Now I'm going to tell you a story about driving transformation
at a company that's 90 years old.
And it's kind of a fun story.
And we'll eventually get into a lot about how Palantir has changed our life.
So I used to sit right here in Palo Alto.
I was here for many years.
I was the last CIO of Hewlett Packard
and the first CIO of Hewlett Packard Enterprise.
And I actually flew back to Arkansas because I'm from Arkansas
and I went to a Razorback basketball game and flying back,
the guy in the seat next to me was a Tyson Foods guy
who I'd actually gone to high school with.
So how weird is that?
And he says, Would you ever think about coming to Tyson Foods?
And I said, no.
And he said, Well, I'm going to have our CEO give you a call on on Monday.
So seriously, the CEO of Tyson Foods gives me a call and we're talking.
And I thought it was kind of interesting.
And he says, you know, one of the things that we have
that you'd be thrilled to know
is we have a new world class cutting edge data center.
And I thought this.
I thought, My God, are you kidding me?
Who's building data centers today?
This was 2017.
But I'm a huge Razorback fan and I'm from Arkansas,
so I thought I was going to take this and we'll kind of go through this
and see what happens, you know?
And next thing you know, I'm living in Springdale or I actually live in Fayetteville.
I live right across the street from the stadium, which is pretty cool.
But I'm now at Tyson Foods and and I get there and I realize, Oh, my God.
We don't have any cloud.
We don't have any containers.
We don't have a data lake.
Everything is custom there.
People haven't heard of the word Kubernetes.
If you're technical, you know what I'm talking about.
They haven't heard about CI CD pipelines.
They haven't thought about major data ingestion.
There's no RPA.
There's no robotics.
There's nothing.
And so there we go.
So I immediately start setting a transformation strategy and I say,
you know, we got to start signing up some technology partners.
That's one of the first things we've got to do.
We've got to get going on the cloud.
We got to get rid of this data center.
We got it made.
We could turn that into a command center.
Who knows?
And so the rest you've probably read by now one of the biggest things
there that was building a data lake.
We have to get a data lake.
We have to be able to get automated ingestion of large,
large, large amounts of data.
And we've heard that through today.
We've heard a lot of people talking about data.
And it is a it is a a big deal when you deal at large scale.
So, Tyson, when you think about Tyson, you probably think about chicken.
Just a quick aside,
you think about that because chicken is the only branded protein that's branded.
You go buy beef, there's no brand on it.
It's usually a little tray pack and it's clear label and maybe
there's a butcher tag on it or something like that, or same thing with pork.
But anyway, so the story goes on.
This was the technology building.
And I remember talking to our chairman, whose last name is Tyson,
and he says to me one day, Well, what do you think?
And I said, Well, I don't know.
This space is not very optimal for collaboration or innovation.
And he says, Well, we got a building that we'll give you.
And this was our building.
And he said, So give it to architects and figure out what you want to do with that,
because I think it needs some repairs.
It probably does need some repairs.
So we turned that building into this building, which is really cool,
and it is the only building like that at Tyson.
This is what it looks like on the inside.
So we're finally set.
For doing some true innovation and trying to transform this company.
And I kind of learned transformation is a word that people don't like at Tyson.
So we started using the word modernize or enable.
So we started down the path.
Things were going really well.
We started getting into
the first thing we had to do was kind of look at the talent, right?
We've got to change out the way we're doing things.
We've got to look at how we can recruit differently.
Everybody was from the local area.
Compensation wasn't really up to speed.
They hadn't heard of data scientists.
So, you know, I was paying $330,000 a year for people out of MIT at HP,
coming straight out of school for data science.
Get there.
So we start working this stuff around, start doing a lot of recruiting.
My big deal was, Hey, if you come here for, I'll interview you,
but you got to come for three days
because I want you to have one day to shed what you think about Arkansas
and actually see Arkansas
because it's actually a beautiful, beautiful place.
And so we started getting all that done.
We started doing digital literacy, driving a lot of road shows,
trying to show a lot of cool tech things like that.
We canceled a bunch of projects.
They were going live on four different ECCs at the time.
And I'm sitting there thinking, God, I mean, why not ask four?
So we start going with us four we bring in work day, we start, you know,
rationalizing a lot of fully custom apps and there is a mainframe
that's still in existence today.
And we started lining up a whole bunch of technology partners.
A couple of things I'll point out on this slide is one is.
Google and AWSright off the bat.
Right, because that's cloud.
We've got to get to the cloud.
But down at the very bottom of that left side was Zoom.
We made a decision before the pandemic came to move on to Zoom.
And boy, that became prophetic
because as we were killing it with our transformation,
all of a sudden the pandemic came.
Brutal, brutal time.
Everybody here was affected by it, created the whole zoom world.
I mean, how many times did you look at Hollywood Squares like this?
Right. I mean, you're sitting there, you're dealing with it, right?
People are working from home.
It was tough, very tough, tough times.
And for us, it was really difficult because we have about 150,000 employees, um,
and we probably only have about 15,000 corporate people.
The rest are all frontline workers.
If you remember, in that period of time,
Donald Trump was saying we have to continue to produce food.
Food was scarce.
Remember the runs on the grocery stores?
Remember toilet paper?
That was a big run.
We don't make toilet paper, by the way,
but we do make a lot of beef and pork and chicken and poultry and all that kind of stuff.
And so as these spikes are starting to happen with plant workers
and this is a single plant right here,
we're getting to a point where we're shutting down plants.
And when you shut down plants and the President saying you got to stay open
and you got sheriffs showing up and shutting down plants, you got a big problem.
So we start closing down plants.
One after another.
And we eventually we're in the process of shutting down seven plants
while we're trying to produce food for the country
because we're the biggest producer of food in the United States.
I think we're actually second in the world.
Right now, we kind of go back and forth
one week we're one and then the next week or two and so forth.
But anyway, but as my daughter always says,
the sun is going to come up tomorrow.
And, you know, we're looking for a bright light at that point in time.
And what do I what happens?
I'm reading The Wall Street Journal.
I see Peter Thiel's Palantir saw coronavirus coming.
Interesting.
I read this article and I go down the rabbit hole.
Right.
I just one article after another.
I just keep reading all these different things about Palantir and
oh, my God, Palantir's doing this and Palantir's doing this and Palantir's killing that.
And, my God, it was unbelievable.
And then I find this article.
Ontology.
And I remember hearing about ontology way back, way, way back.
And, you know, kind of one of the thing I think is,
God, just how cool is that to just talk about ontological modeling?
That's just kind of cool to talk about.
But then actually when you start thinking
about the power of
ontological modeling,
our mindset was when you start to couple that together
with the semantic layer that that Palantir has,
you've got a huge win opportunity.
Massive, right?
Anybody that's on that, they know exactly what I'm talking about.
And if you're not on it, you'll find out when you get on it.
Because when you can start to make sense out of vast amounts of data
that seemingly are just totally disconnected
and you can find relevance between those,
you're in a very different spot.
And it's interesting because I remember we started on this path
and I remember telling our CEO.
Hey, this plant in seven weeks is going to have 880 people infected
and we're going to shut that plant down.
And they kind of.
We are hearing from Scott again here, and it's doom and gloom and,
you know, that kind of thing.
So that day hit.
883 people were infected because we were driving prediction with Palantir.
Palantir came in and just kind of blew it away.
So I'm sitting there, I kind of got ahead of myself for a second,
but so I was sitting there and I go back to my email because
one of the biggest differences in being at HP and being at Tyson
is at Tyson I get about 700 external emails from vendors
a day trying to sell me some product
when I was at HP and I only get about a hundred and I finally realized,
well, HP makes so much technology.
That's why.
This guy who's in this room today is actually in Fayetteville, Arkansas.
And I'm thinking, how cool is that?
This dude is there and he's already been emailing me.
He's been trying to get time with me.
And of course, I was blowing him off.
That's what we do, right?
I'm the CTO.
I don't have to take a meeting if I don't want to.
So he brings in some cats that are just unbelievable.
Look at how smart these guys are.
Right.
Princeton.
Stanford.
Johns Hopkins.
University of Bath.
My God.
Right.
Dartmouth.
These are Ivy Leaguers.
Fortunately, there was somebody there from the University of Arkansas.
So we had a real smart guy with us, and I felt damn good at that point.
The rest is history.
We go down the path.
We start to work on coronavirus because
coronavirus is killing us and it's getting bad.
We started.
There was a big article published all over many of the newspapers
about the supply chain is broken.
Because we were having a hard time getting food produced.
In a very short amount of time.
We started working on figuring out how bad the spread is going to be,
which plants are going to be affected, how quick are they going to be affected?
We started that's when I had that conversation with the CEO said,
Hey, you know, this plant is going to have 882 and it was 883.
We were dealing with the plant closures,
predicting which ones were going to close.
We started predicting which roles were going to be most heavily infected.
We started looking at the generalized Richards curve model,
modeling that with Palantir,
that started to tell us,
you know, based on county data, all the different data aspects
be able to say this plant's going to go down.
So we need to start shifting product to this place.
Right.
That affected recruiting.
We were able to start to do predictive recruiting and
changing sign on bonuses for frontline employees.
It was a massive win, huge, really big for us.
And it, you know, is interesting because if you're going to get started on Palantir.
One of the things that you're going to be challenged with
is the cultural transformation inside of your company.
And one of the things that I was just kind of thinking about
over the past couple of days is I was thinking about giving this presentation.
Is our jobs as technologists,
as a CTO or as a CIO is to be a great steward of the money.
You've got to really spend wisely and you really got to protect your business case
and you really got to do everything you can to deliver as fast as you can.
Something that makes the most impact.
So velocity is a big deal.
And as I think about that.
That's kind of where we were going.
And so in a very, very short amount of time,
we started driving to that and then we got hit with,
Oh, we as Tyson are going to mandate everybody to have a vaccine.
We were the first big company to do that, if you remember that.
If you knew that at all, we did.
And as we so then we got to start figuring out
can we use Foundry also to help us validate vax cards?
Are they real or are they fake?
Did that really happen?
Did that person really get vaccinated
or not because people were going to be terminated.
And we did that.
And this is what we created.
This was the first piece.
This was the first thing that we did with Palantir.
We created all of this capability.
It was unbelievable.
And if you go back to that cultural transformation that I was talking about,
when you can deliver results this fast.
You break through that barrier because people see the results so quickly.
They come back to you and they go,
Oh my God, they don't have time to think about it and fight it
and organize like they normally do
when they resist the kind of change that they do,
particularly in a company that's as old as we are,
that's been doing things as long as we've been doing them
the way we've been doing them.
When you present something as quick,
it really makes a big game changing change.
So you think about the team, you think about partnership,
you think about the trust.
Do you think about the fact that these guys came in and listened to our problems,
understood our problems?
Helped us create solutions that were very quickly implemented
and made game changing results.
So we then said, Let's expand on Foundry.
Let's take it to another level and let's look at some of our other problems.
Right.
So this is kind of what Foundry looks like if you haven't seen it.
You just got to see it a few minutes ago
when you were looking at the Cancer Institute.
But here on the right, you have the ontological model.
And then everything else is all the data components, all the data elements.
It's massive.
It's huge.
Again, going back to our ontological modeling,
you're finding things that are seemingly disconnected
and finding relevance between them,
which really gives you a stronger correlation.
So we went to a yield optimization and said, you know,
how can we improve the yield in our prepared foods group?
So that's Jimmy Dean, Hillshire Farms, all those kinds of brands we own.
There's 26 different brands in that group.
How can we change that?
At that time, we're spending about $6 million a year on Palantir,
and that found us $10 million value.
So already we're positive, but that's nothing.
This is what that control panel looks like all different ways for us to apply results,
to apply change, to take the hands out of a spreadsheet
and put it into an automated fashion
where we can deliver a result that's tangible and measurable very quickly.
Then we went to logistics optimization.
So we're, I think, the sixth largest trucking line in America.
I think we have like.
I don't know.
2900 trucks.
I don't drive them, so I don't know.
But.
What we were averaging was about 46% of these loads were full.
We brought these guys in.
We put it all in into Foundry.
We started changing the ratio of mix on these trucks.
So we're shortening the distance.
And we're increasing the load.
So now we're at about 87% full.
Massive, huge.
There's another $40 million.
So it's interesting.
If you do your QBRs,
I would always be under attack by our CFO in those QBRs.
All Scott wants to spend some more money and he's spending money
on something called Palantir.
And I've never even heard of that platform.
And he thought it was an ERP.
And sit there and try to explain to him time and time again.
And I remember one time talking about ontological modeling and somebody said,
well, what does cancer have to do with anything?
And it really doesn't have to do with anything here.
We're talking about something very different.
So this was a huge win.
So then and this is what that control tower looks like.
So then we eventually go to inventory management,
which is a big problem because think about this we make a lot of product.
Sometimes that product moves and sometimes it gets stuck in a cooler
or somewhere where we have a saying the cooler is not a customer,
but product can die in the cooler.
And so when you look at the fact that we're saving
$100 million on that alone, it's massive.
So we've more than paid for everything.
And we're just continuing to find more and more once you get all your data
Into Palantir, into Foundry, your kind of use case exploitation is unlimited.
There's nothing that you really can't.
We haven't found a zero sum game there yet.
So very positive.
This is what that control tower looks like.
It's really good.
Really positive.
Last thing I would say is that I think that.
I believe, like I said earlier, we have to move as quickly as we can.
We have to deliver the best financial results
we can with the money that they ask us to use.
Our value here is that we've had about 20 different projects.
We've created over $200 million in value savings.
That's a big deal, right?
This has all been two years.
That's hard to beat.
That's really hard to beat.
It's continued and accelerated our transformation.
Our Head of Insights is here.
He's going to be in some of these breakouts.
And I asked him, can you create something?
Can you tell me what you would say to somebody?
And that's what he said.
He's talking about everything that we've built on Foundry
enables the ability to do it manually
for that person who's far behind the change curve
or to do it in an automated fashion by just pressing
a button and changing the outcome.
So that's my time.
Thank you guys very much.
I hope you have a great lunch.
Appreciate you.