent thatyou're able like influenced
a very focused approach hereand a very specific approach.
But that was a really good pointbecause we know that, right?
Like companies have a rightto look at what employees
are doing with theirequipment and machine, right?
We know that it's usuallysigned some point within your
employment agreement process.
There is certainly a concernhere around data privacy because
there is a variety of statelaws around like what personal
(16:00):
information can be collectedor has to be reported on.
And so I'm not an expert,I'm not an attorney, but I
would also make sure thatthis is like up to speed
with, you know, your legalteam and your security team.
So there may be otherlegal implications that
I'll just call that out.
But yeah, I, there isa cultural problem.
If this is what we'veresorted to for sure.
David Rice (16:20):
It's like one of those where it kinda gives
you the willies, right?
Like for me personally,like I, I leave my laptop
on and then it's like themicrophone's always on.
So like, is it hearing ustalk about like, you know,
you know me talking tomy son about whatever was
talking to my girlfriendabout what, like it's.
Alana Fallis (16:34):
Yeah.
I don't like it.
I don't like it.
That's what I'd say.
David Rice (16:37):
That data's in there, you know?
Alana Fallis (16:39):
Yeah, for sure.
For sure.
David Rice (16:41):
We had having the phone around and
it's always listening.
I think I, it was the otherday as we were talking about
something and the first ad onInstagram was exactly that.
I was like.
Alana Fallis (16:52):
I know.
How is it doing it?
I know it's crazy if a friendrecommends me something, that
thing appears on my Facebookads the next day, like.
Whatever it is, what it is atthis point, but we have some
agency and autonomy and therelationships, to your point
that we choose to cultivate, andthat would not be a relationship
that I feel comfortablewith for my employer.
I'd feel weird about that.
David Rice (17:11):
And I think people are wanting more control over
how their data's used andwhat, how it's collected.
Yes.
So like, yeah.
Yeah.
I think that's why I, youknow, I feel like because
people are invested in that,this is the time to have that
conversation to co-design thatwith them, because there's a
lot of people with opinionsabout this stuff, and.
You can actually probablyhave a pretty interesting
(17:31):
conversation about whatpeople are willing to put up
with and what they're not.
I think that's worth having.
Alana Fallis (17:36):
Yeah, I think so too.
David Rice (17:37):
Alright, the next question.
We discovered that one of ouremployees built a custom beat
GPT to coach him on how toflirt with coworkers, and he's
been workshopping and sendingromantic messages on Slack.
HR is manually combingthrough spreads to find
out how many AI generatedpickup lines there are.
(17:59):
And whether anyone actuallyreplied how and where do
I even add this to policy?
Alana Fallis (18:06):
Oh my God.
I was gooped by this question.
I was absolutely goopedby this question.
What?
What?
David Rice (18:12):
I was like, wow.
I mean, you know, innovation.
He's an innovative spirit.
He's an innovator.
Alana Fallis (18:20):
He's an innovator.
Oh my God.
Okay.
Well, to answer the, firstly,this is crazy town bananas,
but to answer the que thequestion at hand, I mean you
can't have your AI policy,I think account for every
single crazy fringe use casethat people do in Cook Up.
I think your policy shouldnot speak to every crazy thing
people can actually do, butshould instead speak to like.
(18:41):
Best practices, usageof the technology, and
then examples of misuse.
So like it's intended for this.
Examples of inappropriate usewould be X, Y, and Z. But I
don't even think that you needto put this into your policy
because it's common sense and itcan absolutely rise to the level
of harassment if it's pervasive.
So from a policy perspective,outline the intended use and
(19:02):
then maybe one or two or threeexamples of things that are.
Prohibited under the policy, butin this case, you just have to
talk directly to this person.
You should absolutely bewriting up this person.
I wanna know ifany of it worked.
I have so many.
Can you follow up reader?
If this was you, I needto know what happened.
David Rice (19:17):
I mean, this is one where like I don't
env HR people sometimes.
'cause I you, you seethis guy, so it's like
this is hysterical to me.
Like on the surface this isgenuinely funny, but it's
also pretty serious, right?
It's like as the HR person, no,it could really my problems.
Yeah.
You have to address this.
We're entering this likeweird gray zone, right, where
like AI can supercharge somepretty terrible behaviors,
(19:39):
things HR policies were neverdesigned to mitigate for or
you would've never anticipated.
But I think you're right,like you can't list
every possible misuse.
Policies essentiallyshould focus on principles,
respect, consent,professionalism, boundaries.
Whether it's AI, augmentedor not, it still violates
those and it's a problem.
Alana Fallis (19:59):
Totally.
And I would also be willingto bet that this probably
falls under some kind ofharassment policy that you have
elsewhere in your handbooksand employee documents.
So I think this is notlike a specific to how
to use this tool policy.
It's just like a generalprinciple that you probably
have covered in manyplaces throughout like
your handbook and stuff.
But yeah, I wanna knowwhat happened, let us know.
David Rice (20:19):
If you're one of the recipients of one of
these messages, I'm curious,was it a decent pickup line?
Alana Fallis (20:26):
Did it work?
Did it work?
Yeah.
Were you more interested after?
No.
Yeah.
People find new and creativeways to do crazy things
in the workplace, man.
So AI is no exception.
So, wow.
David Rice (20:38):
That was a wild one.
I was like, I saw that onecome in and I was like, oh,
I can't wait for that start.
Alana Fallis (20:43):
I know.
Oh man.
Oh man.
Yeah.
David Rice (20:46):
Alright.
Final question.
I'm struggling with a disconnectbetween what our leadership
says about work-life balanceand what they actually expect.
We promote flexibility,but managers still schedule
last minute Friday eveningmeetings and expect
weekend email responses.
How do I address this gapwithout seeming like I'm not
supporting business needs?
Alana Fallis (21:06):
Oh, this is a tough one because burnout
is just so pervasive.
Like I work in the tech industryand I think burnout is like
a thing that we hear almostevery survey we do, almost
every employee listening, likethere's always this balance
between driving exceptionalbusiness results and being able
to have your team members havea relationship to work that is
sustainable and comfortable.
I think it's about implementingsome kind of framework, or
(21:29):
especially some written guidanceabout defining what's important,
defining working parameters.
Here are the circumstancesor the occasional seasons in
which we may expect you tohave to go above and beyond,
like if you work for any.
Software company, likesupporting for a retail brand,
for example, black Friday is,oh, like people have to be
on, even though it's a dayoff for many other companies.
Right?
So some kind of like bestpractices framework or working
(21:52):
guidelines framework oflike, you know, we promote
a culture of flexibility.
We promote a culture of workingwhen works best for you.
There are times that we needall hands on deck and those
times are these examples,in which case some late
nights may be expected.
As a matter of course, as amatter of day-to-day working
course weekend, email responsesshould not be expected.
So in that case,that's something that
(22:12):
you need to address.
But maybe with partnershipwith your managers, you
can define when we reallyneed it, what's most
important, and when we don't.
But if your managers, I think,run amuck and just like continue
to create a culture wherepeople have to be on 24 7,
they'll start to lose people.
And that's what youwanna get ahead of.
David Rice (22:30):
I would agree.
I've been seeing all kindsof crazy stuff lately.
The 9, 9, 6 thing that'sgoing around, it just
sounds like a nightmare.
And then you've got, I saw onethe other day, this lady said
she's been doing four days of,I think it was like 14 hour
days followed by three days off.
So she's like, oh, I gota four day work week.
I'm like, yeah, and this isa recipe of you're getting
(22:52):
addicted to drugs or something.
Like, what are you gonna keep?
Alana Fallis (22:55):
Yeah, right.
My God.
David Rice (22:56):
I mean, first of all, the word quality is gonna
suffer, so this is already abad business idea in my opinion.
Then, yeah, you're justgonna burn yourself out.
I think from the perspectiveof this question though,
when employees hear onething, they see another.
You don't just losegoodwill, right?
You lose credibility oncewe're all sitting around
having this trust conversation.
But you're eroding credibility,so you've got to weigh
(23:19):
up, like what's gonna makeevery initiative harder?
Well, this is one ofthose things, when we
don't live this value.
This is gonna makeeverything harder.
And people are looking outand they're seeing some
terrible behaviors, like I'mtalking about going around the
professional world right now.
And they're like, listen,if they, I gotta draw
the line somewhere.
So it starts to becomesort of like combative
and that is not where youwant your people to be.
(23:40):
So it's, I think it's, youwanna align leadership intent
with management practice.
Alana Fallis (23:47):
Yeah.
Yeah, that's agreat way to put it.
David Rice (23:49):
That might mean manager training clear
guardrails, you know, holdingleaders accountable to
the same balance that theyexpect employees to have.
Those are all things thathave to happen and I think
you can kind of put a positivespin when you fix this gap.
'cause you don't justimprove work-life balance.
Right?
You actually sort of, basicallyyou're unlocking productivity
'cause you're ensuring peoplearen't running on fumes.
(24:11):
So it's like really focus there.
This is how we'reavoiding burnout.
This is how we're maintainingproductivity, and this is
how we're keeping the culturewhere we want it to be.
It's really attractive to peoplewith the skills that we need.
Alana Fallis (24:23):
There's a real communication and
teaching here around a forestfor the tree situation.
Like you may meet X deadline,but your top talent will
eventually burn out andleave, or may have to
go on a medical leave.
Do you know what I'm saying?
Like you'll see people whoreally start to suffer, but it
always does come from the top.
So like the people who reallyneed to model this behavior
as the executive team.
Who needs to manage thoseexpectations are the executive
(24:44):
team, because some managers,maybe they don't, maybe
either the executive team isnot aware or they're pushing
you know, an unfeasible orunsustainable work culture.
But it's probably the former.
I mean, in my experience, Ifind that it's the former.
David Rice (24:56):
I agree.
All right.
Well, this was a goodround of questions.
Alana Fallis (24:59):
We got some questions answered today.
We knocked a coupleoff our list.
But yeah, keep 'em coming.
Give us your updates.
If you wrote any of these, likelet us know how things resolve.
We'd love to know.
David Rice (25:09):
Yeah, love an update.
Keep 'em coming.
We'll keep posting the linkto the question form, but
feel free to, it's out there.
It's called Talk HR to Me.
You can find thequestion form me.
You can find it on ourwebsite on Alana's articles.
So please do keep 'em coming.
We look forward to it.
Until next time, signup for the newsletter
if you haven't already.
Some really coolstuff is going on.
(25:31):
And until next time, pleasekeep your AI generated pickup
lines out of the workplace.
Alana Fallis (25:37):
Keep 'em to yourself.
Keep 'em to yourself.
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