October 30, 2024 • 28 mins
Matt Calkins is Appian's founder, CEO, and Chairman of the Board. Matt grew Appian from a startup in his basement to the most successful software IPO of 2017 with only $10 million of outside capital. He serves on the board of the Sorensen Institute and sits on the Leadership Council for the Virginia Public Access Project. Matt was the top Economics graduate of his class at Dartmouth. He is the author of several award-winning board games, and is frequently a top finisher at the World Boardgaming Championships.
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Episode Transcript
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Speaker 1 (00:00):
Yeah.
Speaker 2 (00:00):
I grew up in California.
Speaker 1 (00:01):
I went to school in Dartmouth, and I came to
the Washington area for work. That's how I found My
first job was a micro Strategy. I worked there for
about five years before starting appiing when I was twenty six.
Speaker 3 (00:14):
Little culture shock going from California to New Hampshire.
Speaker 1 (00:18):
Yeah, but I was born on the East Coast. Most
of my family was out there, so it wasn't so
shocking to me.
Speaker 3 (00:22):
Well, let's talk about Dartmouth and coming out of school,
because you had that job for five years and then
he started the company that we're going to talk a
lot about today, and that's been twenty five plus years
in the making, which is truly incredible and all the
amazing things that you, the founders and your team do.
But when you were coming out of school and you
had that job, what it exactly did you want to do?
Speaker 1 (00:40):
I loved the idea of getting in the middle of
a cutting edge industry.
Speaker 2 (00:44):
I wanted to be a technologist.
Speaker 1 (00:45):
My degree was in economics, but I wanted to apply
it in business, and I thought the most interesting business
I could be part of would be the software business.
And so I was looking for a software business that
was at a moment of creation, and I found one.
I found an exciting star up called micro Strategy, and
I joined and stayed with it as it grew over
five years.
Speaker 3 (01:05):
So nineteen ninety nine, there was a lot of technology
booming going on. It was really an amazing time. And
this is the fun part of the job when I
get to talk to people like you about the origin,
the epiphany, the idea about starting your own company, and
there's We talked to so many CEOs and entrepreneurs on
this series and they have so many different reasons about
why they wanted to start their company. I'm just going
(01:26):
to guess that you saw a hole in the industry
and you needed to fill it with the idea that
you had that you wanted to do. Can you tell
us about the origin about Appian.
Speaker 2 (01:35):
Yeah, it's really not the case.
Speaker 1 (01:36):
A lot of businesses are started because somebody's got an idea.
Speaker 2 (01:39):
And they source capital to back up the idea.
Speaker 1 (01:42):
We did not have those things, but we started the
business because we felt that it was possible to create
a business that would be a vehicle for making people's
lives better.
Speaker 2 (01:53):
But we didn't know how.
Speaker 1 (01:54):
We didn't have a business plan, and we didn't have funding.
We just had created activity and the intention to build
an institution.
Speaker 3 (02:04):
Well, let's stay with that. So when you came up
with that idea, what did you think was missing that
you could bring customers?
Speaker 2 (02:10):
Well, I think, first of all, we did know a
few things.
Speaker 1 (02:12):
So I had some experience in databases, for example, and
business intelligence. And we also felt confident in our ability
to pioneer a new industry. And so our goal was
too as quickly as possible, get at the forefront of
an emerging industry. That's why we positioned ourselves as analysts
and thought leaders, and we sought our customers as experts
(02:33):
in an emerging field. In this case, it was personalization,
and under that cover we were able to establish the
first set of customers, and that evolved over time for us.
From personalization it became portals, and from portals it became
process and processes Where we landed.
Speaker 3 (02:51):
The name intrigued me, like probably does a lot of
other customers. Where what's the origin of the name of
the company.
Speaker 1 (02:56):
Yeah, well, the name is abstract of course, refers to
the Appian Way, an early highway in the Roman Empire.
Speaker 2 (03:04):
And I liked it. For its abstraction.
Speaker 1 (03:06):
I liked the fact that it was vaguely metaphorical, like
a road could mean a lot of things. That could
mean the way you get to where you need to go,
or a way that you enhance commerce or something like that.
It was even itself a pretty high tech piece of
work at the time, you know, it was macadimized and
it lasted for a thousand years or more.
Speaker 2 (03:24):
It was technological in its day.
Speaker 1 (03:27):
But I like the name mostly for its ambiguity, and
it didn't help it was It didn't hurt to be
early in the alphabet because we ended up at the
top of a lot of lists by choosing a name
that began with a You.
Speaker 3 (03:40):
Know, I love that because I kind of compare that
to maybe a musician writing a song and it's up
to the people that are listening to it to interpret
what the song means. Right.
Speaker 1 (03:50):
Yeah, I think ambiguous was good for an organization that
did not come into being knowing what it meant, what
its business plan was going to be. We knew our values,
we knew what we wanted the organization to achieve, but
we didn't know how.
Speaker 2 (04:03):
And it's a good thing.
Speaker 1 (04:04):
We didn't make the name correspond to the way how
because we were going to change our business plan a
couple of times.
Speaker 3 (04:09):
All right, well, let's dive in with APPING. What's the
mission statement?
Speaker 2 (04:13):
Yeah, well today, all right, I'm going to tell you
about what APPING is. Today. We do processes.
Speaker 1 (04:18):
Processes are like any behavior that an organization executes at scale.
Anything your organization does a million times, that's a process.
And processes are typically unique to different organizations. And so
a process is like the signature of a business. It's
the behavior set. It's the way it touches its customers.
(04:38):
It's the way it onboards new customers, handles their problems.
It's the way it saves money. It's the way it
creates its product. Every of the critical DNA fiber behaviors
that a business does is probably done through a process,
and as such, a process shapes its reputation.
Speaker 2 (04:57):
So they're very important.
Speaker 1 (04:58):
It's important to get it right, to be able to
change it over time, and we are a platform for
automating an organization's processes. We started by allowing them to
just draw a flow chart, and that flow chart would
be automated like a piece of software. But over time
we also filled in the flow chart with digital workers
(05:19):
so that the work could get delegated to a robot.
In some cases that would be robotic process automation or
an RPA bot. In some cases it was just a
business rule for a set of rules, and of course,
in some cases most famously, it's artificial intelligence. So we've
been in the artificial intelligence business for about a decade
as part of the way we execute those processes that
(05:40):
we plan for our clients.
Speaker 3 (05:42):
All Right, I'm going to want to talk to you
about AI and AI regulation because I know that is
a passion project of yours and it's a really big deal.
It's always in the news every day, so I'm dying
to here where you think about everything and where it's
going before we do that. Though, I know there's many
worldwide that know what apping does. But if we were
to give a snapshot to some of our new listers
that aren't familiar with the company, and you give a
thirty thousand foot view about what you exactly do, what
(06:03):
would you tell them?
Speaker 1 (06:04):
Yeah, Appian is the process company. Your organization is made
up of processes, and we're going to help you make
those processes efficient and better, and we're going to run
them with less time and less cost and a higher
success rate than you've been achieving in the past. Your
organization is defined by its processes, and we can help
you optimize them.
Speaker 3 (06:23):
So, preparing for the interview, went on the website. Love it.
It's easy to navigate. But there are a lot of
programs and capabilities, and I know you're probably proud of
all of them and what you offer your customers. But
if you were in an AIRDA, maybe a handful of
them that either you're most proud of or what clients
really want in today's climate. Can you tell everybody about
that and expound a little more on it.
Speaker 1 (06:42):
Yeah, Well, we're conducting this conversation in the Washington, DC area,
which is where Appian's home base is or a worldwide company,
but our base has always been in Northern Virginia in
the DC metro area, and some of the work I
am most proud of over the twenty five years we've
been in business has been right here. For our federal government,
we did the Army Knowledge Online System, which twenty years
(07:02):
ago was called by Wired magazine the largest intranet in
the world. We do wonderful work for the Department Defense
in terms of procurement right now, tens of billions of
dollars annually passed through our procurement systems. We were integral
to getting the Affordable Care Act processing to work.
Speaker 2 (07:19):
You may remember that the website didn't work well.
Speaker 1 (07:21):
The other part of it did work, the part where
you could register by a filled out form. We kept
that running even when the other side was lights out,
and we were able to build that system in just
one month on an emergency basis, And so I'm proud
of how quickly we responded to save that program. So
a lot of the greatest jobs we've done. I mean,
(07:42):
at this point we're around the world. We're about roughly
half of the world's biggest banks, biggest insurers, biggest pharmaceutical companies.
We are, we're in five continents were we're everywhere, But
a lot of the work I'm most proud of happened
right here at our.
Speaker 3 (07:56):
Hometown, Outstanding, Matt. You know, there are so many different
challenges in the industry, and as a layman, as I
read the news between AI and we will talk about
regulation just a second, but you know, I hear cybersecurity
a lot, and that's not only internationally announced domestically With
that said, is it at the forefront? I know each
client is very specific for their needs and what you
(08:18):
do for them, but is that at the forefront usually
when it comes to cybersecurity and everybody trying to protect
themselves in the climate that we're living in today.
Speaker 2 (08:27):
Look, data has never been more valuable than it is today.
Speaker 1 (08:30):
Our organizations will freely admit now data is their greatest asset,
and they're frequently correct. Protecting that information is top priority
for all of our clients. We're not just the process company.
We're specifically at the high end of this industry. We
focus on the big organizations making big bets and defining
themselves through process, and so for them, data is of
(08:51):
the utmost priority. We protect data. We're ahead of the
curve on industry standards and measures that we take to
secure information. That's always been a part of our calling card.
I mean, we started with big jobs like the army
and health and human services twenty odd years ago, and
(09:12):
so we had to care from the beginning about the
sanctity of confidential information. So yeah, that is a big, big,
big deal, and privacy is also a big deal.
Speaker 2 (09:24):
This is a major issue these days.
Speaker 1 (09:26):
It's not whether your data will be stolen, but whether
it will be taken with your own permission or with
some semblance of permission in order to train somebody's AI algorithm.
This is a big issue today. Organizations are afraid to
use AI because they don't trust that AI will be
private enough with their data, and so they don't want
to train an AI algorithm that they don't own and control.
(09:49):
That's a big issue and it's holding back the evolution
of this industry.
Speaker 3 (09:52):
All right, well, let's expound that a little bit, because
I know that when it comes to AI and AI regulation,
this is really something that's very important to you, your team,
your clients, but also something that you're at the forefront with.
And once again, just as a layman, I only know
enough to be dangerous. It's on my phone, now, it's
on my computer. I've used it from time to times.
But that for me when it comes to somebody like you,
(10:13):
the industry, and just overall, let's just give it kind
of a thirty thousand foot view about where you are
with AI and regulation and then we can start diving
into that.
Speaker 1 (10:23):
Yeah, let me first of all say what a priority
I believe privacy is in the evolution and the usage
of AI. I think the industry's progress depends on privacy.
And I take this first of all, on the authority
of my customers. I speak with the CIOs that I
work with, and they are all very concerned about protecting
their data. They don't want to share it around and
(10:45):
they don't want to train algorithms on it. And so
we need to reassure them that their data is safe
in AI, and that means creating an AI architecture that
protects their information. And so it's going to be important
just for us to connect with those business users to
reassure them in some better way than we've done so far.
(11:05):
And we've come up with such a way right Appian
has a specific we call it private AI. We have
a specific angle on this business whereby we do not
train an algorithm. We instead take your question that you
want to ask of AI, and we source just the
right information from across your enterprise and send the question
(11:27):
with the data. And that's all that the AI gets
to look at is just that slice of your data.
But it's enough we send the right data, and therefore
AI comes back with an answer that's comparable to what
it would have given if you had first given it
everything you knew, and so it's a low data and
(11:47):
a low trust way of using AI, which suits the
concerns of the modern customer. So that's one way that
we can make progress in AI. It's called request augmented
generation and it depends on a really great virtual database
and we have that.
Speaker 2 (12:02):
We call it a data fabric.
Speaker 1 (12:03):
But because we have that, we can offer this no
training generative AI.
Speaker 2 (12:08):
And it's successful. So that can work.
Speaker 1 (12:10):
However, more broadly, if we were just step back and
say what does privacy mean for this entire industry. I
think privacy is the hinge on which this whole industry turns.
The future of AI is so much better than the present.
We're going to look back on today and say, this
is when they didn't get it. This is when AI
didn't have any value. It's just a parlor trick. AI
is amazing, but it's not productive. It'll be productive when
(12:35):
it understands us, which is to say, when it understands
the person or the entity that's asking the question. AI
can't tell me where to go on a Friday night
because it doesn't know what I like. AI can't write
an email in my voice because it doesn't know my voice.
Until AI knows me, it's not going to be as
useful as it would be if it did.
Speaker 2 (12:58):
The reason it doesn't know me though, because I don't trusted.
Speaker 1 (13:01):
I don't want to train an AI algorithm on all
my emails that I've written, and I don't want to
explain everything that I like, and therefore my lack of
trust is holding back this industry. It's true across the world.
We need to get over that by showing that AI
can be trustworthy. And that's why I encourage this industry
to adopt guidelines that prove it's trustworthy, to be more transparent,
(13:25):
and to make a conscious effort to stop blurring the
lines between what it owns and what it doesn't. I
think the average person understood how much they have personally
trained AI.
Speaker 2 (13:35):
They would be upset, Matt.
Speaker 3 (13:37):
I know that worldwide social media companies, companies in general
are using AI and moving forward with it, but let's
just stay maybe in your industry, if we could domestically
and internationally when it comes to your peers and your
contemporaries and what you do, is everybody on the same
page or are you fighting a battle on your own
right now where are you with everything in your contemporaries.
Speaker 2 (13:57):
We are very different from our competitors.
Speaker 1 (14:00):
Compete against some of the largest tech firms in the
world like Microsoft Salesforce Service Now, and for the most part,
our competitors see AI as a way to get hold
of data. They want to use AI as a way
to control their customer's data. That could be by moving
all the data into their format, into their database into
one consolidated heap that then they have privileged access to.
(14:23):
Or it could be by literally sending the data over
to our competitor, so our competitor can train on that
information and use it to whatever extent the fine print
allows them to in their agreement with their customer.
Speaker 2 (14:36):
We are not doing that.
Speaker 1 (14:38):
We are not using AI as a trojan horse to
get our hooks into any data at all. Instead, we
respect the enterprise of the way we found it. We
use a virtual database to connect things that are not
co located. We don't ask our customers to change their
data's format or location, or to train an AI algorithm
whether we control it or not. Our point is to
(14:59):
empower our customers to get value out of AI without
compromising their data one wit. So we take a very
different approach to this industry than our competitors do.
Speaker 3 (15:10):
I don't want to assume with any advocation on your
part of somebody from your team, but is this something
that you're going to be discussing a Capitol hill or
somebody from your team and talking about this, because obviously
you're very passionate about it, you feel very strongly about it.
But there is a big world machine out there that
does exactly what you're saying that you don't want it
to do, which is grab everybody's information. So what about advocating.
Speaker 2 (15:31):
Yeah, you're completely right about that.
Speaker 1 (15:33):
There's a lot of energy advocating for the lack of
data rights because the leading AI vendors are gaining tremendously
by ambiguous or missing data rights guidelines. We take the
opposite approach, and I personally, as a privacy advocate, take
the opposite approach. And so I've written a set of principles,
published them, and I'm building support amongst the press, fellow
(15:58):
CEOs and cons us for these principles, which speak up
for the owners of data and the sanctity of data.
Speaker 3 (16:07):
All right, well, listen, I want to talk a little
bit about the future because AI is also the future,
and that's part of the component of your company and
where we're all going. But with that said, I know
that you and your team are we sinking down the
line too, and technology is moving very quickly. As you
see your company and the industry moving ahead the next
five to ten years, where is the industry going?
Speaker 1 (16:25):
The AI industry is reaching a fork in the road.
If we can win people's trust and confidence, then AI
is going to become personalized, and when it does, it's
going to become far more valuable, far more valuable than
it is today. Personalized AI is going to be revolutionary.
(16:45):
Generic AI, what we have today is merely intriguing. So
we need to make this turn, and making that turn
depends on trust, and trust is the most important commodity.
Speaker 2 (16:56):
In the past the last year or.
Speaker 1 (16:58):
Two in AI, it has appeared that the most important
commodity is raw data, and the leading vendors should just
take it wherever they can, no matter the costs, no
matter the dubious legality, just take it. But the paradigm
is shifting here to reach AI two point zero, the
personalized AI, that's the real future of this industry. We
need trust more than we need data. Trust is the
(17:20):
only way to get the data you truly need, And
so we're approaching acrossroads and the priorities will have to shift.
Speaker 3 (17:28):
Are there other people in your camp that feel the
same with you?
Speaker 1 (17:30):
You do? Yeah, there are there are others. First of all,
every customer I mentioned to this mention this too.
Speaker 2 (17:38):
They agree with me, and.
Speaker 1 (17:39):
So definitely the consumer base for AI agrees with me.
But does big AI? Does big tech agree with me?
Speaker 2 (17:47):
They don't.
Speaker 1 (17:48):
Their strategy is what I would call run until tackled.
They're just going to take as much data that they
maybe have a right to as long as they can
and use it to the fullest ext that they can
until someone stops them. And that strategy has been working
for him so far because data has been the most
important input to AI.
Speaker 2 (18:08):
It's about to not be, so they need to change
their game. But for now, until someone stops them, that's
their game.
Speaker 3 (18:14):
We talked about some challenges, but I also love to
talk about some of the positive, cool things that are
wrapping on there. And you really are doing so many
innovative things with your clients. I know that there's a
lot of reasons why you and your team get up
every day because you're servicing your clients, You're making them happy,
You're making America and the world safe for a lot
of people out there, especially when it comes to technology, privacy, data,
and everything else out there. Is there something in the
(18:35):
industry right now that with your and you don't have
to name the client, Matt, but you're most proud of
that you're making a difference to you and your team
right now that you know is really special.
Speaker 2 (18:46):
Yeah. Absolutely, I love this technology.
Speaker 1 (18:48):
And one of the reasons I've been able to stay
with this for twenty five years is I believe that
it serves a larger purpose in the world than just
moving money from one account to another. I think that
we're empowering people to extend their capabilities through digital assistance,
and we are allowing organizations to have and reinforce the
(19:11):
personality they want to have.
Speaker 2 (19:14):
Organizations for the last couple decades.
Speaker 1 (19:18):
Have all felt that they needed to trade their personality
away in favor of the most efficient, cost efficient set
of behaviors. And so every corporation seems alike, or almost
all of them seem alike to us right now.
Speaker 2 (19:31):
They all use.
Speaker 1 (19:34):
Generic phone lines and generic emails, and they all appear
to us as robotic, impersonal and indistinguishable. Our processes allow
an organization to create its own personality and live up
to that, and that raises the standard of living for
(19:55):
all of us because none of us wanted to deal
with robotic, indifferentiable vendors. We wanted them to be able
to live up to their brand promise and their expected identity,
and with this technology they can. And then secondly, we're
about the interface between people and machines. When you draw
a flow chart and it turns into software right on
(20:17):
our platform, that's fundamentally what we do. You are extending
your reach and commanding a computer to follow your instructions.
It's like a simple form of programming, but a very
powerful form. It's very human, it's very intuitive, and it
allows people to interface, collaborate, and direct machines better. And
(20:41):
so I'm proud of the effect that we're having both
on people who become stronger and on organizations who can
finally assume their attended personality.
Speaker 3 (20:50):
Man if I could do this, indulge me just for
a moment. I always love to talk to leaders, especially
with your company. I mean, you are worldwide, so there's
a lot of people on your team. Obviously you are passionate,
you have a vision, but you want a company you
run a certain way. But also we talk about the
work life balances for people, and some people have very
high security clearance and some don't, and some are living
(21:10):
all over the world and some right here in the DMV. Well,
that said, with so many people that are on your
team and handing down the message about how you would
like the company to be run, but making sure that
everybody's a happy employee, have that work life balance, but
also get the job done, how do you do that
leadership wise?
Speaker 1 (21:28):
All right, Well, that's a challenge, and it becomes a
greater challenge with scale, It becomes a greater challenge with distance,
and we have offices all around the world. We are
furthermore a values driven organization, which is to say, we're
more dependent than most companies on having a set of
values and having them broadly adopted.
Speaker 2 (21:47):
They shape the way we work and the way we are.
Speaker 1 (21:49):
Different from other firms, and so it's more essential for
APPY and to be able to convey its values across
oceans and across a larger team that it is their companies.
We've never tried to be like other firms, and I
don't want to be like them now. And so first,
it's a great deal of communication. I'm constantly writing things
(22:11):
and saying things about what we stand for and how
we work, and so it's a constant expression of values
back to the team. You have to enforce values when
you hire and when you promote, so consciousness about what
your values are and bringing them to bear on those
moments of truth is very important. I think it's important
(22:31):
to have as many people come together as possible. I
believe that when people are together, they exchange information about values,
they confirm values, and they understand the differences in the
organization better. So I'm a proponent of working in the
same place to the degree that we can, and I
think Appian is a magnet for people who feel that
(22:54):
way and are interested in the kind of personal development,
career development, and highly charged collaboration that are possible when
we get together in the same location. So we're always innovating,
we're always growing, and we need to keep finding ways
to stabilize and enhance our values at scale in a distance.
Speaker 3 (23:15):
I appreciate all your thoughts on that. Thank you so much.
I've really enjoyed the conversation. I do want to wrap
up with some final thoughts from you, and we've talked
about a lot in the short time we've had a
chance to get to know each other, Matt, but just
maybe some recapping, some final thoughts. The floor is here, sir.
Speaker 1 (23:31):
Ah Well, I never thought i'd be with the same
organization for a quarter century. We've grown over that time,
and it feels different, and I think it's the difference
and the impactfulness of what we're doing that keeps me here.
I'm also very proud of the fact that all four
founders of this organization are still here in an executive
(23:53):
capacity twenty five years after we founded it. That says
something about loyalty and decency and mutual respect, and I
can't think of any companies that have achieved that. And
so while I'm surprised that we've been able to maintain
this growing organization for a quarter of a century, when
(24:14):
I look back on it, every year made sense, and
it makes more sense now than ever because the stakes
are higher than ever. I feel like we can have
a greater impact to help people than we've ever been
able to before. And if our culture is harder to
establish across a global organization. Then at the same time,
it is more impactful because there's more people to influence,
(24:35):
and therefore they can have a greater impact, and our
culture can go farther if I can.
Speaker 2 (24:39):
Establish it in all those people.
Speaker 1 (24:40):
So, because the game keeps changing, because the stakes keep
going up, and because I get to work with good
people that I'm fortunate to have worked with all this time,
I'm still at it twenty five years later.
Speaker 3 (24:53):
It's a truly amazing story. If you do me a
favorite because I'm a sports guy. I've been in my
industry for thirty years, and when I was reading up
about you, you really used a very cool sports analogy
about pulling a goalie. And we have a lot of
future entrepreneurs that listen to the series, and it obviously
spoke to me, but I think it would speak to
a lot of people because sports crosses over to business
(25:13):
just about every day as far as I'm concerned. Can
you share that analogy because I thought it was fantastic.
Speaker 1 (25:18):
Oh yeah, you're referring to some research I did, yeah
long ago, when I was in school, about when a
hockey team should remove its goalie the hockey team is
losing toward the end of the game, and it has
to make a decision about when to take its goalie
out of the game and add another player who could
conceivably score a goal, who could be part of a
powerplay style situation.
Speaker 2 (25:40):
Knowing that when they do that, they increase the.
Speaker 1 (25:43):
Chances that a goal will be scored against them by
more than they increase the chances that they will.
Speaker 2 (25:47):
Score a goal.
Speaker 1 (25:48):
So it is a move you would only make if
you needed to change the game dramatically and you were
going to lose if you didn't change it.
Speaker 2 (25:58):
But the question is when when you pull that goalie. Now.
Speaker 1 (26:02):
Back at the time that I did the research, which
was the early nineties, I felt that the hockey statistics
world was not very well developed and that goalies were
rarely pulled outside of the final minute maybe two at
the most of a game. And I found that that
was probably a mistake. That a team should pull its
(26:24):
goalie a bit earlier, and in a truly important game.
A team should pull its goalie even when it's losing
by two goals, which is almost never done. Even if
it's losing by two goals and relatively earlier, then it
would pull the goalie if it was losing by one goal.
So if you're losing by one, you should have your
goalie out two minutes or before the end of the game.
(26:46):
But if you're losing by two, you should pull your
goalie by maybe four minutes out from the end of
the game. If it's a truly important game and you
don't care about being embarrassed losing by three or something,
you should pull your goalie an additional minute or two
beyond that in order to have a longer period of
high variance. Even if the mean next and the expected
value goes against you, the higher variance makes it more
(27:09):
likely that you're going to win a game you otherwise
would have lost.
Speaker 3 (27:12):
So I know there's a lot of data in there,
but I also thought there was a life lesson in
there too about actually just getting ahead of things. And
because I'm a sports guy, made a lot of sense.
I'm a big hockey guy too, So I love your
analogy that you put together, Matt, and I think there's
always life lessons from sports that we can apply to business. Well,
let's do this. Let's wrap up by giving the website
to everybody. I know that you're always looking for the best,
and the best there is a careers tab there. But
(27:33):
there's so much information on this wonderful website of Appy
and if you can give the website to all our
listeners Matt appian dot com, that easy listen. It is
a treat to get to know you continue success. It
really is in the making twenty five years of you,
your founders and all the amazing things that you're doing.
And Matt, the one thing that I took away beside
the amazing things that you offer, and also how you
(27:55):
feel about AI regulation when I talk in this series,
no matter what people do and what company, they have
a passion for what they do. And I can tell
that you have that. And I'm always very appreciative of
people that are passionate about what they do and that
gives them an extra head start and everything. So thank
you for your time and thank you so much for
joining us on CEOs.
Speaker 2 (28:11):
You should know, thanks so much. Dennis
Yeah.
Speaker 2 (00:00):
I grew up in California.
Speaker 1 (00:01):
I went to school in Dartmouth, and I came to
the Washington area for work. That's how I found My
first job was a micro Strategy. I worked there for
about five years before starting appiing when I was twenty six.
Speaker 3 (00:14):
Little culture shock going from California to New Hampshire.
Speaker 1 (00:18):
Yeah, but I was born on the East Coast. Most
of my family was out there, so it wasn't so
shocking to me.
Speaker 3 (00:22):
Well, let's talk about Dartmouth and coming out of school,
because you had that job for five years and then
he started the company that we're going to talk a
lot about today, and that's been twenty five plus years
in the making, which is truly incredible and all the
amazing things that you, the founders and your team do.
But when you were coming out of school and you
had that job, what it exactly did you want to do?
Speaker 1 (00:40):
I loved the idea of getting in the middle of
a cutting edge industry.
Speaker 2 (00:44):
I wanted to be a technologist.
Speaker 1 (00:45):
My degree was in economics, but I wanted to apply
it in business, and I thought the most interesting business
I could be part of would be the software business.
And so I was looking for a software business that
was at a moment of creation, and I found one.
I found an exciting star up called micro Strategy, and
I joined and stayed with it as it grew over
five years.
Speaker 3 (01:05):
So nineteen ninety nine, there was a lot of technology
booming going on. It was really an amazing time. And
this is the fun part of the job when I
get to talk to people like you about the origin,
the epiphany, the idea about starting your own company, and
there's We talked to so many CEOs and entrepreneurs on
this series and they have so many different reasons about
why they wanted to start their company. I'm just going
(01:26):
to guess that you saw a hole in the industry
and you needed to fill it with the idea that
you had that you wanted to do. Can you tell
us about the origin about Appian.
Speaker 2 (01:35):
Yeah, it's really not the case.
Speaker 1 (01:36):
A lot of businesses are started because somebody's got an idea.
Speaker 2 (01:39):
And they source capital to back up the idea.
Speaker 1 (01:42):
We did not have those things, but we started the
business because we felt that it was possible to create
a business that would be a vehicle for making people's
lives better.
Speaker 2 (01:53):
But we didn't know how.
Speaker 1 (01:54):
We didn't have a business plan, and we didn't have funding.
We just had created activity and the intention to build
an institution.
Speaker 3 (02:04):
Well, let's stay with that. So when you came up
with that idea, what did you think was missing that
you could bring customers?
Speaker 2 (02:10):
Well, I think, first of all, we did know a
few things.
Speaker 1 (02:12):
So I had some experience in databases, for example, and
business intelligence. And we also felt confident in our ability
to pioneer a new industry. And so our goal was
too as quickly as possible, get at the forefront of
an emerging industry. That's why we positioned ourselves as analysts
and thought leaders, and we sought our customers as experts
(02:33):
in an emerging field. In this case, it was personalization,
and under that cover we were able to establish the
first set of customers, and that evolved over time for us.
From personalization it became portals, and from portals it became
process and processes Where we landed.
Speaker 3 (02:51):
The name intrigued me, like probably does a lot of
other customers. Where what's the origin of the name of
the company.
Speaker 1 (02:56):
Yeah, well, the name is abstract of course, refers to
the Appian Way, an early highway in the Roman Empire.
Speaker 2 (03:04):
And I liked it. For its abstraction.
Speaker 1 (03:06):
I liked the fact that it was vaguely metaphorical, like
a road could mean a lot of things. That could
mean the way you get to where you need to go,
or a way that you enhance commerce or something like that.
It was even itself a pretty high tech piece of
work at the time, you know, it was macadimized and
it lasted for a thousand years or more.
Speaker 2 (03:24):
It was technological in its day.
Speaker 1 (03:27):
But I like the name mostly for its ambiguity, and
it didn't help it was It didn't hurt to be
early in the alphabet because we ended up at the
top of a lot of lists by choosing a name
that began with a You.
Speaker 3 (03:40):
Know, I love that because I kind of compare that
to maybe a musician writing a song and it's up
to the people that are listening to it to interpret
what the song means. Right.
Speaker 1 (03:50):
Yeah, I think ambiguous was good for an organization that
did not come into being knowing what it meant, what
its business plan was going to be. We knew our values,
we knew what we wanted the organization to achieve, but
we didn't know how.
Speaker 2 (04:03):
And it's a good thing.
Speaker 1 (04:04):
We didn't make the name correspond to the way how
because we were going to change our business plan a
couple of times.
Speaker 3 (04:09):
All right, well, let's dive in with APPING. What's the
mission statement?
Speaker 2 (04:13):
Yeah, well today, all right, I'm going to tell you
about what APPING is. Today. We do processes.
Speaker 1 (04:18):
Processes are like any behavior that an organization executes at scale.
Anything your organization does a million times, that's a process.
And processes are typically unique to different organizations. And so
a process is like the signature of a business. It's
the behavior set. It's the way it touches its customers.
(04:38):
It's the way it onboards new customers, handles their problems.
It's the way it saves money. It's the way it
creates its product. Every of the critical DNA fiber behaviors
that a business does is probably done through a process,
and as such, a process shapes its reputation.
Speaker 2 (04:57):
So they're very important.
Speaker 1 (04:58):
It's important to get it right, to be able to
change it over time, and we are a platform for
automating an organization's processes. We started by allowing them to
just draw a flow chart, and that flow chart would
be automated like a piece of software. But over time
we also filled in the flow chart with digital workers
(05:19):
so that the work could get delegated to a robot.
In some cases that would be robotic process automation or
an RPA bot. In some cases it was just a
business rule for a set of rules, and of course,
in some cases most famously, it's artificial intelligence. So we've
been in the artificial intelligence business for about a decade
as part of the way we execute those processes that
(05:40):
we plan for our clients.
Speaker 3 (05:42):
All Right, I'm going to want to talk to you
about AI and AI regulation because I know that is
a passion project of yours and it's a really big deal.
It's always in the news every day, so I'm dying
to here where you think about everything and where it's
going before we do that. Though, I know there's many
worldwide that know what apping does. But if we were
to give a snapshot to some of our new listers
that aren't familiar with the company, and you give a
thirty thousand foot view about what you exactly do, what
(06:03):
would you tell them?
Speaker 1 (06:04):
Yeah, Appian is the process company. Your organization is made
up of processes, and we're going to help you make
those processes efficient and better, and we're going to run
them with less time and less cost and a higher
success rate than you've been achieving in the past. Your
organization is defined by its processes, and we can help
you optimize them.
Speaker 3 (06:23):
So, preparing for the interview, went on the website. Love it.
It's easy to navigate. But there are a lot of
programs and capabilities, and I know you're probably proud of
all of them and what you offer your customers. But
if you were in an AIRDA, maybe a handful of
them that either you're most proud of or what clients
really want in today's climate. Can you tell everybody about
that and expound a little more on it.
Speaker 1 (06:42):
Yeah, Well, we're conducting this conversation in the Washington, DC area,
which is where Appian's home base is or a worldwide company,
but our base has always been in Northern Virginia in
the DC metro area, and some of the work I
am most proud of over the twenty five years we've
been in business has been right here. For our federal government,
we did the Army Knowledge Online System, which twenty years
(07:02):
ago was called by Wired magazine the largest intranet in
the world. We do wonderful work for the Department Defense
in terms of procurement right now, tens of billions of
dollars annually passed through our procurement systems. We were integral
to getting the Affordable Care Act processing to work.
Speaker 2 (07:19):
You may remember that the website didn't work well.
Speaker 1 (07:21):
The other part of it did work, the part where
you could register by a filled out form. We kept
that running even when the other side was lights out,
and we were able to build that system in just
one month on an emergency basis, And so I'm proud
of how quickly we responded to save that program. So
a lot of the greatest jobs we've done. I mean,
(07:42):
at this point we're around the world. We're about roughly
half of the world's biggest banks, biggest insurers, biggest pharmaceutical companies.
We are, we're in five continents were we're everywhere, But
a lot of the work I'm most proud of happened
right here at our.
Speaker 3 (07:56):
Hometown, Outstanding, Matt. You know, there are so many different
challenges in the industry, and as a layman, as I
read the news between AI and we will talk about
regulation just a second, but you know, I hear cybersecurity
a lot, and that's not only internationally announced domestically With
that said, is it at the forefront? I know each
client is very specific for their needs and what you
(08:18):
do for them, but is that at the forefront usually
when it comes to cybersecurity and everybody trying to protect
themselves in the climate that we're living in today.
Speaker 2 (08:27):
Look, data has never been more valuable than it is today.
Speaker 1 (08:30):
Our organizations will freely admit now data is their greatest asset,
and they're frequently correct. Protecting that information is top priority
for all of our clients. We're not just the process company.
We're specifically at the high end of this industry. We
focus on the big organizations making big bets and defining
themselves through process, and so for them, data is of
(08:51):
the utmost priority. We protect data. We're ahead of the
curve on industry standards and measures that we take to
secure information. That's always been a part of our calling card.
I mean, we started with big jobs like the army
and health and human services twenty odd years ago, and
(09:12):
so we had to care from the beginning about the
sanctity of confidential information. So yeah, that is a big, big,
big deal, and privacy is also a big deal.
Speaker 2 (09:24):
This is a major issue these days.
Speaker 1 (09:26):
It's not whether your data will be stolen, but whether
it will be taken with your own permission or with
some semblance of permission in order to train somebody's AI algorithm.
This is a big issue today. Organizations are afraid to
use AI because they don't trust that AI will be
private enough with their data, and so they don't want
to train an AI algorithm that they don't own and control.
(09:49):
That's a big issue and it's holding back the evolution
of this industry.
Speaker 3 (09:52):
All right, well, let's expound that a little bit, because
I know that when it comes to AI and AI regulation,
this is really something that's very important to you, your team,
your clients, but also something that you're at the forefront with.
And once again, just as a layman, I only know
enough to be dangerous. It's on my phone, now, it's
on my computer. I've used it from time to times.
But that for me when it comes to somebody like you,
(10:13):
the industry, and just overall, let's just give it kind
of a thirty thousand foot view about where you are
with AI and regulation and then we can start diving
into that.
Speaker 1 (10:23):
Yeah, let me first of all say what a priority
I believe privacy is in the evolution and the usage
of AI. I think the industry's progress depends on privacy.
And I take this first of all, on the authority
of my customers. I speak with the CIOs that I
work with, and they are all very concerned about protecting
their data. They don't want to share it around and
(10:45):
they don't want to train algorithms on it. And so
we need to reassure them that their data is safe
in AI, and that means creating an AI architecture that
protects their information. And so it's going to be important
just for us to connect with those business users to
reassure them in some better way than we've done so far.
(11:05):
And we've come up with such a way right Appian
has a specific we call it private AI. We have
a specific angle on this business whereby we do not
train an algorithm. We instead take your question that you
want to ask of AI, and we source just the
right information from across your enterprise and send the question
(11:27):
with the data. And that's all that the AI gets
to look at is just that slice of your data.
But it's enough we send the right data, and therefore
AI comes back with an answer that's comparable to what
it would have given if you had first given it
everything you knew, and so it's a low data and
(11:47):
a low trust way of using AI, which suits the
concerns of the modern customer. So that's one way that
we can make progress in AI. It's called request augmented
generation and it depends on a really great virtual database
and we have that.
Speaker 2 (12:02):
We call it a data fabric.
Speaker 1 (12:03):
But because we have that, we can offer this no
training generative AI.
Speaker 2 (12:08):
And it's successful. So that can work.
Speaker 1 (12:10):
However, more broadly, if we were just step back and
say what does privacy mean for this entire industry. I
think privacy is the hinge on which this whole industry turns.
The future of AI is so much better than the present.
We're going to look back on today and say, this
is when they didn't get it. This is when AI
didn't have any value. It's just a parlor trick. AI
is amazing, but it's not productive. It'll be productive when
(12:35):
it understands us, which is to say, when it understands
the person or the entity that's asking the question. AI
can't tell me where to go on a Friday night
because it doesn't know what I like. AI can't write
an email in my voice because it doesn't know my voice.
Until AI knows me, it's not going to be as
useful as it would be if it did.
Speaker 2 (12:58):
The reason it doesn't know me though, because I don't trusted.
Speaker 1 (13:01):
I don't want to train an AI algorithm on all
my emails that I've written, and I don't want to
explain everything that I like, and therefore my lack of
trust is holding back this industry. It's true across the world.
We need to get over that by showing that AI
can be trustworthy. And that's why I encourage this industry
to adopt guidelines that prove it's trustworthy, to be more transparent,
(13:25):
and to make a conscious effort to stop blurring the
lines between what it owns and what it doesn't. I
think the average person understood how much they have personally
trained AI.
Speaker 2 (13:35):
They would be upset, Matt.
Speaker 3 (13:37):
I know that worldwide social media companies, companies in general
are using AI and moving forward with it, but let's
just stay maybe in your industry, if we could domestically
and internationally when it comes to your peers and your
contemporaries and what you do, is everybody on the same
page or are you fighting a battle on your own
right now where are you with everything in your contemporaries.
Speaker 2 (13:57):
We are very different from our competitors.
Speaker 1 (14:00):
Compete against some of the largest tech firms in the
world like Microsoft Salesforce Service Now, and for the most part,
our competitors see AI as a way to get hold
of data. They want to use AI as a way
to control their customer's data. That could be by moving
all the data into their format, into their database into
one consolidated heap that then they have privileged access to.
(14:23):
Or it could be by literally sending the data over
to our competitor, so our competitor can train on that
information and use it to whatever extent the fine print
allows them to in their agreement with their customer.
Speaker 2 (14:36):
We are not doing that.
Speaker 1 (14:38):
We are not using AI as a trojan horse to
get our hooks into any data at all. Instead, we
respect the enterprise of the way we found it. We
use a virtual database to connect things that are not
co located. We don't ask our customers to change their
data's format or location, or to train an AI algorithm
whether we control it or not. Our point is to
(14:59):
empower our customers to get value out of AI without
compromising their data one wit. So we take a very
different approach to this industry than our competitors do.
Speaker 3 (15:10):
I don't want to assume with any advocation on your
part of somebody from your team, but is this something
that you're going to be discussing a Capitol hill or
somebody from your team and talking about this, because obviously
you're very passionate about it, you feel very strongly about it.
But there is a big world machine out there that
does exactly what you're saying that you don't want it
to do, which is grab everybody's information. So what about advocating.
Speaker 2 (15:31):
Yeah, you're completely right about that.
Speaker 1 (15:33):
There's a lot of energy advocating for the lack of
data rights because the leading AI vendors are gaining tremendously
by ambiguous or missing data rights guidelines. We take the
opposite approach, and I personally, as a privacy advocate, take
the opposite approach. And so I've written a set of principles,
published them, and I'm building support amongst the press, fellow
(15:58):
CEOs and cons us for these principles, which speak up
for the owners of data and the sanctity of data.
Speaker 3 (16:07):
All right, well, listen, I want to talk a little
bit about the future because AI is also the future,
and that's part of the component of your company and
where we're all going. But with that said, I know
that you and your team are we sinking down the
line too, and technology is moving very quickly. As you
see your company and the industry moving ahead the next
five to ten years, where is the industry going?
Speaker 1 (16:25):
The AI industry is reaching a fork in the road.
If we can win people's trust and confidence, then AI
is going to become personalized, and when it does, it's
going to become far more valuable, far more valuable than
it is today. Personalized AI is going to be revolutionary.
(16:45):
Generic AI, what we have today is merely intriguing. So
we need to make this turn, and making that turn
depends on trust, and trust is the most important commodity.
Speaker 2 (16:56):
In the past the last year or.
Speaker 1 (16:58):
Two in AI, it has appeared that the most important
commodity is raw data, and the leading vendors should just
take it wherever they can, no matter the costs, no
matter the dubious legality, just take it. But the paradigm
is shifting here to reach AI two point zero, the
personalized AI, that's the real future of this industry. We
need trust more than we need data. Trust is the
(17:20):
only way to get the data you truly need, And
so we're approaching acrossroads and the priorities will have to shift.
Speaker 3 (17:28):
Are there other people in your camp that feel the
same with you?
Speaker 1 (17:30):
You do? Yeah, there are there are others. First of all,
every customer I mentioned to this mention this too.
Speaker 2 (17:38):
They agree with me, and.
Speaker 1 (17:39):
So definitely the consumer base for AI agrees with me.
But does big AI? Does big tech agree with me?
Speaker 2 (17:47):
They don't.
Speaker 1 (17:48):
Their strategy is what I would call run until tackled.
They're just going to take as much data that they
maybe have a right to as long as they can
and use it to the fullest ext that they can
until someone stops them. And that strategy has been working
for him so far because data has been the most
important input to AI.
Speaker 2 (18:08):
It's about to not be, so they need to change
their game. But for now, until someone stops them, that's
their game.
Speaker 3 (18:14):
We talked about some challenges, but I also love to
talk about some of the positive, cool things that are
wrapping on there. And you really are doing so many
innovative things with your clients. I know that there's a
lot of reasons why you and your team get up
every day because you're servicing your clients, You're making them happy,
You're making America and the world safe for a lot
of people out there, especially when it comes to technology, privacy, data,
and everything else out there. Is there something in the
(18:35):
industry right now that with your and you don't have
to name the client, Matt, but you're most proud of
that you're making a difference to you and your team
right now that you know is really special.
Speaker 2 (18:46):
Yeah. Absolutely, I love this technology.
Speaker 1 (18:48):
And one of the reasons I've been able to stay
with this for twenty five years is I believe that
it serves a larger purpose in the world than just
moving money from one account to another. I think that
we're empowering people to extend their capabilities through digital assistance,
and we are allowing organizations to have and reinforce the
(19:11):
personality they want to have.
Speaker 2 (19:14):
Organizations for the last couple decades.
Speaker 1 (19:18):
Have all felt that they needed to trade their personality
away in favor of the most efficient, cost efficient set
of behaviors. And so every corporation seems alike, or almost
all of them seem alike to us right now.
Speaker 2 (19:31):
They all use.
Speaker 1 (19:34):
Generic phone lines and generic emails, and they all appear
to us as robotic, impersonal and indistinguishable. Our processes allow
an organization to create its own personality and live up
to that, and that raises the standard of living for
(19:55):
all of us because none of us wanted to deal
with robotic, indifferentiable vendors. We wanted them to be able
to live up to their brand promise and their expected identity,
and with this technology they can. And then secondly, we're
about the interface between people and machines. When you draw
a flow chart and it turns into software right on
(20:17):
our platform, that's fundamentally what we do. You are extending
your reach and commanding a computer to follow your instructions.
It's like a simple form of programming, but a very
powerful form. It's very human, it's very intuitive, and it
allows people to interface, collaborate, and direct machines better. And
(20:41):
so I'm proud of the effect that we're having both
on people who become stronger and on organizations who can
finally assume their attended personality.
Speaker 3 (20:50):
Man if I could do this, indulge me just for
a moment. I always love to talk to leaders, especially
with your company. I mean, you are worldwide, so there's
a lot of people on your team. Obviously you are passionate,
you have a vision, but you want a company you
run a certain way. But also we talk about the
work life balances for people, and some people have very
high security clearance and some don't, and some are living
(21:10):
all over the world and some right here in the DMV. Well,
that said, with so many people that are on your
team and handing down the message about how you would
like the company to be run, but making sure that
everybody's a happy employee, have that work life balance, but
also get the job done, how do you do that
leadership wise?
Speaker 1 (21:28):
All right, Well, that's a challenge, and it becomes a
greater challenge with scale, It becomes a greater challenge with distance,
and we have offices all around the world. We are
furthermore a values driven organization, which is to say, we're
more dependent than most companies on having a set of
values and having them broadly adopted.
Speaker 2 (21:47):
They shape the way we work and the way we are.
Speaker 1 (21:49):
Different from other firms, and so it's more essential for
APPY and to be able to convey its values across
oceans and across a larger team that it is their companies.
We've never tried to be like other firms, and I
don't want to be like them now. And so first,
it's a great deal of communication. I'm constantly writing things
(22:11):
and saying things about what we stand for and how
we work, and so it's a constant expression of values
back to the team. You have to enforce values when
you hire and when you promote, so consciousness about what
your values are and bringing them to bear on those
moments of truth is very important. I think it's important
(22:31):
to have as many people come together as possible. I
believe that when people are together, they exchange information about values,
they confirm values, and they understand the differences in the
organization better. So I'm a proponent of working in the
same place to the degree that we can, and I
think Appian is a magnet for people who feel that
(22:54):
way and are interested in the kind of personal development,
career development, and highly charged collaboration that are possible when
we get together in the same location. So we're always innovating,
we're always growing, and we need to keep finding ways
to stabilize and enhance our values at scale in a distance.
Speaker 3 (23:15):
I appreciate all your thoughts on that. Thank you so much.
I've really enjoyed the conversation. I do want to wrap
up with some final thoughts from you, and we've talked
about a lot in the short time we've had a
chance to get to know each other, Matt, but just
maybe some recapping, some final thoughts. The floor is here, sir.
Speaker 1 (23:31):
Ah Well, I never thought i'd be with the same
organization for a quarter century. We've grown over that time,
and it feels different, and I think it's the difference
and the impactfulness of what we're doing that keeps me here.
I'm also very proud of the fact that all four
founders of this organization are still here in an executive
(23:53):
capacity twenty five years after we founded it. That says
something about loyalty and decency and mutual respect, and I
can't think of any companies that have achieved that. And
so while I'm surprised that we've been able to maintain
this growing organization for a quarter of a century, when
(24:14):
I look back on it, every year made sense, and
it makes more sense now than ever because the stakes
are higher than ever. I feel like we can have
a greater impact to help people than we've ever been
able to before. And if our culture is harder to
establish across a global organization. Then at the same time,
it is more impactful because there's more people to influence,
(24:35):
and therefore they can have a greater impact, and our
culture can go farther if I can.
Speaker 2 (24:39):
Establish it in all those people.
Speaker 1 (24:40):
So, because the game keeps changing, because the stakes keep
going up, and because I get to work with good
people that I'm fortunate to have worked with all this time,
I'm still at it twenty five years later.
Speaker 3 (24:53):
It's a truly amazing story. If you do me a
favorite because I'm a sports guy. I've been in my
industry for thirty years, and when I was reading up
about you, you really used a very cool sports analogy
about pulling a goalie. And we have a lot of
future entrepreneurs that listen to the series, and it obviously
spoke to me, but I think it would speak to
a lot of people because sports crosses over to business
(25:13):
just about every day as far as I'm concerned. Can
you share that analogy because I thought it was fantastic.
Speaker 1 (25:18):
Oh yeah, you're referring to some research I did, yeah
long ago, when I was in school, about when a
hockey team should remove its goalie the hockey team is
losing toward the end of the game, and it has
to make a decision about when to take its goalie
out of the game and add another player who could
conceivably score a goal, who could be part of a
powerplay style situation.
Speaker 2 (25:40):
Knowing that when they do that, they increase the.
Speaker 1 (25:43):
Chances that a goal will be scored against them by
more than they increase the chances that they will.
Speaker 2 (25:47):
Score a goal.
Speaker 1 (25:48):
So it is a move you would only make if
you needed to change the game dramatically and you were
going to lose if you didn't change it.
Speaker 2 (25:58):
But the question is when when you pull that goalie. Now.
Speaker 1 (26:02):
Back at the time that I did the research, which
was the early nineties, I felt that the hockey statistics
world was not very well developed and that goalies were
rarely pulled outside of the final minute maybe two at
the most of a game. And I found that that
was probably a mistake. That a team should pull its
(26:24):
goalie a bit earlier, and in a truly important game.
A team should pull its goalie even when it's losing
by two goals, which is almost never done. Even if
it's losing by two goals and relatively earlier, then it
would pull the goalie if it was losing by one goal.
So if you're losing by one, you should have your
goalie out two minutes or before the end of the game.
(26:46):
But if you're losing by two, you should pull your
goalie by maybe four minutes out from the end of
the game. If it's a truly important game and you
don't care about being embarrassed losing by three or something,
you should pull your goalie an additional minute or two
beyond that in order to have a longer period of
high variance. Even if the mean next and the expected
value goes against you, the higher variance makes it more
(27:09):
likely that you're going to win a game you otherwise
would have lost.
Speaker 3 (27:12):
So I know there's a lot of data in there,
but I also thought there was a life lesson in
there too about actually just getting ahead of things. And
because I'm a sports guy, made a lot of sense.
I'm a big hockey guy too, So I love your
analogy that you put together, Matt, and I think there's
always life lessons from sports that we can apply to business. Well,
let's do this. Let's wrap up by giving the website
to everybody. I know that you're always looking for the best,
and the best there is a careers tab there. But
(27:33):
there's so much information on this wonderful website of Appy
and if you can give the website to all our
listeners Matt appian dot com, that easy listen. It is
a treat to get to know you continue success. It
really is in the making twenty five years of you,
your founders and all the amazing things that you're doing.
And Matt, the one thing that I took away beside
the amazing things that you offer, and also how you
(27:55):
feel about AI regulation when I talk in this series,
no matter what people do and what company, they have
a passion for what they do. And I can tell
that you have that. And I'm always very appreciative of
people that are passionate about what they do and that
gives them an extra head start and everything. So thank
you for your time and thank you so much for
joining us on CEOs.
Speaker 2 (28:11):
You should know, thanks so much. Dennis
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