Enterprise AI That Manufactures Results

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Well Lord Sarfraz, thank you for the magnanimous

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introduction There. Really appreciate it. All right, So

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first of all, welcome, Deb. Really appreciate you joining us

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here. We started the morning with Jim Snabe, basically

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painting a great vision of the autonomous enterprise, And that

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was followed, not the five year old English teacher, that was

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followed by Nikhil, taking us through a whirlwind of the

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technology that actually enables that, And I would say, Deb, now

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this is the hard part, which is, how do you operationalize exactly

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in a massive Fortune 500 company, So thank you for

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joining us to kind of tell us how to do this. Maybe we can

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start with Dow and the complexity of operating a

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business like Dow and just paint the picture for us as a current

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state.

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Yeah, well, before I do that, I want to thank you

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for inviting us to be a part of today. It is a great honor to be

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here and amongst such great colleagues. When I think about

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like the purpose of coming, I just want to thank you and the

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entire team at C3 AI for getting us together, because it is

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really valuable to share the stories with each other and hear

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where you're going, So thank you.

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Super.

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Yeah, you know, let, it again. Thank you for

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the great intro about Dow. I feel like, you know, magnanimous

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is quite nice, how you put that, But for those who may not know

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who Dow really is, at the end of the day, you know, we are 130

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year old company, so we kind of have some legacy about how we

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work. We are a material science company. We operate with about

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100 different locations that you can think about. We have 35,000

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employees around the world, and we operate some of the world's

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most complex and energy intensive assets, And so when I

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think about that, you know, we then transform chemistry into

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great products. It is true, you are surrounded by Dow from the

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chairs we sit in, to the lipstick on my face, to the

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shoes we're wearing, to the clothes we have on, but you also

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to think about some of the fun things that we do, Right? I

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think a lot about this room might care about data centers

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and we think about moving from water cooling to liquid cooling

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to the silicone that might be on the chipset or in your phone.

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So you can think about us in a lot of different ways, but all

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that complexity ties back to our really big assets, And I love to

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tell people these fun facts. One of them alone is like the size

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of Manhattan, right? three miles by three miles is a facility, So

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now you think about that asset and that asset, How do we take

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care of it? And that is where some of our partnership comes

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into play, But those are really important things to us, to keep

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running, to serve all of our customers and you around the

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world.

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So that's the core, and the upstream, if you will, is

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are these, I guess you call them steam crackers, so massively

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energy intensive, massively complicated to operate, units

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and when those things are operating well, everything

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downstream of that, all the products you produce into the

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various end markets are basically flowing through.

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That's actually where we started our journey, Deb, which is asset

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performance or asset utilization, So if you can

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improve the asset utilization by a percent makes a

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massive difference to Dow and obviously keeping it running

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but also improving the efficiency, So maybe you can

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just talk a little bit about the journey there.

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Yeah, well, and I think one of the great

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partnership elements between us and C3 is the knowledge you

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bring, and that is not easy to impress our team members with

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having extensive knowledge, So I think let's start there with the

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high caliber of people and the knowledge you brought to the

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table, but also this partnership word, and I do mean that

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seriously, in that within Dow, and you might imagine in an

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environment where I think the numbers we have, like 1,600

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phDs, you know, we have this real value of insight and

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knowledge and s of, you know, engineers, when we can put

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those two together, And I think that's really been the nice

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partnership. Is we've been able to take our knowledge and our IP

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and our internal capabilities and models and match them with

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C3 and the platform to really focus and in this particular

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instance, we're talking about our asset and increasing asset

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reliability, And so working together wasn't flawless to

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begin with, right? As most things you work

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through and tweak these things, but I think we've been really

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pleased with the partnership, And then, of course, we started

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in a certain class, and now we're also extending beyond, So

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starting about very narrow, and that was our approach. I know

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different companies have a different approach, but right

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we try to be very narrow within the landscape of Dow to prove

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value and then extend to a broader set of our assets.

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And I think the point about your PhDs and data

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sciences, et cetera, I think Dow is now self sufficient at

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basically configuring models, tuning models, deploying models

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so that actually was, it started with C3 doing some of that work

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on and partnering with the domain expertise that Dow has on

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operating steam crackers and furnaces and all that, But very

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quickly, Dow became self sufficient at actually using C3

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to tune their own models, and so that was an important part of

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the consideration, right.

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For us, for sure, right, is to be independent to

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well, we're good at asset operations, right? So this is

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not too dissimilar. It's an asset that we want to operate.

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But you know, we're also having conversations, are there other

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places to use, in this case, the platform or an asset to us to

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broaden across the landscape of Dow and get more value.

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And the journey, I think, was actually, is very

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similar to what Nikhil presented, that Koch FHR is on

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which is to it's hard to use, but it's autonomous site

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operations, But a very obviously, we have to be very

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concerned about, extremely concerned about the safety of

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the operations. Autonomous is not a light word to use in the

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context of Dow.

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No, and you know, hey, if we did have to have

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people operating, there'd be great thing if they were fully

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safe and secure, But I think we have to wait some time and

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distance before we're going to really be in that situation

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today where we're not going to have people there to oversee the

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decisions, or at least surround So for sure, I love the idea of

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fully autonomous, There just has to be a lot of proof points on

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the way for us to get there.

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So it's like the assisted lane versus completely

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autonomous.

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It's somewhere between, I think it's somewhere

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between gyms two and five, right? I think we're in the

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assisted but we're advancing a bit, and our aspiration is

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probably somewhere in there.

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Got it, Super, So Dow announced this massive

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transformation, which is super impressive. I think it's called

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transform to Outperform. Could you give some context on that

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and actually the choice of Transform to Outperform as the

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title for it?

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Yeah, And so maybe, similar to some of the

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people in the room that we have had three years of being in the

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bottom of a cycle, and that has proven to be financially

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difficult, and we are underperforming for where we

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would like to be, So just having said that, you know, we are also

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looking really internally at ourselves and saying, okay, like

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we have got to transform the way we work. There's all sorts of

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capabilities that we should be embracing. As I mentioned, we're

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130 year old company. We might have some legacy ways of working

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that we need to challenge constructively and really try to

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do differently, So our ambition is to take out 2 billion of

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cost. 2 billion. Yeah, 2 billion is the number, And so when we

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think about that, our aspirations are going to come

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from growth, but there's also some aspirations that are going

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to come internally, And so internally it's going to be, you

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know, how do we get more efficient? how do we streamline?

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How do we really look at the way we work? and then, of course

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when we do that, AI and automation are a portion of it.

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I'm not quite sure how the media wants to cover that, but it

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seems sometimes there's a there's a higher correlation

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that AI is solving all those issues. It's not, but it is an

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important ingredient in the steps forward for us, But really

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transform to outperform is what it is, right? Like, if we can

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transform internally, then we're going to outperform the

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competition, and at the end of the day, that's what we want to

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do. We want to beat the competition to satisfy you, our

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customers, at the end of the day.

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So give an example or two of that, So it's operating

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more nimbly in the customer side and then the operation side. Can

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you bring it to life for us?

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I can bring that to life for you, And if you

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allow me to talk about, maybe I'll intertwine AI a moment for

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you, Right? If you allow me to do that, because it isn't wholly

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going to be AI, but I do want to at least share a bit about this.

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So when we think about, or at least I try to talk about AI

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internally. I try to talk about in three ways. One is you as a

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person, right? You have your own AI. You're gonna have your own

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AI agents, you know, hopefully you're all loving copilot in

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your daily lives. Our leaders love it to help at year end

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review time, right? Like it's certainly making you more

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efficient, And then the other two ways that I would be

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thinking about AI, at least within the landscape of Dow, is

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from our end to end processes, So you can think of your standard

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order to cash processes, right when we think about like, how do

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we have the start and the end, hire to retire, any of these end

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to end processes, we are starting to look at, how do we

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use AI agents and other automation more extensively than

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we have historically. The third way I would talk about AI, and

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do talk about it, is within specific domains, So within R&D

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how are we using AI to help us get to innovations faster? But

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that doesn't really affect the finance team, right? It's really

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contained within a domain, and this is where we often talk

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about C3 today for us, is playing in the domain of our

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operations space. You are helping us make our assets more

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efficient, and we're using A in that regard, but to stitch that

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all together in transform to outperform we're really

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evaluating end to end, and those processes and practices in

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streamlining the way we do the work we do, and where will AI be

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A big part of that, or just simply streamlining the

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processes we have? Supply chain planning might be a good place

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to think about in terms of streamlining, to transform the

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way we work and outperform where we are today and where our

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competition is.

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Super, I like that framework. It actually mirrors a

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little bit of what Nikhil was Does.

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It Does. That was not planned. That was not

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planned.

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So I think Dow, you've identified an order of nine end

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to end processes.

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Yeah, nine or ten, somewhere in the direction

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and then for each of those there might be

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yeah.

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Supporting domain specific capabilities that get

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orchestrated, And then this team level automation, that's

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kind of the third layer in this process, And so when you pull

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all this together, Dow transforms, so you basically are

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forecasting better what products are needed, so that you can

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exactly you've got it.

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Schedule production better, so that you can have the right

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that's the picture.

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Levels of inventory and so you can serve the customer, on time

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in full Exactly you've got it That's the picture. Maybe if this is relatable to

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in full

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some, but within the landscape of Dow, we have some businesses

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that are truly more of a commodity type business, and

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then we have a specialty type business. You'd know that those

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are different in terms of sophistication and complexity

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for sure, if you try to manage your working capital in a

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certain way to optimize what is good for your commodity

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business. It's actually not great for your specialty

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businesses, right? Because you're trying to reduce your

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working inventory, So we're trying to manage between these

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dualities that we live in terms of the landscape of Dow

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and for sure, to your point about trying to streamline these

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processes in terms of, can I have a little bit more inventory

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in these and how do I optimize for a specialty business, and

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where can I really get efficient on my commodity business in the

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inventory? So it is a struggle today. Like I said, we've got

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some legacy things that we're working on, but our aspiration

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is to really aggressively, and that's why we're announcing

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these things, is to aggressively hit at these different ways of

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working

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and it is aggressive. I mean, your timelines, this is 2

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billion, not in five years.

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No, it's in two years. Yeah, And we already had a

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brilliant. Like, we already had one before we tried to do

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you know, so, yeah.

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So this is moving fast, so maybe turn to, Deb

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the hard part, which is, how do you get everybody on the same

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page? How do you get it working with business, working with your

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commercial, working with, so, how do you operationalize this?

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Yeah, and, you know, it's not an easy thing, right? I

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think we've all would probably have some commonality in that. I

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think the number one thing to work on is, our collaboration

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right? and I think to where we started, even with our

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partnership, is you got to work through some of the difficult

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moments. Think we're all aligned on the prize. Sometimes it's how

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you get there, And so it's a really strong collaboration that

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we're trying to bring between the business and the outcomes

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they need. Our team as a technology team, where is our

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purpose in helping achieve those outcomes? And then we think

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about partners like C3, how do we have you be a part of the

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table? we're not going to build everything. I love again, the

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platform, And I think Nikhil's question is, Are you gonna go

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build all your own? no, we just don't have the time at our pace.

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How do we strategically think together? Where do we get to

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leverage a platform and a strong partnership to bring into that

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intimate circle of really trying to transform yourself, because

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you're not going to bring in every vendor to do that, but

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where we have strong vendors and strong partnerships, I think is

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really important to collaborate and work on the really difficult

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task at hand, with candor, with trust, and most importantly

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with the results.

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Super, and so just to kind of summarize that, where

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there are pre-built applications you can roll out very quickly

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that might be like, C3 AI Demand Forecasting or supply network

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risk, etc, For the long tail, there is C3 Code, which

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you saw this morning.

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I did get a personal demo this morning because I had to

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miss some things yesterday.

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What did you think?

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No, you know, actually, you know my team was part of my team was

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with me, and I was, like, doing a little elbow jab. Because I

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was like, okay, we have some really old code, not that any of

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you have this problem, we have some tech debt in some of our

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environments, including like VB6, which I know we're, you

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know, alone in that category, Everybody else has fixed that

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problem, But we were, we were at least saying, hey, that

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might be really transformative to taking care of some of our

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tech debt. We had been talking about supply chain and using

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capabilities, but with code, we were definitely brainstorming

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from that venue to this one, about where could we really see

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some capabilities and some value, and how could we go do a

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pilot on that pretty quickly, And I think everybody's pretty

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optimistic that there's some real value to be had in the tech

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debt and remediation of tech debt without maybe as much

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effort, because we just don't have the time and energy to

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replatform all of those things, Right?

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I actually hadn't thought about that angle, but

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that's true. As Nikhil kind of showed again, if you can express

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the business problem in English, we can then interpret that and

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generate code that's consistent to the platform, So yeah, it's

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using all the same ontologies. It's using all the same security

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guardrails and interaction with the LLMs, etc, to actually

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recreate and reduce the footprint. Of a lot of it

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costs in that area.

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Again, and very old assets that are all around the

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world with different people who created different solutions over

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A long period of time, you know, it's just too much effort to try

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to harmonize those all in one big effort, And so it'll be

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interesting to see, like we love to be a proof point, at least in

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our brainstorm on the way from there to here, which was, hey

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could you help us with that, let alone the other tasks at hand?

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Because most of most IT budgets, I'm not

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asking about yours here. Deb, just to be clear, is basically

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in maintenance and keeping the lights on.

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It is, And if you want to transform to outperform, how

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do you lower your cost of maintenance and increase the

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oxygen you need to do the new fun stuff, right? and I think

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classically, if you're running a technology budget, you're really

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good if you got 80% maintenance and 20% projects, wouldn't that

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be fun if that were a little bit different? I mean, I'd love to

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tip that upside down, But even if I got to 50/50, in a

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manufacturing world now, financials and banks have

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different metrics for that 80/20 rule, but in our landscape, if

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we could really pivot that, you could either create the oxygen

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you need to go do the new things, or lower your overall

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cost.

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Super, something we could talk about

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we will.

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Off stage.

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Have the team join in, right? Have everybody join

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in.

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Let's do it. Just a couple of couple of other

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topics. I know Microsoft is a huge partner for Dow.

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Absolutely.

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Can you talk a little bit about how you see kind of C3

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and Microsoft accelerating Dow's journey?

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Yeah, And I think this is what I meant earlier

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when I was talking about the collaboration we need to

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transform. I think we need those few really strong partners, And

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you know, trust is earned. I don't know that it's always just

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granted, And when I think about the partnership, C3 AI and

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microsoft come with already a great partnership, and we

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individually have great partnerships, So I think, you

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know, we're better together when we can come in and deal with the

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difficult situation, So Microsoft's just been a

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tremendous asset along the way. You know, in our Azure

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environment, we're exclusive to Azure in that regard, So we do

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have high expectations, though, that for both of those

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companies, you bring us your best resources, And so I do

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think, as I said earlier on, like you have brought and

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impressed our organization with some really great talent, And I

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think the combination of Microsoft's talent, Dow's

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talent, and C3 AI's talent, I get excited about, what else can

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I challenge you guys with, or what else can we come up with

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along the way?

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Yeah, and C3 is obviously working with Microsoft

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to integrate and use all their latest services, And then we're

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working with Dow to make that, operationalize that adapt.

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There is one other kind of dimension, Deb, that I wanted to

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touch on, which is, you have a innovation arm, which is a

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licensed technology licensing arm.

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We do.

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Maybe talk a little bit, just give the audience a

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little bit of context on that, because I think you package up

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your IP and, yeah, show others how to run steam crackers across

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the globe.

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Yeah, I'm gonna do a little bit of a talk about, I

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have some experts in the room, So after this, like, if you have

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interest in understanding innovation. There's a great team

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here who would be happy to engage more, But if I, at the

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beginning, told you about the various expertise we have

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between our engineering and our PhD chemists, we do in the

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traditional material science way, have abilities to license

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our IP and that's innovation, is the arm that licenses those

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things, and over time, we have partnered with C3 AI to say what

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we have created in this space for our assets and how we're

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actually using C3 AI along with our IP, Should this not be

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something that we can help others who run furnaces and

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crackers and assets like we do, jump start and leapfrog to a

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solution, So innovation is the way of using what we have

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co-created and licensing it to others so they can have speed to

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market, instead of having to start at ground zero and

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benefiting from our investment, but also we can pay it forward

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and then earn a little bit from that IP along the way.

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So that's a that's another dimension of the

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partnership, which is when we say, deploy C3 AI Asset

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performance or Reliability into Dow, we're actually

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incorporating Dows decoking- models, proprietary models, if

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you will, then that solution is packaged up and then made

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available to the industry.

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Yep made available to industry Unovation is happy to talk about that and what it

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might bring to help others, As I said, like accelerate from what

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we have spent time, because we've been working for a few

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years together, right? I think we've been four years at this.

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So how do we help you accelerate and get to value as well?

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Super, maybe I can just conclude on what advice would

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you have, Deb, for this audience that's embarking on their

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transformations?

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You know, and it's always an interesting question Is, what

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advice do you have? I would really start and, first of all

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like the intentions you're trying to achieve, Sometimes I

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think we approach different efforts like these

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which are, hey, I just have a short term task, and I need some

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sort of result, and I'm gonna go fast, and I'm gonna call that a

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transactional situation. I think when we've approached C3 AI

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it's been more about a longer term journey, And if that is

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where you're at, then How do you treat this as a partnership

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where you're trying to say, okay, I'm going to start here

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but with a platform like this, there's a lot of capability that

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you can have in your future, but staying focused, and I will say

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we stayed very focused in our asset way, right, in terms of

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looking at this is where we want to target and now through a

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partnership, So I guess my advice is, are you trying to

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achieve a short term tactical solution to fit a problem, or

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are you trying to achieve a longer term partnership with

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greater outcomes? And again, we've been able to co-create and

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collaborate and create a better outcome, because I think we

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oriented ourselves on commitment to partnership, and this is

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quite transformative, if you choose it to be, So I would

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orient myself on that, And then I think the other thing is, be

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open to new ways of working, like we've really had to explore

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different approaches, and a trusted partner can hold a

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mirror up and say, well, yeah, I know you've done it this way

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but perhaps we should think about doing it a different way.

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That's great. Thank you for that, but, it's really

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consistent with what we're focusing the company on, which is better

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supporting rapid scale up of these transformations, so it's

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absolutely consistent with that, We're really looking forward to

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going on this autonomous Dow journey with you, and really

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really appreciate you joining us today. Thank you.

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No, thanks for having me And hopefully everybody has a

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great transform.

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Excellent, Yeah thanks so much.