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Every product leader has to make them: the high-stakes decisions that define outcomes, shape careers, and don't come with easy answers.
The Hard Calls podcast, hosted by Trisha Price, features candid conversations with product and tech leaders about the pivotal decisions that drive great products and the pressure that comes with it. From conflicting priorities and unclear success metrics to aligning teams and navigating executive expectations, you will hear compelling stories and best practices that drive business outcomes and help you make the Hard Calls.
Real decisions. Real stakes. Real leadership.
Presented by Pendo
Learn more at pendo.io/
Follow Trisha Price on LinkedIn: https://www.linkedin.com/in/trisha-price-3063081/
Trisha Price: Hi everyone.
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See you there.
Jeff Lash: I look at AI as another
tool, another arrow in our quiver.
I like to say that no
one wants your product.
They want some sort of outcome and your
product helps them achieve that outcome.
I would say the same thing
for most of AI, right?
No one wants AI.
They want something that AI
can maybe help them achieve
that thing, that outcome, quicker,
faster, easier than before.
Trisha Price: Hi everyone, and
welcome back to Hard Calls, the
podcast where we highlight the best
product leaders from across the globe.
If you're new to the show, I'd like to
invite you to hit follow or subscribe.
We wanna make sure you stay up to
date with all the latest episodes.
Today I'm joined by Jeff Lash, who is
currently VP of Product Management at
Insperity, where he is helping shape
product strategy that delivers HR services
to small and medium sized businesses.
Jeff has been in product for over 20
years, including advising product leaders
at Forrester and Serious Decisions.
Jeff has spent a lot of his career
building great product teams where
product didn't really exist yet, which
makes him a great guest to chat today.
Welcome to the show, Jeff.
Jeff Lash: Thank you for having me.
It's great to be here.
Trisha Price: Yeah, it's gonna
be a great discussion today.
As you know, the name of the show
is Hard Calls, and it's called Hard
Calls because I mean, that really
is what our job's about every day.
And so before we jump into all, all
things product, I'd love for you to
share with us today, what's one of
the hardest calls you've had to make?
Jeff Lash: So I was thinking back
the first product management job
I had was, managing a product
that was built for physicians.
So I worked for a medical
publishing company, so a company
that provides medical books,
journals, physician information.
So if you go to the doctor and the
doctor's looking up a drug interaction
or a treatment option on the computer,
it might be a product like that.
This was years ago, I managed a small team
and the product we had was for physicians.
There was a. Sister product we had
that was made for nurses and they were
built on the same technology platform.
So there were some features
we were designing specifically
for one audience or another.
and there was another product team
that handled the nursing product.
But there were some
features that were shared.
And so I took over the product.
I took over the team, and then a
probably couple months into the role.
Learned about a new feature that was
being developed for nurses, which
was basically a dictionary feature.
So nurses are reading something, they
see a big medical award, they don't
understand, they can look it up.
That was something that, that was highly
requested among the nursing audience.
The product manager of my team
was planning on rolling that
out to our physician audience.
That wasn't something I
had really heard about.
We had done some customer research.
We had a whole list of.
Features that had been requested
as, as most product managers do.
And that wasn't really
something high up on list.
And so I remember asking around
and asking the product manager and
saying, why are we launching this?
And the answer is, well, you
know, they're, they're building
it for the nursing product so
we can get it kind of for free.
I said, yeah, but are people gonna use it?
Well, maybe some medical students
might use it or, or maybe this.
And, and I, as I dug into it, it was like,
this was not something we were launching
because people really were asking for it.
It was like, oh, well, what's the harm?
And my answer was, well,
there is some harm.
It's one extra thing that
takes up the interface.
There is some development time, there's
QA time, there's code complexity.
Some people might say, why are you
launching this dictionary feature
when you're not launching these other
features that we've been asking for?
So I made the hard call to say, no,
we're actually not gonna launch it.
Product manager was a bit
surprised and a bunch of the
other people were a bit surprised.
My boss at the time actually was
completely supportive and backed me up
and I, I think it very much set the tone
for how I wanted to manage the product
going forward differently than it had
really not been managed in the past.
And so I think that to me was at
the time, a very difficult call.
Looking back, I'm like,
oh, that was really easy.
But it was, you know, I was new to
the role, I was new to the product.
I'd inherited a team, and so.
I'm looking back.
I'm really glad and proud I made the
decision, but, you know, certainly
at the time there was a little anxiety
in terms of, you know, how are people
going to take this internally and,
and how will they feel about it,
especially if a, if a bunch of work
has already been put into doing it.
Trisha Price: Yeah.
I, I love that hard call.
I think it's a really good one because.
You know, the best product managers and
product leaders, as you know, they drive
outcomes and they drive value to our users
and value to the companies we work for.
And there's still a cohort of product
managers and product leaders that
celebrate because they put something
on a roadmap and they shipped it.
And this is like a perfect example of
like, I did it, I shipped it, I did it.
There's something else coming out like,
but if it isn't useful, it's just clutter
and it's just frustrating to the end user.
and so less is more.
Sometimes it's delivering the right
features, you know, designed in the
right way, not just delivering more.
So that's a, that's a great example.
Jeff Lash: Yeah.
I actually, it's funny you mentioned that.
I've been in situations where ne never a
team that I manage, but either when I was
doing more like consulting advising or
other teams in other parts of companies I
worked in actually had annual objectives
for number of features launched, not
value, added, not impact on retention
or new sales or things like that.
Literally it was, you know, I have to
launch four new features this year.
And so I, I joke sometimes it's the.
The, you know, oh, we, we check the
box, we wipe our hands, we have the
pizza party, and then we move on
to the next thing, which is, yeah.
Luckily, I, I've, I've very much seen
a shift in my, you know, 20 years of
product management away from that.
But it still does come up and it
Trisha Price: Still does.
Jeff Lash: You know, I think
it's something a lot of product
folks struggle with to this day.
Trisha Price: Yeah.
Well, I know one thing that you and I have
talked about before and I think is super
interesting, I think our listeners will
enjoy, is, you know, when we're making
these hard calls, the concept of like a
reversible decision versus an irreversible
decision, and just sort of impact of
those and how you think about building
software in sort of these two buckets.
Tell us a little bit about that, Jeff.
Jeff Lash: Yeah, I mean, I you know,
product folks, product managers
are making decisions every day.
some of those decisions have
ninja major implications.
Some of them are minor implications.
Some of those decisions are easy
to reverse and some are not.
you, you actually, I think the phrase
you used is one way doors versus
two-way doors, which I've never heard
before, but I really liked that.
So, you know, I worked in a lot of
companies that were a lot of products
that were information services
companies where there's IP that we are
providing to clients to a platform.
Once you decide to give clients access
to a certain corpus of content, a certain
type of content, if you decide you don't
want to give that to them in the future.
Undoing that is very difficult.
It can be done, I've done it.
But you know, you say, oh, you
get access to, in the case of that
publishing company, all of our books
and all of our journals, including
these special ones, and then we decide,
oh, these special ones, we don't,
we actually wanna charge extra for.
Undoing That decision is very difficult.
So this idea of thinking, well, before
I make a decision, I think about
how hard would it be to undo this,
either if I got the decision wrong or
our strategy changes in the future.
Generally as a general rule, it's much
easier to give people something later
than it is to try to take something back.
So that dictionary example, if we had
decided, oh, the dictionary isn't a good
feature, yeah, we could've removed it.
And you know, honestly in that case,
not many people would've complained.
'cause I don't think the doctors
would've used it a whole lot,
but some people would've.
They would've gotten used to it
and it probably would've snowballed
and escalated other things.
So I like to think about, you know,
how hard is this decision to undo?
if we decide that we don't wanna
do it later, we wanna change it.
And, and also, what are the other options?
You know, I think one of the biggest
changes in product over the past decade
or so is, is experimentation, right?
I think people always wanted to
experiment, but we never really
thought about it as much because
technically it was just so difficult.
So now if I say, Hey, I might want to.
Create, you know, allow people
to access this content they
didn't have access to before.
I can do it in a very controlled way.
I can do it to a small audience.
I can, you know, have them opt in.
I can, you know, give
warnings and things like that.
There's all these sort of tools
and technologies obviously, as
you know, that make this possible.
So I think that gives us more flexible.
So it's not a, you know.
Stay up all night fretting
over your decision.
It's all right.
Let's maybe run some experiments or
tests to give us some more data and
confidence before we make a decision.
Trisha Price: Yeah, I love that.
I think, you know, experimentation in
this one-way, two-way door concept or
reversible, irreversible decisions is
such interesting thing because one to
your point, if you know something is a
very difficult, maybe it's not completely
one way door, but it's really hard and
painful to your point, to pull back.
Then you can do even more
experimentation, right?
To be more confident in your
decision before you go with it.
But on the other hand, sometimes
it's a scarier place to do
experimentation because even if
you've only introduced it in a small
group, you've introduced it, right?
And so it's just, it's just a fun
and interesting sort of debate to
have with your team and yourself
when you're approaching these more
difficult, irreversible decisions.
Jeff Lash: Yeah, and
I'll just add onto that.
I think, you know, obviously there's
a lot of product folks that are
doing a lot of experimentation.
One thing that I don't hear discussed
as much in those scenarios is the other
stakeholder and audience implications.
So a lot of it is, oh, you know,
can development add that switch?
Can we add that light
switch to turn it on or off?
and how quickly can we
get that development done?
But I've worked pretty much exclusively
in B2B enterprise sales type environments.
Usually with a direct sales team.
So when we decide to run an
experiment, it's not just me and the
development team and the designer
deciding we're gonna run experiments.
It's alright, I need to figure out
which clients are going to see this
and I need to talk the to the account
teams that are at those clients.
I need to understand what the
situation is that those clients and
is there something that, is there a
big renewal coming up that this might
positively or negatively influence?
I need to talk to our marketing team.
'cause if they're marketing and saying.
You know, X, Y, Z is not included and now
we're temporarily making X, Y, Z included.
That impacts our marketing.
So this is really where,
Trisha Price: And support, right?
Jeff Lash: Exactly.
Trisha Price: How confusing.
How confusing for your support team
when they get a support ticket.
And they didn't even know that
these people have a different
experience than everyone else.
Jeff Lash: Support legal, finance.
I mean, I've been in situations where
especially like with, with on more of
the information services side, when you
decide to make information available, that
changes like your financial accounting
in some cases of how we look at usage and
if there are royalties we need to pay.
So there's all these sort of implications.
So it's not just.
Yes, there is definitely the
technical, how do we make it
happen and from an experiment
standpoint, how do we structure it?
But it's all those other stakeholders.
So I think that that sometimes people
get frustrated and it's like, oh,
that means I need to slow down.
To me, it's just, we
need to be more careful.
It doesn't mean you can't do it, it
doesn't mean there's, I'm gonna generalize
and say there's probably a lot more steps
you have to go through in B2B than B2C
where you can just like try out a new
feature today and turn it off tomorrow.
But I think it also is a lot more
powerful if you can get it right
and you can get sales on board,
support on board, et cetera.
you can get their buyin
and hopefully some help.
And I've done some things like that
where we did some experiments that
in, that gave us a lot of data and a
lot of confidence, both with what we
saw our users doing, but also with the
other internal audiences, our internal
ecosystem that we were partnering
with, that gave them an understanding
of how we were approaching something.
So when they say, Hey, why
don't you just do X, Y, and Z?
We can say, well, we're trying it
this way and we're trying to get this
data and here's how we need your help.
And that way when we did make
some decisions, they were on
board with it as well, and they,
they knew something was coming.
Trisha Price: I love that.
So in this era of AI driven development
and all the tools that are coming and.
We're using.
It's, I mean, it's wild.
It's such a wild and fun time in
product and it's just changing the game.
How have you seen that influence
how you think about experimentation?
Jeff Lash: I like to describe
this era of AI as kind of like
the web in the late nineties.
If, if anyone remembers or was
alive or, or was involved then
like, you know, in 96, 97, 98, like
the web was, you know, burgeoning.
Like certainly it was being used, but I
don't, we had, we had no idea of the full
potential and the opportunity, and I feel
like that's kind of where we are with ai.
Like certainly it has
been around for a while.
It didn't just pop up a couple years
ago when with Open AI, but I think
we can't even, I can, I can't, I'm
not supposed be, I cannot personally
fathom all the opportunities and
all the things that will change.
So I look at AI as, as another
tool, another arrow in our quiver.
I like to say that no
one wants your product.
They're, they want some sort
of outcome and your product
helps them achieve that outcome.
I would say the same thing
for most of AI, right?
No one wants AI.
They want something that AI can
and, and AI can maybe help them
achieve that thing, that outcome.
Quicker, faster, easier than before.
I'll use an example.
One of my favorite AI tools I use,
I'm a big pickleball player and coach
Trisha Price: Me too.
Well, I'm not a coach, but I just love it.
I'm not a coach, but I love it.
Jeff Lash: But there's a great app that
I use that you can record your matches
and upload it and it uses AI and it
basically tells you, you know, it
gives you a lot of guidance, whatever.
So to me, AI is not the
exciting part of it.
The exciting part of it is.
One of the things it does is it cuts
out the dead time between points.
If you've ever played pickleball or watch
pickleball, like you play a point and then
the the point is over and then it's like
10 or 15 seconds before the next point.
So if I need to watch a match, it might
be 14 minutes end to end, but this tool
automatically cuts out that dead spot.
So.
I can watch a match one of my matches in
seven minutes or eight minutes instead.
So to me, the value is not the AI,
the value is it takes me less time to
watch one of my matches, or I want to
just see all the shots that I missed.
It can show me that.
So AI is just a tool that
helps BH, G, that outcome.
So I think right now there seems to be
a lot of excitement about AI for AI's
sake or, you know, the, the differences
in the cool things, how, how AI works.
But to me it's really
more about the outcome.
I want to create a better presentation.
I want to write a more coherent email.
I want to, you know, save me
lots of time doing research.
I want to, you know have my code
refactored much cheaper than it would
cost me to hire a human to do it a much
quicker, you know, things like that.
So I think the more we can think
about outcomes, you know, the more
we can figure out how AI helps.
I've seen also situations where people
are using AI and it's like, you don't
need to, or it's actually not the
most efficient way of doing things.
So I think there's lots of
opportunities, lots of possibilities.
We haven't begin to even
explore all of them.
But that's how I look at it, is
like at the end of the day, I'm
trying to achieve something.
My clients, my customers are
trying to achieve something.
And are there ways that AI can.
Help, just like there are other ways
that other things can help as well.
Trisha Price: Yeah, I, I mean,
it's, it's really fascinating.
You know, I've been seeing really
cool things with AI lately, to
your point where, you know, you've
got product managers or designers
able to generate code and we're
able in a matter of minutes.
Hours to create new experiences and have
them testable and usable for customers.
So when you talk about this
experimentation concept that you're
talking about and getting more confidence
for these irreversible or complex hard
calls, like the fact that we can now
have an idea, use AI, have 2, 3, 4,
10 different experiences ready in a
10th of the time, it would've taken
us to do just one and now be able
to your point, to put that behind a
feature flag and pick a segment of our
customer base and try it out to have
a level of confidence to make the hard
call is just, it's just fascinating.
It's fascinating to watch
what's happening out there.
Product managers using, you know, tools
like granola or just the transcripts from
their calls and having agents searching
for things like bugs or enhancement ideas,
and automatically taking that bug and
fixing the bug and having code fixes in
production before you're off the call.
And it is just wild what's happening to
our lifecycle and our ability to go fast.
But to your point.
You can go really fast and
just create really bad stuff.
So if you don't know the job to be
done and you don't really understand
the customer value and the problem
you're trying to solve, who
cares that you went fast with ai?
You know?
Jeff Lash: Well, and I think there's
absolutely, and the other thing I
think is there's also plays where,
places where AI can get you certainly
efficiency gains, but there's also places
where like that's not the bottleneck.
So as you, I think another
example I thought of.
Yes.
Like in the, in the old days and
probably many people still, like
if I want to test a concept with
customers, yeah, I might need to mock
up a wire frame or create a prototype.
And in the old days, like I remember
coding prototypes by hand at HTML
or doing 'em in PowerPoint 'cause
there wasn't any other tool.
Yeah.
So now I can go to an AI tool,
I can type a couple sentences or
upload a, upload a transcript of a
meeting and it'll create a prototype.
Awesome.
In the areas I've worked in, B2B.
The biggest,
bottleneck.
The thing that takes the most amount
of time in the prototyping and
testing process is recruiting users.
So yes, I can create a prototype
in one hour rather than three days,
but if it still takes me a week
to recruit people and a week to
conduct the interviews, that's.
That's saved a little bit of time, but it
hasn't really nailed the biggest problem.
So I think if you look at a lot of, and,
and, and honestly, like maybe there's
a tool out there that helps with that.
I don't know, I haven't looked
at it yet, but I think, you know,
yeah, we can apply AI in places that
like save us some time, but is that
really where we can best use it?
And, and it's, and look, and the
answer might be, Hey, it's still
an hour rather than three days.
And that's good.
Yeah.
But I think it's also, you know,
there's a, there's a saying, I'm
not sure who to attribute this to.
'cause I've heard it from multiple people.
I'm not sure what the original author is.
You know, when, when Agile was
all the rage, it was, you know,
agile can help make bad, help
you develop bad products quicker.
Right.
And I feel like with AI now, yeah,
anyone, anyone in their brother, anyone
in their brother and sister can create
a thing with, with a vibe coding tool.
Doesn't mean that it's actually
what people want, doesn't mean it's
actually designed the way people want.
It has the right features.
Right.
Not to mention even all the technical
safe security stuff backend.
So yes, I mean, there's a lot of
talk about, you know, how is product
management gonna change in the era of AI?
And, and it certainly will, but at the
end of the day, someone still needs
to be responsible and accountable for.
What are our client's needs?
You know, what is, what is the customer
problems we're trying to solve?
What is the market opportunity and what is
the best way or a, a good way to solve it?
Yeah.
'cause I can create a product
very quickly, but it might not.
Address needs.
It might not be a pervasive problem, might
not be a problem that people will pay to
have it solved and they're, it might not
be the best way to solve the problem.
So, yeah, I can create something
quick, but maybe if I spent more time
actually answering those questions,
I mean, I I think you're right.
Feed that into the AI tool.
Trisha Price: I actually think AI
really magnifies the need for great
product sense and product taste.
Yeah.
And the role of product managers.
And I do think it's amazing
how fast we can go, and I
think it's changing everything.
But what it isn't changing is great
product managers means you understand
customer value, you understand what
you're trying to deliver, and that
is just more important than ever.
So I couldn't agree with you more on that.
You know, another thing that that is
hard for product managers is this always
balance between short term demands.
Right.
There's this constant
pressure, customer requests.
Sales has the biggest deal ever, and
they can't possibly close it if you
don't magically deliver something
with long-term product strategy.
How do you, how do you handle that?
How do you coach teams to handle that?
To decide what deserves
attention and, and what's noise?
Jeff Lash: There's a lot of
frameworks and approaches.
You can say, all right, we're gonna devote
X percent of our development resources to.
Sales requests and X percent to
bug fixes and things like that.
Or we're gonna allow people to, you
know, give sales a budget or give
executives over like things like that.
And I think those are all good.
I think those are good general frameworks.
I don't think there's one right
one, I think, but having some sort
of structure like that is good.
The thing that I've found that is more
important is the fact that that approach.
How you answer those questions
really depends on where your product
is at, where your company is at.
So, you know, look, if you are a, and
I've never worked at environment like
this, but if you're in a startup that is
running out of funding and you're worried
about getting to the next paycheck,
yeah, you might say, all right, we're
gonna do some things that are gonna help
land a big client, even if that's not
exactly what we wanna do long term, but
because we need to pay people next month.
Right?
So I think that is completely reasonable.
Now, obviously, if it pushes you
way in the wrong direction, it might
actually, you know, sink the company.
But within the, within
the realm of reason.
I think that's appropriate.
If you have a situation where, you
know, customers are generally very
happy, but you're you're kind of like
in the middle of the market and not
really doing anything exceptional and
you've got a really visionary Cee o or
executive that is one of these people
that sometimes comes up with these.
Amazing blockbuster ideas and
they come to you with an idea.
It's like, I might be more
likely to try that, maybe
experiment with it, not like Yeah.
Put all my resources towards it.
Trisha Price: Yeah.
Jeff Lash: I've been in situations where
I've managed products where retention is
really good, but new client growth is not.
So we foc, we, we rotate
and focus on that.
I've been in situations where
we had multiple different
personas and one persona is
really happy and another is not.
So we focus on that.
So I think.
This idea of like, oh, you al you,
you always say no to a customer
or you always say no to executive.
Like, I think, I don't, I I think
those are sometimes too broad.
I think the context of where your
product's at, where it is in its
lifecycle, how it's performing,
how the company is doing.
You know, are you in a startup?
Are you an established company?
Are you.
PE backed and looking for an exit, right?
All these sort of things like are
factors that, yeah, there's no formula
I can give you to do it, but I think
thinking about those sort of things,
and again, I think it's also aligning
your stakeholders so it's not just a
product manager sitting in their office
on their own, making that decision.
It might be, hey, like go go to your
marketing colleagues and say, Hey, you
know, I've noticed we've got, this
product, you know, it's for administrators
and teachers, and the administrators
seem really happy, but you know, the
usage among teachers is not what we want.
Like, so I think maybe next.
Quarter, we need to
focus more on teachers.
You know, like just even that
conversation and then talking to sales
and getting people on board with that.
Again, it's not a scientific waiting
process, but I think even just my
experience with a lot of products is.
There's no one right answer.
There might be a couple wrong answers,
but there's no one perfect right answer.
So it's more like, Hey, we've got
five things we could do, and all these
five things probably need to be done.
And, you know, there's not, we're
not gonna have terribly different
outcomes if we choose one or the other.
Yeah.
So it's more about getting agreement
and alignment and just moving forward.
Trisha Price: I, I really, you know,
agree with you on alignment and getting
input from, you know, other parts of
the business and other stakeholders.
I also.
I'm gonna be even one step more
severe than you were in agreement,
which is, I hate when people make
decisions based on formulas and
spreadsheets and, and set percentages.
To me, that just means you're not.
Helping run the business.
You're not in the business, you're not
understanding, and so you're relying
on a spreadsheet and you're relying on
a formula to make a decision for you.
I'm not saying I'm not data driven.
I am always looking at
data to make a decision.
ARR impact, you know, time to value.
Is retention a problem?
Is new growth a problem?
I'm always looking at data, right?
Are where, how?
How much is this particular
product or feature being used?
Why is this the right strategy?
How is this chasing our
scorecards and North Star metrics?
Yeah, but.
When you're making a decision because
you like had some weighted formula
of three different people's opinion,
you know, or you set it and forget
it and say, this percentage of my R&D
budget goes to X, Y, and Z. Like to
me it's just like you're giving up.
Actually participating and
understanding the business.
'cause business pivot all
the time and there's new data
and information all the time.
And so I am in violent agreement, but
even one step further that those tools
are not helpful and that you really have
to do the work to make the decisions.
Jeff Lash: So a classic example of
this is like feature prioritization.
Trisha Price: Yeah.
Jeff Lash: you know, I've, I, when I
was at Serious Decisions, we built a
feature prioritization tool and we,
you know, used it a lot with clients.
But when we, when I did that, and
I did this a little bit in my time
at Forrester as well, when I did
that, I always was very careful to
talk to them about how to use it.
So, for example, I don't remember how,
like imagine and, and most people have
built or used some sort of peach or
prioritization thing before, right?
You have a bunch of different criteria.
You weight them, you score each feature
on it and you come up with the numbers.
Let's imagine your scale goes from
zero to 100, and you have one feature
that's a 94.2 and another that's a 94.9.
Like to me, I a hundred percent would
agree with you that like that doesn't mean
the 94.9 is better because it's scored.
Point seven better.
Depending on Steven's mood that day,
he could have scored it a little
higher or lower, like, you know.
But what I have found is that these
things kind of clumped together.
So I could probably say the things
that scored in the nineties are
probably more valuable than the
thing that scored in the sixties.
Right?
So my, my coaching to people was
always like, don't rely too much
on the numbers, but they do tend
to sort themselves out, right?
The cream of the crop seems to rise
to the top and the stuff that's not
good seems to rise to the bottom.
So don't obsess over the details of it.
I, I'm gonna take, maybe
take a more moderate view.
Like, I think they can be helpful
tools to help, but they are not
going to give you the answer.
Right?
They're not, to your point.
Like, it's not like just
rely on this directly.
and it's, and oftentimes some of
those nuances I talked about are not
captured in a, any formula, right?
It's, oh, you know, did we
lose a big client last week?
Or is this something that, you
know, our investors are asking for?
Like, those sort of things are the.
That's the gut part of it.
And that's the where you need to
just make, make the hard calls
as you make the hard calls.
Trisha Price: And, and I just see too
often that people who rely on spreadsheets
are the people who haven't put the
work in to build a real product sense.
Yeah.
And really understand the business
and really understand the customer
value and jobs to be done.
And so, you know, it's like
an easy fallback mechanism.
And to your point, it's not that you know,
any kind of prioritization numbers or.
Frameworks can never be
helpful to make decisions.
It's just when people begin to rely on
the framework instead of understanding the
business, they get themselves in trouble.
Jeff Lash: A hundred percent.
Yeah.
Yeah, and the framework's only as
good as your, the data behind it,
like if you don't know answers to
the question, just making up answers
and putting numbers in there is.
This is gonna be worse than not gonna be.
Yeah.
Trisha Price: Or not being opinionated
as a product manager and just
saying, I collected everybody else's
opinion and waited these things.
And this is giving me the answer.
I think great product
managers are very opinionated.
Jeff Lash: I like to say
product management, product
development is not a democracy.
Trisha Price: Agree a
hundred percent with you.
Yeah.
So I know Jeff, you've had some
really interesting experiences
in bringing product lead
processes, mindsets, behaviors, and
product management principles to
companies that are more traditional
enterprises or non-software companies.
The product itself wasn't
software, but the way things were
delivered was using software.
Tell us some, some key lessons.
I know a lot of our listeners
are in the same boat.
I say all the time.
Every company is a software company
now, and so, you know, what
are some key lessons that you've
learned specifically through driving
mindset change from the inside?
Jeff Lash: Yeah, and, and just to
for context though, I've worked in
a couple different industries, but
there's some commonalities among
both the products and portfolios I've
managed as well as when I was doing
what I was in an analyst advisor role.
A lot of the clients I was working
with were not technology companies.
When I say technology companies, like
in the classic sense, meaning like.
Creating software or hardware that
is sold into the IT department.
So most of my work, most of the clients
I work with, and I would imagine a
lot of your listeners are financial
services companies, healthcare companies,
manufacturing companies, even consumer
goods, where like technology or software
is part of the value proposition.
Either it is literally part of what the
user is paying, the customer's paying
for, or it is an enabling factor.
you know, we have online checking
accounts and really the checking account
is, provides some value on its own.
But the online portal and the.
Mobile app and all that stuff.
so I think the first thing is really kind
of understanding, like you said, like
understanding the business and thinking
about it from a business perspective.
Like how does the company make money?
What, what are people
actually paying money for?
What are they buying?
And understanding how your
products fit into that and how
the technology fits into that.
most recently, the past, you know.
10, 15 years I've worked in companies
where we are selling subscription
services where part of the value is
actually access to human experts.
So literally the fact that I could
talk to someone on the phone who is
an expert, I can call them up, I can
set up an appointment with them and
they can give me guidance, right?
That is, that is truly a
human delivered service.
So understanding, yes, we can do great
things with technology, but that's
part of the value proposition as well.
So I think that number one is just
understanding that that bigger
picture, how the company makes money.
How we sell our services and
where the, the products and
the technology fits into it.
I think the second thing is probably
trying to not talk in product language or
technology language as much as possible.
Trisha Price: Yeah.
Use real words.
Don't try to just confuse people.
Jeff Lash: I, I had a, I had a boss
who was fond of saying like, you know,
don't use a multi-syllable world word
when a single syllable word will do.
You know, and I, and I'm probably
as guilty of that as any one
way to really try to simplify.
You know, fewer words, simpler words,
not 'cause people are not intelligent,
but just really to kind of step back
and think about your audience, right?
So if you, if I'm working with
a technology group inside a
company, like, yeah, I'll be able
to talk about technology stuff.
But most of the people in the
company are not technology people.
They are, you know, I worked
with nurses and doctors.
I work now with HR experts and,
payroll experts and things like that.
So, so try to understand their language,
talk their language, and, and love that.
Simplify things in ways
that works for them.
Trisha Price: You know, I, I love that,
that that is like sometimes product
people can, and engineers do this too,
you know, either use complex product
language in terms to hide behind the
fact that they don't really wanna
get into the meat of the discussion.
Or sometimes people can use it, you know.
Unintentionally, like they're
just, it's, it's just the
way they do things, you know?
And that's, that's okay.
And, and understandable.
and sometimes I think people use it to
sort of hide behind things, you know?
And so I love that advice.
I love it for, to your point, when
you're in a traditional company and
making sure you bring everyone along
because other people in the company
have great ideas and have input.
And when you kind of like,
product geek out, which I love
to do, but they you've lost them.
Yeah.
But I think that's great advice,
even in the most, you know, modern
technical SaaS companies too, because
forcing ourselves to use real words
and language versus just our fun
product speak, brings everyone along.
So I love that advice.
Jeff Lash: I'll give you a real example.
So I, I started with Insperity just about
a year ago, and, you know, one of the.
First things at the top of my list
was to obviously understand our
clients, understand the market.
And so, you know, when I worked, when I
would talk with salespeople we would call
our business performance advisors, or I
talked with our client liaisons, who are
the people that manage that relationship.
I didn't go to them and say, I would
love to do some product discovery work,
particularly contextual inquiry, and then
maybe some card sorting, I would say.
Because if I did, they would've, you
know, their eyes would've rolled back.
Like what?
Trisha Price: No, no, no.
Jeff Lash: They'd say, I'd say I, I
would say like, Hey, I would love to
talk with some clients to understand.
Why they chose us as a vendor, you
know, how, what they like about our
product and what we can improve.
And I would also like to see how
they use our products and services
in the course of their day.
I'm saying the same thing, I'm
just saying it in language and to
your point, I that's probably good
language use with anyone as well.
So I think just to your point,
I don't, I don't think most
people do that intentionally.
I think it is just, we're so used
to talking our language that we
just assume that everyone else
talks that language as well.
And it can happen even with.
Words that are simple.
The classic example I use
is the word roadmap, right?
Roadmap means something very
specific to a product manager.
I bet if you go to a salesperson and a
marketer and a developer and you know
a customer and say the word roadmap,
they're gonna have very different
pictures, something in your mind.
So,
Trisha Price: mm-hmm.
Jeff Lash: I'm not gonna say a roadmap is
good or bad, or you should or shouldn't.
It's, but like, rather than
saying roadmap, like what is,
what really are we talking about?
Is it a. Promise of what
we are going to deliver.
It is a vision of the future, is it?
Things like that.
So even just simple words
like that can often get
misunderstood and misinterpreted.
And I think it's, to your point, probably
common everywhere, but certainly more
so in companies that that did not
grow up as technology companies like.
'cause I read your point,
I think most companies.
Are or have a major component of
technology, but I think it's more
like, did you grow up in that world
or did you, you know, come over
and realize that needs to be part
of your, your culture over time.
Trisha Price: Yeah.
Jeff, I, I totally agree with you.
in terms of language and being inclusive
for our other stakeholders, I think
that's such a great, a great approach.
Any other key learnings that you
wanna share with our listeners
in terms of, you know, bringing
a product mindset and product
practices to a traditional company?
Jeff Lash: I think the only other
product I'd say is just that, that
whole stakeholder management and
understanding the ecosystem partners,
again, I, I think it's, I'm not gonna
say it's more important, but I think
there's a really big part of that.
So much of the.
The stuff I read and the stuff people
talk about is about like, you know,
product management and developers
and your engineering counterparts
and your design converts, which
again are very, very important.
But my experience is that those
relationships with finance, with legal,
with customer support, with sales are,
are just as important, if not more.
Totally.
Yeah.
and I think again, because in a
non-software company, that's how.
The company, again, makes money.
That's how, that's how they become.
That's the how they deliver.
And maybe not just make money.
That's how they deliver value
to an organization, right?
So understanding how those other factors
number one, it gets you an understanding
of how the organization works.
Number two, it gives
you credibility, right?
If you're just focused on.
My technology that they're gonna,
you're gonna be perceived different
as understanding, oh, well here's
how our support team operates.
Here's how our call center operates.
Here's how, here's what legal's
prioritizing, you know, for right now.
That certainly gives you a level of
credibility and I think, and ultimately
all that information will help make
your products better too, because you're
not just designing something in a silo.
You're understanding how the product
you're in charge of a creating will
work in this giant ecosystem where.
Most companies are delivering value
through many other mechanisms,
not just through the one product.
If you've got a, if you're a one
product company and your entire
revenue is based on, you know.
Sales or subscription revenue of your
one product, maybe a little different.
But even then still you've got support.
You've got marketing, you've
got legal, you've got finance,
got all these other people.
Trisha Price: I call that Jeff, I
often call that whole product, right?
Yeah.
It's like we think about
shipping our product as just
the technology, but it's not.
It's the experience.
It's everything around it.
So I love that.
Well, Jeff, it has been
absolutely incredible to
have you on Hard Calls today.
Thank you for sharing your experience
and your wisdom all the way from
irreversible and reversible decisions
to the impact of AI and to helping
build a product mindset and making sure
all your stakeholders are included.
I know it's a lot of great information
for our listeners, so thank you so
much for being on the show today.
Jeff Lash: Thank you
very much for having me.
I enjoyed the conversation and
I appreciate the opportunity.
Trisha Price: Thank you for listening
to Hard Calls, the product podcast,
where we share best practices and
all the things you need to succeed.
If you enjoyed the show today, share
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