Transcripts
Data governance should not mean no, it does not mean stop compliance, doesn't mean stop the innovation.
Speaker A:It just.
Speaker A:Let's sit down and have the discussion.
Speaker A:I might say no, but that might be the word.
Speaker A:But if we change this, if we do this, maybe we can come up with an idea that will foster some new innovation, that will foster some great idea, like how to get the value out of the data you just mentioned and continue to move forward.
Speaker B:Welcome to behind the Product, a podcast by Sep, where we believe it takes more than a great idea to make a great product.
Speaker B:We've been around for over 30 years building software that matters more, and we've set out to explore the people, practices and philosophies to try and capture what's behind great software products.
Speaker B:So join us on this journey of conversation with the folks that bring ideas to life.
Speaker B:Hey, everybody.
Speaker B:Welcome back to the show.
Speaker B:I'm your host, Zach Darnell.
Speaker B:Our guest today is Karen Hyman.
Speaker B:She's the VP of Data Governance at Rolls Royce.
Speaker B:We talk a little bit about her journey, but specifically in her current role leading data governance globally in a highly regulated and complex business.
Speaker B:We discussed some of the nuances and practical approaches that she's found to be helpful.
Speaker B:And just a quick note that this episode is actually kicking off a series that we're doing on the show focused on data.
Speaker B:With data becoming more and more important in our world of technology and business, we thought it'd be helpful to explore this area and share various aspects.
Speaker B:Really hope you enjoy this series.
Speaker B:If there's something specific that you'd like us to talk about, shoot us a note@podcastep.com all right, let's get to the show.
Speaker B:Hope you enjoy.
Speaker B:All right, so I thought we could start with just a little bit of context setting for anybody listening who doesn't know who you are.
Speaker A:Okay.
Speaker B:Obviously you've been at Rolls Royce for a little while, 12 years, just a little bit.
Speaker B:And you've probably been in a few roles up until that point.
Speaker B:Just based on LinkedIn.
Speaker A:Yes, yes.
Speaker B:So I thought maybe we could start there, tell us a little bit about maybe the summary right before Rolls Royce, and then maybe what it's looked like to be at Rolls Royce through some of the recent transitions that I've read about and kind of like the current role.
Speaker B:Let's level set.
Speaker A:So I went to college for computer science and mathematics.
Speaker A:You didn't have to spell, you know, was the joke.
Speaker A:But very logical brain, you know, coming out.
Speaker A:So I came out of college, went directly to IBM as a software engineer.
Speaker B:Oh, cool.
Speaker A:It was way back when, you know.
Speaker A:So I was one of the only females, right.
Speaker A:In my gr.
Speaker A:I was the only female in my class.
Speaker A:That graduating class for computer science at IBM.
Speaker A:I worked at a customer site.
Speaker A:So they had outsourced all of their IT work, network and software.
Speaker A:And I was part of the software team.
Speaker A:It was.
Speaker A:Can't say enough about the experience there, but I did everything, you know, back then.
Speaker A:I created the databases, I designed it, I coded it, I tested it.
Speaker A:It was all.
Speaker A:We thought we were on the high end when we went to C at the time, but I was a COBOL programmer.
Speaker A:If anyone knows COBOL still, Rumen might
Speaker B:be able to relate.
Speaker B:I don't know how far back you go, buddy.
Speaker C:Never did cobol.
Speaker C:It's a FORTRAN though.
Speaker A:Yeah.
Speaker B:Okay.
Speaker B:They're like cousins, right?
Speaker B:Close enough.
Speaker C:It was an era.
Speaker A:So I would say that was my first foray into data.
Speaker A:Right.
Speaker A:You didn't realize it back then, but I was creating the databases, I was creating those relationships.
Speaker A:I didn't do an entity relationship diagram.
Speaker A:Right.
Speaker A:Didn't know what that was back at the time.
Speaker A:So my career with IBM lasted several years.
Speaker A:I started getting into project management because we had to do it all.
Speaker A:So I was kind of doing both.
Speaker A:And I found out I liked doing plans once again fit into my logical brain of mapping something out.
Speaker A:So when I left IBM, I decided to become a full time project manager.
Speaker A:But I stayed in the IT space because that's what I knew, that's what I was comfortable with.
Speaker A:So I went to a smaller company than IBM, not saying much.
Speaker B:There's a lot of those out there.
Speaker A:A lot of those out there.
Speaker A:And it was a full time project manager there.
Speaker A:I was certified through certificate at IUPUI and enjoyed it.
Speaker A:Happened on LinkedIn to see a posting for a project manager at Rolls Royce and thought, let's give that a shot.
Speaker B:Oh, so that was your foray into roles was as pm.
Speaker A:Was as a pm.
Speaker B:Oh, wow.
Speaker A:So I was a PM for the data team.
Speaker A:So I had, I had all of the, you know, the projects, led all the projects that they were working on.
Speaker A:But that was my first foray into a strictly data type role.
Speaker A:Yes, we were, you know, the data engineers were creating all the software and stuff, but it was my first foray into that and my first foray into something highly compliant, highly sensitive where you have to start thinking about the rules.
Speaker A:It's not just building something, it's the access management.
Speaker A:Who can see it and where can it be placed?
Speaker B:That's only getting worse now with CMMC here.
Speaker B:Less soon, right?
Speaker B:Yeah, not worse, just more.
Speaker A:Yes.
Speaker A:So I have been with that team pretty much, you know, from start, from my start until almost to where I am now.
Speaker A:I don't work with.
Speaker A:They don't report directly to me now, but I still work with them on a high, you know, on a basis.
Speaker A:So I became, you know, project manager, program manager, manager of the team.
Speaker A:And then Rolls Royce saw the need for the data governance.
Speaker A:You know, they saw what was happening with the NIST rules with the CMMC in the US and then I also look at a global team, so I have to worry about the UK rules, the EU rules, any of our customers.
Speaker B:So it's like DoD and Mo mod.
Speaker A:Mod.
Speaker A:So it's Cyber Essentials plus which is based on CMMC, the NIST rules.
Speaker A:So they're similar.
Speaker A:So if we put in, if we put in the rules and the processes, we can just do one and roll
Speaker B:it out to everybody.
Speaker A:To everybody.
Speaker B:Okay, so the kind of Venn diagrams overlap quite a bit.
Speaker A:Yes.
Speaker B:Yeah, that makes sense.
Speaker A:I mean the process is due about only certain nationalities can see this now.
Speaker A:The exact nationalities.
Speaker A:Right.
Speaker A:That's a different story.
Speaker B:Sure.
Speaker C:And in your current remit, are you mostly focused on defense or defense and commercial?
Speaker A:Both or so in my.
Speaker A:So I do sit in the defense business, but I've also taken on a look at the global capability for it.
Speaker A:So that has been a lot of my work here in the past years.
Speaker A:What are, you know, globally, what are we doing?
Speaker A:One of the things we're trying to do is roll out a global process for data.
Speaker A:Not one for defense, not one for our civil business, not one for our power systems.
Speaker A:What is a global process that everyone can use?
Speaker A:So yeah, I do come from the defense background, so I always will interject that in there in those global meetings.
Speaker A:But it's just needed.
Speaker A:But yeah, I am looking at it from a global point of view.
Speaker B:I've heard data governance, governance in general can be a little bit buzzworthy, not to discount it, but just people have different definitions.
Speaker A:Exactly.
Speaker B:How do you think about.
Speaker B:How would you describe data governance to somebody else?
Speaker B:Just for somebody listening, that's not steeped in this world.
Speaker B:What's their mental model?
Speaker A:So it's all about for me is making sure we're doing the right correct thing for our data to be in compliance and reducing the risk.
Speaker A:Those are, it's around compliance and risk from my point of view, or at least in the role I'm in and
Speaker B:given the fact that this is across the globe, not Even just the U.S. what are the things that are gnarliest inside of those two things?
Speaker B:Think about process and you think about risk.
Speaker B:What are the things that are hardest to manage inside of those two buckets?
Speaker A:For me, it's about being a global company with global data.
Speaker A:But yet the compliance is very tricky because we might have the same set of data across the pond as in the US but.
Speaker A:But you can't see them, you can't merge them.
Speaker A:So it's all about that compliance of how do we properly use the data and be able to get the best value from the data but still be compliant.
Speaker B:Do you find that it can be challenging sometimes to.
Speaker B:You've got this background of starting as an engineer.
Speaker B:Raman, I appreciate this about him.
Speaker B:He was a software engineer at SAP Day 1, and I get to ask him stories from yesteryear about those days.
Speaker B:And he can relate to something at a very deep technical level that I'll never be able to do.
Speaker B:You find that because of that background that you have, you can bridge that gap between the other business leaders across Rolls Royce that you're working with, working with technical teams to kind of bring those folks along for the ride.
Speaker B:What does that look like inside of your organization?
Speaker A:I think it's very helpful.
Speaker A:Right, because like you said, our businesses, they don't care.
Speaker A:Care where the data sits or they just want to be able to use the data.
Speaker A:But yet I can talk to the enterprise architects technically enough to help explain the business problem and what needs to be done, and I can sit in on those meetings and understand and not be lost.
Speaker A:So if the enterprise architects are delivering me a piece of software, I can have those conversations with them to give them my not only my requirements, but also help, you know, talk through the whole process and the discussions from a business point of view and from a IT background point of view.
Speaker A:And so.
Speaker A:And then in talking with the business, it also helps, you know, convert those requirements, you know, into something I see what the business wants, I see what the business needs.
Speaker A:How do you talk to your IT folks that are delivering the tools?
Speaker A:Because I don't deliver any tools.
Speaker A:I just sit there and here are the processes on using the tools, or here are the tools I need to deliver my processes.
Speaker A:So I kind of span those two layers.
Speaker A:And I think having the IT background just helps me tremendously.
Speaker A:And I also a joke.
Speaker A:I always tell my team I was a software engineer.
Speaker A:I can know when you're lying to me.
Speaker C:You're BS Detective.
Speaker A:Yes, yes.
Speaker B:It's there.
Speaker A:It's there.
Speaker B:I appreciate those of you that can do that.
Speaker C:So you must deal with a lot of different kinds of data.
Speaker C:Maybe talk about that a little bit.
Speaker A:So we have, you know, we're a defense company, so you have that data.
Speaker A:We have, you know, we have hr, we have employee data.
Speaker A:So there's all of that PII data that you, you have to worry about.
Speaker A:And then we have a power systems business that has a different sorts of regulations on them.
Speaker A:They sit in Germany.
Speaker A:And then we deal with data from structured, which most people, when they think about data, thinks about structured data.
Speaker A:Right?
Speaker A:The data that sits in the database.
Speaker A:Well, no data is unstructured.
Speaker A:I try to get across to Rolls Royce.
Speaker A:Everyone touches data every day.
Speaker A:You just don't realize it.
Speaker A:You're creating an email that that's data.
Speaker A:You're creating a word document or PowerPoint presentation.
Speaker A:Right.
Speaker A:So we have to be able to solve and put in place the processes for all of that.
Speaker A:The one process that will fit for everyone across all the businesses and still be able to deliver as one global Rolls Royce.
Speaker B:Do you feel like, is that a feasible goal?
Speaker B:Like, I could make assumptions that you've got, I don't know, I'm going to say 60,000 employees.
Speaker B:I'm probably wrong there, but there's a lot.
Speaker B:50.
Speaker B:Okay.
Speaker A:I was too far off.
Speaker B:Hey, you've got these three main business units that you just talked through.
Speaker B:Is there really a single process that could apply to everybody?
Speaker B:Like, is that even a feasible thing?
Speaker B:Or is it like the 80, 20 rule?
Speaker B:You know, like the Pareto principle?
Speaker B:I can get mostly there, but then, you know, there's a little bit of nuance here, a little bit of nuance there.
Speaker A:It goes down to yes, at a high level.
Speaker A:And we rely a lot on the Dharma organization.
Speaker A:Right.
Speaker A:I don't know if you guys, if you're a member of Dharma, so it's data management professionals.
Speaker A:So they have something called a dumbok.
Speaker A:They've already done this.
Speaker A:I'm not going to reinvent the wheel.
Speaker A:So let's let them follow the data management lifecycle.
Speaker A:We can put that in place.
Speaker A:Now, when you get to those lower level details, like each team will might have a specific need.
Speaker A:And then as long as I have the high level, and then they can go and throw their processes, but as long as they're following my high level and then just add what they need to theirs, I think it solves it.
Speaker B:Oh, okay.
Speaker B:So there is some room to move within the box.
Speaker B:But as long as you're in the box, we're good as long as you're
Speaker A:in the box, as long as you've thought about it.
Speaker A:And like I said, let's look at these industry standards that are out there and just rely on them to help us along.
Speaker B:I would have made the assumption that because defense civil power systems, you've got really stringent rules on the defense side of things in multiple countries, you wouldn't be able to use the industry standards because those industry standards would apply to less regulated environments potentially.
Speaker A:Well, it's just about adding the regulations into it.
Speaker A:If you think about that data management life cycle, right?
Speaker A:Create, change, store, share, then archive, delete.
Speaker A:That's just one high level life cycle of a data.
Speaker A:Everyone's doing it.
Speaker A:It's just what do you add into each step?
Speaker B:Yeah, that was not the assumption I would have made.
Speaker C:Have you found that sort of the rabid investments in AI, whether they're productive or not, has put a strain on that or raised the urgency of your work?
Speaker A:I think it hasn't put a strain on it.
Speaker A:I mean, I'm excited about what AI can do for us.
Speaker A:It's all about getting value back for Rolls Royce.
Speaker A:So I'm excited.
Speaker A:I want to be able to share the data.
Speaker A:Has it put an urgency?
Speaker A:I don't know if I'd call it an urgency, but it's put a need out there to make sure you have good quality data, make sure that you can use the correct data or you are using the correct data for the right answers.
Speaker A:So it's put a need for that.
Speaker A:But that's no different than any other app that was out there 20 years ago, I think.
Speaker A:But it's just, I think having AI out there, it's that name, it's that visibility, which is a good thing.
Speaker A:I am so happy people are talking about data.
Speaker C:No, I share that.
Speaker C:So sometimes we'll walk into a conversation and somebody is very excited about pursuing some kind of solution with AI.
Speaker C:And very often immediately after they say that, great, now let's talk about the data that's going to feed this thing.
Speaker C:And there's always a set of epiphanies that follow, like, oh, this is where we are now, we need to go get those things cleaned up.
Speaker A:Yeah, we joke.
Speaker A:It's always, you have that saying garbage in plus whatever still equals garbage out.
Speaker A:That's the joke.
Speaker A:So
Speaker B:have you guys had some recent, I'll say, like customers, whether they're commercial or defense, interested in more, I'll say, AI things?
Speaker A:I would assume so.
Speaker A:I have not been Involved with direct external customer talks about that, but I would assume.
Speaker A:So everyone's talking about it.
Speaker A:So how can we help them with their data?
Speaker B:Yeah, I could again make the assumption, given that it's a DoD environment or MoD, whatever that is, they wouldn't be one.
Speaker B:They wouldn't be interested in using that or would be too afraid to use it, given the sensitive nature of that.
Speaker B:But I don't know.
Speaker A:There's still always.
Speaker A:You can put controls around it, right?
Speaker B:That's true.
Speaker A:You can do it on a very limited set of data.
Speaker A:There's all about.
Speaker A:To me, it's not just the big AI, but it's all about machine learning.
Speaker A:We've got this data, how can we learn from this data and make improvements?
Speaker A:So I would think anyone wants to do that to create some value for our customer or for Rolls Royce that makes sense.
Speaker B:What about the technology stack?
Speaker B:We've got the process and maybe some overarching modern ways of thinking about data governance.
Speaker B:You mentioned that we're not responsible for the tool set, but I would imagine it informs to some degree the tools and frameworks, platforms that you guys can operate within.
Speaker B:Is that true?
Speaker B:Not true.
Speaker A:I think it's the other way around.
Speaker A:By what frameworks and what we can operate in and how we have to operate kind of maybe informs what tools we use.
Speaker A:Okay, so because of we may need to host something here and here and different spaces that might limit us because how can it all talk in the end?
Speaker A:But my requirements go in and I might sit on the discussions of what are the three top tools and let's rank them and do it.
Speaker A:But I think it's the tools that we have looked at are capable and there's big tooling out there now in data governance, data cataloging, data quality, all of the things data.
Speaker A:So it's a good time to be starting and looking at them.
Speaker B:I have an interesting question, but it's a complete pivot, so I'm going to make sure Raman doesn't have a follow up.
Speaker B:All right, you just mentioned for good time for data right now.
Speaker B:It's probably been trending in that direction for the last few years, especially with LLMs and all the generative stuff going in there.
Speaker B:What would you tell the person that's wanting to get into a data role?
Speaker B:Because that's, that's probably a new wave of job security coming up here.
Speaker B:What would you.
Speaker B:What given your path, what should they know?
Speaker B:What should they be thinking about?
Speaker A:If you follow my path, it's like start at the bottom, like we said, you know, we started start as either a developer or even a data analyst and then go to maybe you know, some, a data scientist or an information management.
Speaker A:For me it would be all about learning the processes, you know, getting in with what is new on the forefront, getting into these organizations or these groups that, you know, just think outside the box, you know, or have industry standards.
Speaker A:But it's about knowing, I think everyone should have that foundation because if you don't have that foundation and that understanding of what an entity relationship diagram looks like, of what tools I can possibly use if I'm going to have to classify my data, there's a lot that goes into knowing it.
Speaker A:And if you don't have that foundation of starting from the scratch, I think it would be more difficult because if you look at my team, most of them, they don't all come from an IT background, but they come from that they have dealt with data in some sort of way.
Speaker A:So if you want to be a data architect or you want to lead a data governance team, you've got to know that foundation, but you've also got to be following what that industry is doing, doing out there.
Speaker C:I have a follow on that.
Speaker C:I'm curious and maybe test a theory.
Speaker C:I have always thought to be any good at the data work even I'm going to say very low level data engineering work, you probably have to have a deeper understanding of the business like what is this data, where's it coming from, where it's going to, what's its purpose than I would say even a lot of software development, I find it in my experience.
Speaker C:I'm wondering what you have seen.
Speaker A:So the best data engineers are those that can talk to the business, that can understand and sit down with the business and say, all right, map me through your day to day and watch it.
Speaker A:And then in their head the business might not be showing them, but the data engineer is following the steps of the data and where it needs to be.
Speaker A:You know, from ingest to egress.
Speaker A:Right.
Speaker A:So I fully agree with that, that those are probably the best data people, but you also have those people that just come in from day one and can just see it.
Speaker A:So you know, there, I won't say that's the only way.
Speaker A:There are just some of those outliers as well.
Speaker A:Right.
Speaker B:One of the things that I was thinking about as you guys were chatting just there, so you know, I like to classify myself as more of like maybe a business minded guy that happened to work in tech for the last 20 years.
Speaker B:So I'm technical, but I've never been an engineer and I like to understand things well enough to at least be conversant data.
Speaker B:So far this year, it's been harder like a steeper learning curve for me for some reason than other things I've had to learn in the past.
Speaker B:Do you have kind of a, as you're working with maybe like your business partners that aren't as technical across Rolls Royce?
Speaker B:Do you have the three things that you try to educate them on?
Speaker B:I'm creating a number for you.
Speaker B:So that may not exist.
Speaker B:What are the things that you think?
Speaker B:Some of the folks that need to at least just have a conversational understanding of data and what's important, what they need to understand as it relates to making good decisions.
Speaker A:So it's that whole data flow, understand the flow of their data and that can be easily be done.
Speaker A:Just sit down and talk to me and write in words what you're trying to do, where your data is coming from, receiving it in an email and then you're putting it in this application and then you're sending it through some secure FTP site.
Speaker A:I'm making something up, sure.
Speaker A:But that's number one is being able to talk them through.
Speaker A:And I think you can do that at a high level, enough that you don't need to be technical.
Speaker A:And then it's about getting them to understand what is their role and responsibility as a data steward or a data user.
Speaker A:So, so that is something that I think every company needs to define for their company is what is their role, what are the data roles and what are you expecting from them.
Speaker A:And then the third and final point that I'll put from my compliance hat is around compliance, right?
Speaker A:Understanding what is maybe the classification of data, what are the controls around that data?
Speaker A:Once again, you can talk high level, you can talk that from a.
Speaker A:You don't have to get technical and say, hey, you need to put these RBAC models and something on that.
Speaker A:But who can see this data in general?
Speaker A:But to me, those are the three big things that I think would make a successful transition from a business project that's helpful.
Speaker B:Actually, it's not as in depth as what I could assume in my head, you know, because you hear all these words and it's like, well, how deep do I really need to go to actually understand this to help inform a decision?
Speaker A:And that's why you have, you know, or at least that's why I have a data team to help you.
Speaker B:Right.
Speaker A:You know, you don't, you don't need to know everything.
Speaker A:Now there are those people that are going to be curious and will learn and we will engage with them and love them because it makes my life easier down the road.
Speaker A:Right.
Speaker A:But you know, rely on the data team.
Speaker A:We're there to help.
Speaker B:I love that.
Speaker B:Innovation's another hot buzzword that's been around longer than data has been hot or AI has been hot here in the last few years.
Speaker B:However, it is a vital part of most businesses as they continue to grow and stay competitive in the marketplace.
Speaker B:They need to continue to have more things that they come to market with or maybe make small things better.
Speaker B:Again, I could make the assumption that this is challenging inside of your world given all the constraints that you guys have to navigate with DoD MOD, civil power systems, complex business.
Speaker B:How do you handle data access for maybe something coming out of an engine that you guys are making?
Speaker B:We need real world data to then inform the next generation.
Speaker B:Is there any challenge there as a business that you guys have to handle from a data governance or data perspective to foster innovation?
Speaker A:I mean, there's always challenges.
Speaker A:Right?
Speaker A:But I also want to say data governance should not mean no, it does not mean stop compliance, doesn't mean stop the innovation.
Speaker A:It just.
Speaker A:Let's sit down and have the discussion.
Speaker A:I might say no, but that might be the word, you know, but if we change this, if we do this, maybe we can come up with an idea that will foster some new innovation that will foster some great idea like how to get the value out of the data you just mentioned and continue to move forward.
Speaker A:We do have to think about compliance, right?
Speaker A:You know, I mean, that's just a day to day.
Speaker B:Probably not.
Speaker B:You don't want to get sued by the dod.
Speaker B:That's probably good.
Speaker A:Well, I mean, I think we all need to think about data, right?
Speaker A:It's not just, it's not just the dod, it's just data in general.
Speaker A:So.
Speaker A:But data governance should not equal no.
Speaker B:You might hear no, but no, but I like that.
Speaker B:How does it inform your own personal data philosophy?
Speaker B:I know Raman and I have talked about this a little bit, you know, like free service.
Speaker B:Gmail is probably the easiest example.
Speaker B:Like I know they're looking at stuff and I get to use that service for free and I don't really care.
Speaker B:I personally, Zachary, I don't care.
Speaker B:I'll use that service for free and I'll use a ton of them for free.
Speaker B:And it just doesn't bother me too much.
Speaker B:But some people have a very strong opinion about, well like that my data should Be mine.
Speaker B:And a lot of data advocacy, privacy advocacy, in that kind of bucket.
Speaker B:I don't know, I'm kind of curious where you land on this.
Speaker A:You know, I'm more strict now, obviously, that I'm in this role.
Speaker A:I do go back and look like, you know, LinkedIn.
Speaker A:What data have I put out there on LinkedIn?
Speaker A:I'm very careful where you give it.
Speaker A:I do have a Gmail account that I use for those.
Speaker A:What I would hope would be my junk mail.
Speaker A:I don't check it, you know, but
Speaker B:where you get your free codes and 30% off.
Speaker A:Something like that.
Speaker A:Right.
Speaker A:You know, but I am very careful, you know, more so now than what my date, you know, what data is out there?
Speaker A:What data do we share?
Speaker A:So no credit cards, like if I'm traveling or something, you know, let's not put my credit card information on a phone while sitting in the airport, using the airport WI fi or something.
Speaker B:Okay.
Speaker B:So there's some habits that are baked in.
Speaker A:There are some new habits that you've had.
Speaker A:Yeah.
Speaker B:Do you ever give anybody, like, here are the three things that you should be thinking about, like, I don't know, over Thanksgiving and some spicy conversations with family like, grandma, you really shouldn't be doing that.
Speaker B:Come on.
Speaker A:No one asked me about what they should be doing.
Speaker A:It's more they come to me here, fix this.
Speaker A:I usually get called after the fact.
Speaker B:Are you your family's IT person?
Speaker A:Yes, I was.
Speaker A:But now that the younger generation is coming on.
Speaker A:Right.
Speaker A:They know more about it than I do.
Speaker A:I joke.
Speaker B:Oh, it's the beauty of this not being live.
Speaker A:I am so sorry.
Speaker A:I thought I turned it off.
Speaker B:How dare you have a telephone potential spam.
Speaker B:Uh oh, you should probably answer that one.
Speaker B:They probably want to ask you some questions about your data on my work phone.
Speaker C:So here's my current version of what you described.
Speaker C:And I think it was the exact same thing when everybody started Twitter, Facebook, Insta, whatever.
Speaker C:Like, it's free.
Speaker C:That means you're the product, your data is the product.
Speaker B:Right.
Speaker C:So now I find myself educating, frankly, fairly highly placed people who are using free versions of ChatGPT or Claude or whatever.
Speaker C:You have to understand everything you're putting in there.
Speaker A:I do not have a TikTok account.
Speaker C:That's what you're paying with, right?
Speaker A:I do don't have a TikTok account.
Speaker A:I don't have an Oura ring.
Speaker A:Because that's their new thing.
Speaker A:That's how they're making money, is they're selling your data.
Speaker A:Now I do have an Apple Watch.
Speaker A:And some people are like, isn't that the same?
Speaker A:I was like, it's a little bit more controlled on the Apple Watch.
Speaker B:It does seem like, yeah, Apple seems to have a pretty good grasp on privacy.
Speaker B:Interesting.
Speaker A:So it's things I think about now that were before.
Speaker A:I probably.
Speaker A:I would love to be able to have the ring and not the watch.
Speaker B:Oh, really?
Speaker B:You don't like the Apple watch?
Speaker A:I'm just.
Speaker A:I'm done with it.
Speaker A:I don't, you know, I don't like.
Speaker A:I'm now to the point where I got it for a very specific reason, like being able to have text all the time was a very.
Speaker A:And now it's like, no, I don't want to be able to.
Speaker B:I don't want to be left alone.
Speaker A:Oh, yes, exactly.
Speaker A:Exactly.
Speaker C:I'm curious.
Speaker C:I think you've made a pretty compelling case that, yes, Rolls Royce has some interesting data scenarios, but good overall governance frameworks more or less cover most of that.
Speaker C:Now, where I wonder if in aerospace you have a sort of different scenario is you have these scenarios.
Speaker C:Rolls Royce makes the power system and somebody else makes the airframe, and potentially there are others.
Speaker C:And then you have a defense customer who wants all the data and who owns what data and how is this data flowing between you and who's making.
Speaker C:I don't know if you could talk to that.
Speaker C:Any interesting perspectives about that?
Speaker A:You know, it's about how the contracts are in place, what data we can get, and we just have to.
Speaker A:In the end, there are customers.
Speaker A:Right?
Speaker A:Customers are always right.
Speaker B:So even if they tell you to violate their own restrictions, Right?
Speaker A:Yeah.
Speaker A:It has not happened that I know of.
Speaker A:So luckily we don't have to worry about that.
Speaker A:But, yeah, we've got to be able to handle what they give us and have those conversations.
Speaker A:This is either why we want the data or this will help you.
Speaker A:So we've had certain instances where, no, you're not going to get the data.
Speaker A:Okay, that's fine.
Speaker A:There's nothing we can do about that.
Speaker A:But we're in a partnership with, like you said, airframers or with our customers, so we're here to help them.
Speaker B:Is data governance like, I'm going to say, like the processes and risks?
Speaker B:Is this an active game or is it a.
Speaker B:We're going to put a plan in place and it's going to run pretty well for five to 10 years, and we're just going to make sure to execute the plan for five to 10 years and then maybe we'll take a Look at it again.
Speaker B:Or is this something that is ever evolving?
Speaker B:I'm going to kind of like assume something like CMMC never came out and is not, you know, coming up here later this year.
Speaker B:But.
Speaker B:But assuming that was not the case, is, is this one of those things where it's a big design up front and then it's just about stewarding the plan forward?
Speaker B:Or is there an ever evolving conversation around the how we have been in
Speaker A:an ever evolving conversation up to now.
Speaker A:Okay, I would love to get to a place where it's like, all right, it's just running.
Speaker A:It's in place now.
Speaker A:Let's go improve.
Speaker A:But the world's been changed.
Speaker A:I mean, AI has come so quick.
Speaker A:Think of all the innovation has come so quick.
Speaker A:And data's always at the forefront.
Speaker A:I don't want to say we're reacting, but were a part of that foundation.
Speaker B:So I mean, you have to respond to the market.
Speaker A:You have to respond to the market.
Speaker A:So eventually, you know, and maybe not,
Speaker B:maybe, maybe it will always continue to
Speaker A:be, but it's interesting this way.
Speaker A:Right?
Speaker A:You know, it keeps my life fun.
Speaker B:That's true.
Speaker A:Life is never boring.
Speaker A:When you go a day at work.
Speaker B:Yes, that is my personal nightmare.
Speaker B:Boring days at work.
Speaker B:Yeah, that would drive me nuts.
Speaker A:Maybe one or two would be nice a year.
Speaker C:Okay, that's fair.
Speaker B:That's fair.
Speaker C:Can we talk about the CDO network?
Speaker A:Sure.
Speaker C:Is that inbound for our conversation?
Speaker B:Let's do it.
Speaker C:I would love for you to tell the story.
Speaker C:How did this come to be?
Speaker C:And man, what is it for?
Speaker A:Okay, so for.
Speaker A:So we have partnered with Tech Point to create the CDO networks.
Speaker A:Chief data officer is the term.
Speaker A:But we realized not all companies have a chief data officer.
Speaker A:So we're just looking for your highest level data person, whether it's analytics, AI, in my case, data governance.
Speaker A:But how it started is when I took this role, there was already a Indianapolis CDO forum in place.
Speaker A:It was a grassroots built with help from some.
Speaker A:Someone that is big in the data community.
Speaker A:Kind of worked as well with CDO magazine.
Speaker A:So it was already in place.
Speaker A:I joined, I joined the committee, you know, the planning committee as well.
Speaker A:So sat on there for several years.
Speaker A:People moved on and off the planning committee.
Speaker A:You know, people left the company.
Speaker A:So we were having less and less support from, you know, the original companies that helped set us up.
Speaker A:So it came to be.
Speaker A:Bill was chair is we kind of called it, and I was his vice chair chair.
Speaker A:And it got to be.
Speaker A:For the past couple years, it was just Becoming harder and harder.
Speaker A:It was all on us to come up with topics, get people to go, where are we going to host?
Speaker A:Even just the logistics where we're going to host it.
Speaker A:And we didn't have a budget for food and drinks, and we didn't have time to go look for sponsors.
Speaker A:So one of the days, Bill and I, we would talk on a quarterly basis, and he works, you know, near my home.
Speaker A:So we always like to meet in the middle for lunch.
Speaker A:You know, Rosie's Cafe, if you ever go.
Speaker A:We love it in Carmel.
Speaker B:Zionsville or Carmel.
Speaker A:Carmel.
Speaker A:Carmel.
Speaker A:Carmel's in the middle.
Speaker A:I do like the scienceville location too, you know.
Speaker B:Yes, it's quaint.
Speaker A:Yes, it's quaint.
Speaker A:So one day we were just like, well, what can we do?
Speaker A:Who can we get to help?
Speaker A:So we just started brainstorming, and I think a CIO meeting had just happened.
Speaker A:And I was like, either he or I was like, what do we.
Speaker A:We reach out to Tech Point.
Speaker A:So Rolls Royce had already been a Tech Point member, and I contacted our contact, and actually, I think Allegian was as well.
Speaker A:So we reached out to Ginger and just said, hey, we would like to know if you would have any interest in bringing this on, like, the CIO network.
Speaker A:So I want to say that was like June or something.
Speaker A:Maybe even.
Speaker A:Maybe even, you know, a little bit earlier.
Speaker A: , early summer, time frame of: Speaker A: Of: Speaker B:Oh, wow, that came together quickly.
Speaker A:Yeah, it did.
Speaker A:And so they were interested.
Speaker A:They started reaching out.
Speaker A:And, you know, the.
Speaker A:Bill.
Speaker A:Bill and I now laugh.
Speaker A:You know, they wanted to sign a contract.
Speaker A:We're like, okay, we'll sign it.
Speaker A:But I mean, this.
Speaker A:The indie CDO form has no, like, say there's nothing, you know, but okay, if, you know, you want to own it.
Speaker A:I don.
Speaker A:We didn't care.
Speaker A:So, yeah, so like I said, that happened late spring, early summer.
Speaker A:And then we had several meetings where we discussed some topics, what we were looking for.
Speaker A:And we were very clear that we did not want this to be.
Speaker A:We wanted to keep the high level, those people making decisions.
Speaker A:That's where we wanted to sit in the space.
Speaker A:If you wanted a data engineering or just an AI conversation, that's not where we're sitting.
Speaker A:We want the highest level of your data person for your organization.
Speaker A:So they agreed.
Speaker A:And then we started planning our kickoff, which happened, I believe, in August.
Speaker A:I believe.
Speaker A:And yeah, from there, we now have a full committee.
Speaker A:It's not just Bill and I planning the Events.
Speaker A:We have three or four other people, I can't remember offhand.
Speaker A:And you know, Tech Point drives it.
Speaker A:Tech Point does all the logistics.
Speaker A:They do the sponsors and Bill and I just get to sit back and enjoy the fun and do what we're good at.
Speaker A:Right.
Speaker A:Let's plan these topics.
Speaker A:All right.
Speaker A: our topics planned for all of: Speaker A: 's going to be four events in: Speaker C:You want to give a teaser or a top secret.
Speaker A:So the first one In February is February 19th will be information versus knowledge versus data management.
Speaker A:Differences, similarities, you know, just that discussion.
Speaker B:I love it.
Speaker A:Yeah.
Speaker B:And then Q2.
Speaker A:Q2, I can't remember what because since we're planning Q1, I can't remember what
Speaker B:we're actually, I'll make sure whoever's listening to this, it's in January.
Speaker B:That way there's a little bit of, a little bit of time for them to register and go find you guys.
Speaker A:Yeah, yeah.
Speaker A:So yeah, go to if you want to join.
Speaker A:It's, you know, Tech Point has made the decision.
Speaker A: At least for: Speaker A:So, you know, we are looking for all industries and, you know, all size companies.
Speaker A:You know, someone came up at the breakfast, you know, this week and said, hey, well, it's just me, I'm a one stop shop.
Speaker A:I was like, well that means you're the decision maker for your, you know, your company.
Speaker A:Please join us if you're curious.
Speaker A:And he did.
Speaker A:He had some data questions and so he joined.
Speaker B:That's really good.
Speaker B:What's your vision for the CDO network?
Speaker B:What do you hope it becomes?
Speaker A:I hope it becomes.
Speaker A:I want it to be that place where if you have questions, people go to.
Speaker A:And I want it to be for all of Indiana too, not just Indianapolis, but I want it to be that.
Speaker A:It's all about being that community, that community of space.
Speaker A:And that's right now what we're looking for is to have the community community where we can go talk.
Speaker A:Yes.
Speaker A:We have quarterly events but my favorite outcome of that would be is a group of three or four people got together and then they're like, oh, we have the same problem.
Speaker A:Let's go do a happy hour talk.
Speaker B:Yeah, let's meet at Rosie's.
Speaker A:Yeah, let's meet at Rosie's.
Speaker C:Yes.
Speaker B:I love it.
Speaker B:That's fantastic.
Speaker B:Well, that's where you and I met, I think was the kickoff for the CBN network.
Speaker A:Yes, exactly.
Speaker B:So that was perfect.
Speaker B:We're starting, we're going Rosies.
Speaker B:Isn't our future good?
Speaker A:All right.
Speaker B:Thank you for coming to spend time with us and sharing a little bit about your journey and CDO network and what's going on in a very highly regulated global enterprise when it comes to data, because that does not sound like an easy task.
Speaker A:Well, we're up to the challenge.
Speaker B:Thank you so much, Karen.
Speaker A:Thank you.
Speaker A:It.