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>> Ganesh Bell, President of Uptake, welcome to Stanford.
Thank you so much for coming.
>> Thank you, thank you for having me here.
>> Tell us a little bit about Uptake.
What is the company, and who are your customers?
What are you accomplishing in the digital industrial transformation?
>> Sure, so Uptake, we have a mission, a world that always works.
What it means is, simply, we are in industries where they're asset-centric.
These are the infrastructure that powers the world, and we build a AI,
machine learning, and IoT platform, on top of which we're building applications.
And we're adding deep industrial content, content meaning we understand that,
in many of these industries, there are critical assets, so
we have a database of how all these assets are going to fail.
We've catalogued about 55,000 ways these assets are going to fail,
across many different industries.
We like to think of it as 55,000 ways the world will stop working.
So we apply machine learning and
data science to make sure that we can actually predict, and therefore,
we can drive outcomes for customers, whether it's uptime, reliability.
But from there, we can optimize the entire business.
>> Well, previously, you worked at GE.
You were the Chief Digital Officer for a while, you worked in GE Power.
Why did you leave GE to go to a startup, which is now a big startup, like Uptake?
>> Actually, the most important thing is why I came to GE in the first place.
>> Okay.
>> So I remember when GE called me, more than four and a half years ago.
They were trying this idea of software.
I think Jeff, at that time, the Chairman of GE, had a belief that data and
software will fundamentally change the industry.
And I had a similar belief that software will reimagine businesses and
industries as we know it.
So I actually ended up selling GE the idea of digital, and ended up being the first
Chief Digital Officer, and building the power digital business.
So it was really a moment of do I believe my own bullshit, that businesses and
software will be reimagined with software, and
I got a chance to go do that at the biggest scale for a long time.
And for more than four years, built a successful business in digital for
power, which became the blueprint for all of GE Digital.
>> Mm-hm. >> And towards the tail end of my career,
where some of the biggest believers, like Jeff, had left, and
some of my bosses had left.
But I still believed that GE was a fantastic company, and a great company.
But I also believed that the business model of doing digital
was directly in conflict with the existing business model of doing services.
So I actually believe that this has to be done in a fiercely independent way.
>> Okay. >> And
Uptake was the best thing out there, and I joined forces with the founder.
>> All right, so if you look at Uptake, it looks like any digital company we can
see anywhere in the world, here in Silicon Valley, Beijing, Shanghai, Berlin.
How do you bring domain knowledge of the industrial areas
that you're serving with a, largely, what looks like a digital DNA company?
>> That's a great question, because if you think about all these industries,
they've all operated with data to some extent, except they've been about first
principles, physics-based analytics, right?
And that was good enough to operate the world where we only used
a little bit of the data.
But in the last five years, I would say machine learning and cloud technologies
have caught up to a point where we can process all of the data.
And with machine learning, we can actually surpass first principles,
physics-based analytics to get to truly predictive analytics.
And so you really need machine learning,
AI at the core of what you do, and that's what Uptake has done.
In addition, we had actually brought domain expertise with operators.
So our head of energy was the head of power,
president of power at Exelon at one point, and
he was also the chief innovation officer and chief information officer.
So knowing that domain matters quite a bit.
And we used to do ads, in the past,
that our data scientists wear steel-toe boots, and it's actually technically true.
Our data scientists visit a wind farm or a mining operation.
So it's combining the domain, and knowing people who know the industrial aspect.
That's why we also bought a company called Asset Performance Technologies,
where it was about 32,000 man hours of domain expertise.
Cataloging every single critical asset, how it fails,
what the preventative maintenance strategy is.
So digitizing that, and learning on top of that is really where the value is.
>> Last week, we had Sam Allen, the CEO of Caterpillar, visit our Systems Leadership
class, and he talked about what they're doing on digitization.
How does a company like Uptake figure out where in the technical stack you
want to play and own certain things,
and where you want to partner with your industrial customers?
>> Actually, Caterpillar is a customer of ours.
Uptake started joining with Caterpillar.
There are many divisions of Caterpillar that deploy our software.
Where decide to play is very simple,
which is there are many companies that sell enabling technology.
In fact, I would say, the industrial IoT,
there is a whole new stack that's emerging right now.
It's very similar to how it was in enterprise software in the 90's,
where there was database servers, app servers, integration servers,
analytics servers, applications, and so on and so forth.
There was portal servers and everything.
We kind of see that again,
which is data aggregation at the industrial sensor level.
There's Edge, where you can do computing there, and there's also all the layers
of contextualizing data, app platforms, analytical platforms, tools, and apps.
What we do is platform, which is really about software to build software, and
so we can help companies that are in industries where
they're actually digitally backwards.
So they need high productivity, almost bulletproof kind of a platform, where it's
like bumper bowling, where every time you bowl, you're going to hit a pin.
So if you build an app on our platform, you will build an app.
It's not left to some IT magic.
And on top of that, we're building applications, but
where we really play is outcomes.
So we focus on how do we impact the financial statement of our customers,
which means reducing operating and maintenance cost,
or improving their output, or improving their uptime.
So if we start there, the CEO, CXO level, we can work backwards.
We're not a Azure, we're not AWS.
We love all of those guys.
We run on top of that.
>> All right, so you talked about enterprise software and
the enterprise Internet, and you were at Oracle for a while, at SAP.
>> Mm-hm. >> How is the industrial Internet
different than how we might think about the enterprise Internet or
the consumer Internet?
>> That's a great question.
Actually, if you take a step back,
enterprise software is not a very long-running discipline.
It's only a few decades old, right, and I would argue that
we're actually at a seminal moment in just history of enterprise software.
Why do I believe that?
In the last several decades, enterprise software was all about
humans entering data and automating business processes.
That was true until now, but
now we're in a world where machines are generating data.
Robots and drones are increasingly at work with wearables,
and humans augmented by machines are generating more data.
So we believe that we're going to be in a paradigm of where it's about automating
decisions versus automating business processes.
That's fundamentally different.
And the next thing is we see that, in many of these industries that have been left
behind, industrial world especially, there is a separation that's happening.
Between what I call the physical model of the industry, which is assets, and labor,
and parts, and people, and the economic model, more importantly,
the future economic model.
If you take a utility, for example, it's no longer about producing electrons,
it's about selling services beyond the electron.
So as the gap becomes wider, there's a bigger value creation opportunity, and
I also believe that the technology shift is happening.
If you think about enterprise software history,
when we went from a mainframe to client-server, it was a new market.
When we went from client-server to distributed computing, new market.
When we went from distributed to SaaS, it was a replacement market.
>> Mm-hm.
>> So far, we've only redid what we did in a new architecture.
We never reimagine.
I think that reimagination's going to happen right now, and
that's why we believe it's going to be very different.
>> So one of the things we've learned about the industrial market is
it's not as quick to change as some other market segments.
>> Yeah. >> How does an independent company like
Uptake think about its rate of growth?
You've taken venture capital money.
How do you think about traditional metrics that might come from a technology company,
but applying to a market that sometimes takes a little bit longer to evolve and
accept new ways of doing things?
>> Yeah, so startups are going to be always different than large companies,
where, when I was at GE and running a very large P&L,
it was about operating profit every quarter, right?
Whereas in a startup,
it's really about growth, customer acquisition, and onboarding new customers.
So we have lots of proxy metrics.
We actually measure things like, for example,
how many hours are our algorithms trained on.
For example, some of our predictive machine learning algorithms are trained
on over 1.2 billion hours of operating data.
Right, that's an important metric for us.
How many models are we deploying?
How quickly can we deploy new data science models?
But at the end of the day, we're going to measure things like orders, bookings, and
how we're growing the customer.
But you're right, that these industries are long sales cycle, so
the question is, can we actually do quick wins?
And also, there are some fast movers.
Sometimes we'll do lumpy, big deals, and the art is moving from the lumpy,
big deals to a volume revenue engine, and I think that's the real challenge.
>> Well, Ganesh,
it's fascinating to see how Uptake is entering this market as an outside player.
We really appreciate your coming to Stanford to discuss systems leadership,
and thank you so much for the time.
It's great to have you. >> Thank you, thank you for having me.
>> All the best. [MUSIC]