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0:00:05.7 Announcer: Welcome to The Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language. Here are your hosts, Moe, Michael and Tim.

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0:00:21.9 Michael Helbling: Hey, it’s episode 189 of your favorite analytics podcast, The Analytics Power Hour. I don’t know why I said it was your favorite, but I’m just maybe trying to do that thing where I mentally create a space for that for you, but anyway, let’s start into the show. Tim Wilson, you’re my co-host on the show. How are you doing today?

0:00:43.9 Tim Wilson: I’m doing all right.

0:00:45.3 MH: As you see, I’m still mixing it up when I started doing co-host intros.

0:00:49.2 TW: That’s good. Yeah, I wasn’t ready. The wittiest thing I could come up with, I usually have three or four sentences to ramp up to it.

0:00:55.0 MH: Well, you’re doing it right now. Okay, Moe Kiss, [chuckle] you’re my other co-host. How are you doing?

0:01:01.1 Moe Kiss: I’m great, thanks.

0:01:02.9 MH: Awesome, alright. One of the things that’s common across the three of us, and probably most of the people listening is we all have our own story and analytics career. And you know when you start out in your analytics career, it can go a lot of different directions. One possible path is to take your data career all the way to the C-suite. And when we look at companies today, there are more and more C-level data roles out there, and so as an industry, we have to start thinking seriously about how we’re gonna prepare for and fill those roles. But what does a Chief Data Officer actually do? None of us, as far as I know, Tim, our Chief Data Officer, so I think we needed a guest, someone who could help us with a discussion on this topic, and luckily we have Mai AlOwaish. She is the Chief Data and Innovation Officer at Gulf Bank. She has held industry roles, places that you know and love, probably like InfoTrust, Blast Analytics. She’s a winner of the Digital Analytics Association President’s Award, and she also serves on the DAA Board of Directors, and today she is our guest. Welcome to the show, Mai.

0:02:17.2 Mai AlOwaish: Thank you, thank you. It’s a pleasure to be here.

0:02:19.7 MH: Yeah, it’s awesome. I’m so glad you could make it. We’re delighted to have you. So Mai, I think one of the things probably to talk about first is just… I think people would benefit from just hearing a little bit about your background, some of your career journey that got you into the role you’re into today, and maybe we’ll start with that and use that as a spring board for some further conversation.

0:02:40.3 MA: Of course. I mean, many of us are past digital analyst moving to digital and then pure data roles. It’s something I thought I’ve had a unique path, but then the more data officers I meet, I find similar stuff. So currently, I serve as the Chief Data and Innovation Officer, and the innovation was just added last month honestly. So for the past year, I served as a Chief Data Officer at Gulf Bank based in Kuwait. The 10 years prior to that, I was in United States, I worked with Google partners that you talked about, InfoTrust, Blast Analytics. And the 10 years prior to that, I was actually in Kuwait, home, where I worked with banks before. And the way I started my career really is web development. So my first job and funny enough, it was at Gulf Bank. So my first job was doing web development and doing the online banking solutions.

0:03:36.5 MA: So back then, I remember launching my first online banking for the bank, and it was a big hit then to just log in and see your transactions and history or get a text message. And that’s where the e-commerce was really going strong, about 20 years ago. And 10 years, then I also worked a few airlines where we launched the first online booking and all that fun stuff. And many of the people… When I moved into digital analytics around 2010, many of the people came from the exact same background, people doing e-commerce, web development, and then moved into the analytics for e-commerce. So that was the first switch between pure development and pure analytics at around 2010. And then 10 years in… After doing 10 years of analytics and mainly focused on e-commerce but not all. So at some point I worked with the analytics for non-profits and funny enough analytics and nonprofits, they treat it exactly like e-commerce instead of revenue, they call it donations and that’s it. But really the same approach. [laughter]

0:04:43.3 MA: So it was fun and it was rewarding to get more dollars in for revenue. But 10 years after working with all the amazing Google partners and other agencies in the United States, I was offered this role to come into Gulf Bank to run as a Chief Data Officer. And I was the first generation Data Officer. So they never had the data office, it was something that they just starting to have. And I was thinking, “Oh wow, Are they late to the game?” But then I found out many banks are just late to the game when it comes to e-commerce and so on, just because they really are comfortable with the business model that they have and people need money and loans, and they don’t have to really up their game on FinTech, but now they’re feeling the pressure with FinTech and saying, “Okay, we need to monetize our data.” And as I came into the role, I remember January of last year, I was like, “I’ve done so much of digital and all of that, but the data in the bank is not just the online stuff, there’s so much offline that I have to work with.” And at some point I was thinking, I really have to up my game on the offline stuff. And then I was on this panel discussion in some conference with Chief Data Officers of other financial institutions and FinTechs, and two of them were digital analysts before. One was actually working with Google, yeah, and I was like, “Okay, I guess they made the right choice.” [laughter]

0:06:10.0 TW: But with the gap, I’ve gotta, like… Were there people who’ve been at Gulf Bank the whole time, like if you come back and they’re like, “Oh, you were… ”

0:06:18.6 MH: There was one, there was one guy who would…

0:06:21.4 TW: Just one. Okay. I hope people find you.

0:06:23.3 MH: Yes, yes. So there was a guy, he was like, “Oh my God, I met you in like the induction training when we met, 20 years ago,” but yeah. But I remember at that moment with the conference and I was like, “Okay, so digital analysts are becoming the next generation of chief data officers, because all of the people in e-commerce are way ahead in terms of monetization, that other organizations really need that edge and they want someone who’s been there, done that and monetized on data, so they can put that into practice for the other industries.” And now it’s feeding into innovation, so as of last month, what they added is they added innovation into the data office, because they understand that most of the innovation monetization, it’s data-driven, so they added that to my office, and this is a new challenge as of 2022.

0:07:16.0 MK: It’s interesting though, because already you’ve said quite a few times about monetizing the data and one of the things I really wanted to find out, like I just assume that such a huge part of the role would actually get almost drowned in compliance and governance. I feel like you could almost make the entire role just about that and you would still have a very busy job.

0:07:39.6 MA: So yeah, I mean, that’s what worried me when I joined the bank, at the beginning, I’m like, “Am I just gonna just do data governance and so on?” But honestly, no, the way banks are set, there’s a whole compliance unit that deals with just compliance. And there is usually somebody called the data privacy officer, so the data privacy officer is purely dedicated to working with compliance that we certify with everything that has to do with customer when it comes to GDPR or things like that. Then we are compliant, and that’s the expert, the chief data officer role in a bank, what I’ve seen from the other organizations that I’ve met is, their role is really upping the game data across the organization, making sure that everybody has access to the data that they need, that they self serve with analytics, that they are able to get the value. So my role right now, there is a data governance part of my team which handle kind of, I don’t wanna say the boring stuff, but just the data quality documentation, master data, data catalogues and things like that, but then there is another part of my team which is doing the MIS and analytics.

0:08:52.1 MA: So there is the day-to-day reporting, which any bank and organization has to do. But then there is the analytics and the monetization on reports, and that’s where as a data officer my role is to make sure that every department in the bank has the data that they need, has the right data, and that they can get value from it. It can come in many different formats, part of it is setting up the right technology, but another part is really educating the people on getting all aboard with the data-driven agenda.

0:09:26.4 TW: Well, on that, ’cause specifically on the… ‘Cause even on the… There’s the governance side, kind of Moe thing that could get bogged down. I hear you say self-serve, and I think, wow, it could become the… Getting bogged down in the BI platforms. And then you just said it, it’s the technology and the knowledge of the people. And I remember seeing, I think last year, there were some things you were posting on LinkedIn that seemed much more about championing and educating the people in the process, but does the technology of self-service, does that wind up under you? Does that run the risk of creeping in or is it more the helping people think about data?

0:10:10.9 MA: So basically, all of the posts that you’ve seen where about a program that we launched called the Data Ambassadors. We believe in data democracy. And I wanna make sure that there’s no single department that does the business intelligence and then gives everybody the insights, but rather the departments dig their own insights. But before I get any technology or solution that is self-serve, my approach was we start with the people and then go with the technology, because if I get the highest and latest technologies, but people can’t use it or people will use it, but just extract Excel sheets and then do their own thing. And it happens all the time. So we…

0:10:55.5 TW: I’m laughing ’cause I’m thinking of a very specific client where it’s been like three years and there’s that one person and she’s like “That’s great that it’s in here, but how do I get it so I can export it,” so…

0:11:05.1 MK: One person? I have a team who do that.

0:11:07.6 TW: Yeah.

0:11:09.7 MA: [laughter] Yes, it’s all an over, it is all over. And that’s what I said, ’cause the first thing they asked me when they hired me as a data officer like, “Yeah, so where are you gonna get for the data warehouse or data lake and all that stuff?” I’m like, “Oops, wait, wait, before I get any kind of technology or investment… I’m not trying to be cheap, I’m really trying to build the right people and the right audience before we go ahead and buy all these technologies and implement them.” So, what we’ve done is kind of the network of champions, as you guessed, Tim, is basically every single business department had to nominate some people and the nomination wasn’t so hard because they nominated the people that actually do the day-to-day reporting. But then I asked them just to add two more, which are young and ambitious, just in the mix. And with that mix, we had 140 ambassadors total. And we have… And that makes up…

0:12:07.9 MA: If we’re thinking head office operational staff we have around 900, so that’s a big portion of our staff going through this. ‘Cause we needed to make sure that at least 10%, 15% go through this, that’s how we change the culture to become data-driven, and then the next step is actually even management will get a real-time access to some reports instead of waiting for someone to send them a report or tell them the results. And then what we did with those people, they said, “Oh, okay, so we’re gonna become data ambassadors and we’re gonna learn some tools,” I’m like, “Nope, not yet. First, we’re gonna teach you data quality, [laughter] and like really changing the mindsets about how to look at data, how to extract data, what are the best practice? What does it mean to be, you know, a user of data? What responsibilities do you have now that you create reports for your team?” You know, it comes with powers and it comes with responsibilities as well. So it was more about culture and also we had to make it so much fun, so for them to be interested in such things. And now three months in, next month, we’re gonna start doing the technology training and the new platforms and so on.

0:13:18.7 MK: But sorry, how… I’m just like listening to this being like, how did you start this from the ground up and carve out the time? Like, it sounds like you’re doing the work that every data leader dreams of doing and is like, this will make the difference, but then they just end up somehow in the day to day putting out fires and don’t get to step back and be like, this is how we change the organization. Like how have you protected your time?

0:13:44.7 TW: Well, let me, and we do an add on to that as to whether it is that, that there was buy-in to a chief data officer, whether that was a piece. ‘Cause I think that that’s what I’m like, even getting the buy-in, like even broadening, if you go to most companies and say, we need to have 10 to 15% of the people go through this program, there would be pushback. And I kind of of wonder if that was, if it was, but is there a degree of, because the organization made the commitment to create this role, did you come in with the kind of clout and authority somewhat? Not that you didn’t still have to, you know, do all sorts of cajoling, but yeah, I’m kind of having the same reaction to Moe like, “oh my God, how did you actually get the buy-in?”

0:14:26.8 MA: So, I mean, I do have a folder in my documents that says the CDO sales package or the CDO sales tools. So you have to become kind of a salesman to the management at some point to really sell this data game to them. You know, what’s in it for me. Why should I let my people go through this training what am I getting out of this? Why should we waste all their time? Or, you know, and I said, invest in their time to actually, you know, learn these tools. So it took a lot of education. I remember working with one of the consultants, his name is Tom Redman. He’s called the data doc worldwide. So ’cause I figured that data quality had a lot of data quality issues and our data and needed a doctor.

0:15:11.5 MA: So one of the things I told him, you know, and I said, you know, Tom, we try to do this and there’s so much and so much, you know, I’m not gonna say opposition, but some people don’t actually get it. “Yeah, you’re the data officer. You go set up the systems, get the report and we’re done, you know?” And he’s like, well, one of their main roles is to teach up and we teach up, we teach up from all the way to management and the board all the way down to like, you know, mid managers. So thankfully I really enjoyed teaching across in my life, it wasn’t so hard for me to actually stay and teach up everybody, but it was starting with the top. And as Tim said, our management or kind of the strategy of the bank was to digitally transform.

0:15:58.0 MA: So there was kind of buy in on the overall agenda. But they’re like, “we don’t know, we don’t know. So you do your thing,” and I’m like, “well, we need your support as management to actually change the culture, but we need to start with the people.” So first I had to meet with the top management or the C-level and then I had to go and meet every department with kind of senior managers in every depart it and tell them exactly why we’re doing this, how we’re doing it, what’s in it for them. And then kind of get the nomination from each department. So I remember kind of the same slide deck, probably I went through it 20 times, you know, and then the managers who went there, I made makeup. So it took a lot of work to actually ensure that these managers understand why we’re doing this.

0:16:45.1 MA: And then once they did the nomination, I got more pushback from the actual ambassadors that were nominated. Like they call my team like, ” we’re not really techy people. We just like extract reports and for the days to days stuff. So I don’t think I should be an ambassador.” I’m like, you know what? Just attend the first session and we’ll talk later, if you don’t qualify, we’ll do it.” And also C people, you know they were so interested right now and they’re waiting for the next session. And they’re, you know, they understand that data it really benefits them. It makes their day to day… If they know the actual approach, if they know the, how to do the right reporting with the right self-serve approach that they can actually help their department really be independent and not dependent on another unit sending me this file or sending me this report or this external agency, you know, building this report for me once they understand how self-serve can help them. They were totally sold from all levels from the kind of the junior reporters, all the way to management, because what I did is did some pilots with a few departments here and there and now they became my salesmen to other departments. Oh, look what we did. And this worked, and now we can, you know, they want… Other departments want the same.

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0:18:01.1 MH: All right. Let’s step aside for a brief word about our sponsor ObservePoint. You know, I really miss doing this on our last episode, but Moe, you did a great job.

0:18:12.4 MK: I’m pretty happy that you’re back on point on this one.

0:18:16.9 TW: Is he back on point or is he back on ObservePoint? Am I right? Am I right?

0:18:24.4 MK: Oh, Jesus. [chuckle]

0:18:25.0 TW: I’m here all week, folks.

0:18:26.5 MH: Yes. Yes, you are. It’s almost like you never go away actually. And you know, something that we actually want to never go away, well, obviously the integrity of the data collection on our site, and that’s what you get with ObservePoint.

0:18:40.2 TW: Nicely segued there, Michael, but you’re right. ObservePoint is a great platform for automatically auditing your data collection for errors across the whole website, alerting you immediately if something goes wrong and providing reporting so you can actually track your data quality over time.

0:18:56.8 MH: Yeah, that’s right. And ObservePoint can play role in privacy compliance too, isn’t that right?

0:19:02.4 TW: Absolutely. The platform can be used to regularly audit and identify all the tech collecting on your site to make sure you’re compliant with digital standards and government regulations for customer data or for customer data, if you’re in Australia.

0:19:16.2 MH: That’s great stuff, no matter which continent you’re on. So if you wanna learn more about ObservePoint’s many capabilities, you can request a demonstration at observepoint.com/analyticspowerhour, so go there now and do that. All right. Let’s get back to the show.

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0:19:34.7 MK: So you keep talking about this course, what are we in these sessions? What’s the gold that you’re feeding them?

0:19:42.5 MA: So, nice, and it’s funny. It is a course, and we had… We named them actually. There is the 101s, Data 101 and Data 102, then we had the 201 series, which was kind of advanced, so we literally had to come up with a curriculum. And that’s one of the things with when I started doing this, I said, “You know, we need to spin off a Center of Excellence under the Data Office because there’s a lot of teaching happening.” So we did two series, there was the 101 series, which has kind of a data literacy program, that was for the juniors, and I’ll come to that in a minute, but then the 200 series, which was for the ambassadors, so the people actually… Knowing Excel or other business intelligence tools that they learn… First session was pure roles and responsibilities of data. So we got this concept from… There’s a great book about data quality that says like Getting in Front of Data, and it explains two concepts on data customer and date creator. So if you are somebody who creates the report, you are a data creator, if you’re someone who reads data from another report, then you are a data customer, and at some point, you’re a customer and a creator at all time because you need data to create more data.

0:20:57.4 MA: And then we talked about how that translates into their day-to-day job, for example, as a customer, if you see bad data, then you need to report it. As a creator, you take ownership on this data, and so on. Kind of them playing games in the classroom about “Who is my data customer?” and they try to think, “Oh, so that department actually gets data from me, and that department is affected by my data,” and I… “Do you even know your customer?” You know how we only say you have to know your customer? And they realized… We played this role-play game, and it’s always a workshop more than a classroom where you play this role-play is that when you create the support to send it to those customers, do you know that they actually read it the way you intended that they read them? Is this really serving their purpose or are they getting the report and they have to do 20 manipulation to get what they want? And that’s when they realized, “Oh wow, we really have to open communication channels between departments for the creators to talk to the customers,” and that concept really changed the whole way that they look at their role, that I’m not really extracting reports, I’m really helping kind of customers and I need to provide good customer service.

0:22:07.7 TW: I like… I feel like analysts will also often… They fall into… They’re like, “My job, I need to get the report or get the analysis out.” I will rail against them like saying, “You’re so… You’re driven by a deadline, you produced the deliverable, and then you were so relieved to have it done that you just sent it out,” and it’s interesting that… And on the data customers, they’re like, “No, no, I’m just waiting for stuff to be delivered to me,” whereas it sounds like that sort of framing is saying you actually have mutual responsibilities. When I’ve watched an analyst actually, I’m like, “Well, if you don’t know that about the business, why don’t you just ask the person?”

0:22:46.4 MA: Exactly.

0:22:46.6 TW: Or why don’t you share the preliminary to get their initial thoughts, because if you’re confused about what’s going on, they might know, and it’s been funny every time… I’ve had it happen multiple times with the analyst saying, “Oh, I wasn’t actually sharing a final deliverable, I kind of collaborated with my partner, the data customer throughout, and it came out much, much better.” And I was like, “yeah.” So that… But it’s interesting ’cause it seems like the way you’re framing it is like people sometimes they draw a box, they treat themselves as the data creator, not thinking about their customers.

0:23:21.6 MA: Exactly.

0:23:21.6 TW: And on the flip side, the data customers think that, “No, I’m just the recipient. I don’t have any responsibility to close the loop, so.”

0:23:28.8 MA: Exactly, and as a customer, you have a responsibility to basically articulate your need to the creator, because if you tell them, “I need the support about,” I don’t know, “credit card transactions.” “Okay, in what currency, in what format? How often? What time?” all of that stuff. Because…

0:23:48.5 TW: What time frame? Yeah.

0:23:49.4 MA: Yeah. And there’s all this stuff where sometimes, basically, data customers will call my phone, “Give me all the transactions for our priority customers.” “Well, all the transaction, you really need all of that?” And that’s where customers need to communicate better, and creators need to actually know their customers to have that kind of communication between the two, and that’s where the start to all of the optimization of data and reporting across the enterprise.

0:24:16.0 TW: Did you get… And maybe this is more at the selling it to the managers, kind of pre-ambassador… As you were sort of… ’cause it sounds like you had a pretty clear vision and a pretty clear strategy for how you wanted that to roll out, and you’ve told that like, “Yes, I had to do the deck 20 times, but surely in 20% of those were you running into the people who maybe they felt that they needed to use data better, but they also were pretty stuck in their beliefs about how… Were you having one saying, “I don’t wanna hear about all this people process ambassador, just tell me what the new BI tool is”?

0:24:55.6 MA: Yes.

0:24:55.8 TW: Like how much… Were you running into that?

0:25:00.2 MA: There were a few, which… What we call, also in that same book, I love that book, Getting in Front of Data, it describes them as the data factories, so they’re like, “We know what we’re doing and now you have everything, and we can operate on our own.” And that’s where I told them specifically that you are actually a data factory, and some of these factories will have to be demolished. And some people were not too happy to hear about that, but as long as you explain why we’re doing this, because we have to centralise or adopt a single source of truth for the bank. You can’t run your own thing and just do this, and we need you to help the other customers.

0:25:48.1 MA: So, as long as they feel that they’re actually needed and other people need them to succeed, they start to kind of feel, okay, so I’m needed elsewhere, and I need to contribute because my team or expertise or knowledge will have impact on other departments. And as a bank or other specifically, there’s a lot of data shared across the bank, because it’s one client, but every department uses the same dataset, so once… I think once they realize that it’s not about the reports, it’s about the bank trying to adopt kind of a new culture, it’s about the other department depending on them, they kind of let their guard down and all I tell them like, just give me one session and then we’ll talk. And once they understand that the whole data customer creator and responsibilities like, “Oh my God, it’s a bigger network. It’s not just me and my department that reports, it’s everybody across,” then they’re pretty sold into it.

0:26:48.2 MK: So it’s like creating shared responsibility, right? It’s not one person’s responsible, it’s the team’s responsibility, and by suggesting and putting it forth as a team concept, people feel this like, I guess, bond or loyalty to do a better job together.

0:27:04.6 MA: Exactly, and they understand that everybody impacts the data, and everybody impacts kind of the bottom line of the bank because of their contribution to the data, whether it’s quality or reporting or whatever that they do that… We did something called of the chain effect, where the report that you create today goes to this department and then that department, and then some decisions are made at the board level because of a report that you created today, and that’s when they understand, Okay, so we’re… Everybody is part of this game, and we often played the soccer game, and said, Okay, It’s like soccer, you keep passing the ball, which is the customer record or report, but you are… You are a contributing factor to the overall strategy. So they feel like responsibility, like you said Moe.

0:27:46.4 MK: Mai, I literally am doing a presentation on data education this week, and you have just given me the best analogy to use, this couldn’t be more perfect, timing-wise.

0:27:56.6 MH: And we’re done, yeah.

0:27:57.9 TW: But you’re gonna convert yours to Aussie rules football or you’re gonna stick with soccer.

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0:28:05.2 MA: Yes, I was doing a training yesterday too, so we have… What we call them, the front liners, which is the branch staff, and this one, these go through the 101 training, which is a simpler training, but kind of, you’re mainly creators and this is how you live your day and so on. And then I asked, who plays soccer? And nobody raised their hand. And I said, Okay, basketball, nothing. And I was like, Oh, okay, how about cards? And then and we do have a game in Kuwait called Kot, and it’s kind of… I don’t know, not blackjack. I don’t know what’s the similar game, but it’s a six-player game where teams of three play together, and then we had to do the analogy, but on a card game, but it still worked. [chuckle]

0:28:48.3 TW: So can we… A lot of this, and I know it’s like the… It always seems like… I may be over applying the benefit of trying… A lot of what you’ve pulled off because of… Literally, because of the title, I went through an early part of my career, not having much patience for, it has to be top-down, it has to be executive driven, the more I get, the more I say, Well, yeah, but if you try to do this data stuff bottom up, it’s gonna be a long, long haul. So in some essence, it seems like there was a decision or a commitment that was made before you arrived because somebody or some collection of people said, We’re not getting the value that we need, and maybe the cleanest way is to stand up this office, this role, do you have not like… Do you know what that history… Or I guess most companies seem like they don’t have a CDO right now, if you said all companies, and it may be different by different sectors, maybe banking is more likely to, but do you have a sense of what got them to that point of saying, “We gotta double down on this.”

0:30:07.3 MA: Right. So the bank, as part of their bigger digital transformation agenda, they were doing a core banking transformation. So the core banking systems are being kinda upgraded to support all the latest digital stuff and so on, and then the CIO kind of realized how much reporting and then data manipulation is happening, and it was all… Of course, data warehouse lived in IT, and it was any kind of reporting or any kind of data updates or things like that, at all kind of sent over to IT. And it was the CIO kind of call where he said there’s like a thousand reports that you’re asking us to recreate as part of this core banking migration, there should be someone who is deep into the data who can say, Why are we creating all these reports, what can be automated, what can be not, and tech people or pure IT teams, they focus on the platforms, on the actual technology on the software, but when it comes to data, it’s a soft thing that they’re like, I’ll give you the hardware and the software and you take care of it. So their idea was somebody to really come and look at the reporting aspect for the new core banking. I think what he did not know or think about is the whole learning culture.

0:31:25.1 TW: Sure, it was the Chief, I’d say it was the Chief Reporting Officer, and you’re like, No, no, no, no, no, we’re not gonna make it to the Chief Reporting Officer.

0:31:31.7 MA: Exactly. [laughter] Yeah, and I think they just realized how… Or I don’t… I didn’t think they took it beyond kind of just data and reporting or PRMS, and when I came in and I said, Listen, it’s more than just reporting platforms. It’s the people, it’s the culture, it’s whatever platforms we do, like I said, they’ll go back to their Excels the next day, if you don’t change it. And then there was, How can we make money on the data and all of that buzzwords. You can’t get there, if you can’t change the actual mindset around the data.

0:32:08.8 MK: But what about the team internally, ’cause surely there’s also… Like, I don’t know, a big portion of the company, or maybe… Maybe not that big, but a team of people that work with data who have probably been trying to fight the good fight for a long time and come up against, I guess the culture that maybe wasn’t there yet like… Were they receptive to the strategy you put forward? ‘Cause it does sound like you went in with this idea of, “Here’s how I wanna drive us forward”

0:32:39.0 MA: So when I came in, there was no data team. There was two people handling the data warehouse and IT. And that was it. So it was a one woman show when I joined and I was like, “Okay. How’re we going to do this?” And that’s when I kinda drew the picture of kind of, there is a core data team which is my team, which is now a team of eight and then there is the extended data team, which are the ambassadors across all departments. And I call them ambassadors, because they work with me but they’re planted elsewhere in all these business departments. And when I first started I said… Whoever’s doing data warehouse and IT, I inherited those people, just the two team members that moved over. But then the start was, let’s have people running the whole analytics, how are we gonna do the analytics, the reporting and then some… Two team members for data governance.

0:33:38.8 MA: But starting that team, that’s when I realized, “Okay, I don’t wanna make… My department is not gonna create reports. My department is not gonna clean data” Because if there is messed up data in some department, they will clean the data. I’ll tell them how, I’ll give them the tools. So I enable and I empower others to do their job. To me, it’s like I work for the common good. And I’m a partner for all these business departments, but they gotta own their data and… In a way we call them data stewards or data owners. There’s all these cool names, but they have ownership over the data and they take responsibility of their data.

0:34:17.0 TW: So, and I might have… If I misheard, or I’m extrapolating… So does the CIO own still the core technology?

0:34:29.6 MA: Yes.

0:34:29.7 TW: That the data is housed in?

0:34:30.6 MA: Yes.

0:34:32.4 TW: So your relationship is… So where does the data governance and I guess even data stewardship… Is that kind of federated out to the different teams that are actually the data owners, the business process owners? Or how does that… How’s the CDO-CIO relationship, I guess is…

0:34:54.7 S1: Yeah. So we… Both of us kind of… The CDO-CIO, we work together a lot, we’re partners, we report to the Deputy CEO, both of us. So, I work with him a lot, because I need my data to sit on some platforms and technology. And he works with me a lot, because when he is upgrading a system or something, the data needs to be migrated well, plan the… All of that design of the soft… So I work on the soft stuff, he works on the hard stuff, really on the hardware and the software. But not really software software, but the data sitting there. But I have a data engineering team, that’s not engineering in terms of hardware, but really doing the heavy querying pipelines, ETLs, all of that, that’s data engineering. The CIO really, is a key partnership between CIO and CDO for any technology project that we do like the core banking now. When we’re changing core banking migration, they’re taking care of all the software and I’m taking care that, the data that goes into that software is good, the reporting that’s building on it, and so on. We’re actually building an online banking now, a new app and so on. So they’re building the apps and all of the native apps, all of that stuff, but I’m building the analytics into the app. So there’s this strong partnership between the CDO and CIO for any kind of technology project before anything happens.

0:36:17.3 TW: Is the app gonna use GA4? [laughter]

0:36:18.6 MA: Of course.

0:36:19.9 TW: You’re the most knowledgeable person and getting your… [laughter] Getting your hands back dirty, back to your earlier roots.

0:36:27.5 MA: Yes. Oh my God! I was talking… I was actually giving a GA tutorial to one of the teams today. But it was funny and I enjoyed it because like, “Okay, let me log back in and see what we have” And then, it’s like we’re trying to build more people with GA4 and all of that stuff. And again, I’m trying to do the same approach for Google Analytics where in our website right now, there is… Dozens of departments have their content on the website. There’s is the corporate banking and wealth banking, investment, all of that stuff. And everybody has a stake or everybody has something they wanna know what their customers do on the website. So right now we are onboarding department by department, so they get their own access into GA4 and they self serve again with the web analytics. So, they’re not ambassadors that really kind of… I don’t know, I would call them maybe web ambassadors, that’s a cool name. But yeah, that’s something to think about. But they’re enjoying that, “Oh my God! I can dig my own insight, and I don’t have to wait for the marketing team to do this.” I said, “Yes, nobody wants the website or at least the analytics of the website” And again, we have to run another education for GA4 and data studio and all that fun stuff.

0:37:42.8 MK: I’d like to just touch on the role with, I guess the executive team. It does sound like… I know Tim’s kind of touched on this already, that it sounds like you needed the buy in. But the the bit that I probably wanna turn to is more about the buzzwords. Because sometimes when they’re bought into needing a CDO is because they are like, “We should do machine learning and we’re gonna put everything in a box and we’re gonna do personalization” And they come out with all the buzzwords. Have you…

0:38:13.7 MH: Wait, hold on. “One to one marketing”

[laughter]
[overlapping conversation]

0:38:16.1 MH: Just a couple more [chuckle]

0:38:19.3 MK: And yeah, they just come out with all these buzzwords, and that’s their expectations. Have you encountered that at all or chatting to the other CTOs in your network?

0:38:27.5 MA: Oh yeah, they showed me a report that was prepared by a consultant before I joined about everything that they can do with data. And you know how consultants really add all these fun…

0:38:37.4 TW: Consultants are the worst. They are. They really are the worst.

0:38:41.7 MA: I haven’t been one, I don’t know. [laughter] But like they tell, like you should do this and you should do that, and there’s all these opportunities that you missed because you’re not having machine learning and all of that stuff. And the thing is, is as long as you draw a roadmap to the management and tell them that this is where we’re headed, but we need to start with the basics. Before we build and get to that machine learning, we need to do this and we need to do this. And really explain it to them in English honestly, they don’t wanna know the tech words and all that stuff, they just wanna know how does their department grow in terms of… Or mature in terms of data. And I called them or I told them that we need to get to walk before we run. Because right now, we’re not even crawling, with data with Excel and all of that, it’s kind of the basic stuff. And that’s where it… They understand that you can’t just jump all the way to machine learning and predictions without getting some of the basics first.

0:39:46.5 TW: Well, ’cause I feel like that’s the sort of thing. Like the crawl, walk, run. You can have that, do you get some of the like, “Oh yes, yes, we understand that we can’t do machine learning until we have the basics down, so can we do machine learning next month?”

[laughter]

0:40:04.0 TW: It’s one of those words in the moment when its specifically calling it out, that we have to… The do, do you… Is it a constant pressure where they’re saying, “Yeah, yeah, yeah, but Mai, you’ve had three months now, can we do AI?” And you’re like, “Come on.” Or do you feel like you’ve kind of gotten… It feels like it partly… Maybe because of the breadth of the scale, you’re kind of moving everyone along at the same point, or you still… Do you still have people saying, “I read an article, I read an article in Forbes and they said, I need to be doing GPT-3 auto customer communication generation?”

0:40:44.6 MA: And one thing about the banking world is, it’s a bit slower than when you’re in e-commerce and all that stuff, they understand, “Oh yeah, oh, the regulators have to approve this now, or we have to run this across three months of try before we roll it out to customers.” So the pace is slower and they’re more patient when it comes to rolling out things because they really worry that it might really affect customers or regulators, of course, as penalties or things like that. So that’s one thing where I think it’s not too crazy as much as in my previous life when I was working with e-commerce, we could do everything over a week, it doesn’t matter, “It’s Black Friday, we gotta get it done, and so on.” [laughter]

0:41:32.8 MA: Versus here, I think it’s more about getting it right and making sure that it’s in compliance with everything and making sure that we do this and… A lot of people in tech that I’ve seen here is actually they play that compliance card a lot to delay stuff, but… We all have a card, in every industry. [laughter] But it’s more of a different way of thinking that they look at it, which I think was helpful because it gave us some time to actually build the basics and start with the structures before we go into AI and machine learning and so on.

0:42:11.5 MH: Okay, it is time for that quizzical query, the conundrum that gives everyone such fun. It’s the Conductrics quiz. Tim and Moe, are you excited?

0:42:24.4 MK: Very.

0:42:24.8 TW: You bet you.

0:42:26.2 MH: Alright, well, let’s get into it, but quickly, a word about the sponsor of the Analytics Power Hour and the Conductrics quiz are sponsored by Conductrics. They build industry leading experimentation software for AB testing, adaptive optimization and predictive targeting. For more information on how Conductrics could help you, visit conductrics.com. Alright, let’s get into the quiz. Tim, you are representing a listener, do you wanna know who that listener is?

0:42:56.0 TW: Absolutely.

0:42:56.9 MH: It is Adam Wodehouse, awesome.

0:43:00.1 TW: Wooo.

0:43:01.0 MH: And Moe, you are representing Robin Dickenson.

0:43:05.9 MK: Hello, Robin.

0:43:07.7 MH: Let’s get into the quiz. Here we go. And this one is a good one. [laughter] As Tim and Moe… In other words, it’s got that narrative style that we like so much. [laughter] As Tim and Moe sit quietly in their thoughts, Michael starts to play a YouTube video on his computer and music fills the room. Rather than get annoyed by the interruption, as he normally would, Tim breaks into a large smile and says, “Ah, Tom Lehrer! While my favorite is poisoning pigeons in the park, I do love Lehrer’s New Math. What made you put this on, Michael?” Moe rolls her eyes and mutters, “Of course, Wilson loves this”. [laughter]

0:43:45.8 MH: Well, Michael explains, “I have this data file that has numerical value stored as hexadecimal, which is base 16, and since Lehrer’s song “New Math” was all about doing arithmetic in different bases, I thought this would be a good background music while I figure out how to do this. For example, does anyone know what 22B is in base 10?” And after a long pause, Moe answers, “I’ll give you a hint. It’s also the name of a Charlotte Gainsbourg song.” [laughter] Okay. What is the name of the song that we’re looking for? Is it A-555, B-428, C-771, D-568 or E-281?

0:44:41.3 TW: Come on, this I ought to be able to do the math real quick.

0:44:44.9 MK: You know the funniest thing is like back in my heyday, I used to have things to convert this. I had notes somewhere on how to do this.

0:44:53.0 TW: Really?

0:44:53.7 MH: This is one of those times I could actually know the answer, but I really don’t. [laughter]

0:45:00.2 TW: Well, I should be… Oh my goodness.

0:45:06.2 MH: Alright. What are we thinking?

0:45:09.1 MK: I’m gonna eliminate number five.

0:45:10.4 MH: E-281. Okay, considerate eliminated, that is not the song, which is great because you’re such a fan of Charlotte Gainsbourg’s discography.

0:45:24.3 TW: I’m gonna say that it is… I’m gonna go that it’s actually four, 568.

0:45:30.1 MK: As in that’s the answer?

0:45:32.3 TW: As in that’s the answer.

0:45:33.8 MK: Wooo.

0:45:35.7 TW: That is 568, D. But yeah, that’s me doing only part of the math and not realizing that 555 is up there, too. B would be 60D. Yeah, I’m gonna go ahead and go with that, even though I think it may also be…

0:45:50.4 MH: Well, one thing that D definitely is, is the date of the Paris student protests in May of 1968, but it is not the answer. So that means Robin Dickenson by default, you’re the winner. It is A-555.

0:46:09.1 MK: Woo-hoo.

0:46:09.1 TW: I get to the… I will say that I was like the 222, the 2 was 256 times two, so 512, and then I was just struggling to add 512 plus 32 plus the B would be, good lord, like another eight… Yeah.

0:46:26.0 MH: Yeah.

0:46:26.6 TW: I just… I missed the 555 was there, but I’d gotten a ballpark of it.

0:46:32.3 MH: There’s… All of these you could have easily realized that there’s other answers for these, which B-428 is the month and year of both Tom Lehrer and Serge Gainsbourg’s birthdays. C is Charlotte Gainsbourg’s birthday. E-281, which we eliminated, is Paris Hilton’s birthday. So there you go. Little fun facts, but 555 is the answer. Robin Dickenson, you’re the winner, Moe, great job, sometimes you just get out of the way and the good things happen, that’s right. [laughter] Alright, so that’s the Conductrics quiz for this week. Big thanks to Conductrics for sponsoring. Let’s get back to the show.

0:47:20.2 MH: So, Mai, I wanna sort of change gears a little bit and talk a little bit about… So you just mentioned that this year you’ve added innovation to your portfolio, and I think that makes a ton of sense because there is always in a data organization sort of this not well-defined drop-off point of sort of like, well, once we start seeing where we should go with all of this, who should take it from there?

0:47:45.8 MA: Yeah, right.

0:47:47.0 MH: And it sounds like you have a good perspective, but could you talk a little bit about how that came to be and sort of maybe some of your initial vision for how you’re gonna be driving that? I think that’s… Because it’s sort of the data and action part of it, in a certain sense, which I think our listeners would find pretty fascinating.

0:48:06.7 MA: Right, right. So how it came into my lab, kind of the innovation, it wasn’t really a part of the plan, I’ll be honest, but there was this kind of… There was a mandate by our regulators to actually… They asked all banks to actually form an innovation unit and make it kind of a part because they want banks to catch up with FinTech. I’ll be honest, banks are lazy when it comes to like, okay, let’s get digital and do all of that stuff, but they wanna make sure that when FinTechs are coming, and as the regulator is kind of cleaning a lot of these FinTechs and cryptocurrencies and all that stuff, that the banks are able to catch up and not lose business heavily to them.

0:48:51.0 MA: So, they were… There was a mandate to do that innovation, and it’s funny when the Gulf Bank first approached me, they actually wanted me to run this, but then I was like, “You know, I’m really interested in data analytics, we’ll do that, and maybe that would come, I don’t know.” And then I think as I started running the data and working more of the big scale analytics of the bank, I realized how that kind of fits in very well with the data, because my analytics and on monetization team will feed the ideas into the innovation team. And again, the innovation team will need feedback, and you need data for that and so on.

0:49:32.3 MA: So, what happens, at least to equate to how they do it is they nominate somebody. And I had to go through an interview with the regulator to make sure that they do have the qualification to run the innovation as part of this, and it was an interesting interview to see how the regulators see kind of the innovation as part of the big picture, and all of that. So what we’re doing right now is really… Like I said, I do have governance and I do have the data engineering team, which are working on the harder and boring stuff of that data, but my analytics and monetization is gonna be tightly linked with the innovation, and also the digital analytics is gonna also play a big part of that, because a big part of it is personalization when it comes to innovation.

0:50:20.8 MA: And when we say personalization, a lot of people are digital right now, and that’s where we catch them, that’s where we know them. So it’s my big picture or my kind of plan for it, is first they wanted to call a digital transformation, and I said, “Listen, once we digitally transform, there’s nothing more to do,” so if we just focus on the innovation aspect, on coming up with more ideas through data, that’s, I think, the right way to bring it forward to our teams and to ensure that we can innovate, but we innovate with what? With data. And I think…

0:50:53.9 TW: Yeah, no, I love that.

0:50:56.2 MA: I think one of the things that we might try to do is similar to how we did ambassadors across, we can have innovators club across, because ideas come from everybody in the bank, and you just have to prototype it, try it and innovation. And I attend this kind of CDO magazine, they has CDO ambassadors called Arks quarterly. And then the other day, there was two of them which became Innovation Lab officers or something like that. I’m like, “Okay, again.” That’s the same trend happening again, where people in data are moving into innovation. The way they described it, so I wanted to ask them how are they running this innovation, and they said listen, “We do everything that other departments can’t do.” That’s how they do the innovation. I’m like, “That’s an interesting way to look at it.”

0:51:48.1 TW: The cynic in me wants to be like, “Data’s like innovation.” Everybody wants to do it. And they think they’d be good to do it. But they’re actually, most people are actually kind of resistant to change. Right?

0:52:01.3 MA: Oh yeah.

0:52:02.2 TW: If you’d swap out data for innovation and saying that, “Oh, I want to… Yes, we need to be very data driven, and yet we wanna operate in the old way.” Same thing with innovation. Innovation it’s like a sexy word, to be innovative. But it’s actually hard both to move forward. Both of them need to change something about the way you’re working.

0:52:26.3 MA: Exactly.

0:52:26.6 TW: And human nature is to not change. So it seems like they both… I think you’re actually, with the update to your title, you’re the chief uncomfortable situation officer.

0:52:37.8 MA: I think that’s a very accurate discovery.

0:52:41.2 TW: Making people uncomfortable.

0:52:42.8 MA: I know. That’s why I had to… We’re running this ambassador program trying to push people out of their day to day style of doing things, we always had to kind of gamify it somehow to those ambassadors because it’s hard to, like you said, to change the way you do things and we need to really focus on one part as Moe said was the responsibility aspect, is that you’re responsible. There’s a big responsibility behind your role as a customer, creator, ambassador, all of that. But then we really gotta make it fun because we’re really asking them to change and, really sell it to them in a way.

0:53:19.2 MH: Yeah. And so, I’ve got another question, which is a little more individual, but I think might be insightful. Obviously, managing all of this change and sort of this transformation, that doesn’t come without challenges. I’m sure not every day is an amazing day. And as you look at your experience as a leader, what attributes or personality traits have sort of stood out to you as getting you through and accomplishing some of those things? Because I think… Obviously to me, I love how you’re coming across on the show. And I can see as we’re talking, I’m like, “Wow, you’ve got such confidence and such poise around this and yet at the same time… ” Most of us analysts are always questioning ourselves and doubting whether we’ve got the right track, and I’m thinking, I was like, “Maybe that’s what it takes.” To be the CDO, maybe you need to sort of just find that gear. So I’m just… I guess the question I’m asking is, “Yeah, what part of you is helping you drive this success that you’re seeing?

0:54:28.8 MA: Yeah, and I question myself all the time, every day, it happens [laughter], like everybody else. But yeah [laughter]

0:54:36.2 MH: No, don’t we all? Of course, yeah. [laughter]

0:54:39.4 MA: But I think one of the things I read, there was the book it’s called “The CEO journey.” So I read this before I started my job. I took few months off, and I read that book. And one of the things it said that, as a CEO, you’re in continuously be talking and talking to everybody across all level, across different business backgrounds, different… It’s like you’re constantly talking. I’m like, “Okay, that’s okay.” I could talk, but the part I think was being able to talk to people, and really communicate, get that kind of common ground, however their business background, their level and organization, and how you can make that effort with other people.

0:55:26.3 MA: I think the main leadership quality was building the communication skills and I think being a consultant for 10 years, working with different stakeholders, managing all these stakeholders, working with business tech, mad customers, happy customers, all that stuff gives you a lot of communication skills and how you cater to that you talk to. And I think that came in very useful in my current role, that I’ve been into consulting for a long time and worked with hard and crazy customers sometimes. And now it’s so comfortable for me to kind of come and talk to junior, senior, board level because I’m constantly talking about data. Like I said, part of it is just teaching up, but part of it is selling it. And being able to relate, and communicate, and make partnership with others regardless of their background or how much are they opposing me but I can start to build a partnership. I think that’s the key quality, is communicate to really partner with the other.

0:56:32.0 MH: Yeah, no, I love that. Thank you so much.

0:56:34.2 TW: It’s like an inadvertent callback to the Episode 186 where we were talking about different types of companies to work for. I don’t know that we hit on, but I think… Because Mai, you’re making the point that that is one of those things that you can get from consulting is that comfort with educating, reading the room, thinking on your feet, all of that to try to affect change and that is a really, really useful skill even though now you’re applying it very, very in the most in house you can get in kind of an executive level role.

0:57:09.0 MA: True, true.

0:57:09.4 TW: But applying those skills.

0:57:11.5 MA: And I’ve seen a few other leaders that I met while doing those 20 repetitions of the same slide deck. One day there was a financier, she’s like, “Yeah, you come from a consulting background, huh?” Because she was in consulting, too. [laughter]

0:57:29.9 TW: It takes one to know one. [laughter]

0:57:32.0 MA: Exactly. [laughter] So it really comes in handy and useful to actually kind of have…

0:57:37.8 TW: You must have talked about deliverables in that slide deck then.

0:57:40.9 MA: I can’t remember what it was exactly, but I think it was… ‘Cause in that meeting there was a lot of people opposing. And those were the data factories that I’m trying to demolish. And she saw how I have a good listening ear. Before you talk, you listen to all the stakeholder issues. And sometimes as a consultant you’re a therapist to your client, you just listen and listen and listen, and then come up with a solution or talk. So it helps when I’m trying to get the buy-in from people across.

0:58:15.2 MH: 100%. Alright. And as a consultant to this podcast as the facilitator, we do have to start to wrap up a little bit here. This has been such a great conversation though, Mai. I just really have appreciated hearing your perspective and some of the things you’re doing to drive this sort of data transformation and innovation there at Gulf Ban, so thank you so much.

0:58:38.9 MA: You’re welcome.

0:58:40.4 MH: One thing we love to do on the show is go around the horn and do a last call, something that we’ve seen recently or wanna share that might be of interest to our audience. Mai, you’re our guest, do you have a last call you’d like to share?

0:58:52.9 MA: Sure. I published an article about enabling data-driven transformation, and the way I call it, is I call it a recipe for data culture. So I published part one recently, and part one is coming up in a few weeks. Part two is coming up in few weeks. I really suggest that people read it to understand how can we build a data culture. And it doesn’t just apply to banks, it applies to everybody. And the funny part that at the beginning of the article, the example that I give is about digital marketing and how people can become data driven with digital marketing. So I think it might be very relevant to the audience that you have.

0:59:32.7 MH: Excellent, thank you very much.

0:59:34.6 MA: And it’s published on CDO Magazine.

0:59:36.5 MH: Alright, okay, perfect. Yeah, we’ll get a link to that.

0:59:39.6 TW: You don’t have to be a CDO to read it though?

0:59:42.2 MA: No. [laughter]

0:59:42.4 MH: That’s right. No, you do… I hope not ’cause I already read it, and I’m not a CDO.

0:59:48.7 TW: Congratulations, you’re the CDO of the analytics panel.

0:59:52.5 MH: Yeah, we’ll see. Oh, thank you. Wow, well, we’re gonna do some data ambassadorship here, Tim. But actually before that, Moe, would you like to share your last call?

1:00:02.5 MK: Sure. Well, given it was International Women’s Day just a short couple of weeks ago, I wanted to share this little quote that I heard which I just absolutely loved. And I don’t know why, it just really got me thinking about the women that are around me. So the quote is “Surround yourself with women who would mention your name in a room full of opportunities.” And I don’t know, I just think it really summarizes that idea of having a group of women around you to really support you, and I feel like in my career I have been really lucky to have that. So yeah.

1:00:38.3 TW: Is there attribution for that quote or you just… I mean…

1:00:41.5 MK: Sure.

1:00:42.2 TW: Do you know who… Did somebody specifically say it or no?

1:00:44.4 MK: No, I don’t know, it’s from Instagram. Tim, what do you want from me? [laughter]

1:00:46.8 MH: Oh Instagram.

1:00:50.8 TW: From Instagram. Okay.

1:00:52.1 MH: Okay. Nice. Alright. Tim, which podcasts are you gonna mention on your… No, I’m just kidding. What’s your last call?

1:01:00.6 TW: I’ve got a couple of podcasts. But my source of many last calls winds up being Walt Hickey and Numlock News, past, past guest. And the most recent discovery, by way of Numlock News is Philip Bump. He’s at @pbump on Twitter. He’s basically like a data-vis guy at the Washington Post. But he has a newsletter, a weekly news newsletter called “How to read this chart”, which I’ve only recently subscribed to, but it’s kind of a fun… He’s very thoughtful, he brings together different threads from data visualization and does some like recreation and original data visualizations, and is just kind of an entertaining and thoughtful read. So fill up your inbox with one more weekly e-newsletter with “How to read this chart”, is my last call. What about you, Michael?

1:01:58.1 MH: Well, I’m glad you asked. So I recently ran across an article by a guy by the name of Arpit Choudhary, I might be getting his name wrong. Arpit. Arpit, I don’t know how I pronounce his first name. But it’s about data collection or behavioral data collection, and in sort of the more modern data stack context and I thought that’s actually a pretty valuable piece of information. And he walks through some things in that article to sort of like a guide for analyst and data engineers around that specifically. ‘Cause when you’re doing a lot of event data now in GA4, but previously in things like Mix Panel, Heap and other tools, thinking about how you might migrate that into a broader data warehouse has been a stumbling point for a lot of product analytics team. So I like that article a lot. And it was, I think, a very helpful primer on a few topics. So that would be my last call.

1:02:52.2 MH: Alright, well, I’m sure you’ve been listening and you’ve been thinking, “Wow, I’m ready to become a CDO.” Well, I don’t know, maybe you are, maybe you’re not, but we’d love to hear from you, and we would love to hear your thoughts on the episode. And so the best way to do that is through the Measure Slack or on Twitter. And we’d love to engage with you on this topic. And obviously, we wanna thank Josh Crowhurst, our producer, for doing such a wonderful job of helping us put the podcast together. And once again, Mai, thank you again so much for taking the time to share your insight with us. A very cool conversation. I really appreciate it.

1:03:34.1 MA: Thank you for having me, this was a pleasure. I’m so glad to be here.

1:03:37.7 MH: Yeah. Well, I can’t wait to see the innovations that come from the work you’re doing there. And the world just needs more of this. So I’m thankful for you and all the great work you’re doing.

1:03:49.4 MA: Thank you.

1:03:50.2 MH: So alright. Well, and there you go. As I say, no matter what your level, I know my two hosts probably agree, Moe and Tim, we should all keep analyzing.

1:04:07.2 Announcer: Thanks for listening. Let’s keep the conversation going with your comments, suggestions and questions on Twitter at @AnalyticsHour, on the web at analyticshour.io, our LinkedIn group, and the Measure Chat Slack group. Music for the podcast by Josh Crowhurst.

[music]

1:04:25.3 Charles Barkley: So smart guys want to fit in, so they made up a term called analytics. Analytics don’t work.

1:04:32.9 Thom Hammerschmidt: Analytics. Oh my God, what the fuck does that even mean?

1:04:41.8 MH: What am I missing, Tim?

1:04:45.6 TW: I don’t know, something critical that I’ll blame you for later.

1:04:48.5 MH: Probably… Yeah, later, you can blame me later. Okay, let’s do this. [chuckle] Oh, we need to backup. In the show prep document… So I think you’re in the document. If you look, I’ve highlighted a…

1:05:05.0 TW: Hey, Michael, you need to make sure that the bio is right, yeah.

1:05:08.3 MH: Thank you, Tim, that’s what I depend on you for. And don’t be afraid to bring up some of the culture stuff too if you’d like, because I think that’s… Well, I literally just did a talk about culture at Super Week like…

1:05:23.7 MK: Nice.

1:05:24.4 MH: A few weeks ago, so I’m like, “Yeah, please bring that up.” [laughter]
[music]

1:05:33.2 MH: The jet lag fools you into thinking you’re sicker than you are, I think.

1:05:37.1 TW: It’s like shovelling snow for two hours, shovelling snow for two hours with jet lag, and I then I was like… Two days later I’m like, “Oh, that was COVID”. [laughter] Yeah, that’s why I was so tired.

1:05:49.4 MH: I on the other hand took it much more seriously than Tim did. Anyways, alright. Enough of this. We’ll get started.

1:05:55.9 MK: I feel like that’s a first right?

1:05:58.3 MH: What?

1:05:58.8 MK: You taking something more seriously than Tim?

1:06:03.0 MH: Yeah, just life in general. Yeah, Josh, let’s make sure that that gets in the outtakes. [laughter]

1:06:10.5 MK: That’s funny.

[music]

1:06:14.4 MH: Rock flag and innovative data ambassadors. [laughter]

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