Shownotes
In this episode of the Future Proof HR podcast, Thomas Kunjappu sits down with Jamie Rivero, HR Director at MYCO Mechanical, Inc., to explore what disciplined HR leadership looks like in a rapidly changing environment. Drawing on nearly two decades of experience across manufacturing, logistics, healthcare, retail, and construction, Jamie shares how HR leaders can navigate AI adoption and major system decisions without losing credibility or trust.
Jamie explains why moving too fast on AI and HR technology often creates more problems than it solves. She unpacks the importance of understanding the business before evaluating tools, pressure-testing vendor claims, and building ROI cases that connect time saved to real business outcomes rather than surface-level efficiency metrics.
The conversation also examines where AI can support HR teams and where human judgment must remain central. Jamie outlines how HR leaders can reduce low-value work with technology while protecting high-stakes decisions like hiring, performance management, and employee relations, offering a grounded view of what it takes to lead HR through ongoing change.
Topics Discussed:
- Why HR leadership today requires judgment, not just tools
- Slowing down AI adoption to avoid costly implementation mistakes
- Evaluating HR technology through a true business lens
- Building credible ROI cases that executives trust
- Lessons learned from failed or delayed HR system implementations
- Negotiating vendor contracts and protecting leverage during implementation
- Where AI belongs in HR and where humans must stay in the loop
- Preparing HR teams for continuous change without eroding trust
If you are an HR leader, people strategist, or executive navigating AI, HR technology, and constant change, this episode offers practical insight into how experienced HR leaders make decisions that stand the test of time.
Additional Resources:
Transcripts
And it's like everybody thinks AI.
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Just because it's AI, it's going to
simplify things, or it's going to reduce
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costs, or it's going to reduce headcount.
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And I feel like you really need to
do a lot of due diligence when it
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comes to vetting AI technology and
really figuring out and spending
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the time if it's the right fit.
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Thomas Kunjappu: They keep
telling us that it's all over.
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For HR, the age of AI is upon
us, and that means HR should
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be prepared to be decimated.
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We reject that message.
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The future of HR won't be handed to us.
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Instead, it'll be defined by those
ready to experiment, adopt, and adapt.
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Future Proof HR invites these builders to
share what they're trying, how it's going,
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what they've learned, and what's next.
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We are committed to arming HR
with the AI insights to not
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just survive, but to thrive.
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Welcome to the Future Proof HR podcast,
where we explore how forward thinking
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HR leaders are preparing for disruption.
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Thomas Kunjappu: and redefining what it
means to lead people in a changing world.
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I'm your host, Thomas
Kunjappu, CEO of Cleary.
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Today's guest is Jamie Rivero,
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HR Director at MYCO Mechanical, Inc.
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A strategic global HR and operations
leader, Jamie focuses on aligning
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human capital to business outcomes.
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Building culture that drives performance
while safeguarding compliance and risk.
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With experience leading transformation
and fostering resilient teams, Jamie
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blends integrity, a clear strategic
vision, and hands-on operational
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chops to deliver measurable results.
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Jamie, welcome to the podcast.
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Jamie Rivero: Thank you for having me.
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Thomas Kunjappu: So tell me a little
bit about your background and the
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scope and industry that you work at.
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Jamie Rivero: Sure.
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So I've been working in human
resources for about 18 years.
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I've worked in grocery, like
grocery retail, healthcare,
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manufacturing and logistics,
where I spent most of my career.
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And now about six months ago, I
made the jump into construction,
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which has been definitely a
change, but there's definitely some
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similarities in the manufacturing
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and warehousing background.
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And I oversee all facets of HR.
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So from recruitment all the
way up to talent development,
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full life cycle of employment.
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Thomas Kunjappu: That is a
lot of different industries.
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I'd be excited to get into what's similar,
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what's different.
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But first, I'd like to ask you a little
bit about how you've maybe moved across
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different companies with AI-driven
cultures that are a little bit different
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or attitudes towards AI and or technology.
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Can you tell me a little bit about
these mindset shifts and what that
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means for you being an HR leader?
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Jamie Rivero: So I definitely
have dealt with a stark difference
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in terms of attitude shifts
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towards AI.
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So my previous company was running
towards AI at a very fast pace,
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which I am all for AI, but I feel
like right now it's like a buzzword.
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And it's like everybody thinks, you know,
AI, just because it's AI, it's going to
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simplify things, or it's going to reduce
costs, or it's going to reduce headcount.
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And I feel like you really need to
do a lot of due diligence when it
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comes to vetting AI technology and
really figuring out and spending
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the time if it's the right fit.
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And where I'm at now, definitely not as
running towards it that quickly, which
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is obviously a big difference, but I
actually welcome it because I do, I feel
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like you need to find the balance with AI.
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And I'm sure we'll jump into it
a little bit more in terms of why
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that is and why that's a benefit.
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Thomas Kunjappu: So then what does
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that mean for you as an HR leader in
your day-to-day when you have this?
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Because it's one thing for the business to
have like an attitude or a certain culture
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around AI, but then what does
that mean for you and how your
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daily rhythms are different?
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Jamie Rivero: Yeah, so AI definitely
has hit HR as an industry very heavily.
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And it's a topic at all
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the conferences.
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I've been seeing it for
the last couple years.
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It's like most of the content
at HR conferences is now AI.
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And where I feel like it's a little
bit challenging is I feel like so
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much technology has flooded the space
right now, but there hasn't been a
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whole lot of framework in terms of
best practices on how to implement it.
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What are the implications of AI
technology, especially from a
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legal and a compliance standpoint?
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And that's a lot of the feedback that I've
heard at a lot of these HR conferences.
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It's like AI, AI, but it's like,
how do we actually implement it?
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What are the best practices?
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And I feel like maybe we ran a little bit
too fast towards AI and we skipped some of
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those steps.
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And I feel like a lot of companies
are now trying to figure out
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all of that kind of legal
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and compliance aspect, which
I think is really important.
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And for me, also, HR, there's a
HR, there's a human aspect to it.
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And we can talk about later about
the implications of when it's
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appropriate to use AI technology.
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But there's certain things in HR where I
don't know that it's ever going to make
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sense for AI technology to be utilized.
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And that's something that I feel like as
HR leaders, we really need to figure out.
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And I feel like also we also
need to embrace AI technology.
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Like I know there's a lot of
people who are resistant to
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it, because a lot of times when
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you hear AI, you think, you know,
it's going to replace jobs, and
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it's going to eliminate our jobs.
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And I feel like we need to be open
to it, but also understand, like,
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it's not going to take our job.
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And I feel like if you position
yourself, like you will be
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a very valuable HR person.
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Like there's no way that AI technology
is going to totally eliminate your job.
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Thomas Kunjappu: So there's a lot to
unpack there, but let's start with, I
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guess, just the concept up top, right?
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That like from a vendor perspective,
there's been lots of pushing of
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the technology into the HR realm.
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You've had some experience with this.
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Like do you evaluate a potential
partnership in, I guess you call
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it right, it's a flooded market.
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Jamie Rivero: Yeah.
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And it definitely is a flooded market.
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If you walk expos at conferences,
I would say probably like 40
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to 50% of it now is all AI
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technology, maybe more.
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And I would say definitely,
first and foremost, you need
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to understand your business.
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And when I say that from an HR
perspective, it's not just understanding
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your business from an HR perspective.
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If you want to be an effective
HR leader, you need to understand
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the business as a whole.
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And that's something that I always
try to do anytime I join a company.
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I want to understand my role,
but I also want to understand
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how my role impacts other
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areas of the business.
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Because oftentimes when you're
implementing AI technology,
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like it's going to impact not
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just HR.
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And if it's from an HR
perspective, it's going to impact
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other areas of the business.
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So I think having a full
understanding of that.
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Also vetting the software.
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Is this a software
company that is brand new?
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Has it been around a while?
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Understanding does this
software fit my business today?
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And is it going to fit my
business if my business doubles
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or triples?
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I think oftentimes people make a lot of
short-sighted decisions and I've seen
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it over the years where it's like you
decide on a technology or a software
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and, you know, it fits your business
today, but then you're not thinking
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a couple of years down the road, is
this software going to be able to grow
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and support the company as we grow?
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Because there's a lot of money
and time that gets spent in
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implementing different types
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of software solutions.
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And there's nothing worse than
spending a ton of time on a project.
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And then three years later, you're
like, this doesn't fit anymore.
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And then also definitely
diving into the ROI.
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So I feel like a lot of these software
companies, and I see it because I've been
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through a lot of these sales pitches.
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It's we can save you $1.2
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million, we can save you $300,000.
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And it's and it goes back
to my point of you really
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need to know your business because
you should be calculating the ROI.
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Obviously they can give you
tips and help you with it.
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But I always get fearful when
companies are like, we'll do
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the ROI calculation for you.
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And then they start throwing these
random numbers and it's, we'll even
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talk to your executive team about it.
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And I'm like, I can't even imagine like
putting you in front of my executive team
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because you don't even know our business.
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Like they're going to poke holes in that.
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So I think it's really important to
vet that and also get references.
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Like I've been through sales pitches.
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I've been through almost to the point
where we're going to sign and they can't
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produce references that are similar to
our business or who could talk to what
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exactly we need the software to do.
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So I think it's really hammering
home, like spending a lot of
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time in that due diligence phase
before you sign a contract.
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Thomas Kunjappu: Got it.
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So due diligence, understanding your
business, figuring out your process.
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There's the understanding
the potential vendor partner.
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And if you put it all together, you
can create something that can work.
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But then I've also heard about
leveraging pilots wherever
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you can try before you buy.
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Does that generally work?
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Has that worked for you or
does it depend on the use case?
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Jamie Rivero: It's a great idea in theory.
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What I oftentimes find is there are a
lot of software companies that will offer
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you pilots, but it's oftentimes not live.
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It's a sandbox type of territory
where you can't really fully
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see what it can do as it's
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integrated into your business.
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And that's where I found I
oftentimes struggle because I've
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run into situations, and I'm
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sure a lot of people experience this
where, sales people will tell you
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whatever and they'll tell you, oh, yeah,
the software does this, it does that.
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And then it's like you get midway through
the implementation and it's no, actually,
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it can't do that or that's custom.
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And then they try to charge you for
the development and stuff like that.
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And that's why I say I think pilot
programs are definitely helpful.
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And the more that you
can see live, the better.
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But you also have go into
it knowing like, it is very
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difficult to vet everything out.
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But I think it's important.
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Like, you don't want to skip
that due diligence phase.
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Thomas Kunjappu: And then do you
think that there's some things that
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are just I don't know, are there some
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use cases or types of areas
that are just really hard to
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do right and leads naturally to
over-promising and under-delivering?
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Or is it really just, in your
experience, about the specific
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partnership in question?
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Jamie Rivero: I think it's a mix of both.
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A lot of companies have very specific ways
and processes that they do certain things.
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I'll give you an example,
performance review process.
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I ran into a situation where
I didn't feel 100% about the
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performance module of the software.
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I knew going into it was probably going
to be a little bit of a challenge, but
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I was a little surprised during the
implementation of how hard it was to get
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the system to do something so simple.
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And I think that companies need
to consider that when they're
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evaluating software, like how firm
are you on your existing process?
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Because a lot of times like you have
to adapt and sometimes you have to
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pivot and change to make things work.
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And then there's certain companies
where they're just dead set on
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this is how it's going to be adapt.
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And sometimes you have to pivot
and change to make things work.
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And then there's certain companies
where they're just dead set on
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this is how it's going to be done.
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And then obviously it's a big
problem when the software solution
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can't do what you need it to do.
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And I think that I'm running into a lot
of that in the market right now where
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it's like they lack the customization.
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And I think that if you're
a company where you need
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customization, that's something you
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really need to vet in
the process early on.
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But if you're not and you're looking
for more of that out of the box turnkey
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solution, then that works for you.
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But it just depends on like the specific
processes of your business and how married
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you are to them.
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Thomas Kunjappu: I see.
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So then you mentioned ROI and how
that's important own yourself and
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understanding the nuances of the business
versus something that's more generic.
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Can you tell me a little bit about
your, at least your mental model for
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making these ROI cases to leadership?
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What are the inputs and the kind
of the so what's that you go for?
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Jamie Rivero: Yeah.
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So most of my career, and I feel
like I've been very successful
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with pushing big initiatives because
I do spend so much time to figure out
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what the ROI is and really lay it out
where it's like when I'm coming to the
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executive team to spend money or to
implement something, I've already thought
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through in terms of what are the benefits,
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what are the downfalls, so
the pros and cons, what are
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the costs associated with it?
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When will we typically see the ROI?
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What are all the inputs
or processes that go in?
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How am I measuring them, understanding
like what is the expected outcome,
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but also taking a step further.
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And I found that obviously I was in
an operations role heavily as well.
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Everybody wants technology and
they want enhancements and stuff
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like that, but they come at a cost.
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So what are we getting from the cost?
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And oftentimes I'm laying out, okay,
we're going to free up this many
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hours a week, or we're going to free
up this person, but then also coming
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with a plan in terms of this is
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Speaker 3: This is now what I'm gonna
do with this person, or this is now
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what I'm gonna do with this time,
or I'm gonna eliminate head count.
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I feel like taking it so far, like
that has made it very easy for
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me to get things pushed through.
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Jamie Rivero: Whereas I've seen
other people, they struggle.
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It's this software is going
to cost $57,000 a year.
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And then you have executives,
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like, where are we getting this money?
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Why are we going to spend on it?
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What's the value?
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And that's why I think it's important
to really be able to build that business
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case, because I think it makes it so
much easier, but also understanding.
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Maybe you go through the ROI process and
you realize, and I've actually ran into
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this, where the software looks so great.
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It looked like such a great solution.
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It was cutting edge, leading the market.
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But then I'm like, wait a
minute, there's no ROI here.
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Or the ROI is so minimal compared to
the amount of work and stuff like that.
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And it's just there's no
justification for the cost.
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And sometimes that does happen too.
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Thomas Kunjappu: So you told me
something that, you just mentioned
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something that's this next level,
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which is an ROI calculation
typically says, look, we saved this
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many hours or this many dollars.
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And that's usually expressed
in time for personnel, right?
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Maybe there's other things about like
outcomes, whether it's whatever it is,
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error reduction or compliance,
which is just useful or some
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kind of employee productivity
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benefit as well.
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But strictly on the HR team, it's
typically about like hours saved, right?
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That goes into the outcome.
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But then you're taking that a step
further to say why the hours saved
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matter, not assuming that everyone
thinks that itself is a goal.
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Because why, after all,
does the HR team get paid?
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It's to spend time doing
things that is valuable, right?
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But then if you're going to save time,
you're saying, but then here are things
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that is business aligned that we can do
that is even more important that we're
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going to be able to do with that time.
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So the ROI isn't like this many hours
saved, but it's these other things
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done without any new additional hiring.
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Jamie Rivero: Yeah, absolutely.
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Because you have to be careful.
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I've run into situations where
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I've had managers come to me and we
had invested a bunch in enhancements,
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software development, that type of stuff.
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And they're still telling me that
they're overloaded with their work
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and they need more head count.
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And I'm like, but wait a
minute, we've done all this.
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So there's something wrong there.
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So I think like being able to make that
case of this is what we plan to save
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and taking a step further and sharing.
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This is the value that we can bring
to the business and looking at more HR
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related activities that maybe have fell
by the wayside that we could focus on.
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Or I feel like businesses
are also changing so rapidly.
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And I think a lot of businesses want
like that human connection still.
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So if we can free up our HR team where
they're not doing these monotonous
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type tasks, what more can we add
on their plate that is going to
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connect to the bottom line of the
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business or connect to our
strategic goals of the business?
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Thomas Kunjappu: Yeah, there's so many
different interrelated problems, right?
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And it's sometimes hard to
pinpoint exactly what it is.
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So I feel like there's
something there in that story.
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Can you tell me a little bit more about
that manager or management investment?
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What was the initial thinking?
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And I imagine there was some kind of
like software or technology solution
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that we thought would solve the
problem, but maybe it was still there.
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So what was the initial thinking?
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And then how did that evolve?
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And maybe you can
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think of everything as an experiment
along the way that worked or
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didn't work, but maybe the root
cause itself was misdiagnosed?
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Or how do you think about that?
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Jamie Rivero: Yeah.
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So obviously there were a
lot of enhancements that
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were made in our ERP system.
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And we have an in-house team, but
we also had consultants and there's
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a lot of costs that's associated.
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And oftentimes when you're looking
at those enhancements, you want
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to understand what is the ROI?
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Is this worth our time and money?
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And having the manager fully understand or
present what exactly is this change going
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to simplify and taking it a step further.
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And one of the things we were seeing
a number of enhancements being
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made, but it was like business
was not drastically changing in
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terms of sales, but the manager
continually was like, I'm overloaded.
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My team's overloaded.
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So then I'm questioning,
okay, what is going on here?
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We did these four things and this
was supposed to reduce our spend.
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And I'm going back into all the
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fine details of these projects.
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And for me, really management issue.
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But also it made me kind of
question, okay, maybe we need to
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dive deeper into your analysis.
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And that was a pain point I've
learned over the years is like,
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you can have teams do analysis of
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This has been a fantastic
conversation so far.
354
00:18:27,064 --> 00:18:29,854
If you haven't already done so,
make sure to join our community.
355
00:18:30,094 --> 00:18:32,764
We are building a network of the
most forward-thinking, HR and
356
00:18:32,764 --> 00:18:35,944
people, operational professionals
who are defining the future.
357
00:18:36,424 --> 00:18:39,034
I will personally be sharing
news and ideas around how we
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00:18:39,034 --> 00:18:41,044
can all thrive in the age of ai.
359
00:18:41,404 --> 00:18:44,389
You can find it at go cleary.com/cleary
360
00:18:44,819 --> 00:18:45,429
community.
361
00:18:46,054 --> 00:18:46,894
Now back to the show.
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Jamie Rivero: whether it's time studies,
whether it's ROI and stuff like that.
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But it is really important.
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Like you can't always take
everything at face value.
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And you need to, especially when there's
a significant amount of money involved,
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you really have to take the time to
go through that analysis and make
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sure are they looking at every aspect?
368
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Are these calculations correct?
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I've seen issues where
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there's a formula and it's when
you're authorizing financial expenses
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or implementing something big
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that's going to disrupt the business.
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You want to make sure that You want to
make sure that you're doing it right.
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And that you're spending money
that is actually adding value.
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And for me, like what I was seeing was
maybe these weren't the right solutions.
376
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Like maybe we weren't spending our
time and money in the right areas.
377
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And it made me dive deeper into the
specific management of that area.
378
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And obviously, it's a lesson learned.
379
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Like you really can't just blindly take
everything you have to dive in and make
380
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sure that analysis is 100% accurate.
381
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And if you're not sure, then you need to
make sure that you're asking the right
382
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questions to get to the bottom of that.
383
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Thomas Kunjappu: And which part of
that involves like understanding
384
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how the business works, right?
385
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Or how that group is actually doing
their like day-to-day activities that
386
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leads to this analysis and this set of
concerns, which you're trying to solve
387
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for with some kind of process or software.
388
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Great point.
389
00:20:05,356 --> 00:20:07,026
So it's okay.
390
00:20:07,106 --> 00:20:10,506
Maybe you don't necessarily trust
vendor math or manager math.
391
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And you want to ensure that
you're double checking the work
392
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yourself and that makes sense.
393
00:20:16,446 --> 00:20:20,376
And now that we're in this age of
AI, are all these things the same?
394
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Or do you feel like it's all these
cautions that you have, these lessons
395
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that you've learned from trying to improve
outcomes and get to higher ROI and all
396
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these steps that we talked about in this
age of AI, does it feel any different
397
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than, I don't know, the age of SaaS or any
kind of technologies beforehand in terms
398
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of your process or even the challenges?
399
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Jamie Rivero: It
certainly feels different.
400
00:20:45,646 --> 00:20:49,096
I think the more implementations
you go through, the more
401
00:20:49,096 --> 00:20:50,706
sales pitches you go through.
402
00:20:50,706 --> 00:20:56,726
I think that there's a sense of, I don't
know if jadedness is the right word.
403
00:20:57,356 --> 00:21:00,946
But as you go through these
different experiences, you learn,
404
00:21:01,306 --> 00:21:05,426
like, I went through a number of
very large software implementations
405
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over the last couple of years.
406
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And while they all panned out
at the end, for the most part, I
407
00:21:11,326 --> 00:21:13,286
did run into a number of hiccups.
408
00:21:13,776 --> 00:21:18,556
And for me, I've always tried to take
those setbacks as like lessons learned.
409
00:21:18,566 --> 00:21:24,886
So like now every time I go into another
software evaluation, I'm always like,
410
00:21:24,996 --> 00:21:28,261
I have in the back of my
head, learn this the hard way,
411
00:21:28,306 --> 00:21:29,706
make sure you do this better.
412
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And I always try to do a postmortem
anytime I do like an implementation
413
00:21:34,636 --> 00:21:37,066
of any sort, because I want
to understand not just from my
414
00:21:37,066 --> 00:21:39,676
perspective, but also what
my team has went through.
415
00:21:39,676 --> 00:21:42,236
What could we have done differently?
416
00:21:42,246 --> 00:21:43,606
What did we learn?
417
00:21:43,676 --> 00:21:45,536
What did we not vet properly?
418
00:21:46,066 --> 00:21:50,926
And then as we go through more and more
of these implementations, we're in a much
419
00:21:50,966 --> 00:21:57,456
better mindset and much stronger in terms
of hopefully really vetting them out
420
00:21:57,466 --> 00:21:59,996
better, but also being able to deliver
421
00:22:00,016 --> 00:22:02,696
exactly what we're intending to get.
422
00:22:03,826 --> 00:22:06,776
Thomas Kunjappu: Anything in particular
that I know it's every, depending on
423
00:22:06,776 --> 00:22:10,831
what kind of project and the vendor and
the context, it all can be very distinct.
424
00:22:10,831 --> 00:22:13,561
And you're talking about the processes
that if you have that in place, it's
425
00:22:13,561 --> 00:22:19,111
helpful, but any particular other
meta lessons or big ones that come to
426
00:22:19,111 --> 00:22:20,431
mind that you'd be willing to share?
427
00:22:20,961 --> 00:22:21,371
Jamie Rivero: Yeah.
428
00:22:21,371 --> 00:22:25,651
So I went through an experience
earlier this year with a payroll
429
00:22:25,661 --> 00:22:26,101
vendor.
430
00:22:26,601 --> 00:22:30,831
It was payroll HRS and
it was a great system.
431
00:22:31,511 --> 00:22:33,021
I still love it.
432
00:22:33,041 --> 00:22:38,111
the system the implementation process was
horrible and I learned a lot of lessons
433
00:22:38,111 --> 00:22:44,221
throughout it one of the caveats and every
HR person anytime you bring up payroll
434
00:22:44,221 --> 00:22:48,681
systems we all have gripes about all
of them there is not a perfect payroll
435
00:22:48,701 --> 00:22:55,691
hrs system out there but for me i had a
challenging implementation because there
436
00:22:55,691 --> 00:22:59,151
were a lot of things that were promised.
437
00:22:59,211 --> 00:23:03,781
And I was very smart about it in
terms of getting things in writing.
438
00:23:03,781 --> 00:23:07,131
Like I would not agree to sign the
contract until I got certain specifics
439
00:23:07,131 --> 00:23:11,231
in there because the certain specifics
were, they depended upon our business.
440
00:23:11,281 --> 00:23:14,241
And for me, like they
were major deal breakers.
441
00:23:14,251 --> 00:23:17,271
If you can't do this, then this
is not the software for us.
442
00:23:17,291 --> 00:23:22,891
And I should have known early on that this
implementation was not going to go well.
443
00:23:22,891 --> 00:23:24,261
And I was smart about it.
444
00:23:24,271 --> 00:23:26,821
So one of the things I've
learned in implementations is
445
00:23:26,831 --> 00:23:28,491
in any software agreements,
446
00:23:28,991 --> 00:23:30,951
don't pay a lot for implementation.
447
00:23:30,951 --> 00:23:35,081
Like oftentimes when they quote you,
they will throw like high numbers for
448
00:23:35,081 --> 00:23:38,171
this is our implementation fee, or
this is the cost of implementation.
449
00:23:38,191 --> 00:23:40,511
I've always negotiated
them down substantially.
450
00:23:40,511 --> 00:23:42,991
Because what I've learned is once
451
00:23:42,991 --> 00:23:46,331
you pay those big fees for
implementation, they have you on the hook.
452
00:23:46,951 --> 00:23:52,911
But if you pay a lot less, they have more
in the game than you do at that point.
453
00:23:52,931 --> 00:23:56,801
So it becomes easier from a
negotiating factor as well
454
00:23:56,801 --> 00:23:58,531
as trying to get stuff done.
455
00:23:59,081 --> 00:24:00,681
And with this payroll
456
00:24:00,681 --> 00:24:05,151
provider, there were a lot of things like
there were delays in terms of starting
457
00:24:05,191 --> 00:24:09,801
implementation, which our business was
dependent upon the system going live
458
00:24:09,801 --> 00:24:14,481
in January, because we had performance
reviews, there were benefits involved,
459
00:24:14,481 --> 00:24:16,351
like there were a lot of moving pieces.
460
00:24:16,381 --> 00:24:18,231
And they had assured me like, we're gonna,
461
00:24:18,771 --> 00:24:19,721
we're gonna go live.
462
00:24:19,721 --> 00:24:22,161
And I knew it's probably
not gonna trend that way.
463
00:24:22,181 --> 00:24:26,461
And it got worse as the implementation
went, was moving forward because
464
00:24:26,461 --> 00:24:29,711
it was like more and more things
were getting dropped on us.
465
00:24:29,771 --> 00:24:31,141
I'll give you a quick example.
466
00:24:31,151 --> 00:24:34,601
So we were in two countries, we're
in the United States and Canada.
467
00:24:34,941 --> 00:24:39,851
And one of the premises of this
software move was I wanted a payroll
468
00:24:39,851 --> 00:24:44,271
system that could do both US and
Canada in one system, rather than
469
00:24:44,271 --> 00:24:46,411
running two standalone programs.
470
00:24:46,951 --> 00:24:50,031
They assured me throughout the process,
we can do Canadian payroll, went
471
00:24:50,031 --> 00:24:52,821
through the demos, talked to a client.
472
00:24:52,881 --> 00:24:54,961
But one thing that wasn't
disclosed to us was that
473
00:24:54,961 --> 00:24:57,881
they couldn't pay Canadian
employees directly.
474
00:24:57,941 --> 00:24:59,301
They weren't set up yet.
475
00:24:59,691 --> 00:25:04,471
So we would have to export a file
out of the system, then move it
476
00:25:04,471 --> 00:25:07,721
to our bank, who would then pay
the Canadian employees directly.
477
00:25:08,121 --> 00:25:11,891
They dropped that on me, I guess,
four weeks when we were supposed
478
00:25:11,891 --> 00:25:13,861
to go live, like four weeks before.
479
00:25:14,341 --> 00:25:17,441
And I'm like, wait a minute, it's
not just I just send a file to
480
00:25:17,441 --> 00:25:18,961
the bank and then they just pay.
481
00:25:18,961 --> 00:25:22,131
There's a lot of stuff that's
involved in terms of that.
482
00:25:22,861 --> 00:25:27,431
Then it got to a point where I
actually had to delay the project.
483
00:25:27,431 --> 00:25:29,871
Like I had to stop it essentially
because there were a lot
484
00:25:29,871 --> 00:25:30,711
of things that were popping
485
00:25:30,711 --> 00:25:33,561
up that were like out of the
scope of the original agreement.
486
00:25:34,096 --> 00:25:36,311
Even in like the learning
management piece of it, they were
487
00:25:36,311 --> 00:25:38,041
trying to pass costs along to me.
488
00:25:38,041 --> 00:25:39,906
And I'm like, wait a minute,
I have in writing like that
489
00:25:39,971 --> 00:25:40,901
you were paying for this.
490
00:25:41,341 --> 00:25:44,081
So it got to a point where I had
to stop the project completely.
491
00:25:44,081 --> 00:25:47,941
And because we didn't spend that
much in the implementation, we had
492
00:25:47,941 --> 00:25:52,101
a lot of negotiating power because
they had so much more tied up into
493
00:25:52,101 --> 00:25:53,821
this implementation than we did.
494
00:25:54,171 --> 00:25:55,021
But it was a mess.
495
00:25:55,051 --> 00:25:56,161
I learned a lot from it.
496
00:25:56,171 --> 00:25:59,151
It was a great, I still
think it's a great system.
497
00:25:59,531 --> 00:26:05,386
But it taught me the importance of things
that we probably should have vetted
498
00:26:05,396 --> 00:26:09,726
better up front, as well as the importance
of getting certain things in writing.
499
00:26:11,276 --> 00:26:12,006
Thomas Kunjappu: Great points.
500
00:26:12,006 --> 00:26:16,916
And now we're really talking about
like contracting in that detail, right?
501
00:26:16,976 --> 00:26:18,306
Yeah, in a true partnership, right?
502
00:26:18,306 --> 00:26:21,836
There should be skin in the game
a little bit on both sides, right?
503
00:26:21,836 --> 00:26:23,376
It needs to be fair.
504
00:26:23,791 --> 00:26:28,616
And that's a great example of
something at surface level.
505
00:26:28,856 --> 00:26:31,536
And even at level two, the
answer is yes, we're aligned.
506
00:26:31,536 --> 00:26:35,256
But then, and even post-pilot, when
you're actually getting to an actual
507
00:26:35,446 --> 00:26:39,476
four weeks beforehand, you actually
learn something where there's so many
508
00:26:39,476 --> 00:26:42,806
assumptions that were like made that
was not, there was not alignment on
509
00:26:43,436 --> 00:26:45,426
or potentially was willfully hidden.
510
00:26:45,496 --> 00:26:46,066
I'm not sure.
511
00:26:46,526 --> 00:26:49,396
But these are the, yeah, like
all these pitfalls, but a common
512
00:26:49,396 --> 00:26:51,536
theme I'm sensing here is it
513
00:26:51,536 --> 00:26:54,676
really maps to your
business processes, right?
514
00:26:54,696 --> 00:26:57,316
You need to understand like
what is, what matters and
515
00:26:57,896 --> 00:26:59,296
doesn't matter to your business.
516
00:26:59,371 --> 00:27:01,131
I don't know if you had a great bank
517
00:27:01,131 --> 00:27:05,421
and it's an automated process to
just whatever it is you need to do
518
00:27:05,421 --> 00:27:07,911
to transfer the money and make
it happen, that's one thing.
519
00:27:07,911 --> 00:27:12,981
But you can't change banks
because of many other reasons.
520
00:27:13,011 --> 00:27:15,691
That leads you to a
black hole here, right?
521
00:27:15,691 --> 00:27:20,261
So it really is getting to as many
detailed levels of understanding
522
00:27:20,261 --> 00:27:25,001
about what really matters and you're
inflexible on versus what you could push
523
00:27:25,001 --> 00:27:26,931
forward on from a process perspective.
524
00:27:27,451 --> 00:27:32,386
Within this or many other projects,
what are your tools to bring
525
00:27:32,586 --> 00:27:34,406
skeptical leaders alongside?
526
00:27:34,566 --> 00:27:36,406
So let's say you've done your own math.
527
00:27:36,466 --> 00:27:36,726
You feel like this is a project that you
528
00:27:36,726 --> 00:27:36,746
want to move forward with, whatever it is.
529
00:27:36,746 --> 00:27:37,566
And you're looking've done your own math.
530
00:27:37,576 --> 00:27:39,856
You feel like this is a project
that like you want to move
531
00:27:39,866 --> 00:27:41,126
forward with whatever it is.
532
00:27:41,531 --> 00:27:45,526
And you're looking to bring in
it could be leadership or it
533
00:27:45,526 --> 00:27:47,276
could be the management team.
534
00:27:47,706 --> 00:27:48,636
How do you bring them along?
535
00:27:49,696 --> 00:27:50,086
Jamie Rivero: Yeah.
536
00:27:50,086 --> 00:27:54,576
So oftentimes whenever I'm
thinking or trying to solve a
537
00:27:54,576 --> 00:27:56,396
business problem, I'll oftentimes
538
00:27:56,396 --> 00:27:57,176
talk to you.
539
00:27:57,266 --> 00:27:58,766
I would talk to the executive team.
540
00:27:58,806 --> 00:28:03,756
Hey, we have this issue and really
try to get their candid perspective in
541
00:28:03,756 --> 00:28:09,096
terms of what the actual issues are,
show them that I fully understand what
542
00:28:09,096 --> 00:28:11,536
the business issues are, and really
543
00:28:18,326 --> 00:28:19,386
push back on it.
544
00:28:19,416 --> 00:28:24,486
And then I take that feedback,
and I'm gonna do my own research.
545
00:28:24,506 --> 00:28:29,066
And oftentimes, when I'm pitching certain
things, I'm already taking into account
546
00:28:29,086 --> 00:28:34,506
that skepticism or their concerns and
making sure that I'm addressing them
547
00:28:34,506 --> 00:28:39,086
so that they feel comfortable and
that I'm not dismissing them or trying
548
00:28:39,086 --> 00:28:41,336
to forge ahead without their buy-in.
549
00:28:41,336 --> 00:28:44,966
Like I at least want to make sure
that I take the time to address it.
550
00:28:45,446 --> 00:28:49,626
And I've found that's very helpful
in getting things pushed through
551
00:28:49,756 --> 00:28:51,116
and also finding advocates.
552
00:28:51,326 --> 00:28:54,461
Like certain times on the executive,
they're going to, there are certain
553
00:28:54,471 --> 00:28:56,031
people that are going to align with you.
554
00:28:56,031 --> 00:28:57,551
They're going to buy
into what you're doing.
555
00:28:57,551 --> 00:29:01,911
So having them help to push things
through, I find is very helpful,
556
00:29:01,911 --> 00:29:04,871
like getting people on your
team and getting them to buy in.
557
00:29:05,401 --> 00:29:08,701
Because when they start to see
like maybe certain other people
558
00:29:08,701 --> 00:29:10,191
that they have a lot of respect for
559
00:29:10,211 --> 00:29:15,891
also sold on this, I think it becomes
a lot easier to get people on board.
560
00:29:16,491 --> 00:29:19,486
And then also just making sure
that you include the people in
561
00:29:19,531 --> 00:29:21,101
the process who are skeptical.
562
00:29:21,161 --> 00:29:23,661
If you go back to them and you
address all their concerns and they're
563
00:29:23,661 --> 00:29:27,741
still skeptical, there's been times
where I've set calls up with certain
564
00:29:27,761 --> 00:29:30,241
implementation people or subject matter
565
00:29:30,241 --> 00:29:34,731
experts to flush out those concerns
and alleviate that if they're
566
00:29:34,731 --> 00:29:38,051
going to hold the process up for
moving forward with a solution.
567
00:29:39,221 --> 00:29:40,091
Thomas Kunjappu: Love those tips.
568
00:29:40,101 --> 00:29:43,876
So let's circle back to something
you brought up way up front, which
569
00:29:43,876 --> 00:29:48,841
was actually about how you think
that with AI technologies, there are
570
00:29:52,041 --> 00:29:55,821
some processes that you feel
like, especially in HR, you always
571
00:29:55,821 --> 00:29:58,241
want humans in the loop, right?
572
00:29:59,581 --> 00:30:01,741
So tell me a little bit about
how you think about this.
573
00:30:01,741 --> 00:30:06,821
How do you think about where,
how to bring in AI versus not?
574
00:30:08,121 --> 00:30:13,001
Jamie Rivero: So I think a lot of
the lower level tasks, they talk
575
00:30:13,011 --> 00:30:14,951
about AI a lot in talent acquisition.
576
00:30:14,951 --> 00:30:15,071
And
577
00:30:15,071 --> 00:30:16,081
I think it's super helpful.
578
00:30:16,081 --> 00:30:19,271
And that is one area that I've
definitely implemented AI with.
579
00:30:19,301 --> 00:30:19,641
But
580
00:30:20,201 --> 00:30:24,831
where I don't think it's a good idea is
where it's making final hiring decisions.
581
00:30:24,931 --> 00:30:28,701
So I think definitely having
it help through writing job
582
00:30:28,701 --> 00:30:30,311
descriptions, sorting through
583
00:30:30,311 --> 00:30:34,256
applicants, some of the candidate
communications in terms of
584
00:30:34,351 --> 00:30:37,191
scheduling interviews or sending
rejections, that type of stuff,
585
00:30:37,191 --> 00:30:38,591
I think is definitely helpful.
586
00:30:38,601 --> 00:30:43,951
But where I would never want to put AI
is like making final hiring decisions,
587
00:30:43,951 --> 00:30:48,841
because I feel like there's a lot that
goes into making a hiring decision.
588
00:30:48,841 --> 00:30:52,491
And I would never fully feel
comfortable like having technology
589
00:30:52,491 --> 00:30:53,811
just make that decision.
590
00:30:54,171 --> 00:30:57,511
Even like handling like sensitive
employee, like relations
591
00:30:57,511 --> 00:30:59,111
issues and stuff like that.
592
00:30:59,401 --> 00:31:03,781
I don't think AI technology
should be involved in.
593
00:31:03,811 --> 00:31:08,351
I also like anything with an ethical
gray area, like I would never.
594
00:31:09,251 --> 00:31:10,501
It's just me, like I just
595
00:31:10,501 --> 00:31:12,951
wouldn't feel comfortable
having AI technology.
596
00:31:12,951 --> 00:31:15,621
But I feel like it's very
valuable for a lot of
597
00:31:15,621 --> 00:31:20,171
those lower level, low value type
tasks and stuff like that, but also
598
00:31:20,171 --> 00:31:24,121
finding that balance because I feel
like i've seen it from employees
599
00:31:24,321 --> 00:31:26,191
where they get frustrated if they
600
00:31:26,201 --> 00:31:28,691
think something's an AI response.
601
00:31:28,751 --> 00:31:32,991
If they get an email from someone
and say they use ChatGPT or whatever
602
00:31:33,011 --> 00:31:35,491
to write it, it does not go well.
603
00:31:35,501 --> 00:31:36,021
I've also
604
00:31:36,021 --> 00:31:39,121
gotten pushback from employees that
are like, my performance review was
605
00:31:39,121 --> 00:31:41,591
written by ChatGPT instead of my manager.
606
00:31:41,611 --> 00:31:44,301
So like, I feel like you
got to find a balance.
607
00:31:45,681 --> 00:31:46,541
Thomas Kunjappu: Yes.
608
00:31:46,541 --> 00:31:50,021
And those are great examples
of the first one, the email
609
00:31:50,021 --> 00:31:51,061
depends on what the email is.
610
00:31:51,061 --> 00:31:53,881
But if it's like you're, you think you're
talking to a human about a particular
611
00:31:53,881 --> 00:31:58,121
job issue, and you feel like you get
a robot thing back unexpectedly, or
612
00:31:58,221 --> 00:32:01,661
obviously performance management,
that's something that is high stakes.
613
00:32:01,691 --> 00:32:04,901
And you want to, if you're going
through the trouble of going, having
614
00:32:04,901 --> 00:32:07,781
this process, you're doing it for some
reason, or if it's meaningless, maybe
615
00:32:07,781 --> 00:32:11,421
then, and go ahead, put in the AI in
it, but then why have the process?
616
00:32:11,571 --> 00:32:12,311
One might ask.
617
00:32:13,166 --> 00:32:14,166
So, right.
618
00:32:14,346 --> 00:32:14,696
Then,
619
00:32:17,236 --> 00:32:20,396
I just want to push you a little bit
more on these ethical kind of things.
620
00:32:20,396 --> 00:32:20,436
Even in performance reviews or
621
00:32:23,066 --> 00:32:28,466
in hiring decisions, what do you think
about AI technologies enabling you in
622
00:32:28,466 --> 00:32:33,836
the background to, I don't know, pull
in a bunch of scores and give you some
623
00:32:33,836 --> 00:32:36,216
context help make a hiring decision?
624
00:32:36,236 --> 00:32:41,186
Or help a manager pull in a bunch of
data around activities and time tracking
625
00:32:41,186 --> 00:32:47,551
information and performance 360 feedback
to give you a starting point upon which
626
00:32:47,571 --> 00:32:51,581
then the trained manager, the trained HR
person is supposed to take further action.
627
00:32:52,311 --> 00:32:55,411
Do you see risks even with
that kind of approach?
628
00:32:56,751 --> 00:32:59,421
Jamie Rivero: I'm actually
in support of a lot of that.
629
00:32:59,491 --> 00:33:04,521
I think where I see the risk is
where I see certain managers who
630
00:33:04,781 --> 00:33:06,501
that's what they're going to rely on.
631
00:33:06,531 --> 00:33:10,691
They don't want to think they're just
going to say, okay, this looks great.
632
00:33:10,691 --> 00:33:13,351
Or AI told me to make this decision.
633
00:33:13,351 --> 00:33:14,041
So I'm going to make it.
634
00:33:14,041 --> 00:33:17,271
So I think it, I think it just
gets into knowing your workforce,
635
00:33:17,271 --> 00:33:22,021
but also like training and the
education of your management team.
636
00:33:22,031 --> 00:33:25,616
But I do feel like there is a
lot of value in AI technology,
637
00:33:25,616 --> 00:33:30,296
especially I've done it where I'm
dumping data into an AI technology.
638
00:33:30,296 --> 00:33:34,286
And I'm like, summarize this, and it can
spit it out very quickly, much quickly
639
00:33:34,286 --> 00:33:38,326
than years ago, where I was spending a
ton of time trying to make the perfect
640
00:33:38,326 --> 00:33:40,446
summary or presentation on something.
641
00:33:41,136 --> 00:33:44,851
But yeah, I think just like the
education of the managers, knowing
642
00:33:44,891 --> 00:33:48,971
your workforce, certain workforces,
they're very innovative, very ahead
643
00:33:48,981 --> 00:33:50,781
when it comes to management development,
644
00:33:50,781 --> 00:33:51,331
stuff like that.
645
00:33:51,331 --> 00:33:55,291
And then there's others where you
probably need to spend some more time,
646
00:33:55,331 --> 00:33:57,851
like investing into that management team.
647
00:33:59,391 --> 00:34:02,191
Thomas Kunjappu: So then if you're
looking ahead, you, a fool's errand, but
648
00:34:02,211 --> 00:34:06,391
let's try it, Jamie, in the next like
two or three years, what do you think a
649
00:34:06,391 --> 00:34:09,271
future ready HR team looks like for you?
650
00:34:10,630 --> 00:34:15,110
Jamie Rivero: So I would say finding
that balance of like human centric
651
00:34:15,121 --> 00:34:20,371
leadership, I think that people
still crave that human connection.
652
00:34:20,371 --> 00:34:22,701
And that's what I hear
from a lot of employees.
653
00:34:22,721 --> 00:34:25,371
I don't think we should
fully walk away from that.
654
00:34:25,371 --> 00:34:28,241
So it's like finding that like mix.
655
00:34:28,650 --> 00:34:34,071
Also having the tech savviness, I
think technology is really valuable.
656
00:34:34,071 --> 00:34:37,511
And I think as HR professionals,
we need to embrace it.
657
00:34:37,821 --> 00:34:40,053
We need to not be scared
of it, not run away.
658
00:34:40,053 --> 00:34:40,860
away from it.
659
00:34:41,501 --> 00:34:45,460
And also just ensuring
that we're also changing.
660
00:34:45,460 --> 00:34:48,766
Like I've noticed I've been in the
workforce now for about 18 years.
661
00:34:49,081 --> 00:34:53,311
And I've noticed over the last 10
years, things have dramatically changed.
662
00:34:53,331 --> 00:34:57,771
And I also see a lot of
companies who are not adapting
663
00:34:57,791 --> 00:34:59,861
are not doing well financially.
664
00:34:59,861 --> 00:35:01,751
And I think that really speaks to it.
665
00:35:01,751 --> 00:35:06,371
And I think as HR professionals,
if we want to position ourselves
666
00:35:06,381 --> 00:35:10,511
to be leaders in our area or
industry, we need to embrace change.
667
00:35:10,571 --> 00:35:12,861
We need to stay on top of it.
668
00:35:13,111 --> 00:35:16,131
It's no longer you get your HR
certification and you're good.
669
00:35:16,271 --> 00:35:20,211
Every year I'm continually doing
professional development because
670
00:35:20,221 --> 00:35:22,271
things are changing so rapidly.
671
00:35:23,811 --> 00:35:24,321
Thomas Kunjappu: Absolutely.
672
00:35:24,321 --> 00:35:26,831
So then do you think there's, I
don't know, new skills that will
673
00:35:26,831 --> 00:35:34,121
be emergent even more or new titles
even, or a mix is the mix of an HR
674
00:35:34,271 --> 00:35:37,001
team in, is that like the skill sets
675
00:35:37,001 --> 00:35:39,746
does it get, does that
change a little bit as well?
676
00:35:39,746 --> 00:35:40,156
Do you think?
677
00:35:40,746 --> 00:35:43,666
Jamie Rivero: Yeah, I think
people analytics is huge.
678
00:35:43,666 --> 00:35:46,896
So like metrics was like the
big buzzword I remember for a
679
00:35:46,896 --> 00:35:48,056
number of years, but now it's
680
00:35:48,056 --> 00:35:50,106
switching to analytics, which
I think are so important.
681
00:35:50,116 --> 00:35:54,706
And I think that I'm seeing a
lot more technology type roles.
682
00:35:54,716 --> 00:36:00,096
So whether it's AI managers, project
management of AI product owners,
683
00:36:00,466 --> 00:36:04,296
that type of stuff, because it
does require a certain skillset
684
00:36:04,306 --> 00:36:08,016
to be able to evaluate, implement
these softwares and also run them.
685
00:36:08,036 --> 00:36:11,656
There's a number of HRIS softwares
where you actually need a team of
686
00:36:11,666 --> 00:36:13,886
people to run the day-to-day of them.
687
00:36:14,326 --> 00:36:18,926
So I'm seeing a lot more
technology-capable type roles
688
00:36:18,936 --> 00:36:21,256
hitting the market over the
last couple of years for sure.
689
00:36:21,256 --> 00:36:23,396
And I'm sure that's going
to continue to grow.
690
00:36:24,846 --> 00:36:25,156
Thomas Kunjappu: Great.
691
00:36:25,156 --> 00:36:28,586
So thank you for this a wonderful
conversation jamie we've been
692
00:36:28,641 --> 00:36:32,816
really going in detail to the
nitty-gritty of identifying a
693
00:36:32,816 --> 00:36:34,556
project on making sure that it
694
00:36:34,556 --> 00:36:38,426
actually aligns with the business
overall and then figuring out
695
00:36:38,556 --> 00:36:40,566
how to vet different vendors
696
00:36:40,586 --> 00:36:46,036
an roi case doing the math yourself
including and double checking things
697
00:36:46,116 --> 00:36:51,316
alongside vendors and managers all the way
before you actually can get some value.
698
00:36:51,326 --> 00:36:55,486
Thank you for sharing some of the
failures along the way or setbacks that
699
00:36:55,486 --> 00:36:59,316
help you get lessons and get stronger.
700
00:36:59,316 --> 00:37:02,046
And there's some great
negotiating tips in there as well.
701
00:37:02,466 --> 00:37:02,836
Yeah.
702
00:37:03,106 --> 00:37:04,976
Like everyone has to feel like
they have skin in the game, right?
703
00:37:04,976 --> 00:37:08,836
In a project that's involved
in trying to get it successful.
704
00:37:09,431 --> 00:37:14,901
Thank you again and for all the folks
out there who are future-proofing
705
00:37:14,911 --> 00:37:19,021
their own organizations and their own
hr functions i hope you found some
706
00:37:19,021 --> 00:37:25,391
value in this conversation and once
again we'll catch you on the next one.
707
00:37:26,251 --> 00:37:29,311
Thanks for joining us on this
episode of Future Proof HR.
708
00:37:29,551 --> 00:37:32,161
If you like the discussion, make
sure you leave us a five star
709
00:37:32,161 --> 00:37:35,041
review on the platform you're
listening to or watching us on.
710
00:37:35,461 --> 00:37:38,401
Or share this with a friend or colleague
who may find value in the message.
711
00:37:38,701 --> 00:37:43,651
See you next time as we keep our pulse on
how we can all thrive in the age on AI.
