Rusty Ramer’s book *Working as Designed* critiques the stagnation in modern analytics and marketing organizations, where decades of investment in tools and teams have led to inefficiency and poor customer outcomes. The core issue lies in siloed operations focused on reach and volume, rather than solving real customer problems with timely, relevant engagement. Ramer argues that companies have reached market saturation and now must shift from "lazy marketing" to deep customer understanding. This requires a fundamental rethinking of how teams operate—moving beyond isolated functions to cross-functional, agile teams that test, learn, and iterate rapidly. These teams focus on identifying customer problems, not just demographics, and deliver measurable outcomes through value exchanges. The book champions a hybrid model: preserving centers of excellence for standards and discipline, while empowering agile, mission-focused teams to solve customer problems. Crucially, success is measured not by activity or tool usage, but by actual customer impact. Ramer also highlights the flaw in traditional customer journey diagrams, which are unrealistic and overly simplified. Instead, micro-journeys based on real-time customer needs are more effective. The transformation demands a cultural shift in reward structures—from incentivizing activity to rewarding measurable results. His insights are framed as a conversation, not a lecture, making them accessible to executives and practitioners alike. The episode concludes with a recommendation to listen to Chris Hayes’ *The AI End Game* podcast, which offers deep, thought-provoking perspectives on AI’s societal and ethical implications.
(upbeat music)
Welcome to the Analytics Power Hour.
Analytics topics covered conversationally
and sometimes with explicit language.
Hi everybody, welcome to the Analytics Power Hour
and this is episode 303.
Does it ever feel like we repeat the same steps sometimes
even though no one's really thinking about
whether they actually apply in the scenario,
that old saying the definition of insanity
repeating the same activity
while expecting different results?
I think we've all been there.
And yet as analysts, maybe we're slightly more clued in
to when it's happening than others in a business.
I'd like to think so, maybe not.
The idea here is, are we thinking a step or two deeper
as analysts or are we just sort of rolling
with the same set of activities
with no critical thinking applied?
Well, we're going to talk about it.
And now I want to introduce by two co-hosts
who are definitely deep thinkers, Julie Hoyer.
Welcome.
- Hey there.
- And Val Crowe.
- Hello, hello.
- How's it going?
- Good.
- And I'm Michael Hoblin.
Well, we wanted a guest.
And our guest is someone we have had on the show before,
but not for a while now.
Rusty Ramer is the founder and chief product officer
of Star Rise AI. Prior to that, he held analytics
and marketing leadership roles at GSK in Vanguard.
He has a new book called Working as Designed.
And today he is our guest.
Welcome back to the show, Rusty.
- Thank you. Thanks for having me back.
I appreciate it.
- And as far as bios go, you know, Val and I also worked
with you on the board of the Digital and Lux Association
back in the day.
So we are friends going back a long way.
So it's great to have you back on the show.
- All right, so to kick this all off, you wrote a book.
So obviously you've been thinking about this for a long time
and then you decided like to get pretty serious about it.
Talk about that a little bit,
because I think probably something was brewing for a long time.
It kind of came out in the form of the book,
but like, just talk about that journey a little bit
and then we'll dig into some of the content
that some of the things in the book itself.
- Yeah, you know, people ask me,
when did you start the book?
Well, I started, I feel like I started the book 20 years ago,
right, it's the experience of the last 20 years
that I think, you know, at Vanguard it was about building,
you know, at the front end of the digital way,
building out the capabilities of, you know,
a user experience organization,
a data and analytics and data science organization,
marketing and MarTech, and then, you know,
digital transformation, then going to GSK
and helping them a different problem, right?
They had all of these capabilities
and it was about, you know, why aren't these capabilities
working the way that we think that they should?
Why haven't we gotten the value out of all of this?
And that's a pretty common problem, I think,
as I've moved on to consulting,
I can see it over and over again at different companies
and it felt like a problem that I had experienced solving
and that I was surprised as so prevalent out there.
And so I felt like I had something to say about that
and I wanted to put it down in writing
and my experience is what I was observing
and what I think the solutions
and the core of the problem and the solutions to that are.
So that's really what it was.
- No, I think that's great.
So talk a little bit about the book contents itself,
like, you know, kind of what was the driving idea behind it.
- Yeah, I think there were two key observations.
One was sort of, where are we now, right?
Like looking around at different organizations,
I see the same problems, identifying that problem
and sort of describing the solutions that I've put
towards that and what I think the core of the solution is.
And then secondly, like, how did we get here, right?
Like there's a pretty clear path that led to this place
that we're in and it's both of those things
that I think were what's in the book, you know,
to sort of describe how we arrived,
what it is that the problem is that you're feeling
and then how do you solve that problem
are really sort of what's underneath it.
- So what are some of those symptoms
of like how we got here, let's dive into it.
- Yeah, okay.
Well, let me start with what I think
people are probably feeling today, right?
So as I led each of those organizations,
whether it was user experience or it was analytics
or Martek in the tech side, media,
I think everybody in those organizations feels like
there's something wrong with the,
like we could be doing so much more with what we do here.
Like we're so underutilized to this problem of growth
or whatever the company is trying to solve.
And I think that feeling comes from very siloed organizations,
I think I think I see the problem that chief marketing officers,
chief growth officers, chief commercial officers
have spent a lot of money over the last 10 to 20 years,
buying software, buying capability,
hiring teams, building teams.
And largely I don't think that they're getting a large
percentage of the potential value
all out of all of that investment that they've made.
So from the C-sweets perspective,
I've put a lot of money into this on faith
that this will produce value for my commercial organization.
And it just doesn't seem to change the net result very much.
And I don't understand what's wrong here,
but it's not working.
And I think the reality of that is going back
and looking at the history of how we arrived here
and the moment that we're in.
And I think to switch gears a little bit,
I think if you go back 20 years before the internet,
1998 or whatever you're sitting at your work computer,
you don't even have the internet on your computer, right?
I mean, it's hard to even imagine the world back then,
but that's the way that it was.
And marketing your organization was print,
maybe some partner distribution methods,
but it was expensive.
Print is really expensive to send out.
And so TV ads are there, there's some phone advertising,
but everything is an expensive channel.
And so you reach is relatively small.
It's relatively limited by your geography, right?
Well, digital comes into the picture
and completely blows that paradigm out of the water, right?
Now you think about buying an email list
and you're actually rewarded for sending it out
to more people than it can actually,
like the more people you send it out to,
the lower the cost of purchasing that list
goes down for the, right?
So you're rewarded for your reach.
And what that did from an economic standpoint,
it allowed companies to enter markets
where they were not previously competing with their brand, right?
To create, oh my God, now I can reach the world
with what my product or message is,
and I can sell to the world.
So for 20 years, we focused on reaching,
reaching a building capability, digital capabilities
that would help us reach audiences, right?
And even bad marketing with the kind of reach
you were able to achieve with the digital world
drives your organizational growth.
It just does.
I mean, fractional return on that investment
means massive growth for your organization,
just based on the scale that you're currently achieving.
But it's really lazy marketing, to be honest, right?
That reach and frequency marketing is lazy.
And so you've been purchasing all of these capabilities.
You've been buying MarTech stacks, AdTech stacks.
You've been building analytics teams and data lakes
and data environments.
You've been hiring media teams.
All of that has been growing in investment,
but it's all working as like,
we have to build up this function.
It's never existed before.
We've never had an analytics team before.
We've never had a data team before.
And so the mission of those organizations
has been about how do we build and deliver some value
immediately and then scale this organization
to what it's going to need to really drive
the growth of this company.
So we're sort of stuck in that time
where these functions are still working in silos,
trying to do analytics activities
that show we could be the best analytics organization
in the entire world.
We could be the best content creative people
in the entire world.
We can be the best, we need all the MarTech tools, right?
So the MarTech teams are out buying things
that the organization doesn't even need yet,
just to have them, right?
And I think that's not how it's actually working, right?
I think we've saturated the growth market.
We've reached every corner of the market.
We can possibly reach.
And now it's about quality of marketing,
getting back to getting away from reach and frequency
and getting back to timeliness and relevancy, right?
Which means, hey, I actually have to understand my customer
better than I've ever understood my customer before,
in order to show up in a timely and relevant way
to that customer, right?
And that's actually what all of these capabilities
we've been building have been designed to do.
But when you look at the system
that they're operating inside the company,
they're still working in these vertical silos,
instead of working together on horizontal problems,
like growing the company with its customer base, right?
So I think that's a bit of how we got there,
which is understandable, given the thrust of digital
and digital capability and the speed at which that's grown.
And then it sort of explains why we feel
like we're underutilized in the same system as well.
Why people aren't doing more with the data
that we're creating.
Why test and learn isn't being adopted as fast as it should be.
Why media dies at the front door of the company
and OmniChannel doesn't connect to it, right?
Like I think all of these problems are functional silos
out of that sort of arc of growth and evolution
that's happened over the last 20 years.
- And one of the things related
to what you were just talking about Rusty
is that really resonated with me.
I've seen it so many times in organizations.
Like you said, it's like the best content team
in the world, the best performance marketing group
and they produce a lot of reports
with their analyst partners showing all this like progress
and like, you know, performing above industry average
for, you know, those different campaigns.
And so with the way you talked about the book, it's like,
how can we be doing so much that says we're doing well,
but we're still not getting to where we need to go,
and the way the system responds is,
well, we just need to be doing more.
And I was like, great! (laughs)
Highlight underlying, start.
I was like, that is such a repeatable pattern
that I think people absolutely feel.
But like, when was the first time you started to like,
take us back and acknowledge,
boring more on top is just, you know, not moving us forward anymore.
Like, when do you have like a specific moment or story
where that realization really started to come to life for you?
- It's a little of two things.
Again, it's a little of having jumped silos
to build these functions out,
and then getting the GSK and owning sort of every touch point
of the customer, the entire customer experience,
really was like, oh my God,
now I'm sitting on top of this entire organization.
And I'm saying things that they can't soft.
Like, this is like a square peg,
and the problem I'm trying to solve
is a square peg in a round hole operationally.
Like, no one can function the way that I'm asking
for them to function or solve the problems
that I'm throwing onto the table.
And so, transformation sort of has to happen around that.
And I think leaders experience it every day
when there were the ones, you know,
a chief marketing officer is responsible for,
I don't know, 20% growth.
And they go in every year and planning season,
and they set that goal on the table,
and they say, hey, our goal this year
is having handed down to us is 20% growth, right?
And in that room is the head of analytics,
it's the head of media,
there's all these different heads in there
of all these different functions.
And as soon as the media's over, everybody leaves,
and everyone's gonna work really, really hard
to try and achieve that goal,
but they're not gonna talk to each other,
and they're all gonna work in their little silos.
Like, the solution to that 20% growth
is sitting somewhere in the data strategy
or it's somewhere in the media strategy
or it's somewhere in the martex stack.
It's not, it's not, it's all of those things
functioning together to solve that problem
in a way that we have not set up the company to work
or more importantly to reward,
and that's what you're talking about,
because later on in the year,
after we've had that discussion,
and everybody's going off into their silos
and is trying really, really hard to make that goal happen,
to try and be the hero, we're gonna get together quarterly,
we're gonna talk about results,
and we're gonna talk about, we've built new data tables
in the data, and we bought this new,
we replaced this software with some new AI driven, whatever,
and like, we built new customer segmentation model,
like we've got it, we all worked on stuff independently,
but the dial's not turning, because it wouldn't,
it wouldn't give in those pieces,
independently working, rather than, you know,
working together on a common problem, so.
Hey Tim, imagine for a minute,
you're an e-commerce marketing leader,
and you just launched a new checkout yesterday.
And now, you're wondering, did performance change,
or did the tracking break?
Yeah, it's so important, and with the State MCP server,
you can connect an AI assistant to your State account,
and you can ask it, things like checking the container
to confirm that the tracking domain is valid,
review usage before and after launch,
and you can show what changed by browser or client.
So, instead of digging through infrastructure screens,
you can get a plain English operational check.
Yeah, you can also review daily usage,
see which domains are generating traffic,
and check for unexpected costs or surcharges.
That helps an in-house team answer
an important question faster.
Is this a marketing problem, or a measurement problem?
Yeah, hone in on the solution,
and to do that, click the link in the show description
to learn more about the State MCP server,
and how it can help you.
Michael, ask wise, prismversion3.0,
now speaks MCP.
That's great, I love acronyms.
They make me feel like I'm in a meeting,
I forgot to decline.
Well, in this case, it means Prism can plug into
Cod Desktop, Cod Code, and other MCP compatible tools.
Ooh, I do like that,
so Prism becomes part of the workflow
instead of another tab I'm pretending is organized?
Exactly.
From Cod, your users can query the workspace,
trigger analyses, and pull results
into whatever they're working on.
Oh, I love that.
Less way to that come from more.
Oh, look, a usable workflow.
Yeah, and with Prism's memory engine,
skills, permissions, and admin controls,
the context stays managed, not trapped
in one person's chat history.
Really useful.
'Cause I think Cod told me this last week
is not a governance model, not exactly.
So go to ask-y.ai and join the wait list.
And pro-tip use code APH to jump to the top.
That's ask-deleter-y.ai and use code APH.
Prism, fewer tabs, smarter agents,
less workplace archeology.
I think you see it every day.
I mean, they really think you do.
The advantage was having sat above all of those functions
and going, okay, you know what I don't need?
Is more exposures with no one going
to a high-value action on my website.
Like, are you working with the Omni Channel team
to deliver, like after we expose them,
to deliver a journey that moves them closer
towards the high-value action that I want?
Oh, no, you guys never talk.
Okay, this is a system that produces and rewards this.
And now we need to change the system
that we're all operating in to reward,
to give you a different problem to solve
and to reward you for working as hard as you're already working,
but to solve a different problem
than what you're trying to solve today, right?
So.
- And what you said really hit home of,
it's time for us to turn back to thinking
about how timely and relevant it is for the customer.
And I have also found working with a lot of my clients
is that in the pressure of activity,
like you were just describing in the silos
of their organization and the pressure
to do more, get more out of it.
Or at least that's, again, the habit that we've created.
People very quickly lose the lens of the customer
and the customer experience.
And like at the end of the day,
that is what all the functions
that the company need to work together to change.
I am curious how have you found a way to help teams
get back to thinking about the customer
or helping teams reach across to the other teams involved?
And I'm curious from the different positions
that you've held or now even moving into consulting,
like you mentioned, is there anything you use
to kind of convince people of that
or scenarios where you've been able to help
change those working habits?
- Yeah, and Julie, two things there.
I think first, I probably even said those words too,
getting back to the customer experience.
Honestly, it should have always been
about the customer experience.
From the beginning of time, right?
When it was a small hardware store
that you walked into in your neighborhood,
like they knew in order to do business,
they had to help the customer solve a problem.
And I think as this digital era has helped company scale,
I mean, any company you take,
if you go back 20 years and look at what they were,
you know, the number of people that work there,
the size of revenue, all of that,
that is a magnificent scale.
And I think that challenges companies
to figure out how to even grow their organization
to be that big and handle that much customer work.
But I don't think we ever should have lost track
of I still actually need to be good with customers.
That's why I called a little bit of lazy marketing
in between because it did get away from that,
even though it shouldn't have.
And now, if you're going to grow,
you've reached as much as you're going to grow
with that marketing.
If you want to grow that baseline from what it's at,
you've got to get good at the customer experience.
You have to solve customer problems again.
So you've got to know your customer better
than you ever have before.
And again, the good news is all of this tech stack
and everything we do is actually ideally designed
to solve that problem.
You're just not using it.
The cover is a shovel upside down, digging a hole.
That's actually the metaphor that's
trying to be conveyed on the front of the cover.
You have the right tools.
You've just got to flip it over and use the other end.
And it will solve the problem for you.
So to your point, Julie, I think what I like to do,
I always, as a leader who's led a lot of transformations
over the last 10 or so years, I always
think it starts with vision.
I think you sit down and you talk about,
what do you need to be in five years from now commercially?
What goals do we need to be achieving five years?
And how do we have to operate in order to achieve that?
And well, we need to do more when you're OK, OK, great.
A fundamental question I love to throw in there
that's sort of a blockbuster question that really stops
the conversation in its tracks is, OK, what are the customer
problems we have to solve in order
to turn them into better customers?
To achieve that result, you just talked about.
And they just stop.
And there's no answer to that.
There's just silence.
And I go, look, fundamentally, marketing
is about changing mindsets.
If they were already going to buy it,
I wouldn't need to waste money marketing to them, right?
That I wouldn't need to do that.
So it is about changing a customer that isn't going to do this
to some degree, maybe some customers
are further away from doing it than others.
But in some way, it's about interjecting myself
into that customer and changing an outcome
that benefits the customer and me at the end of the day.
And if I'm asking you, what is it going
to take to change the mindset of your customers
or what problems stand in the way
your customers being better customers for you,
then I don't know how you're ever going to achieve those goals.
That is fundamentally the question that the only way
to achieve growth is solving those problems
for your customer.
And the fact that you're sitting here quiet tells me,
we haven't done enough to know our customers
and what problems they have that are preventing them
from being better customers for us.
And that's something we better get back to doing.
and look.
I'm not the first person to preach customer eccentricity,
but I think it's been a forgotten concept.
And I think people, many companies would say
that they are customer centric
'cause they have a lot of customer data.
But that customer data is a lot like saying,
this side of the river holds the biggest fish.
So if I fish here, I catch big fish.
It's not how to catch them.
It has nothing to do with how to catch them.
And so you really don't know your customers
'cause you don't know what the problem is.
And therefore you can't solve it
and move big fishes or small fishes
over to the side that you want them to.
And so I think it's about that.
I think that's the moment where they kind of sit back
in their seats and go, you know what?
Maybe we actually don't know the key to that question.
And knowing it is unlocking the future for us.
So how do we do that?
And so you've got an ear to start talking about
how you start solving that problem, right?
And how you start getting back to knowing your customers again.
- And you know what's interesting?
You talk about knowing your customers.
Another thing I've run into a lot is
when we get into like segmentation of customers,
again at the thought of, oh, we'll figure out who's alike
and then we'll market to them accordingly, right?
It's like getting at the idea of caring about the customer,
figuring out how to work with each user type.
But sadly, the first thing I see a lot of my clients
reach for is they segment them based on outcome.
They say, who are my big spenders already?
Or who are already really loyal
and who are the people who are not loyal?
Which is interesting because it's so backwards
to thinking, well, wouldn't you describe them
by similar characteristics?
And then you'd hope to interact with them
to then drive the actual outcome measure
for the different groups.
But I find it really interesting
that so many companies end up actually segmenting
on outcome, which seems so backwards.
It's so about you, not about your customer, right?
You're saying, and I get it, it's particularly in pharma, right?
Like that's an industry that I spent time in
that I could see right away grew on a really expensive resource
called a salesperson showing up at a doctor's door, right?
Which I don't know, cost something like $300
every knock on a doctor's door.
And though that ability has drastically been reduced
by legislation, they don't really have the ability
to do what they used to be able to do.
Or BS is effective with sales folks as they used to be able to.
So they're going digital, but it's exactly that, Julie.
When I think about sending a very expensive resource
like a salesperson out, I can't send them out
to very small customers, but the customer opportunity
is very small.
I have to send them out to the place
that they could have the potentially biggest impact
on my bottom line.
I get it.
But when you extend that thinking to digital,
you're making a mistake, right?
Like digital doesn't cost the same amount of money.
And that was, you were putting the problem set on a human
to interact with another human to figure out
what the problem actually was that needed to be solved, right?
Now, you've got a digital ecosystem, which
can reach bazillions of people, very, very low cost.
But you don't know the problem you're solving
as you're blasting all this stuff out all the time.
So you still create segments that are like,
these are the biggest fish.
Let's spend the most marketing dollars
on these biggest fish when in reality, if you step back
and you said, you know what?
There's probably only four or five problems
that my customers have that if I could solve these problems,
they would be a better customer for me, right?
And if you segment your customers on that first
and say, OK, here are big fish and little fish
that all share the same problem.
And if I can solve that problem, I would turn all of them
into better customers for me.
Now, some of them, within solving that,
there may be different ways of solving it.
I may send a rep out.
And maybe I wouldn't send a rep out to a small one.
But I know the problem I'm sending the rep out to solve.
And I know what I'm asking my digital marketing
or my customer journey marketing to solve as well.
It's just I'm deciding how much to put into the solution.
But the solution is the same across the board
in terms of the value that has to be exchanged with that customer
to move them from where they are to where I want them to be, right?
So I think that segmentation has a place.
It just isn't the first cut of segmentation.
It's a second or third layer of segmentation
that says, OK, once I've segmented on the problem,
I need to solve.
And I've got solutions to that problem,
which is a portfolio of solutions.
I can decide which of that portfolio of solutions
I should invest in, which customers
based on cost and potential return on that investment.
And I think if a company gets that far in there,
having and hawing about the incremental value
of a solution on a certain subset of users for a problem,
like, I'm sure they're doing pretty damn well.
Because that is like top tier thinking,
if you've made it to that step, I want to come meet your company.
Yeah, like, honestly, totally.
Well, and so I cannot wait to talk about some of that portfolio
stuff in the way you're talking about thinking about.
But I want to go back a little bit to the transformation
it takes to be able to get to what you guys were just talking about.
Because I know you reference like the cover of the book
is about like turning around the tool like you have it.
You're just not using it correctly.
But I do have the privilege of being in your circle
and so I and you're also the king of analogy.
So I can't wait till we do the tally at the end of the episode
for all the amazing analogy.
See, it was, and there's so many that have stuck with me.
But I remember you were talking about a team that was mobilized
and ready to do some of this work.
And I think the way you phrased it, hopefully, I don't
butcher it is like, we're ready to work together
to make things giving dinner.
And the request I'm getting is for a side of cranberry sauce,
more cranberry sauce, just like put more cranberry sauce on my plate.
And so I want to talk a little bit about like,
ooh, needs to be involved in some of this transformation.
And how do these groups kind of work together?
Because like Julie said, getting an organization
to like put aside your segmentation
that you've been so emotionally like your crutch
for the past however many years to something
that you're talking about with this transformation.
I'll go a little bit more about like what that takes
and who you have to get bought in.
Yeah, it's a great question.
And as I just mentioned with the customer centrity, right?
Like I'm not the first person to preach customer centrity.
I mean, that's been out there for a long time.
I think there are, this entire book is not
about any one unique concept.
It is more about all of these concepts that companies
are putting into play.
Like they think they're being customer-centric,
but they're not applying it correctly.
They have agile, but they aren't totally applying it
from front end to back end.
It's only a tech build.
It's not a front end strategy, right?
So I think it's on, this book is about a lot of those tools,
not just MarTechStack and hadTechStack and teams
that you have built, but also ways of working
that you've deployed, but you've only got like a percentage
of it's deployed, right?
Because this is where it comes together, right?
I think at the, there's sort of an arc of maturity
you go through here, right?
I think there's sort of, when you don't have functions,
you build centers of excellence to create consistency
across your organization and to get you over the large investments
that need to be made around capability and discipline
and structure, you know, the design systems
for the UX team, you know, analytics.
So you don't have 10 sources of truth.
You're down to a limited set, you've got definitions
of data dictionary, like all those things come
with center of excellence and they're really good
and they're really important.
But ultimately, when you talk about solving
these customer problems, they largely become
a bottleneck pretty quickly, right?
Because you need localization of the problem solving
and not only that, you need quick feedback loops, right?
This is where, you know, Val, of all people test and learn,
right, is so close to your heart, but how difficult
is that to introduce into a company that's organized
into the site, like it doesn't work?
First off, it takes them nine months to take an idea
to market, when it takes nine months and nine months
of cost to get an idea in the market, I can't do two of those.
I just need to get it out and get some kind of result.
I have no time to test any alternate ideas, right?
So this has to get these teams that can do this
work closer to the front end, be able to deliver pieces
of things in a hurry, evaluate quickly with analytics
if it's working or not, and pivot quickly.
It can't go through year long planning cycles,
nine month delivery site, it can't do any of that.
Like that, look, you're not going to build that thing
overnight, you have to mature to it, but ultimately,
when you have a team that is comprised
of all of the different functions that make digital run
from data strategy to analytics and two kinds of analytics,
right, longer term analytics and fast, quick, dirty,
is it worth the thing we just put out in the market?
How much traffic's coming to the website from that?
What are they, are they achieving high value act?
Like quick and dirty, to media buying, like all of this
needs to be done on a rapid scale with a team
that comprises all of those disciplines, right?
It's not cheaper, won't tell you it's cheaper.
Centres of excellence are really cheap
'cause you scale them across the entire organization.
When you start building these teams,
you're borrowing discipline from the centers of excellence
and you're dedicating them to a set of problems, right?
So you might say, in this case, you might say,
all right, let's pretend we're at a pharma company
and we've identified that there's a set of,
there's a large, a valuable cluster of customers
who need more evidence in order to write the script
for our drug over what they're currently writing the script for.
We've got a better drug,
but they've been writing that for 10 years,
the existing drug, our new drug, better results.
But we have to prove that to them in order to get that, right?
Now, there are different value exchanges
that can happen to do that.
You can get them data and white papers
that say the results are better.
You can have them talk to appear.
You can get them to a conference
where they see somebody a key opinion leader speak on it.
So there's different ways of solving that.
But I've got to build journeys to get them
to those high value actions.
I've got to get somebody to a conference
and that means I've got to make them aware of the conference.
I've got to find the right people
who would be open to going to a conference.
Maybe that's geography-based.
I've got to build a journey that makes it easy for them to--
there's a whole journey that goes behind delivering
that value exchange, right?
I need a team who is dedicated to that problem set
of not just delivering those value pieces,
but also evaluating, are these the right solutions
to somebody that even needs more evidence?
Or are there better solutions out there?
Maybe a podcast on something like this
might be a better solution, whatever.
So they're looking at not only the tip of the spear,
the high value actions, or the value exchange pieces,
but also are we getting people to sign up for those things?
Are we actually exchanging those value
when we pick a customer and we say,
we want this customer to attend a conference?
How good are we getting them to be able to do that?
Are we improving the journey that gets them to do that?
Are we-- when they do go to the conference,
is that the right solution?
Is that moving them or not?
That all needs to be rapid design, analytics
behind it very quickly.
And so you need a team who has all of those disciplines
or can borrow all of those disciplines to deliver in that
in a very agile or lean way.
You're working model with some hybrid of agile,
lean kind of on-bonish thinking that you put together
to solve that problem.
But every two weeks, you're putting something out into market.
You're getting results back immediately,
and you're saying, OK, this is working or this isn't,
working fail, go on to the next idea.
And that's where Test and Learn finds its home.
With all of these other disciplines,
helping to do segmentation more precisely,
maybe we targeted the wrong audience with that message,
content helping to improve the messaging consistently,
time after time-- you got all of that at your disposal
to try and solve that problem.
Now, it is more expensive.
I will say it again than the center of excellence.
But if all the center of excellence is doing,
is pumping out more cheaper?
That's not impact.
This is impact, because I'm going to give them a problem.
And I'm going to say, here's the population that I know
that I want you to target.
To change-- this is the population I have to find
is having the problem of needing more evidence.
And I'll be able to look at that population and say,
they've moved or they haven't moved as customers
as a result of the actions that this entire team has put forth.
So I have a measurable result of impact at the end of that,
in a way that a center of excellence
who just pumps out websites or pumps out email campaigns
or pumps out, like, doesn't have any connectivity
to an output or an impact output associated with it.
So it's just pumping out actions, but not results.
This is tied to a result.
Really, how you started to find what, like, a journey.
So you were saying it's for a specific audience,
like, with the same problem.
Because another thing I find is I spend a lot of time
talking to my clients and stakeholders
about, like, a journey, what they consider a journey.
I've heard people say, you know, maybe the poorest, right,
is, like, well, the journey should
be defined by the business ahead of time.
What does the ideal flow?
But then these companies spin up, you know, huge websites,
huge digital ecosystems.
They offer labs.
They offer webinars.
They offer, you know, e-com online or their sales people
in person, right?
And it gets very complicated fast.
So then people want to say, well, we have all this behavioral data.
Let's just use AI to surface the pattern.
And that will tell us the actual journeys.
But what I hate about both of those
is it's completely disconnected to the customer.
And so I just, I really like how you put those bounds around it,
because I think that's something that I've been searching for,
because I've started to just get so crabby when people
want to talk about journeys.
I'm like, if we're getting journeys again,
like, there's no good answer.
But I really like, yeah, the angle you're taking on it.
So Julie, you just stepped on a landmine for me.
Like I hate customer journey exercises.
Oh my God.
In my life, if I could count the number of times,
I'd walked by a room and looked in and saw
like this massive arc of customer journey with stars
and arrows and boxes.
Like graphic designer skills going to waste on this magnificent
board that is a customer journey, right?
Like from whatever biggest waste of time I've ever seen.
Actually, it's an exercise that's probably
not a waste of time to do, but is so non-reality, right?
So this is the analogy I like to give around this.
If we were to take the average American's lifespan
and say, well, what's the journey?
Well, I don't know, I'm born.
If you average it out, you're born, you graduate high school.
You're born to two parents.
Oh, by the way, you're a family of 2.5.
I don't know who the 0.5 is, but you have a 0.5 of a sibling.
You go to high school, you graduate,
you go to some for your college, you get married,
have 2.5 kids of your own, you retire, whatever.
Like that's your entire life story.
You go on vacations, you retire, that's it.
Literally no one in the United States lives that life.
Literally no one lives that life.
That's what a customer journey on a wall
looks like at a company.
And no one actually walks through that thing that way.
That's an average of people's lives
that literally no one lives.
The reality is, some people do go to college.
Some people are born with six siblings,
six siblings, some are born with one, right?
Or none, just one individual child.
Some go to college, some don't go to college.
Some big get married, some don't.
Some get divorced.
Some have kids with the first relationship.
Like it's messy, the real world is messy.
You can't create an arc that touches all of those points
and pretend that that's a reality.
That is not a reality.
What you can do is, it's exactly what we're sort of
talking about here is say, okay, no, I can't do a whole arc.
But if somebody's online shopping for a kayak,
I can give them a journey to get them to a kayak.
I can detect that and I can get them to the kayak, right?
Like, and maybe they buy another one after that.
So that's like a divorce.
They go through the same purchasing thing again.
Okay, no problem, right?
If it's fine.
Like you can only sort of detect in the moment
what their need is and try to solve that need.
And you have different needs that you can solve for,
but you can't configure them in a definitive way
that they're gonna go through them, right?
Like even after, even if you say,
my biggest problem with this new product launch
that I have is I have to create awareness.
No one knows about my new product, I'm about to launch
into the market.
Okay, well, your first journeys are all gonna be around
awareness based, right?
Okay, great.
Let's fast forward five years into your new product out there
and a competitor comes into the marketplace, right?
Here's a really good customer of yours
that keeps buying your product,
but suddenly there's a competitor in the market.
Well, they might have to go through awareness again.
The awareness might be how your product is better
than what the competitors product is, right?
Like sometimes they go back through the same journey again.
That's what I'm saying.
So I think to try and create a journey
which links all of these sub journeys together is insane.
It never happens, but there are micro journeys.
And at the end, at the tip of a micro journey
is a value exchange.
If I can get them to do this,
they will move closer to being a better customer for me.
And if I can use data and analytics
to determine what that need is,
which is what I should be using it for,
then I can put them on the right journey
and score and evaluate my ability to deliver a good journey
and a good value exchange
to move them towards it being a better customer for me.
I think the other analogy that's in the book
that kind of works well here is the game of Plinco, right?
Which is this old wooden nickel game.
Drop it in the top, it hits these nails
and there are four buckets at the bottom
that have different points associated with them.
I think the wooden nickel is the customer.
And I think at the bottom are the journeys
that we're trying to put them on.
Like, okay, if I could get them on this journey,
they'll become a better, if I can exchange this value
with them through this journey, I'll make them a better customer.
Each one of those nails they're hitting on the way down
is an opportunity, it's an interaction with your brand
that is an opportunity for you use data
and that interaction to try and guess which bucket
they need to be in at the bottom of that.
And that is the game of data and analytics
at the end of the day.
And I use this to look at patterns and identify
what my customer need is at scale for this group of people,
this is the problem that they have with our brand.
And if I can identify that, now I know
from marketing what problem I have to solve,
I can measure the actions that I'm taking the journey,
that I'm taking to try and get them to exchange
that value, which I believe was I can measure all of that
and tell you how effective all of that is
at changing my customers into better customers.
- I like that a lot.
And I will say that the one thing that I repeated in my notes
was I went through your book, I was like,
the process is testing, like in there.
And I come up and I'm like, look at it.
Like that's, yeah, we're the outfits and I love that.
So like if we have these problem mobilized pods
that are focused on continuous delivery
of the portfolio of solutions
that could potentially relieve ourselves
some of these problems, like paint the picture.
'Cause the one thing that we didn't really get to talk
about too much is like the system
and the system's expectations of how people behave today
and how they're kind of rewarded for activity
to how the system behaves in this like more idealistic vision
that you've painted, like can you talk a little bit about that?
- Yeah, I mean, again, and we've achieved this, right?
I think at GSK, this was sort of the pinnacle
of what we were able to do was put these teams together
and the reward structure completely changes, right?
We're not rewarding activity anymore.
We're saying here's a population that needs to move closer
to the ideal customer set that we have.
And here's a set of problems that we believe
is standing in the way.
of them being that iterate and solve that problem, right?
Validate that we've even got the, like maybe we've got the wrong,
the way we've segmented these customers into this problem set,
maybe wrong.
The, the value, the products, right?
And the experience products, the value exchange,
experience products, that should, you know,
our conferences, maybe that isn't the answer
to this problem that we think it is.
Maybe that really doesn't move a customer forward.
So look at the portfolio of things
that we're trying to get them to do.
And our ability to actually get them to do that
and help us optimize that.
And the way, again, reward.
Again, I think people today in the silos
of the existing system are really innovative and ingenious.
I think every team I've ever led has extremely talented people
in it who are trying really hard
and defining new ways of solving problems for the company.
It just isn't latched up to something,
a common problem that actually delivers impact,
the way that this system does,
and that we can reward and recognize those
for that kind of innovation and ingenuity
against a well-defined problem
and a system that can measure the actual outcome
of the efforts that they're doing, right?
And so again, I can measure the cost of,
you know, in a really,
in a, with a really broad brush,
I can measure the cost of my centers of excellence today.
I know how much they cost me.
I know how much the tech stack they're working in cost me annually.
I know how much head counts in there.
I know contracts.
I know all the answers to that right at a very high level.
I know that cost and I also know
how much our impact that entire organization
is having out in the real world in terms of growth.
I know those two things and I know this model
is significantly more expensive than that model,
but I can show the results and the outcomes
are significantly higher than the money
that's being spent in this other model.
And when I can do that,
I can reward and recognize the people within the system
for the amazing ingenuity that they're having
within that system.
- So in the operating model chapter,
you kind of develop this idea of like developing
those cross-functional teams as opposed to sort of like
center of excellence concepts.
So just to clarify boundaries a little bit,
and also I think if I was a business leader listening,
I sort of have some questions about like,
how deep should that go?
Should I try to take everybody?
'Cause like some people are just specialists,
like they are working on that thing
and do I need to throw them in a cross-functional team
or is there sort of that structure?
And then I set up like a tiger team sort of set up.
Like how do you bridge that gap for people
or advise people?
- Yeah, I think it's a great question Michael.
And I think there are,
it's hard to put that in the book.
The experience and what I think,
because I think, well, I say this because I think
a smaller company has a different answer to that question
than a larger company does.
So it's hard to prescribe that clearly.
But here's what I would say.
I think, you know, this is another analogy for you about.
I think potato chips with no ridges
break really easily in the dip, they do.
The reason ridges were invented
is it makes the chip stronger, right?
But ridges only go one way.
- You can't have to orient the chip correctly, Rusty.
- Well, that's correct.
- Yeah, yeah, come on.
- You know what's a stronger answer, yeah.
- I think it's a good answer.
- This is our first time dipping a chip.
- Anybody who dips horizontally
is making a huge mistake and that's the other thing.
- There's gonna be half a chip in the dip.
That happens, it's not gonna be good.
No, but what's even stronger than that, right?
Which I would say, if you only went with teams
that were, you know, journey aligned,
you would have hearts on, it's stronger than the plane chip
where nobody's aligned to anything,
but it isn't the strongest function
that you're the strongest model that you can have.
The strongest model is the waffle fry.
Seriously, the Chick-fil-A waffle fry
is the strongest potato in the world.
It can't be broken anyway, you try it.
So you get it.
Cross-cutting is actually twice as strong as,
and I'm sorry, there's probably some engineer
that'll tell me that.
- You can do a waffle chip.
- Tater goes. - Is that a thing?
- Has a waffle chip, they do.
- They absolutely do.
That is a supreme dipping material.
- Vehicle.
- It's nice, it's real nice.
- Yes, yes.
So you get the point.
I think you can't just go one direction with this.
I think to your point, Michael, in addition to these,
the players on these teams that are multi-functioned,
cross-striped, whatever you wanna call it,
still need to belong to a discipline, a guild,
which belong, the center of excellence still needs to exist.
The work just doesn't get done in the center of excellence.
It's now transferred out to these teams.
But the members of that team belong to the guild
of the center of excellence, because if you just let it go,
you lose all the discipline of a center of excellence
that has, well, updates the technology
and the stack that they actually work in
to make sure that continues.
That there's a roadmap for that.
That documentation continues.
That standards for design continue, right?
You can't turn it all loose.
I think you still retain a small center of excellence
that continue to represent the guild and the need of the guild
to be able to do its job fast and effectively.
I also think it can, in a large organization,
you should separate out the value delivery products.
So conferences, white papers,
these things should be developed by teams
outside of the journey teams.
Journey teams should be mainly focused on identifying
the right audiences, moving those audiences
through the content journey and evolving the content journey
to more effectively move them to exchange the value.
But that portfolio of value things is actually another team
that should actually develop and own those.
Ultimately, if you can afford to do it,
I think if you're a small organization,
this sort of collapses a little bit on itself,
you know, smaller teams, smaller, see if you,
you know, all that stuff.
Then you run into the age-old glingerie,
Glenn Ross problem, you know, these leads.
These leads are really good.
Exactly, it's a great movie, by the way.
No one has the patience to watch that movie anymore,
but it is amazing dialogue.
Well, before Michael says what I think he's about to say,
I have to ask, the book was written in a very specific format,
the way to kind of phrase it.
So I think what you need to tell your future readers
that are currently listeners a little bit about
how you made some of those choices.
Yeah, good question.
So I actually wrote it long form originally.
So it's a 500 page, there's a 500 page version of that book.
And before I even started writing the book,
I have some mentors that are sort of guiding me
through the process of written books before,
they are C-suite individuals who sort of were the people
I was trying to speak to the most
to help them understand why the money that they're spending
isn't, you know, returning what they really want.
And so I had pitched the idea to them very early on.
'Cause this book is this worth a book
and they were like, oh my God, yes, definitely write that book.
So they sort of helped me affirm
that there was something to be said here.
I developed the 500 page, or I send it to them,
and they're like, I'm not reading.
Like, who are you talking, like, what is this?
Like, I don't have time to read this, you know, whatever.
And they're like, when you came in here,
you told us about this and we were all in,
we totally understood it and we were ready to go back
to our companies and make a change.
Just tell us that's like, talk to us like you did then.
And so I had to go back and take the 500 pages
and turn this into what is more of a conversation
with the reader than, you know, then the 500 pages.
It is really meant to be a conversation.
It is spaced with timing, which, you know,
when you first open it, it'll look like poetry.
It is not poetry, but you will, after the first page,
you'll sort of fall into this groove of single spacing pauses
versus double spacing pauses.
And it helps make the points that I'm trying to make
in shorter, you know, less stories,
less, get to the more, get to the point CEOs sort of speak.
And it, you know, it condense the books significantly
and it helped me say the same thing
in a lot less words that I think C-suite people
will be willing to endure.
In fact, to funny story here, I'm working,
I'm more of a podcaster.
I'd listen to things more than I read the physical copy.
So, yeah, I get the book published and I'm working on,
okay, now I gotta get to the part that I would actually enjoy,
which is the podcasting part.
And everybody's like, my mentor's like,
you have to do it, it has to be your voice.
So, you gotta do this.
And I'm like, okay, well, I've never done this before.
So, okay, let me look in.
This was a lot of work editing and all that.
But I'm like, wait, there are these great AI products out there.
Now, you record like a 30-second sample.
And it'll, I'm like, yes, this is it.
I'm gonna do this, right?
So, I go, I buy the software, I record a 30-second sample.
And then I immediately turn it loose
on the first chapter of my book.
And it actually did a pretty good look.
It did a really good job of being me reading the first chapter,
which was the problem, right?
Yeah, listen, I turn all of my devices to like speak in British,
because everything sounds smarter if you have a British accent.
I mean, you sound brilliant with a British accent.
Like Siri talks to me, because I'd like to think
that I'm an around smart piece.
So, okay, all my devices speak with a British accent to me.
The opposite, right, so you could read the script of idiocracy.
But if you do it with a British accent,
it sounds like the Magna Carta, it's amazing, right?
Oppositely, if you have a Philadelphia accent
and you read the Magna Carta,
you sound like you're reading it at idiocracy.
And that's exactly what I was like, oh my God.
Do I, is that my accent?
Do I sound like that?
It was terrible.
So, I ended up having to hire someone to do it.
It's almost done, but like it's so much,
but I'm not even, I'm only right to the guy in email,
because I don't want to hear my voice now, I won't talk.
I don't want the phone, I'm just like, "I don't want the ear off there."
(laughs)
- Water. - My water, water.
- All right.
This was awesome. - This was awesome.
- This is so good.
And the book is really good.
And it does read, once you get into it,
you do read with a little bit of cadence.
I definitely picked that up as I was reading it.
I was like, at first I was like,
"Oh, what's going on with this book?"
And then I was like, "Oh, I actually kind of does flow
once you get used to it."
So it is well worth it.
And I don't think it's just for CEOs either.
'Cause I think even when you're sitting in a seat,
I think you can advocate for some of these things
if you're not the senior executive in your department,
you can sort of raise your hand
or start to apply some of the principles
even in where you're at.
So, okay, we do have to start to wrap up awesome conversation.
Thank you so much for us to spend too long.
And you've been working on this super hard.
It's like, "Wow, you've got a lot done."
I was like, "What have I been doing?"
No, so thank you for all the work
putting that together and coming on the show
to talk about it.
Okay, one of the things we do is go around
the horn and share a last call,
something that might be of interest to our guests.
Rusty, you're our guest,
or might be of interest to our listeners
and Rusty, you're our guest.
What is your last call?
Have you guys read this book?
Analytics, the right way.
Have you heard of it?
It's, I'm sorry.
Yeah, little plug for Tim.
Little plug for Tim.
No, that's good.
Lately, I have fallen in love.
This is the second time I'm listening
to the same seven series podcast.
It's first time I've ever listened to a podcast twice.
It's by Chris Hayes.
It's called The AI End Game.
And it's about seven podcasts,
about an hour each podcast or not terribly long.
He has guests on to each episode.
What I love about it is it covers every,
it's a very top thinking about AI in the world.
Everything from philosophical,
so he'll have some professors on
that will talk about what is intelligence,
what is sentience, and AI ever achieve this
to the political ramifications of how do we govern this,
how do we write policies to control this,
where do we need policy to control it,
to history talking about AI summers and AI winters
of innovation and how we got to where we are
and what the weakness is and strengths
of where we are and capability is, and even economics.
So, you know, what's this going to do to jobs,
or what do we think it's going to do to jobs,
what's it going to do to the stock market,
all of these different things covered in this series,
really big thinking, I think,
from some of the smartest people in the world as guests,
and I really love this podcast.
Like I said, it's my second time through it,
because I think there's so much to think about,
and see differently than the AI software
where we're interacting with every day,
the more larger ramifications of all of this stuff,
which is really cool.
- Nice, I'll give it a listen.
All right, Julie, what about you?
What's your last call?
- My last call, funny enough, is actually a David Epstein letter,
newsletter, and it's him and Brad Stoolberg,
and it's them discussing two books
that they recently published earlier this year.
The books are the way of excellence and inside the box,
and it's a really cool discussion back and forth
in a really nice highlight of both of the books,
and it really made me want to go and actually get them
and read them in full.
And the title of the newsletter
is How to Pay Attention and Care deeply in a chaotic world.
And so I'll just give a few teasers of like quotes
just from the beginning of it,
but it was such an interesting read.
And like I said, I think that the books diving
into these concepts more would be super interesting
to go and check out.
So the first one is the quality of your attention
shapes the quality of your relationships, work, and leisure,
which is to say the quality of your attention
shapes the quality of your life,
which really like hit home for me.
And then they talked about it's changed
from time management to attention management.
And then the last one I'll give you is wealth of information
creates a poverty of attention.
So like those three things just like really caught my eye.
So highly recommend reading the newsletter.
And then I would not be surprised how many people go
and purchase the books for more.
- Yeah, Julie, if we're telling people to like trim down,
like I think that goes against what we're doing here,
but it's over, it's about quality, right?
We've got quality here.
It's okay.
Yeah, that's right, thank you, I appreciate you.
Yeah, keep listening to this but cut everything else out.
- Everything else, you trash.
- We need your full attention, people.
- That's right, now what's your last call?
- Okay, so mine is a New York Times article
that my husband sent me, who is a philosophy major.
And the title is The Revenge of the Philosophy Majors.
And it talks about how a lot of AI companies like Anthropic
and Google DeepMind are recruiting philosophers
to join their kind of crew
and some of the things that they're really leaning into
as some of their skill sets that are different
or have a different perspective or angle than others
is around like obviously the ethics
but like being able to take like abstract concepts
and make it easier to digest
like all those like conceptual challenges around AI
but the one thing that I found really interesting
I mean, it's super interesting
and they have like, you know, a different quote
from different people.
I was like, oh, like what do they call
like forced-deployed philosophers
like thinking of being so funny
and that was like, no, they're just philosophers.
Like, it's just philosophers, that's the title.
It's like, okay, wow, all right, well, there you have it.
But it's just so cool to think about like how AI
and you know, some of these roles
and how it's kind of morphing and changing
what is seen as mission-critical
to like move us forward
but it was kind of a fun read.
So that's my last call.
- So you're telling me they can't be advanced philosophers.
- It's seeing your advanced.
- Advanced philosophizing, sort of like how we do it
as advanced analytic.
- Exactly.
- All right, sorry, that's good.
- No, good, they're data philosophers.
Yeah, exactly, yeah.
- I like that a little.
- I'll tell him that, he'll love that.
But David, in front of it.
- Just to build on that for a second,
there has been a longstanding philosophical test.
I mean, they've been wondering if computers
will ever be able to imitate a human
for a long time, ever achieve sentence or whatever.
And the longstanding test has always been,
if a human in a blind test cannot tell that they're
having a conversation with a computer,
that has been the philosophical bar
that sentience has had to reach in computers.
If it could do that, then it would be blown that away already.
And so the need to define what is it
that makes us different than a computer
is like a huge philosophical debate right now.
And I'm sure that gets right into it.
It's really exciting times for that.
- How about you, Michael, what's your last call?
- Well, mine is a little more fun this time,
but I do love a good allegory
and a blog post that Charlie Tyson
I work with shared with me by a guy named Gerard Rubio.
It's sort of an allegorical story about startups.
And I thought it was well written in kind of a fun read.
So we'll have a link to it.
But basically, he's sort of talking about a guy
who's decided to start a oven business
and goes off into all the different things
that happened to a founder through that process.
And I think now in this day and age,
because it's so easy to do something with AI,
I think everyone sort of has this thought of like,
oh, I should start a company.
And then this will sort of get you through
probably the first few years of that pretty easily.
And if you were thinking about doing a product,
so it's a good read.
It's a fun little read.
All right, well, Rusty again, thank you so much.
What a pleasure.
Have you back on the show and hang out a little bit.
It's always great to appreciate the insight
and the wealth of experience that you kind of distilled
into your book working as designed,
which is available, I believe, on all the major platforms.
So you should probably pick up a copy
just so you can say, I have a book by Rusty Raymer.
And also read it.
It's, yeah, so that's probably more important
than say you have it.
But anyways, all right.
I know as you've been listening, you're probably thinking,
hey, I've got a couple of questions or things like that.
We would love to hear from you.
And the best way to do that is through our website
or our LinkedIn.
Or you can email us at contact at analyticsour.io.
And also, as you're out there listening,
please add a review or comments also where you listen.
On Spotify or wherever.
So we'd love to hear from you or see reviews
and ratings is there as well, always is awesome.
All right, so I think that's it.
And I think I speak for both of my two co-hosts,
Julie and Val, when I say no matter what your organization
structure, whether you're a center of excellence,
a tiger team, or a cross-functional porridge,
or you're defining two big customer journeys.
Keep analyzing.
Thanks for listening.
Let's keep the conversation going
[BLANK_AUDIO]
your comments, suggestions and questions on Twitter at analytics hour on the web at analytics
hour.io, our LinkedIn group and the Measure Chat Slack group, music for the podcast by Josh
Crowe Hurst.
Those smart guys want to fit in so they made up a term called analytics.
Analytics don't work.
Do the analytics say go for it no matter who's going for it?
So if you and I were on the field, the analytics say go for it.
It's the stupidest, lazyest, lamest thing I've ever heard for reasoning in competition.
You do in the French Quarter, nothing crazy.
And we had come out of a place and there was a lady that was really pretty inebriated,
I would say.
And the rest of us were just like, oh well, and we kept going.
But Rusty, because he's such a nice guy, stops to try to help her into a cab and make
sure she's okay.
And she turns around and she goes, you have the most beautiful salt and pepper hair.
Me miles really.
Her two eyes are going different directions.
Yeah.
Go with her.
Right?
No.
It was something so funny because it was like, oh, yeah, it was a Rusty because he tried
to be nice.
And this lady's like, oh, wow.
You're your image cut through the fog that she did, where she saw you clearly.
Oh, five of me, I'm sure.
Yeah.
For the whole group of good looking men that helped me into a cab.
Yeah, I think what the story is, he tells.
Yeah.
Yeah.
You this day, he has this image of her guardian angel, amazing.
Yeah.
He convinced she went to hell unfortunately.
Anyway, good times.
I can, I can, I can hop into the pivots for analysis.
So, listen, I have to write a couple more books at least, okay?
Yeah.
At least.
I'm on it.
My movie is next, by the way.
So that's you.
Oh, well, that's perfect.
Perfect.
See how it looks movie.
That's what I want to hear.
Yeah.
Nice.
The red stapler becomes what would it be?
I was told I could have access.
Yeah.
I was told I could have access to the snowflake tables.
Yeah.
And if I could just, like, please give me back my access to the snowflake tables.
Oh, Gershaw.
Can't you hear it?
It's all a movie.
I'm telling you.
Yeah.
It's the time between Gershaw, Joe Sutherland, and Gary Angel.
Oh, Joe, yeah.
Joe.
Joe.
Wait.
There's somebody else.
Yeah.
He's going to teach you them a pen on.
Three.
Oh.
Have we had Chelsea on three times, too?
I thought so.
Yeah.
Because we did two and quick succession last year with her.
Well, this is what I was trying to do now.
Yeah.
Is this, like, a high problem of, like, 2010 where it's, like, capital basin.
So it doesn't.
Yeah.
Look, it's like a real company here.
Tim does all the work, and he's got four bosses to help him when he did wrong.
Oh, boy.
You know what?
You know what?
Oh.
Meanwhile, meanwhile, Tim's over there typing into Claude and Claude's like, you're
empty right.
I did forget about that guest, you know, and you're right to bring that up.
You're right to call me out on that.
That's right.
When was, like, the last time, like, how many times have Tim and Mo fought or something?
Oh.
Oh, what triggers Tim?
Like, those are always--
Because it takes up on, you know, it's an argument or--
It's pretty, it's pretty good.
Rock flag and turn around that shovel.
Podcast Summary
Key Points:
Analysts often repeat outdated processes without critical reflection, leading to underutilized capabilities despite significant investment.
The core problem stems from siloed organizations that focus on reach and volume rather than timely, relevant customer engagement.
Digital transformation over the past 20 years led to over-investment in tools and teams, saturating growth potential and creating a need for quality over quantity.
True customer success requires solving actual customer problems, not just segmenting based on outcomes or past behavior.
Cross-functional teams must operate with shared goals, blending data, marketing, and analytics to test and learn in real time.
The book emphasizes shifting from activity-based rewards to outcome-based success, where impact is measured through real customer behavior.
Customer journeys should be micro-focused and dynamic, not rigid, linear arcs that don’t reflect real-world complexity.
A hybrid model—combining centers of excellence for discipline and cross-functional teams for agility—provides the strongest balance of structure and innovation.
Summary:
Rusty Ramer’s book *Working as Designed* critiques the stagnation in modern analytics and marketing organizations, where decades of investment in tools and teams have led to inefficiency and poor customer outcomes. The core issue lies in siloed operations focused on reach and volume, rather than solving real customer problems with timely, relevant engagement. Ramer argues that companies have reached market saturation and now must shift from "lazy marketing" to deep customer understanding.
This requires a fundamental rethinking of how teams operate—moving beyond isolated functions to cross-functional, agile teams that test, learn, and iterate rapidly. These teams focus on identifying customer problems, not just demographics, and deliver measurable outcomes through value exchanges. The book champions a hybrid model: preserving centers of excellence for standards and discipline, while empowering agile, mission-focused teams to solve customer problems.
Crucially, success is measured not by activity or tool usage, but by actual customer impact. Ramer also highlights the flaw in traditional customer journey diagrams, which are unrealistic and overly simplified. Instead, micro-journeys based on real-time customer needs are more effective.
The transformation demands a cultural shift in reward structures—from incentivizing activity to rewarding measurable results. His insights are framed as a conversation, not a lecture, making them accessible to executives and practitioners alike. The episode concludes with a recommendation to listen to Chris Hayes’ *The AI End Game* podcast, which offers deep, thought-provoking perspectives on AI’s societal and ethical implications.
FAQs
The core issue is that organizations have built siloed functions with extensive investments in technology and teams, but they're not achieving meaningful results due to a lack of cross-functional collaboration and a focus on reach over relevance.
Because they’ve focused on building capabilities without shifting to a customer-centric model. The systems still reward siloed activity, not collaborative, timely, and relevant customer engagement.
By shifting focus from broad audience reach to solving specific customer problems with timely, relevant, and measurable value exchanges that move customers toward desired actions.
It’s a metaphor showing that organizations have the right tools (like analytics and data) but are using them incorrectly—instead of solving customer problems, they’re just collecting data without applying it.
They enable rapid, agile testing and learning by combining data, analytics, marketing, and customer experience disciplines to solve specific customer problems and measure real outcomes.
Because they represent an average of people’s lives, not real-world complexity. Real customer behavior is messy and varied, and people don’t follow predefined paths—only micro-journeys that respond to real-time needs.
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