Greetings from Austin, Texas.
I'm Nichole Jordan, National Managing Partner
of Markets, Clients and Industries at Grant
Thornton.
We are here live at South By Southwest in
Austin and at our Grant Thornton offices,
here in Austin, with the CEO and Founder of
the Palmer Group, Shelly Palmer.
Shelly welcome, thank you so much for being
here.
How are you?
Very good.
Really pleased to experience SXSW this year,
with you and your team and with so many others,
it was a great opening dinner
- Thank you.
- That you hosted last night.
What all are you excited to see at SXSW this
year?
What are you looking forward to the most?
- So we're living in a time where experiential
marketing is the goal of every marketer.
People seem now to be willing to pay for experiences
more than they want to pay for things.
There are various ways to think about the
change in the world, access becoming as valuable
as ownership.
So if I have access to something, I don't
need to own it anymore.
And the access I want is access to experiences.
And so all around SXSW some of the world's
best marketers, have put together their demonstrations
of experiential marketing for their individual
industries in the interactive side of the
movie side, brand side.
And to me, seeing the state of the art in
experiential marketing is probably the most
exciting part about SXSW.
- I agree with you.
So we've had the opportunity to tour a few
of these experiences now.
And there's nothing that really hits home
more than being able to see AI in action,
or all of the different technologies and what
they're doing from a life science's perspective,
for greater efficiencies for companies.
Give us a few examples of some of the, I know
we're just starting here, but what are some
of the more exciting things.
- So, 180 degrees away from seeing the technology
one of the most interesting events here is
an event from the HBO group about Game of
Thrones, where they built an immersive Game
of Thrones experience.
Now last year, they did it with Westworld.
This year, they've done it with Game of Thrones,
and these are fans experiencing Game of Thrones,
with very little technology to be fair.
But it's the narrative and the story and the
immersion that seems to drive this great emotional
connection.
And I think now when brands are so reliant
on consumer trust, and in a world where you
don't know exactly what's real and fake and
who you can trust, when you form an emotional
bond with a brand, and that brand lives up
to that promise, and the experience matches
your expectation, like that's checking every
box at this point.
It's better than hey, to for two for a dollar,
or it'll 20% off.
None of that seems to matter anymore as much
as do I trust this brand?
And so on the other side of it, when the pure
technology side, there's so much misconception
about what AI is or isn't, or machine learning,
or neural networks, or add your own phraseology
at this point.
There's so many catch-all phrases and buzzwords
being thrown around as if people know what
they're talking about.
And so everybody's adding, like last year
everybody added blockchain, or cryptocurrency,
or tokens, to their title of their company
and increased its value or created a product
line around blockchain.
This year, unequivocally the buzzword is AI.
So everybody's got an AI experience and you
can put it in quotes or you can underline
it.
Some people are calling it artificial intelligence,
some people are calling it augmented intelligence.
The most important thing you'll see here is
how narrow purpose all of the best tools are.
Face Recognition AI, pattern recognition AI,
speech recognition AI, AI that automates a
given task, but it's really purpose-built
to automate that task, that kind of automation
is going to change the world because not that
it's taking over, what it's doing is making
things more efficient and eliminating drudgery
jobs that used to require cognitive workers,
white collar workers, knowledge workers, and
it's that office pool of 20 people who were
processing paper that was still too hard to
do with data processing in the old days, from
the punch card days, cause anything that could
be automated with punch cards already had
been, anything that can be automated with,
optical character readers could do it.
But now, reading the optical characters and
getting it to be text wasn't understanding
what was on the page.
And now the AI can understand what's on the
page and in a natural language understanding
environment, all of a sudden, it's a game
changer.
So we see this automation being super-threatening
to some but also empowering to others.
And so we're in this time of transition and
as you walk around SXSW and you go to the
various organizations that are showing off
their version of augmented or artificial intelligence,
or incorporating it into their experiences,
you get to realize two things.
One, it's very narrow-purpose.
When it's specialized, it's best, when it's
well-trained and specialized, it's best, and
two, you can really start to feel that that
level of automation is going to have an impact
across every industry.
And while SXSW is mostly a lot of marketers
showing off either their marketing prowess
and their marketing skills, this is not limited
to marketing technology, or advertising technology,
or anything to do with branding, this goes
from supply chain, to auditing, to anything
that happens in the back office to anything
that happens in the front office, we're in
a different place now.
And if you look carefully, and you think a
little bit about what you're seeing, that's
the insight you'll draw.
- [Nichole] Really well said, Shelly.
And I want to expand on that a little bit
further, because as you know, we interact
a lot with management teams and boards around
preparing for the future.
And maybe share with us a couple of the key
takeaways or some of the best practices that
you advise management teams and boards as
they are preparing for the future, and thinking
about all of these new technologies.
- So there are two things that we think are
fundamental principles of digital transformation.
First, is that it is not a waterfall project
that you have been trained since B school
to do, it doesn't have a beginning, middle
and ending, it doesn't have an end vision,
where you're going to know when you're done,
it doesn't start from scratch, and just build
and then there's a milestone and build and
there is a milestone, it is not a waterfall,
it's a lifelong commitment to learning and
continuous improvement.
And if you look at innovation and digital
transformation as an ongoing thing, cultural
thing that has to be part of the DNA and has
there has to be organs in the body that are
dedicated to that
- Business as usual.
- Right, that is just table stakes at this
point, routine innovation, continuous improvement
and it never ends, there's no hey, it's in
this budget year, it's in that quarter, no,
none of that, a project maybe, there may be
and whether you choose to do that waterfall
or agile, that's up to you, and you there's
a lot of management techniques about getting
projects done.
You can say, oh, we need to automate the accounts
payable department.
That's fine.
You may think that has an end, it doesn't.
And the reason it doesn't is because when
you finish it, A, the code will need to be
updated, because it will now be partially
obsolete, more importantly, there'll be so
many advances in automation and artificial
intelligence that's trained to do that, including,
by the way, the system you built, that's specially
trained for your corporation, that it's going
to need to be continuously worked on.
And so those teams are never going to be done.
That's a giant leap of managerial faith, right?
And it's also a little strange to say to the
shareholders, I need an unlimited budget for
an unlimited period of time.
In other words, the future we know is going
to change and we need to be ready to adapt
every single day.
So that's the first principle that we kind
of lay out there.
And the second one, is that never do anything
by computer, you can do easier, cheaper and
faster by hand, the exact opposite.
If your guys are doing it in Excel, and the
lady sitting at that desk is the greatest
Excel lady in the world, and she's banging
this stuff out all day long, and you're getting
what you need out of it, when you hire a team
to turn that into a database and an interface,
you better have an amazing reason, an amazing
reason why automating that, or changing the
way it's done is better than Excel.
And I see this like just cause you can doesn't
mean you should, problem happens everywhere.
People are like “We'll automate that, we'll
automate that, we'll automate that.”
It's like, whoa – hold on a second.
- Why?
- That's working fine.
It costs right amount of money, someone with
20 years domain expertise is on top of this.
You're going to automate it for what?
And when you're done, exactly how much better
will it, like incrementally better will it
be?
If you're only talking about marginal utility
increases that you have to measure like with
a microscope, what are you doing?
And so part of our job as advisors in digital
transformation, strategy, design and engineering
is this tell our clients when we don't think
they should hire us or anybody else to do
something.
It's like nah, that's awesome, leave it.
We've analyzed it for you and it's pretty
cool.
These are the things you could change.
Because when you make the commitment to change,
it's not okay, I need a budget for this quarter
and next quarter, and then we'll be done.
That's not a transformation, that's a project.
And it may be called a transformation project
but you're kidding yourselves, you're making
a mistake.
And you assume so much technical debt, that
at the end of it, it looks like a really bad
decision.
And we don't like our clients to make bad
decisions, especially financial ones, where
shareholders will be sad about it.
- Mm-hmm.
Well, you've given us a lot to think about
with that, Shelly, and certainly I know, that's
what our clients are looking for today, just
that honest assessment.
And, really, I think we've seen this movement
away from folks thinking it really requires
million dollar projects to get up and running
in AI or ML, or whatever the case may be,
really start small, and look at the return,
look at the impact that it'll make.
- Absolutely.
And look, I don't have a CEO in any of our
client companies that doesn't owe their shareholders
the greatest amount of shareholder value and
enterprise value possible.
And in most cases, that's governed by EBITDA.
And so there's only two ways to make money,
you can raise the price or you can lower your
costs, but one way or the other, you’ve
got to do something along those lines.
Well, the automation that's possible now,
certainly feels like a lot of cost-cutting
is about to happen.
And my only moral dilemma with this, and it's
a pretty substantial one, is that for every
job you eliminate, someone needs to be retrained,
repurposed and given a job that they excel
at, gives them personal satisfaction and dignity.
And that transition, I think, is the responsibility
of every corporation who's about to eliminate
40 jobs in accounts payable with an automation
tool, it's like great, these people are fabulous.
They have car payments to make, they got mortgages
to pay, they got kids in school, they have
groceries to buy, they're people that helped
you build your company into where you are,
how are you going to empower them for a future
where their time is freed up to do other more
important things with the knowledge and the
experience that they've acquired, making your
company valuable?
And that's the sort of ethical side of the
Palmer Group and it's what we hope that our
transformation clients take to heart because
these are human beings, machines are machines
and humans are humans and being a father and
a grandfather, human beings come first.
- [Nichole] Absolutely.
And just to build on that a little bit, we've
discussed quite a bit at recent conferences,
and in a number of discussions, this movement
towards, or this principle of every company
becoming a technology company.
- Oh, yeah.
- And, tell us what you think about that.
- You know, it's really hard to tell somebody
who's in the beauty business, or the fashion
business, or a bowling ball business, that
they are a tech company.
And especially now, because, and you'll see
it at SXSW everywhere, companies are offering
software as a service, or business as a service,
computers as like, anything that you can put
into a self-serve model is being put into
a self-serve model, including, of course,
cloud storage.
Every big company, Amazon, IBM, Microsoft,
Google, are all selling cloud storage and
cloud computing and Cloud Machine Learning.
So it's pretty easy for you to imagine a world
where your business is you, a laptop, and
a Starbucks card and a lot of cloud-based
tools.
It's very easy to imagine.
It's also easy to imagine how much savings
there is in using those tools because you
don't have to have the people, the knowledge,
or the expertise.
The question you’ve got to ask yourself
is, what are your core competencies, truly
core competencies, and what is the differentiating
qualities of the business, mission, vision
values, content pillars, that the most fundamental
things about your company, that would be better
served if you had a tech team that was dedicated
to it 24 hours a day, trying to put it or
keep it in a certain place?
And a lot of companies don't make that leap.
They outsource a lot of stuff and they bring
in vendors to help and they do all the things
we see in big business, because it's easier
than trying to get a team and do something.
And I understand as well as anyone, when you
a big corporation and you buy a company you
know you can't build it, so you acquire it.
And then you say you're going to leave it
alone but now you're trying to bring it inside.
And then of course it gets destroyed.
And the corporate culture crushes the souls
of the people who run the little company you
acquired, and the entrepreneurial spirit is
just beaten out of them.
We see that happen all the time.
But it doesn't mean it's the wrong idea, it's
just the wrong execution.
There's no version of the world where there's
less data tomorrow than there is today, I
love to say the velocity of data is increasing
or will always increase.
So if you know that as a CEO, if you know
that as a CMO or a CFO, if you know that tomorrow
we're going to be swimming in data, and the
data is going to come from all kinds of places,
passive and active, you know it's just going
to be from sensors, it's going to be from
the first party data from cash registers from
credit card, or whatever it's going to be
from, how are you going to turn that into
action, and who are you going to let turn
that into action?
And how will you create value by turning that
into action?
Data into action to create value.
And that by itself, because the world is filled
with data, you are a tech company, full stop,
because your job isn't doing what you do,
it's turning the data that's generated by
what you do, into action that makes that transaction
better, faster and more profitable, takes
costs out of the city system, enables you
to raise the price, increase the quality,
you can go on and on and on for every single
business metric that you would lay against
that, there's a data turned into action tool
that gives your competitor a competitive advantage.
So you either let that happen to you, or you
adopt a continuous innovation strategy, you
dedicate your company to digital transformation
and you understand in your heart of hearts,
that Jeff Bezos started as a book seller and
realized pretty soon he needed some technology.
So what do they do, they built the tech they
needed, and then they figured out, hey, AWS,
maybe we could sell that to people, we like
this, this works.
And it's a $12 billion-a-year of cloud storage
that, wow, from a tool they needed to sell
books.
So you can go down the list of things that
Amazon created, because they needed it, and
then started to sell it, you could find those
examples in a lot of companies.
And I'm not suggesting that companies change
their businesses, and there may not even be
enough engineers in the world to hire to get
this done.
That doesn't mean you shouldn't have a vision,
that's clear about where the company is, and
where the company would need to be in order
to be a vicious competitor and the survivor,
because it was able to adapt to the future.
So that's the kind of vision we try to put
forward.
That's the way I look at companies being tech
companies.
And so far, I'm not getting a lot of pushback
from our clients.
The problem is that a lot of this takes investment.
And the investment is going to impact, if
it's cash, is going to impact EBITDA, and
you have to make certain numbers to make the
street happy.
And you've got to have good quarter, every
quarter.
And when you don't, then you're not the CEO
anymore, and you can't do the digital transformation.
So there's this interesting balance and dance
between ROI and investment in technology and
in the future that has to be respected.
And it's the hardest part.
And it's why we have a job to be fair I mean,
it's the hardest part but that's why we have
a job.
- It is and thank you for those insights Shelly.
And I think just speaking about the investments
that we all need to be making, and how to
generate the money to make those investments,
as you know, I spend a lot of time in the
growth strategy and in growth, and I have
been really pleased with the ability of these
technologies to help us bring more value to
customers to clients to help us grow, but
mainly to understand their interests, and
create an even better experience, a more relevant
experience for every individual client, as
a person, let alone their company, and I think
technology is dramatically changing that,
which the more value we bring to our clients,
the more we can grow our firm and make these
investments in creating a better future.
I'm just curious if we think about growth
in particular, what are some of the technologies
that have your attention the most as it relates
to maybe AI impacting sales?
I mentioned this at your dinner last night,
which was a great discussion with many leaders,
but maybe AI in sales or machine learning
in growth, what are you seeing out there?
- So growth seems to be the goal of every
P&L owner.
And it's either defined as revenue growth,
or user growth, right?
I mean, some companies have no revenues whatsoever,
they're just growing by the amount of users
and amount of customers that are experiencing
the brand or part of the organization.
The way we look at AI and growth is actually
backwards from the way that you'll read about
it.
Technology is meaningless unless it changes
the way you behave.
And so I'm not building, it's not if you build
it, they will come unless you have a vision
for what it is you're going to build.
So when I think about growth, the first thing
I ask our clients to do, and the first thing
we do with our clients is we train them, the
executive leadership teams, through a series
of workshops and exercises, how to ask data-driven
questions, as opposed to questions.
I need to grow my business.
Well, yeah, I need to grow my business too,
that's not a data-driven, how do I do that,
that's not a data-driven question.
There may be data components to it, but that's
not.
What's the last day I can sell a full-price
barbecue grill in the Home Depot on Route
7 in Danbury, Connecticut before I have to
try and ship it or market down?
Figure that out about that barbecue grill,
and there's 20,000 SKUs you can figure it
out about and all of a sudden you found 25,
30 points a margin you wouldn't have had on
inventory that was going to happen to be somehow
written down.
Wow, that's a data-driven question; that is
a growth driver.
And so if you can have your executives asking
data-driven questions, then you can answer
the question, well, then what data sets do
I have and which ones do I need?
And then when I have them all in one place,
what kind of calculations would have to be
done in order to find the insights I need
to drive growth?
And is that better done with a spreadsheet,
with heuristics, with statistical machine
learning, with AI, with an abacus, with a
carrier pigeon, with a magic carpet, smoke
signals, it doesn't matter.
The tool can't drive the question, the question
needs to drive the tool.
And if you don't know how to ask a data-driven
question in a data-driven world, you can't
grow your company.
And it's so sexy to say yeah, I got this whole
AI going, it's like yeah, why?
Because like what's the purpose of that?
I have a very specific business question I
need answered, I have a very specific business
problem that if I solved, for example, if
a customer walks in the store to buy makeup,
and I know precisely and exactly what her
color story is, and I know her historical
color stories, and the system itself goes,
you know, based on this year's colors, this
will be the perfect array of makeup and treatment
for this customer.
Now that's done everything.
Now you can have a relatively low-wage, well-experienced
human being who knows how to apply makeup,
not have to sit there and like ask 400 questions
of users, you've been to the store 100 times,
you change the experience, you get a different
product mix, you're going to sell more, because
they're going to buy more cause it's so perfectly
matched to them.
And so yeah, what data sets do you need to
make that happen, what permission do you have
to make that happen, and then all after we're
done with all of those questions, and there's
like pages of those questions, what tool set
will I used to bang out the answer?
You know what, leave that to us that's you
can buy that, what you can't buy is what you
know about this color of lipstick and this
color rouge, and this color eyeliner and the
way the fashion patterns and textiles are
going to be in ready-to-wear this year.
And you can expand that to any business.
It could be the automotive business, what
car are you going to buy?
You've been here three years ago to lease
a car, what are you likely to want and what
can we do to incentivize you to come and experience
our brand or our product?
That will be empowered by AI, but that's actually
a misstatement of what's the empowerment.
The empowerment is I'm turning data into action
by asking the right questions of the data,
and then I built a tool to help me deal with
it.
And the best way to think about it, I've said
this a million times, I gave you a 10 by 10
matrix of spreadsheet of just the 10 rows,
10 columns, hey, Nichole, here's 10 rows and
columns about this particular thing.
You're an expert in it, you're going to look
at it for about five minutes and go, yep,
this is this, this is this, you're just going
to know what it is.
But if that spreadsheet was 25,000 columns
by 250 million rows, nobody human can look
at it, a machine needs to look at it.
What the machine is going to do with that
data comes from the insights off of that 10
by 10 matrix.
And if it doesn't, the machine does nothing.
It does nothing.
It's not a human, it doesn't think, regardless
of the name artificial intelligence, it does
what its purpose-built to do, it surfaces
patterns, and it makes inferences based on
correlation, not causality, right?
When these three things happen, that thing
happens.
Well, I don't know the narrative of why, I'm
human, I want to know why, well, these things
happens, this happens, why, why?
I want that narrative because people want
a story.
The computer doesn't want a story, it's a
computer.
It knows that when these three things happen,
that happens.
Well, if that makes you money, you want to
make these three things happen as often as
humanly possible.
Do you use AI for that?
You could, you might be able to use your risk
takers for it.
You might be able to use simple math in a
simple, very inexpensive computer that's in
somebody's handheld.
Who cares what the tech is?
Leave that to the technologists, ask the right
questions, you'll get the right answers.
- Great, great insights.
So asking the right questions.
And so in thinking about 2019, and a look
ahead, and it's been a great year so far,
we've spent time at CES, we're now here at
SXSW together and you are the CES whisperer.
- Yeah
- I'm sure that, are you the SXSW whisperer
as well?
I'm sure you are.
- Well, I don't know if I would live up to
that, but I do love this show and I do love
this event.
It's really not a show, it's really an experience.
- Of course, sure.
- SXSW it's a force of nature.
They've done such a wonderful job building
this into a really wonderful festival with
a lot of great things to see and do.
- Great takeaways.
And what I was curious, in your view on 2019,
and a look ahead, I can see all the things
you've already done in 2019.
Well, but as you look ahead, what are some
of the things that have you most excited for
the rest of the year?
- So I'm really concentrating on two things
right now.
One is 5G, and what that's going to mean to
society writ large, how it's going to be deployed.
It looks like it's going to be industrially
deployed first.
So what does a 5G hospital room look like?
What does a 5G factory floor look like?
How are robotics impacted by it?
The media industry could be completely transformed
in a disruptive, radically disruptive way.
Right now, the cable companies put a cable
in your house and you attach your TV to the
cable and they sell you a video or they sell
you internet access.
In a 5G world, the TV manufacturer puts a
5G radio and a TV set, you put the TV set
anywhere and you don't need a cable company,
you just the content subscriptions.
That's a really radical change in business
model and technology.
And so 5G, and it goes to every industry,
there's a technology called CV2X, which is
Cellular Vehicle to Everything, V for Vehicle,
the number two, and X for everything.
So CV2X is is a Cellular Version of Vehicle
to Everything.
But that means it'll talk to smartphones,
it'll talk to other cars.
So think about this, cars are talking to other
cars, cars are talking to your smartphones,
cars are talking to streetlights, cars are
talking to buildings, cars are talking to
parking lots, cars are talking to each other
and things.
So the amount of data that's going to float
around in that particular world is pretty
insane.
Who owns it, and other insane question, but
at the end of the day, when you start thinking
about all of the stuff that 5G empowers this
low latency, high bandwidth, intense network,
the collective mind of humans is amazing.
The collective mind of things, we have no
idea what that's going to be.
So that has really has my attention.
And I'm spending a lot of time now trying
to sort out when you can use commoditized
artificial intelligence and when you need
to train your own.
So if I need to recognize faces, there a face
recognition databases that are purpose-built
for that.
Facebook has one, they don't rent it out,
but Facebook, Google has one, pardon me.
Somebody could in practice, build a face recognition
tool set that we recognize all the faces there
are and it's purpose-built or natural language
understanding, or natural language processing,
or automatic speech recognition.
If you need automatic speech recognition,
you're not going to build it yourself now,
you going to rent it from Amazon.
No matter what it costs, it is cheaper than
you building it, it's better than you could
build.
So those things are commoditized immediately.
But what is the AI co-worker, what is the
human-machine partner that you need to build
to empower your staff?
Because if the human does what the human does,
and the machine does what the machine does,
and you put it together, then really good
things can happen.
As I said, the machine can look at 25,000
columns by what, 200 million rows, you can't,
but you certainly can tell it how to look
at it.
So the better human-machine partnerships that
form, those training sets will have to be
custom-built, because they have to do with
a company, its own acronyms, its own workflows,
its own supply chain, its own accounting practices.
And so those things, like that human-machine
partnership, what can be commoditized and
what needs to be built and trained fascinates
me a lot.
And then the last thing we spend time thinking
about is in general, from a technology point
of view, where the line is drawn between build
or buy, pure build or buy, which was always
been a really academic exercise, truly academic.
If we build it, it's going to cost X, if we
buy it, it's going to cost Y.
But, now this idea that a cognitive agent
would be an employee of your company makes
you kind of think you want to have unique
employees that live forever, that keep the
institutional memory, that have good understanding
of what's happening.
And so if you had six narrow purpose-built
AIs, one for HR, one for supply chain, one
for MarTech and advertising optimization,
you go down the list, that was really trained
for what you do with the human-machine partnerships
put in place where they belong, I don't know
if you can buy that, you kind of have to build
it.
So I can make an argument for both sides,
but this is like we're laser-focused on how
we make the right business decisions.
There's no such thing as future-proofing,
it can't be done.
But you can set up probable futures and place
some bets in your technology investments that
will give you the most optionality in the
future.
And that's the sort of mental chess game I'm
playing every day, trying to help our clients
navigate an ever-changing world.
- That's terrific.
Excited to stay close to you on this as everything
evolves and Shelly, just appreciate your insights
and appreciate the opportunity to team with
you to help bring more value to our clients
and have enjoyed our partnership.
So thank you and let's go enjoy SXSW.
- Alrighty.
- I'm Nichole Jordan.
To learn how Grant Thornton can partner with
you to strengthen corporate governance, leadership,
diversity and culture, customer focus, and
technology and innovation within your business,
please subscribe to my YouTube channel.
Thanks for watching.
