Watch Oracle’s Stephanie Trunzo on Infinia ML’s Machine Meets World.

Oracle’s Stephanie Trunzo on the Human Emotion of Digital Transformation

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James Kotecki
Sep 23 · 8 min read

Episode Highlights from Machine Meets World

This week’s guest is Stephanie Trunzo, Oracle’s Head of Transformation and Offerings.

“I think about digital transformation as, really, the process of identifying how a business is going to shape their new future by leveraging technology differently than they have in the past. And I think the connection to AI and ML is that so much of it is about data and being data-driven and connecting those thought processes around how you’re going to leverage structured, unstructured, etc., data in different ways as part of that evolution.”

“Part of the process of changing large organizations is accepting that it does take time. It takes repeating things. It takes a lot of false starts. When you’re talking about large scale transformation, you’re talking years, you’re not talking quarters.”

“Working in silos will never offer the opportunities to find those aha moments of where something net new could be created or something disruptive could be created. It will sound really far out there, but get an artist in residence, get an anthropologist, get people from different ways of thinking together to look at those problems.”

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Audio + Transcript

James Kotecki:
This is Machine Meets World. Infnia ML’s ongoing conversation about artificial intelligence. I’m your host James Kotecki. My guest today is Oracle’s Stephanie Trunzo, the Head of Transformation and Offerings. Thank you so much for joining us.

Stephanie Trunzo:
Yeah. Super excited to be here

James Kotecki:
Head of Transformation and Offerings at Oracle seems like a title that you could do a lot with, but also a title people might not necessarily understand at first. What do people think that you do?

Stephanie Trunzo:
I think people have no idea what I do, to your point. But what I actually do is help us think about, from an Oracle perspective with our clients, how do we help them transform with technology and how do we bring all of the great technology that Oracle has into a shape and offerings that make sense for our clients to get to the outcomes that they need to get to. So my job is really about not only helping drive our clients’ transformation, but our own transformation in Oracle, so that we’re defining the way we go to market in a sensible way.

James Kotecki:
What’s the relationship between artificial intelligence, machine learning, and then digital transformation overall? Those terms are often used certainly in the same sentence, maybe interchangeably by some people who think that digital transformation means AI or vice versa. What does it mean to you?

Stephanie Trunzo:
Right. I think about digital transformation as, really, the process of identifying how a business is going to shape their new future by leveraging technology differently than they have in the past. And I think the connection to AI and ML is that so much of it is about data and being data-driven and connecting those thought processes around how you’re going to leverage structured, unstructured, etc., data in different ways as part of that evolution. And it’s really tied really tightly with how you’re going to look at how cloud plays, what that digital transformation means for your company overall. They’re not disconnected concepts.

James Kotecki:
You’ve talked about about transforming three different kinds of systems: systems of record, systems of engagement, and systems of intelligence. So can you unpack those concepts a little bit and what they mean and what people get wrong about that?

Stephanie Trunzo:
So, Gartner introduced something several years ago called bimodal IT. And the idea was that people started really struggling with, how do you serve both systems of record, which are kind of legacy systems, things that have been architected over time, generations of people making decisions, not necessarily intelligently or intentionally — but those are the sources of truth. Those are the systems of record, meaning those are the systems that run the business. And then there’s this conflict with the systems of engagement or interaction, which are the applications where the users live. So these are the points of intersection where people are really doing things with the applications. This third system, kind of like while they’re still struggling with these two, there’s this almost threat looming out there that, you know, AI, ML, all these things we were just talking about earlier, if you’re not paying attention to investing and getting ahead on them, you’re going to miss out, you’re going to be behind, your business is going to get disrupted.

Stephanie Trunzo:
We talk about transforming all three — trimodal IT — looking at all three of those systems, organically and in concert that they’re not three separate siloed systems. It’s not just maybe migrating a legacy application to the cloud. Are you doing it with a thoughtful process of saying, okay, let’s make sure we can intelligently unlock the data in that application as part of the migration to the cloud so that now it’s feeding our systems of intelligence? We can get an AI learning model based on it. We can look at data lakes, you know, the things that they need to do to kind of leap frog the story forward.

James Kotecki:
What’s the dominant emotion, if you could kind of aggregate people’s emotions when they’re going through a transformation like this? Is it fear? Is it anxiety? Is it hopefulness? Is it begrudgingness because this is just one more thing I’ve got to do among the many other daily responsibilities that I have? What’s the emotion driving a lot of this?

Stephanie Trunzo:
It’s a great question. It’s all of those things. A CEO of a big global organization spent a year and a half, maybe more, having incremental discussions about really adopting a different kind of approach towards transformation, but not actually taking any of the steps. A lot of kind of lip service discussions, discussions with the board, that sort of thing. And there was this one pivotal phone call. I will never forget the phone call where he said, “I am emotionally ready.” And so, you know, there was this moment where he kind of said, “okay, I’m not just going to talk about this anymore. I’m ready to commit to it.” And the business changed almost overnight. I mean everything about it. He drove down into the organization a whole new philosophical approach of looking at transformation and kind of driving a real kind of change mentality into the business that it was everybody’s responsibility. I think even just asking the question “What’s the emotion around this?” is probably a great starting point because I don’t think that it is one of the natural go-to kinds of conversations that are happening around transformation.

James Kotecki:
For the CEO who said, “I’m emotionally ready” — maybe you were thinking “finally” — but when you look back at that, is that just how long it takes? And maybe if that person had not been emotionally ready, they wouldn’t have been able to make the rapid decisions that they made after they had made that emotional decision. Does it just take people a lot longer in your experience to get there?

Stephanie Trunzo:
Part of the process of changing large organizations is accepting that it does take time. It takes repeating things. It takes a lot of false starts. When you’re talking about large scale transformation, you’re talking years, you’re not talking quarters. So there’s a lot of incremental change that can happen along the way, but those decisions, yeah. And of course I was like, “yeah, it’s about time,” but it’s easy for me to be ready for someone else to change their business. It’s a lot harder for them to get to a place where — and once that commitment happens and the switch is flipped, so to speak, I always see things happen faster. Now there’s a commitment I’ve gotten over enough hurdles. It’s, you know, the fear is out of the way. And I think enough familiarity too, of knowing what it’s going to look like when they get there.

James Kotecki:
There’s two frameworks that you’ve talked about, the ego-centric and the system-centric ways of thinking about and applying AI. And I want to just take some time to unpack that.

Stephanie Trunzo:
I think of this as like a lens, you know, which lens are you going to put on the problem? Because both are relevant, both are useful. They just are different ways of looking at it. And depending on the problem you’re solving, you might choose a different one. So the idea with an ego-centric lens is that AI, ML, technology period is replicating the human senses. So, you know, it’s an ego-centric approach from the perspective that I’m the — you know, I can only understand things through the lens that I have as a human. Robotic surgery assistants that are helping surgeons or even autonomous cars to some degree, like self driving vehicles, they’re doing things that we as humans know how to do, and we’re just replicating our ability to do them. A system-centric lens is saying, we’re going to look at all the parts of the system and raise them all to their highest value.

Stephanie Trunzo:
And so that means in a full system, the humans in the system, the technology in the system, the environment, the context, the weather, you know, all of the things that kind of make up the full system. Diapers.com, they organized their warehouse in a way that if you walked in as a human would make absolutely no sense. It needed to make sense to the parts of the system that were doing the work, which was the technology in this case. If you had applied an ego-centric lens to that problem, you would have ended up with a warehouse organized that made sense to humans in trying to solve the problem of faster robot pickers.

James Kotecki:
You’ve still got humans that are emotional, intuitive beings that are running these processes and making these decisions about where to allocate resources and what to go forward with. How do you, and how does anyone, get executives to think in terms of jobs that people can’t do? It’s very easy to say, “Oh, a person did this. I’ll get a robot to do it or a computer.” Now you have to come up come up with ideas that are kind of outside the realm of even human tasks in general.

Stephanie Trunzo:
Working in silos will never offer the opportunities to find those ‘aha’ moments of where something net new could be created or something disruptive could be created. It will sound really far out there, but get an artist in residence, get an anthropologist, get people from different ways of thinking together to look at those problems. Maybe pick some of the POC hypotheses and give it to someone who has absolutely nothing on the surface to do with solving that problem and see if they can’t come up with some different way of looking at it where you could apply AI and ML and technology to get to a completely different place.

James Kotecki:
Stephanie Trunzo is the Head of Transformation and Offerings at Oracle. Thanks so much for being here on Machine Meets World.

Stephanie Trunzo:
Thanks for having me.

James Kotecki:
I am your host James Kotecki. Thank you so much for watching. You can email the show mmw@infiniaml.com. You can like us comment, you know what to do. Thanks so much for watching. That’s been what happens when Machine Meets World.

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