About this episode
Think back to when you were first learning to swim. How’d you do it? Chances are, you weren’t thrown into the ocean being circled by sharks. We sure hope not, anyway.
You probably picked it up under the watch of a lifeguard in most cases.But once it became second nature, the lifeguard didn’t hold SO much power. Well, data engineers are the lifeguard, and if there isn’t a checks and balances system between them and the business teams, the engineers will be determining your every move in AND out of the water.
Join Catalog & Cocktails hosts Juan and Tim, with special guest Allison Sagraves as they discuss how you get in the water by yourself without drowning.
Speaker 1: This is Catalog & Cocktails presented by Data. world.
Tim Gasper: Hello, everyone. Welcome to Catalog & Cocktails presented by Data. world, the catalog for leveraging agile data governance to power people and data. We're coming to you live from Austin, Texas. It's an honest, no BS, non- salesy conversation about enterprise data management with a tasty beverage in hand. I'm Tim Gasper, longtime data nerd and product guy at Data. world joined by Juan.
Juan Sequeda: Hey, Tim. I'm Juan Sequeda, scientist guy here at Data. world. And as always, it is a pleasure to spend the middle of the week, end of the day, and go chat about data, have our honest, no BS chat about data. And today, we have a special guest. And this has a little bit of backstory. So, it's Allison Sagraves who is the former CDO at M& T Bank who's an advisor to startups who is a guest consultant. And she's also a beekeeper. And first of all, Allison, how are you doing?
Allison Sagraves: I'm doing great. I'm in the forest near the hives in Buffalo, New York.
Juan Sequeda: Well, I think it's already pretty dark over there. It's still kind of sunny here in Austin, Texas. So, the background story is I was at Gartner and I was at a dinner and we were supposed to sit with people who we did not know. And well, I haven't met Allison and I sat next to her. And five minutes in, I'm like, " I am so lucky I sat next to Allison." We had this phenomenal conversation. We ended up karaokeing that night also. And I think 10 minutes in the conversation, I'm like, " You need to be a guest in the podcast." And here we are. So, super excited to have you here. So, yeah, we're going to have a lot of fun.
Allison Sagraves: Very excited to be here. And that was certainly a fun night. I have not done karaoke in I don't know how many years. And if my family's listening now, they've heard. So, there you go. Your mom's doing karaoke.
Juan Sequeda: I got video evidence on that. So, if people want, you can go ping me. But all right, well, let's kick this off. And tell us, so what are we drinking and what are we toasting for? Allison, kick us off.
Allison Sagraves: Okay. I am drinking red wine. It is a Washington State Red. And the reason I'm drinking red wine is that this wine was served at my daughter's wedding in May. She's from New York state. So, she did a white wine from New York State, Dry Riesling. And her husband is from Washington State. He's my data partner in crime. He may creep into the story at some point. And so, we did a red cab at the wedding, Chad, whatever. So, that's what I'm drinking. And we are toasting to the Buffalo Bills who are playing tomorrow and this has got to be their year. So, to the Buffalo Bills.
Juan Sequeda: All right. Tim, how about you?
Tim Gasper: I am drinking a Roberto Roy. If you're familiar with a Rob Roy which is a Scotch Manhattan, this is a Roberto Roy. So, you switch the vermouth to be Punt e Mes which is like a vermouth but very herbaceous, so tasty, little slightly boozy cocktail. And I will toast to USA moving forward in the World Cup. So, another sports callout, I'm very excited about that.
Juan Sequeda: Wow. Well, I have another boozy drink here. I looked it up. It's called And to All a Good Night cocktail. And this is in sad honor because Mexico just lost so they're not going to be around anymore. My wife is Mexican. So, this is a bourbon and tequila with orange bitters and Angostura bitters. So, also very boozy right now. But still cheering all for World Cup. Every four years, it's something that I look forward to and my entire calendar's all blocked to go watch all the games. Last week, I was waking up at 4:00 or 5: 00 in the morning to watch games, watching games for eight hours straight and then started to work at 3: 00 in the afternoon. So, it's only every four years so it's fine. Cheers. Cheers to sports then. That's what we're cheering to today.
Tim Gasper: Cheers.
Allison Sagraves: Cheers.
Tim Gasper: All kinds of football.
Juan Sequeda: So, our warm- up 20 questions a day. So beach, lake or swimming pool, what's the most fun body of water and why?
Allison Sagraves: Swimming pool because I like to see the bottom and I don't like to share the water with fish.
Juan Sequeda: You have a very... I like how you had that answer right there.
Tim Gasper: That's very succinct. What about you, Juan? What's your choice?
Juan Sequeda: I say it used to be swimming pools just because... I mean, they're always there. But recently, I've gotten more into beaches. My in- laws, as I said they're Mexican, they live in Playa del Carmen in Cancun, so not a bad place where I get to just go visit my in- laws at the beach. So, I've got used to the beach more and more. I'm not a big beach person but I like to sit and sip on a drink, on a cocktail margarita, on a beer and look at that beautiful ocean, for sure. So, beach. How about you?
Tim Gasper: I like the privacy of a swimming pool if it's your own swimming pool but the environment of the beach. So, if I can have my own private beach then that's perfect.
Juan Sequeda: Wow. Fancy. We got to work a lot more.
Tim Gasper: We got some work to do. We'll try.
Juan Sequeda: All right, well, let's just kick to the top. So Allison, honest, no BS, how do we get into this pool, into the data pool, into this data world without drowning?
Allison Sagraves: Well, I guess I would just say that having been in this field for a long time, really on the enterprise data management side of it and as a CDO and now advising and so forth, I'm really interested in just getting in and swimming. And while I don't want to swim with fish, I do want to swim with data. So, I think we just need to make it easier for people. And I'll talk about like, " Does it need to be everybody or should this be more targeted to just really just jump in the pool and really just work with data." We need to figure out how to tune this operating model because in my experience and in talking to a lot of CDOs and people in this field since I left my role a few months ago, there is just kind of this gulf between the progress we've made in terms of data being available and people actually being able to use data to actually derive business value. And I think that there's just too much abstraction and people just need to get, I don't want to mix too many metaphors, but we need to get our hands dirty or whatever. We need to play in the water so that we can just get smarter and evolve. And that's actually why I've enlisted my son- in- law to set up a cloud environment and we're going to do some swim lessons in the cloud.
Tim Gasper: I love that. Get hands- on. Get your hands dirty.
Allison Sagraves: Yes.
Tim Gasper: That's great.
Juan Sequeda: So, I mean, is it just about on the business side just getting that fear, just jumping in? What are the barriers that we have to take a while so people can just literally jump in? Because I get that there's like, " Oh, for you to go swimming, you have to do this and that and that." Is it about barriers that we have to eliminate to make it easier or is it just you need more courage and just literally put your bathing suit in and just get in?
Allison Sagraves: Well, yeah, I think a pool is in a way a good analogy in the sense that a pool is a controlled environment. I mean, people use the word sandbox so I guess we'll use the word pool for today. There are lifeguards to make sure that you don't drown. There are lanes. There are edges. It's not too deep. But you have freedom to experiment but within the confines of some parameters, some guardrails, some controls. And I feel like that what is needed at least on the offensive side of data. From banking, there's a whole defensive side that's a different topic. But on the offensive side where you're really trying to monetize and drive value, you really need some freedom to experiment but within guardrails, boundaries and policies and so forth. So, I would like to be able to jump into a pool and know that I am not going to drown. I'm not going to turn an organization upside down but I'm going to get wet and learn and maybe flounder a little bit. And there's a lifeguard there to save me if I do anything really stupid. So, I just feel like we need to get people... We need to just break this barrier between the people that build things and the people that think of things and just smoosh that much closer together because you just can't ideate in a vacuum. You got to be in it to iterate and to create. And I think we're moving toward that. I mean, certainly, that's the model that we're moving toward. I think it's just way easier said than done.
Tim Gasper: Yeah, I totally agree there. And I think one interesting thing is you mentioned this, the people who are doing the building, the people that are doing the thinking and how do you get them to work together? Or maybe another way to talk about it is more of your engineers, your technical folks, your data- savvy folks and then more of your business folks and folks that aren't as savvy with data. It can be a little easier I think sometimes for the tech- savvy folks to jump, do their cannonball right into the pool. Whereas some of the business folks, they're a little worried and maybe part of that's the technology. And a lot of that may be just the confusion around terminology and just like, " Is there too much BS going on right now in the space where it's like there's mesh, there's lakes, there's this, there's self- service, there's governance, there's so much going on."
Allison Sagraves: All the different tools out there, though.
Tim Gasper: Is there too much confusion? Is there too much BS? How do we bridge all that?
Allison Sagraves: Yeah, I think there is a lot of confusion and I think that this industry really got a complex. Nothing's ever good enough. We've never done enough. We've never built enough. We've never whatever enough. And we just have to give people permission to fail, to screw up. I know Randy Bean wrote a book, Fail Fast, Learn Faster. In fact, it's helping prop up my computer. I've got several books holding up my computer. That's one of them. But yeah, I think it's easy to get lost in the technology. I think we've kind of solved for the technology in a way at this point. And the tools make it much easier to do things in an agile kind of way. And now, we just need to I think give people more freedom and more access. But I think that at some point, I like to talk about I don't know that that's everybody in an organization because I think that we get... Everything is overdone in this business. I think we have to find the people that are working on the things that really matter to the organization in terms of real profitability. Focus on those kinds of use cases and start with them and get those people in the pool working with data and then having some wins and then expanding from there. We tend to think like, " Okay, now we've got to train everybody in the organization." And everything becomes overwhelming. We just need to break things down into achievable steps.
Tim Gasper: I mean, if you tie that to something like data literacy or something like that or self- service. So, can I read a little bit into what you're saying here and that doesn't... Maybe people think that means everyone like everyone needs to be able to do all the things and have access to all the data and all the tools when really it sounds like you're saying, " Hey, this can be a lot more focused?"
Allison Sagraves: Yeah. I mean, I think that a potential failure, a point is that when we scope things too large and we do things at an enterprise level. I mean, you can have a plan to take things to an enterprise but I think you need to start where it counts. So, in service industries, it's probably with a customer. In manufacturing industries, it's your products and your manufacturing operations and so forth. I mean, I think you don't need to get everybody swimming at the same pace out of the gate. I would focus on getting some real... I mean, I'm overdoing any analogy which is really embarrassing, but really getting some true champions in domains that really matter to the business and that are really going to make a difference to the outcomes of the company and the strategy of the business. And I think we need to give people a bit of a pass to say, " Hey, it's okay, we're not going to focus on accounts payable." I'm picking an area. Or, " We're not going to focus on these other areas," because we really need to understand our customers and we're going to focus on that domain and we're going to start there. I'm not saying everybody has to focus on the customer but I think we need to give people permission to, say, to be selective.
Juan Sequeda: This is a true air of honesty. Because a lot of the times, what you start hearing and reading is like, " Yeah, daily literacy, we need to go train everybody." And the point is like, " No, stop it. What are you going to go gain?" Okay. Again, the magic wand example. Magically now, everybody gets trained on data. So what? What's going to come after that? And I think that's why we need to start picking and then understand where is the money, how do we make more money, where's the profitability? And it's just so annoying that we just focus all on the tech, on the data and let's make sure everybody has access to it when we really should be focusing on making sure that we know what we're doing so that we can help drive revenue. So, I'm really glad that you're saying this. And let's be skeptical and challenge sometimes. Do we really need to have that data literacy project program for everybody? I think that that's a strong statement because a lot of people are like, " Yes, we do." And I'm like, " We don't."
Tim Gasper: Or have the same expectations of everyone.
Juan Sequeda: That's the other one, too.
Tim Gasper: Like, " Everybody needs to be trained on Tableau. Everyone must learn Python," things like that.
Allison Sagraves: Yeah. I mean, I think if you want to say, "Okay, everybody needs to be data literate," that's fine. But people may have levels and you may even need to start in some areas. So, I think we need to have permission to change the conversation a little bit because I think that this industry is just like everybody beats themselves up about everything all the time. I mean, I had this thought and then I tested it with a bunch of CDOs that I've met at Gartner and at other events over the summer and fall. And I would say, " Hey." I guess I would point out from the NewVantage survey that's done every year, the new one's coming out in January. This is Randy Bean's company. They say that 75% of people that answer the survey, executives and data, say they're getting value from their data or AI initiatives. But then when they're asked, " Do you have a data culture," I think it was like 19% or something like that that said they have data culture. So, what's that gap between getting value and having a data culture? So, I think that... And so then I started talking to some CDOs from like these were Fortune 100 companies and they were apologizing. I mean, I can't even tell you who these people were but these are world- known names. And they would be apologizing for what they had not done and yet they had accomplished these incredible things. I'm like, " What are we doing wrong that we focus on everything we don't do instead of celebrating, promoting what we do, do and leveraging that to gain momentum and gain funding for our future initiatives?" So, I think there's a bit of a complex in this industry, quite frankly.
Juan Sequeda: So, we're seeing great comments here. I think I see Kara here who says, " I completely agree about Allison's comment. Not everyone needs access to all things and know all things." And then we also have Terry who's saying, " We need to be focusing on training key data advocates, people who can deliver bite- size data literacy and competencies to the people that work with when it's needed. That puts skill acquisition in a perfect position to immediately address the what's- in- it- for- me question." So, that last piece, what's in it for me? This is something that we just miss completely and when we just focus on training for the technical stuff, we miss the big picture. So, this is that transition. And I'm really curious to see how much we can keep on this analogy of the pool. Let's keep pushing this. So, it's like we want to ... Okay, let's go swim but first of all, not everybody needs to get into the pool first of all. And second, not everybody needs to be swimming laps and knowing how to go do freestyle and butterfly. Some people are going to stay on the shallow end so they'll be comfortable there. There are some people who will be very comfortable in the deep end. So, how are we doing with this analogy? Keep this going.
Allison Sagraves: I think it's good like dog paddle is okay. Dog paddle is okay.
Juan Sequeda: Yeah, but this is great.
Tim Gasper: I'm writing that down. We take notes. I'm going to write that one down.
Juan Sequeda: Yeah, dog paddle is okay. Write that down-
Allison Sagraves: Let's just start with dog paddle. I mean, I'm not saying you should live like you should die only being able to do dog paddle, but you have to start being able to float.
Tim Gasper: Yeah. Well, one topic that's I feel like this is related to that, Allison, we talked about in some of the conversation ahead of time before our podcast today is this idea of data products. This concept is becoming very popular now in data circles. And it probably begs more questions than answers per se. But I know some of the goal there is how do we make it easier and more manageable with data and how do we think more about how people get value from data, from all sorts of different technical levels and data literacy levels? Do you have a position on data products? Is that going to help with this swimming problem that we're talking about here?
Allison Sagraves: Well, I mean, I think the idea of data products is a good idea and it's a proven idea from software and so forth. So, I think it's the way to scale. It's the way to ultimately have more of a system around how you treat data assets and get value out of them. I think what I see and what I've now seen in this industry is that we're always looking for what's the one thing that's going to make this all better. And so now, we're like, " Data products. It's all going to be solved by data products." And so, I've actually been thinking about... And again, I am not anti- data product, I'm actually pro- data product. I think this is the proper direction. But I don't think that we've done the work to think about what does it take to actually think of a commercially- viable data product? If we actually thought about what is the skillset that it takes to think about how you actually come up with such a thing. So, I think we just assume we're going to name somebody a data product owner and they're going to magically take this data and magically turn it into something commercially viable. And I don't think we've really thought through what that entails. And I'm not saying that I have the answer, I'm just saying that I think we need to be a little more thoughtful about this notion that just proclaiming that we're now going to organize around data products is suddenly going to solve things. And I was thinking about I actually cannot stand the phrase data is the new oil. I hate when people say things like-
Juan Sequeda: Doug Laney agrees very much with that.
Allison Sagraves: I hate that and I hate it when people say software is eating the world. I hate... I can't stand this stuff. But I do want to use an oil analogy here because I was thinking about this.
Juan Sequeda: We lost the pool analogy now. We're going to oil.
Allison Sagraves: We're going to oil and then we'll come back to the pool. You can just bear with me on this. That's why I'm worried about all these analogies. But I remember... Do you remember when the book on oil, The Prize, Daniel Yergin? You guys probably weren't born when this book came out. He wrote this book about how oil determined the course of humanity and civilization and everything. I remember... Okay, so I'm going to confess, I did not read the book but I read several reviews so I got the concept. And I remember being shocked by the fact that when Rockefeller created standard oil, the consumers for that oil were people that had lamps. By the way, I'm in my cabin. I do have an oil lamp so I can say I'm an actually consumer of that. So, when you think about oil, the market was lamps. It was how many decades later that the internal combustion... And trust me, I know nothing about freaking engines. But the internal combustion engine was created that ultimately created the market for oil that we know of today. And so, I feel like we need to have a sense of patience around what it takes to think of new markets for data. And patience because it takes work to invent and to think of new ways of doing things that are fundamentally different from prior eras. Patience but also urgency around the opportunity that we're presented with. So, that's the tension that I see is that I do think this is the right way to organize but I think we're a little unrealistic about that this is just a magic solution. Because you need the ingenuity, you need somebody to figure out. You need people who can figure out how to actually create products that have real value. And if that were easy, none of us would be working for companies. We would all have invented a product and we would all be running our own business and selling our product. It's very hard to actually create a product, bring it to market and make money off of it. And so, why do we think that suddenly proclaiming we're in the land of data products is a silver bullet.
Juan Sequeda: This has been a very profound rant that you have said. This was very, very important. I think it's... So, you started by minute 21 here. I just want people to go and make sure they'd listen to this. What you just said, we need to be patient to think of new ways of doing things but also have that urgency, that's one very valuable thing to go think about. And then the next thing is why do we think building products is such an easy thing? And I would argue that I think it is easy. And Tim, let's question what we've been doing here. We've been talking a lot about our ABC framework and we stated in a way as if it's like, " Yes, it's what we should do." Now, Tim, you have a product background and you do dedicate your career to creating products. So, you have that pedigree there. But I think this is something that sometimes we make it sound so simple. Yeah, it's just our ABCs. This is a framework that Tim and I have been building is data products should have accountability boundaries, contracts and expectations, downstream consumers and well- defined explicit knowledge. We try to simplify it but we got to be honest, it's not that easy.
Tim Gasper: Yeah. I mean, the ABC's simplified and make it easier to talk about it. And I think that's why it's one of our popular talks that we give is that it's trying to simplify something hard. But the honest truth is I agree with you, Allison, that products is hard. And so, my background is primarily in product management, software product management. And the process and the mechanism of building products is hard. And then if that wasn't hard enough, there's this whole aspect of product market fit. You can build a great product and then nobody uses it. And so, I think that just because to your point, we've come up with this idea in data circles of data products, " Oh, we've got it, that's the silver bullet." But we don't even know what to do with that silver bullet light. Because what does it mean to build those products? What does it mean to manage the life cycle of those products? Juan and I lately have been talking about data marketing. Just because you have a product doesn't mean people are going to use it. You have to market it. You have to enable around it. So, I don't know, Allison, as we're ranting here if we're triggering anything in your thoughts.
Allison Sagraves: Yeah. I mean, I do think it's the right way to organize and there are certain things that are natural products in any organization that obviously this makes sense for. I just think the notion that proclaiming that we're now organized around data products is suddenly going to be a magic pill to solve the monetization and getting value from data issue. I don't think we'll be successful if we don't look a little deeper into what it takes to really get value from data. I just think it's not... If it were easy, we would have done it at scale across industries. And certainly, a lot of amazing things are happening in many sectors. And so, not to minimize human progress in terms of medicine, energy. I mean, amazing things are truly happening but I think we have to be realistic about how hard this is.
Tim Gasper: Right. The time it will take for the value to fully come to fruition. What needs to change? What do we need to evolve here?
Allison Sagraves: I think that we need to have... There's something about the kind of people we put together, the kind of environment we create, the kind of permission people are given to fail, screw up. So, go back to the pool. This may be off whatever. You need to feel comfortable walking in your bathing suit into the pool and not have people judging you. So, people need to be comfortable that they can put their suit on, go swimming and people are not going to say, " Look at that." So, I think there just needs to be a change in... And this gets to culture to make people not be so self- conscious or to have a little more freedom to try things, screw up, try again, work together in new ways. And I think it was really fun the other day when... Well, I'll say it's fun. My son- in- law made beg to differ, probably begs to differ. But at their apartment, he's got a data center. One of their bedrooms, I swear it's a data center. But he's set up a cloud and we're talking about what dataset we're going to pull in. And he's not actually a data engineer, he can do data engineering tasks but he is involved in international manufacturing. And I just saw the power of being able to have an open and honest conversation with somebody who could go get some data, who I could ask questions of, who could make adjustments. And we were a team out on the field talking about how we're going to like, " What's our play going to be?" And you need to have that kind of esprit de corps optimism like hustle, whatever you want to call it, where people are feeling like they're part of a team and they're part of this team working with that team. And I think maybe that's achieved in some companies but I think that that's what it takes is a real hustle factor.
Juan Sequeda: Yeah, no, this goes back into culture. Like you said something early on that the tech is not really the problem anymore, right?
Allison Sagraves: Right.
Juan Sequeda: We're pretty much solved. And I had this post on LinkedIn, very short. It's like, " Hey, 80% of the data problems are really people in process and just 20% are the technology. And guess what? The majority of the people focus on the technology thing and they're doing it wrong." And so, I think it's creating these types of these synergies. It goes back to, remember, empathy and curiosity. Go back to go create that. We're part of a team. I like what you said, we're a team. We're not this team and that team and this team working together. Together, we're going to go work at this. And it's really involved about having different types of skillsets, different skillsets working together because they complement each other. And I think just sadly in a way, this is not just one side. They're I think both, the tech side and the business side that they're like, " Oh, those folks and those folks," and they're not coming together. And sometimes we think it is like, " Oh, we needed a third role that's going to bridge everybody?" And maybe that is the case. But also we should be thinking, it's like, " No, we need to open ourselves. We need to stop judging. We need to all get into our bathing suit and we all swim differently and that's fine. That's what it is. And let's figure out how we complement each other to go achieve our goals."
Allison Sagraves: Yeah. I mean, I think there's talk about the translator role. I heard a podcast yesterday talking about we need the purple people, there's the red people, the blue people, we need the purple people. To an extent, I agree with the idea but I think that if the business people were more tech savvy, the tech people were more business savvy, that you could solve it with the people that you have. I think bringing in more people to orchestrate a conversation just probably adds complexity. So, I think that we need to get a tighter integration between tech and business but I think it's about each person upskilling to be able to have more of a conversation, to have fluency. And there's a great book on this topic by the way I'll throw out. Let's see. It's by Tsedal Neeley. Digital Fluency I think it's called. Digital something, I'll think of it. But she talks about why you don't need to know how to code but you need to be able to be 30% conversant in a foreign language in order to be in a foreign country and be able to survive. So, it's that idea of how do business people be 30% conversant in technology, how do technology people be 30% conversant in business so that you could actually have a meaningful conversation and bring your skills to the table.
Juan Sequeda: Yeah, this goes back to-
Allison Sagraves: Digital Mindset. Digital Mindset.
Juan Sequeda: This is the thing I've been talking a lot about business literacy where we're already talking about data literacy, let's go bring the other side, the business literacy. Now, something I want to go touch on is you were 30 years at M& T Bank. And you ended up like you were the first CDO. You've been 30 years in this area of data and in the financial services. How have you seen the changes, the cultural changes, specifically in this data space for the last 30 years? I would love to tap into your brand, kind of see what has happened and what have you seen over 30 years?
Allison Sagraves: Yeah. So, just a little background. So, I was hired into M& T. And we had a very visionary CEO, Bob Wilmers. He's fun to google, a real character. And M& T has been an incredible success story as a regional bank. And so, he hired a bunch of MBAs from different schools to come to Buffalo, of all places, a place that people wouldn't think to come, I didn't think to come. Now, we have a family and we're rooting for the Buffalo Bills. And I had a series of roles, but my sort of brand at M& T ended up being, " Okay, we have a problem. We don't know how to solve this. Somebody needs to figure this out. So, we'll give that to her." Because I was curious when curious was considered bad. Now, it's a corporate virtue. But back in the day ... And then people will... I mean, I'm not saying anything out of school because I think our culture at the bank was self- aware enough to realize that that was not considered cool to be curious when I started in my career. But ultimately, we had many different things that came up in the past 15 years of my career where somebody needed to start up a function. So, some of the things I did, I set up our outsourcing function. So, I traveled to India and set up our partnerships abroad. I did our resolution plan, the living will. So, I got involved in a lot in data there. I was in finance. So, I had seen data from lots of different perspectives. I understood data. I was always very analytically driven. I think I was one of the first people to order Competing on Analytics by Tom Davenport. It's sitting in my office. So, what happened was... I guess it was around 2015, we didn't have a chief data officer and we needed to appoint somebody. I had a lot of business financial data, strong understanding of the business, could make something out of... could build a function. And so, I was appointed the chief data officer. It was a fantastic role, the greatest role of my tenure. And anyway, so that's how I got into the role. I was in that role for five years. And at that time in the life cycle of the CDO, particularly at banks, there's a huge need to have controls and manage risk. And so, this was largely a risk function at that time. And so, I had to build the foundations and ensure we had trusted data so that we could rely on our reporting and all that kind of stuff. So, anybody that works at a bank knows that there's a huge defensive aspect to being a CEO at a bank. But certainly, that same data can be where you need to understand your customer for BSA/ AML reasons or for regulatory reasons. That same kind of knowledge can be used to understand your customer for marketing purposes and customer experience purposes. So, we were starting that shift to offense. And I think that's where the financial services industry is now, making sure you have a good foundation but then now leveraging that for value.
Juan Sequeda: So, a couple things. One, I see Cara made this great comment, " CDO equals a chief problem solver."
Allison Sagraves: Yes.
Juan Sequeda: And then we have our LinkedIn user which I think it's Mark who says, " CDO is a chief problem solver at the end of the day and why is this broken chain?" So, I think there's also understanding how things work and don't work. And I think it's always about problem solving. So, I really like... This is the critical thing that sometimes we miss today because a lot of these data roles are just so focused on the tech. So, clear message to everybody is you need to understand the business, you need to understand the problem, be a chief problem solver.
Allison Sagraves: Yes. Way to go, Cara. A long time, we've been in the trenches together, we've been in the pool together in our careers. So, it's great to see you.
Juan Sequeda: So, continue on the pool analogy. So, in the financial space, the lifeguards are too overprotective. And in some other areas, the lifeguards are kind of like, " You're okay." Continue this analogy with the pool and the data in different industries and lifeguards and-
Allison Sagraves: Yeah. I mean, I think you want a lifeguard that wants you to learn to swim, be happy in the water, that is invested in your success to learn to be a better swimmer and not there blowing the whistle with the sunglasses on, leaning back in the chair like, " Oh, when is this going to be over?" You want somebody that's cheering you on to swim, not standing there like, " Okay, whatever." You want a partner, not a scold, not a savior. You want somebody that you know will keep you from drowning but somebody who really wants you to swim. I'm taking this a little far but it's like an attitude. How do you have a partnership between people who need to enforce rules, guardrails? But how does that partnership lead to a better outcome instead of creating division? And I think we're too invested in, "Oh, I'm going to enforce this and whatever." You need to figure out how you're going to, to Cara's point, problem solve together.
Tim Gasper: I like that analogy. And I like where we're taking this. To bring this into now the data organization, who is the data lifeguard? Is that the governance office with their enablement hat on? Is it something else?
Allison Sagraves: Well, I mean you could sort of take the story, whatever. There's the governance people. There's the security people. There's the privacy people. There's the engineering people. I mean, you could say there's a lot of lifeguards. So, there's a lot of... And so, I guess when you think about that, that makes it hard to swim when you have a lot of people watching you swim with a particular lens. And it's like how do you bring these people together with their different perspectives and valuable perspectives and important perspectives, security obviously, privacy obviously, but where the whole is greater than the sum of the parts? And where these are... I kind of said this before, how do you create that team that is going to... What's the pool equivalent of getting into the end zone? That's going to hit the edge of the pool and win the race?
Juan Sequeda: There you go.
Tim Gasper: I'm trying really hard to think about the analogy. I'm like, " What is the end zone?" I don't know.
Allison Sagraves: Yeah, win the 100 meter. You're going to win. That's really where you do the four different strokes.
Tim Gasper: Yeah. I love what you're saying though about in our data organizations, I think there are actually, to your point, quite a few lifeguards and they're all looking for different things. And I think there's actually some really tactical application that we can take from this analogy when we think about our own organizations that there's somebody with their whistle in their mouth that is looking for security stuff and there's somebody with the whistle in their mouth looking for privacy stuff. Same for governance, same for data engineering, same for data architecture, same for information management and knowledge management, all these people have their whistles. And some organizations, maybe they're blowing whistles every second. Maybe some organizations, all those lifeguards are looking at each other like, " Who's going to call the whistle?" We don't know. So, I think there's things that we can learn here about how do we streamline our organization to get this lifeguard team working well together and also focus on helping people get in the pool.
Allison Sagraves: Yeah. And again now, not to just go to the Buffalo Bills and switch into a different context but, okay, we're all dusted in the bills here in Buffalo. But watching them play and I talked about this winning ugly on a podcast last week but they will do whatever, I mean any team, but I'm using them as an example here. If Josh Allen has to carry the ball, I mean, he has to run the ball, he will. He'll jump over guys. I mean, it's just is ugly. It's like contact sport. It's physical. It's intense. It's emotional. And I feel like you need that sort of like we're in this together kind of mentality. Not like, " Oh, you can't do this because that's a privacy." And I'm not saying that that's what people do but it's just like how do you bring your lens? How do you bring your expertise in a way that advances the ball, advances the whatever, the yardage in the pool? It's policing in a different way, being a community police instead of whatever. That's a political statement right there. But...
Juan Sequeda: This is a great way... First of all, this pool analogy I think I'm going to give us a round of applause. I think we've done very well with the pool analogy. And I think a takeaway here for everybody is you should think about your whole data landscape with the pool and see how... I'm curious to see what people will come up with the pool analogy. And then talking about pools and waters and stuff, I just want to shout out for a friend, Mark Kitson, who just sent me a picture. He's in Australia and at 6: 00 a. m. and he's walking on the beach right now and he's listening to us live right now from it. So, that's so cool. I love that. We've had this great aha moment. There's not a lifeguard, there's so many different lifeguards. And Tim, you just said something which is like, " Wait, security, privacy, architecture, governance. You're like,'Something's happening. Who's going to blow the whistle right now? Do something.'" And then that's when actually things don't happen and we're not all coordinated. So, I think having too many chefs in the kitchen, too many lifeguards too is not a good thing. We got to figure out what this balance is. And I really like this pool analogy. We got to keep doing it.
Allison Sagraves: Well, from data likes to data pools, there you go.
Juan Sequeda: There we go.
Tim Gasper: Yeah.
Juan Sequeda: All right. Well, this is a good segue. We've had a fantastic discussion. Let's go move to our lightning round which is presented by Data. world, a data catalog for your successful cloud migration. And I'm going to kick it off. So, Allison, first question. Given all the tech improvements spotlight on data, is life easier for CDOs today or is it harder?
Allison Sagraves: What are the roles of this thing? Is this a yes or no or one- word answer or-
Tim Gasper: Yes or no and a little context.
Allison Sagraves: I would say it should be easier. I don't know that it is easier. It should be easier because technology is no longer a constraining factor. And it was in prior eras. It should be easier. Is it easier? I'm not sure. I don't think so
Tim Gasper: Good point. That's a good contrast. All right, second question. You mentioned in our chat today that CDOs are being very self- conscious and they're calling a lot of attention to the gap between the data value that needs to be achieved versus what they think is the data capabilities within the organization. Will that change in the next five years? Will they gain their swagger?
Allison Sagraves: I think we have to redefine what success looks like. And it needs to be much more closely aligned with... I mean, this sounds sort of basic but more aligned to business success. So, I think we need to take a lot of... We need to give CDOs a pass on a lot of things and say, " You know what? You don't really need to worry about these 10 things over here." I mean, we have to be smart and be selective obviously. But I think success should be defined with business success. And it should be more about achieving wins that actually count than pleasing everybody and putting out every fire. There's just got to be a better prioritization so that CDOs can say, " I succeeded because I help the business in these three important ways. And you know what? I didn't do these 10 things over here. And guess what? I couldn't have done these three things if I worried about the 10." And instead of having people say, " I didn't do these 10 things over here," and then when they're asked, " Well, what did you do?" " Oh, I did this thing over here." It's a mindset shift. It's like... There's a psychological term for this but I think the role is people talk about it's too much about what they haven't done. It's a deficit mindset.
Juan Sequeda: This is a big point.
Tim Gasper: Yeah, this is a big change I think that is needed. And there's a lot more thought I think that needs to go into this. We should have a follow- up conversation about this, Juan.
Juan Sequeda: Next question. Who is more important at the data pool? The data lifeguard or the data swim teacher?
Allison Sagraves: Oh wow. I guess you'd have to say the lifeguard because unless the swim teacher could act as a lifeguard, whatever. I hate to get such, it's hard to answer as everybody is the same importance. I guess if I was drowning, I'd want somebody that actually could save my life. But they just don't need to save me from going under water and maybe coughing. They need to save me if I'm drowning. So, I think everything needs to be calibrated to the level of risk.
Juan Sequeda: Nope. I mean, yeah, you are drowning. If you are drowning, you don't want somebody say, " Hey, kick harder, kick harder." No, you want somebody to actually throw you and got to get you out of it.
Allison Sagraves: And you know what? Get me water wings. There's 6. 99 on Amazon. I'll be saved by water wings. I'm not going to be saved by a Patagonia vest.
Tim Gasper: Oh, I love this analogy. I love it.
Juan Sequeda: This is the best episode of analogies, period. I love it.
Tim Gasper: All right, last lightning round question for you. We talked a little bit... You mentioned a couple times data offense versus data defense in terms of some of the use cases. Will data offense really win the day over the next let's say 10 years or is it going to be data defense just done better?
Allison Sagraves: I can move over into the football school and say defense wins championships and everybody can have a big fight about that. So honestly, I think that's sector dependent. So, Tom Davenport did a chart about this in an HBR article. You can all google it. So, I think in financial services, there's probably equal weight to defense and offense. So, I mean, you didn't have a lot of wins in offense and one big screw up in defense, one turnover, you're done. So, that's contextual to the industry. But I think that you can't... So, I will contradict myself. Maybe defense wins championships but you have to have a productive offense.
Juan Sequeda: This is line with what we see. Shannon Moore has a great comment here. " It's about managing risk, managing risk but allow for some risks. So, data governance, security, privacy should be the lifeguard there to keep you from drowning which is to reduce to risk but not remove all the risk, not let you get in the water at all." So, I think that's a great summary. And I'll bring it up later on. Shannon is going to be our guest next week live from DGIQ. So, really excited for Shannon. And also just to bring up Cara again like, " Yes, CDO's report card should be about business results versus fixing the plumbing." Allison gets it. Yeah. And that mindset, you said like, " Oh, we accomplished these three things which helped the company and generate revenue here. We didn't do these other 10 things because if I did those 10 things, we're down to these other three things." Yeah, let's go highlight the business results and say, " I could fix the plumbing in there. You got to choose some things sometimes." But I think that's a really great way of thinking about it.
Allison Sagraves: Yeah, I think the CDOs need to just... There needs to be a mindset shift. CDOs need to make it internally and organizations need to make it as well.
Juan Sequeda: Yup. All right. Takeaways. T, T, T, T. Tim, take us away with takeaways.
Tim Gasper: All right, sounds like a plan. So, you really started this off with, " Hey, there's this data pool, get in, swim with the data, just jump in the pool." And I think that really kind of sums up the theme of what we talked about today and an analogy that I think was used beautifully. So, thank you, Allison, for walking through this. That there's this huge gulf between the progress of data being available versus being able to really use the data to provide value. And you highlighted that folks need to really be enabled to get their hands dirty, play in the water, get smarter and evolve. The pool ends up working like a great analogy here because there's lifeguards, there's lanes, you have a place to test an experiment that's controlled. And it's a place where different people can all get together and collaborate. But one of the challenges that you mentioned is that the industry has this complex that we don't have enough and we need more. And we're just never... We can never do good enough. We're constantly staring at the gap versus what we've accomplished and the progress that we're making. And that we make these statements that are ambitious to the point of not making sense like, " We have to train every single person in the organization on data," or, " Every single person in the data needs to be able to leverage and the organization needs to be able to leverage the data." And the truth is that we probably should not be boiling the ocean. We should be defining success in a much smarter and incremental way. And you said dog paddle is okay. And so, I really want to embrace that. And we talked about how data products is a very interesting concept, maybe can help in all of this. It's an interesting way to scale. It's a process and a system. It's a proven idea from software but it's very easy. And our data industry has a tendency to do this, to get excited about silver bullets. And so, just because data products, eureka, it's not necessarily going to be the answer to all our prayers here. There's a ton of work implied by data products. And if we really want to have, as you said, these commercially viable data products, we've got quite a bit of work to do. We've got quite a bit of things to define. And maybe there's some stuff that we're not really thinking about yet. Maybe our current idea around data products is more like the oil lamp and we still got our combustion engine that we've got to invent here that we haven't quite figured out yet. So, opportunity there but maybe some patience required. Juan, what about you? What about your big takeaways?
Juan Sequeda: So, following up on this, what needs to change? Keeping this analogy, we need to feel comfortable walking in our swimming suit, jump in the pool and just swim without being judged and don't judge other people like that. I think that's... And so again, this is cultural. Everything we've discussed here, technology is there. I mean, it's not a big issue right now. It's a cultural side. We don't have to self- conscious. We need to have more freedom to try new things and screw up and try again. So, it's like this player coach mentality. And we want to be part of a team, not this team and that team and these teams talking... This is a team here altogether. And it goes into the mindset where you brought up this book, the Digital Mindset. You need to have 30% ... You need to be 30% fluent in foreign language to be able to have meaningful conversations in that country. So, business people need to be more tech savvy. Yeah, we're doing this with data literacy but not everybody needs to go do that. But what we need is also the business leaders so the tech people need to be more business savvy. And then I think seeing your 30 years of experience being at M& T Bank, the changes you've seen, I think the takeaway there is chief problem solver. You are there to go solve problems. I think that's the most important thing. I think that's credit to Cara who brought that up right there. So, CDOs really are chief problem solver. And then finally, these lifeguards are really people who should be cheering you to go swim. They're a partner who wants you to succeed, not just to control you and not just to scold you and keep you from drowning but let you swim and actually swim better, get better at it. I think one of the issues is that we just have so many different lifeguards, different people are lifeguards. We have the security lifeguard, the privacy lifeguard, architecture, the governance lifeguards. But we need to figure... We need to realize that we're all in this together like really a community. I think this is where we really need to go figure it out. And as you brought up in the lightning round, it depends on industry too. All right, Allison, how did we do on takeaways? Anything we missed?
Allison Sagraves: Well, as I was thinking about the pools, I was thinking you can learn to swim in an aboveground pool. You don't need an infinity pool. Although I have to say I'm dying to swim in that infinity pool in Sicily in The White Lotus.
Juan Sequeda: There's a lot of different pools to go swim, so for sure. All right, Allison, back to you, some advice. So, three questions. One, what's your advice about data, about life brand? Second, who should we invite next? And third, what are the resources that you follow?
Allison Sagraves: Let's see. Advice, well, as probably a more senior person in life than many of you listening to this, I would say what has worked for me or what I would do differently? I think what I appreciate at this stage of my life is how important relationships are. And you can translate this all to business, to life, to both. Relationships are everything in life and in work. And I have gone through this industry having three kids and raising three kids and now they're millennials and Gen- Zs. And that was very difficult for women in the era that I did that. It's not easy today but hopefully it's getting better. But I think when I look at where I am in my career, the relationships that I made 20 years ago are coming back to me in new ways. And there was somebody that I was involved in outsourcing with who now recommended me to be on an advisory board for a really interesting startup. So, I think it's really important to pay it forward, to give before you get and to really nurture a strong network in, again these words like authentic, they've kind of lost meaning at this point, but in a real way. And if you do that and you have your cohort of people that you go through life with and check in on every so often, that will get you through life and will help you both in work and in life. So, I think it's really... So much just comes down to relationships. I guess that's basic but I say this having lived more years on the planet. So, I feel-
Juan Sequeda: By the way, that was beautifully said.
Tim Gasper: Yeah.
Juan Sequeda: Thank you for sharing that. That's very beautiful.
Allison Sagraves: And I think things that when I look back on my life, I spent way too much time worrying about things or questioning whether I was making the right choice. I would completely not waste that energy. I would have much more trust in my decisions. So, I hope that anybody who is at a different phase in their life doesn't agonize over stuff and worry so much. Just have faith that if you think it's right to just go for it. And I'd say an important thing that my husband Greg and I did is we really live below our means. And that gave us a lot of optionality in our lives to make different choices. And we were never... Even though we both worked for the same companies for a long time, we never had to. And I just would encourage people to think about that as a way to buy yourself mental health and freedom to pursue the things that you want. It worked for me. I'm not saying that's what other people have to do.
Juan Sequeda: Thank you. Again, very beautiful advice. Really, really appreciate that. And we're seeing great comments there. Second question, who should we invite next?
Allison Sagraves: I met a really... Well, certainly there are people listening to the show that I think you should invite. And I want to mention a person that I met in Silicon Valley in September. I don't know if Cassie Kozyrkov has been on your show. She's the Chief Decision Scientist at Google. She moderated a panel at a conference that I was at. I moderated the CDO panel. She moderated the data science panel. We had a fascinating conversation. Do you know Cassie?
Juan Sequeda: I do not.
Allison Sagraves: She has. So, first of all, I would encourage... So, when you ask who do I follow? I follow her. She's got a YouTube channel. She's very active on LinkedIn. She's just really, really brilliant and a go- to person and a really interesting person outside of data as well. So, Cassie would be somebody I would suggest.
Juan Sequeda: Awesome.
Tim Gasper: Great.
Juan Sequeda: And then finally, what resources do you follow? What books or podcasts or people, conferences and stuff?
Allison Sagraves: Yeah. I think for conferences, the MIT conference, the guy that runs the Carnegie Mellon Program that I'm involved in calls it Coachella for CDOs. Maybe other people call it that. Certainly, that's a good one in terms of just if you're a CDO, that's a good conference to go to. We went to Gartner, both of us this year. I hadn't been to that before. I think something like that is a good overall, that Forrester or there are other ones I'm sure, where you can really just meet all the vendors, get up to speed on everything that's happening. So, those kinds of things are good. And then, there are sector- specific things. So, I went to a lot of financial services conferences. I would say that when you go to these conferences, meeting people, building relationships, there are CDOs from financial services that I am still in contact with and that are important in my life. So, I'd say that also select things that are sector- specific or maybe function- specific. And then, I would also love to go to the MIT Sports Analytics Conference. I think that would be really fun. And I think that we shouldn't just think of conferences in terms of our careers. A conference, so to speak, that I'm dying to go to is the Chelsea Flower Show in London. So, maybe 2023 will be my year.
Tim Gasper: All right. Nice.
Juan Sequeda: Well, Allison, this was a phenomenal conversation. But before we say goodbye here, just a quick reminder, next week, Tim and I are going to be live at DGIQ in Washington DC, the Data Governance and Information Quality, Dataversity Conference. And we are going to have a live show. Our guests are going to be Anthony Algmin and Shannon Moore who was commenting over here. Honest, no BS data governance. That's going to be our topic because we're at a data governance conference. And we have set up cocktails for everybody. So, at the conference when you come into the room, we're just going to be giving everybody the honest, no BS, old fashioned so it's going to be such a cool event. So, please be able to look at it so if you're in DC, let us know. We're also going to have a happy hour afterwards so that's going to be next week. We're also scheduling for 2023. We already have a lot of guests ready for that. But please reach out to us. What are the topics that you're interested and that we should be talking more? Who do you like the studio to invite? I'll tell you that we're kicking off 2023 on I think it's January 11th with Bill Inmon, the Father of Data Warehouses. I actually had the amazing pleasure to have breakfast with him this Saturday. I'm so excited for that. And with that, Allison, thank you, thank you, thank you so much for this phenomenal conversation. We did fantastic with this pool analogy. I'm so happy about it. And we did so much. Thank you so much, Allison.
Allison Sagraves: Thank you. Thank you so much. Bye, everybody.
Tim Gasper: Cheers, Allison.
Juan Sequeda: Bye, cheers.
Speaker 1: This is Catalog & Cocktails. A special thanks to Data. world for supporting the show, Karli Burghoff for producing, John Williams and Brian Jacob for the show music. And thank you to the entire Catalog & Cocktails fan base. Don't forget to subscribe, rate and review wherever you listen to your podcast.