[00:02:14] Jonas Christensen: Randy Bean. Welcome to Leaders of Analytics.
[00:02:17] Randy Bean: Thank you. I'm delighted to be here, Jonas.
[00:02:20] Jonas Christensen: I am very excited by today's episode because we are going to be talking about the challenges of the chief data and analytics officer role, or the chief data officer role, depending on what kind of combination of those you like, we'll get into whether they should be combined or not as well in this podcast.
But before we do that, we should hear a bit about you. Could you start by telling us a bit about yourself and your background?
[00:02:49] Randy Bean: Yeah, I've spent an entire career, one might say, an entire lifetime in the data and analytics space, and it was largely by default. I studied English and history and art history and all of that type of stuff, but I wanted to work for a major company, so I went to work for a major bank, bank of Boston, which is now part of Bank of America.
Where the jobs were when I was coming outta school was, it was the early stages of really the development of technology. So I was trained as a COBOL and Assembler programmer, but I was much less interested in the programming and much more interested in the stuff that we were moving around, which was the data.
And I was responsible for the deposit accounting history system. And I remember going to some of my colleagues or leaders and saying, wow, this is amazing. We collect all of this information on our customers, their history, all of their transactions over the past seven years. What do we do with this information?
And the response I got was, well, the regulators make us hold onto it for seven years, then we're able to destroy it. And my response was, wow. You know, what a what a lost opportunity. So after a few years, I moved on to the business side of the bank, helping the organization use the data. Basically do a better job of acquiring customers, retaining customers, cross selling customers that went to work for a number of years for a company that was a leader in an or an early pioneer in database marketing.
Now today that might be known as C R M and work with most of the major banks in North America. There was a lot more than. Helping them get, keep and grow their customer relationships. During the internet era, I went off to Silicon Valley. I helped in co-founding two venture backed startup firms, including one with Kleiner Perkins in 2001.
All of that came collapsing down not knowing precisely what to do next. I started my own firm called New Vantage Partners, and for 20 years we advised Fortune 1000 companies on how to innovate with data, how to build the data culture, how to become more data driven, those type of activities, how to leverage data as a business asset.
Did that for 20 years through many different cycles, and then sold the company in December of 2021 to a global consultancy, Wavestone. And I continue my affiliation with 'em. Now I'm something called an innovation fellow. I equate it sometimes to being professor emeritus. So I do a lot of speaking, writing.
I organize a significant number of chief data and analytics officer events next week in Cambridge, Massachusetts. I'll be moderating for the ninth consecutive year, the C D A O panel. So this year have chief data officers from universal Music, Sanofi Visa, Colgate, Palmolive, and Harvard Business School.
So that will be the ninth year. I'm also organizing four or five other C D A O events this year. And I guess the other thing to mention is that along the way as data gained in prominence, I started to be asked to write, so in 2014, 2015, I wrote a monthly column on Big Data in the Wall Street Journal. I have continued ever since then in Forbes, I write about three to four articles per year in Harvard Business Review a six part series each year in MIT Sloan Management Review.
And during Covid, because I couldn't travel, I wrote a book, Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an age of Disruption, Big Data and AI. So that's, it's a little bit about who I am.
[00:06:37] Jonas Christensen: Great. And I'm sure that a lot of the listeners to this podcast will know your, your writing from, especially the Harvard Business Review.
That's where I've come across it. And also Forbes, of course. So you have contributed to the discourse around data and analytics for quite a long time, and you're a well-known figure. So you are absolutely the right person to be talking about and commenting on the topic of today, which is a very exciting one, which is, The Chief Data Officer and where they're at and where they're going to get to in the future and all the challenges that come with that.
And Randy, I think we should actually start with some sobering facts that come from, from you, from New Vantage Partners, because you recently did a survey and I'll start quoting some numbers in a minute here. Oh, you've got it there. You're holding it up. And right now we're definitely in AI hype mode.
Everyone's excited by AI and ChatGPT has made it real for a lot of people and that's great, but it really seems like this progress is not necessarily driving lots of data related innovation inside organizations that are not these sort of AI tech companies, like our favorite friends, Microsoft, amazon, Google, what have you, the FAANGs, the Big nine.
In all the other companies in the world it's much more mundane. And actually I'll start now reading some of the stats from your report there, which is, that between the first time you did the survey back in 2019 and now 59.5% of executives reported their companies were driving business innovation with data. No change in that period. Just under 41% of executives today reported that their companies were competing on data, which is actually a decrease from almost 48% four years ago.
Almost 40% reported that their companies were managing data as a business asset, which is also a decline from almost 47% four years ago. 24% reported that their companies have created a data-driven organization, which is also down from 31% four years ago. And then lastly, 21% of executives reported that they had a data culture established in their organizations.
That is again, a decrease from over 28% back in 2019. So lots of decreases in these numbers. So we've actually gone backwards at least, maybe not in a an absolute sense, but somehow the goalpost has moved perhaps for what these terms mean. And this is despite nearly 83% of these organizations having a chief data officer or equivalent role in place.
What's going on? Could you tell us about this?
[00:09:28] Randy Bean: Yeah, happy to. And, and this is a topic I could probably speak on all day for many hours because it, it is where I'm focused and because, you know, there's a, there's a lot of topics. The other day somebody introduced me as a AI expert, which I thought was very funny.
And I said, first of all, I'm not an AI expert, and second of all, I'm not sure that anybody is. But when it comes to the role of the Chief Data Officer, let me give you a couple data points. And by the way, we actually started conducting this survey of Fortune 1000 organizations in 2012. We started asking those questions five years ago to track the progress, but initially launched the survey in 2012, prompted by a C I O from actually from JP Morgan of all places, who really wanted to understand whether big data was something that was taking hold within Fortune 1000 companies or if it was just the latest trend.
So that was really the impetus for the survey. So, you know, as noted from the outset, I've been working in the data space long before you know the existence of the chief data officer role, and its various permutation s since then. So, you know, for, for many years, data was a domain of the chief information officer or or other groups within the organization.
But following the financial crisis of 2008, 2009, from a regulatory perspective, there was a real impetus to establish a role where there was responsibility for data. Because so much of the data and numbers that had been produced and shared with the regulators at the time of the financial collapse were, were inaccurate.
So initially, and particularly within major Banks, the CDO role was established purely on the defensive role, regulatory risk management, etc. As it so happens, one of the first chief data officers, actually the first enterprise chief data officer for a major bank was one of the partners within our firm.
So he was hired out of our firm to be the first enterprise chief data officer at Citigroup. So really from day one had a visibility into, okay, what is this new role? What does it mean? Where does it report? What are its responsibilities? And what I've seen over time is that it's a very nascent role in the same way that 35 or 40 years ago, the CIO was.
Inside Joke at the time was c i o stood for Career is Over. In that same respect, CDO is a challenge because, you know, there's not a standard blueprint. Each organization or certainly by industry varies in their vision of how they've applied the role. You know, many CDOs aspired to do more than just risk and regulatory work.
They want to help grow the business insights into customers, and so over time, The CDO role took on a more offensive aspect, and I believe this year in that same survey, if I could pick up the numbers, it was roughly, I'm gonna say two thirds that were now focused. Well, to be precise, 61.8% said that they were focused on offensive activities, growth and innovation relative to defense, regulatory and efficiency, which was 38.2%.
So some progress in in that regard. But you know, it's a new role. Organizations continue to struggle with deriving business value from their data and analytics investments. At the same time, any type of change or transformation, it doesn't take place overnight. So organizations need to be realistic in terms of their expectations of achieving business value. It Doesn't happen over a period of quarters or even a few years. It happens over many years. Earlier in my career, I had a CIO of a major bank that said to me, you know, any significant change, it takes at least a decade for it to take place, at least within a legacy company. So, you know, if you're a greenfield company, like the firms, you mentioned Amazon at the start of the digital era, Microsoft, et cetera, you know, you don't have the burden of all of that legacy baggage.
But if you're a company that's been operating for generations or even for 200 years as some of these major banks, it's a significant change to your business processes, how you operate, et. There is both good news and bad news in this. The bad news is that there's a long way to go, but the good news is that there's plenty of opportunity progress is being made.
My colleague Tom Davenport, who wrote competing on Analytics when reported that only 40.8% of organizations were competing on analytics, he said, you know, when I wrote that book 20 years ago, if you had told me within 20 years, 40.8 would be competing in data and analytics, I would've thought that that was a great accomplishment.
So, A lot depends upon your vantage point as well, whether the, you see the glass is half full or half empty.
[00:14:37] Jonas Christensen: Yeah. And I imagine this goalpost moving all the time for what we call data driven and what we call innovation with data and so on. You, you mentioned a really important concept, which is also another famous Harvard Business Review article actually around being defensive versus offensive with your, with your data.
And the original chief data officer role was very much data, right? So I'm actually thinking data warehousing projects and the data accuracy mainly. Now you're seeing it often also encompass the offensive part, which is the analytics and the driving of business outcomes, et cetera. Where is that going?
Is is this a role we should be considering to be a chief data and analytics officer role most commonly, or where do you see that?
[00:15:27] Randy Bean: Well, you know, that's interesting because in the latest Harvard Business Review article I wrote, I think I called it the CDAIO. Because several organizations were now lumping artificial intelligence into that as well.
So, you know, we can say it's a work in progress in that regard. But a few other points there along those lines, and that is, is that a lot depends upon expectations. So you mentioned that the survey numbers that had gone down. And people have said, you know, why is that? Are we getting worse? And my response is, you know, it can be attributed to a number of factors.
I mean, obviously volumes of data continue to proliferate, sources of data continue to proliferate. But I think over time as organizations become more mature in the role, they also become more realistic. So I think at the outset of many chief data officers and organizations that have newly established the role, they said, well, of course we're data driven.
And of course we're competing on analytics. And of course we have a data culture. But over time, as they become more realistic, they've said, you know, we really don't, and let's not fool ourselves and we have work to do and we should be realistic about that. In terms of the integration of analytics into the role, I think that there's a question in the survey this year that asks whether analytics had been integrated into the CDO role, and I believe that roughly two thirds of organizations said it had.
So clearly this is a trend and direction, and I think it's a very positive trend because often in its initial phases, CDOs were primarily focused on gathering the data, organizing it, making it more accessible, issues around data cleansing, data access, but less focused on the application. I guess one of the things that I try to encourage any organization is that, you know, from my experience, the most successful chief data and analytics officers are those that are closest to the business, and that it all starts with the business in terms of, you know, what are the most important questions that you need to ask as an organization and need to solve to grow your business, to innovate, to effectively serve your customers?
And you know, one of the things that have seen this year is that given various degrees of economic uncertainty and given layoffs in, say for example, high tech industry, and Given bank failures, Silicon Valley Bank, First Republic Bank, Credit Suisse, there's been greater pressure than ever on chief data and analytics offices to prove that they're delivering business value.
So I think my year began 2020 23 on day one. January 1st. Hearing from the Chief data Officer from Verizon that they were no longer in that role, and since then, I believe there's been roughly 15 or 16 chief data officers ranging from Albertsons, to Citizens Bank, to Eli Lilly, to Levi's to State Farm .
You know, the list goes on and on. Have left their roles and when I'm asked, you know, why are they leaving their roles, is it voluntarily or not voluntarily? You know, I say that from what I'm seeing as best I can tell, you know, with kind of a 360 degree perspective that you hear within from others within those organizations as well.
It's really an issue of renewed pressure this year for chief data office and analytics offices to show that business value. And as a consequence, you know, the heat has been turned up. Some people have said, you know, this has become an impossible role, so they decided to move on. Others, they've been put in a situation where it's impossible.
So show us within 30 or 60 days the value that you're delivering. And then if they can't, then you know, maybe that you aren't the right person for the job. I've also seen people, more people with business backgrounds being put into the CDAO role. In other words, like, you know, you, you don't need to be a data management expert. You don't need to be an analytics expert, but what you do need to know is you need to understand our business. You need to understand how data and analytics can be important to our business, and, and that's what we need in this role. So that's kind of a, a, a long-winded answer or perspective on your question, but I'll, I'll pause there and see if you have any follow up on that.
[00:19:57] Jonas Christensen: I definitely do, and one of the things that I say to people often is, this is one of the hardest jobs out there. Objectively. In my opinion, this is one of the hardest jobs out there because it's undefined. It is delivering value through others, not by itself. It doesn't own its P&L . It has to convince all stakeholders to do the right things with the outputs that comes from the, the teams that sit underneath this role.
It's largely not that well understood what data is and where it comes from and what can be done. And the whole AI hype shows that as well, that now everyone wants some AI solution without really understanding where that begins and ends. I could go off on a rant on this too, Randy, if I had the time, but I, I think let's, let's get back to making this really practical because let's define why it is so hard and you actually, I think, have already done that because you say that, The chief data officer actually has seven roles in one.
So could you outline for us what are these seven roles and how maybe that's changed over time? I know you've touched on it, but kind of a little bit of the detail on, on how that's changed over time and, and how that's led to this situation now where there's so much pressure on, on people in these roles.
[00:21:21] Randy Bean: Yes. And you know, it's, it's funny because when I read the questions I thought, you know, maybe I'll just answer those questions as they're posed or, or I come back and say, maybe we should change those questions. And this was one of those, because first of all, I can't remember what the seven roles of the chief data officer are, but it doesn't really matter because that article was written three or four years ago.
And undoubtedly they've changed in some respects significantly. So what I'd say is that at a high level, yes there are the activities, you know, what we call, what one would describe as the data management activities to make sure that your data is in a format that business users can get value from it.
Obviously there's the analytics component is that these days it's the AI component. More and more organizations are looking at the ethical consequences and privacy. So there's those components as well. You know, I, I could kind of go on and on, but you know, one thing that I would say is that, you know, to your point about business sponsorship, you know, one of the things that I see that distinguishes organizations and CDAOs that are most successful is, When the business views you as bringing value.
So for example, JP Morgan, within the past several months, they presented one of their annual reports of quarterly reports, and Jamie Diamond got up there and he cited thing number one. And then thing number two was how data and analytics were making such a critical difference in the business, and he cited all of the examples.
So to me, that's an example of where data and analytics has been embraced and is being successful. On the other side of the spectrum, I see a number of chief data officers that say, Hey, you know, we're doing really great things. We're really doing really great things over here. Don't you see all the great things that you're doing?
So if you have to be the one that's, you know, touting your own horn as opposed to the business saying we couldn't do it without our team here. I think that's a critical difference. And one of the things that have seen over time to the broader questions here is I go in and speak to organizations and meet with their data leaders and they talk about the capabilities that they've created and their data literacy programs and data democratization, et cetera.
And I say, this is all very impressive. And then I meet with the technology teams and they talk about the architecture and the engineering, and data fabrics and data meshes and movement into the cloud and things of that kind. And I say, congratulations on the progress that you're making. And then I meet with a line of business leaders and I say, you know, with all of these investments and activity taking place around data, you must be very excited and realizing a lot of value.
And too many times their response is, well, you know, let me be candid with you. And that is, is we just don't trust the data. We don't feel that we're getting commensurate value from our data and analytics investments. We know a lot of stuff's being built, but we don't even really understand what that is.
We, we don't understand the language that's being used. We're not stupid people, but we, you know, we're focused on driving revenue, improving profitability, serving our customers, and too often we're not getting the data that we need to make those decisions. We're not getting in a timely fashion. We're not getting it in in an easy to access format.
So we realize that a lot of people are doing a lot of work and we realize that we're making a lot of investments, but. For whatever reason, we don't feel that we're getting commensurate value. So I think, you know, those are the issues that organizations really need to grapple with. And sometimes I make the point that, you know, you don't need all of the data to solve the most critical problems of an organization, sometimes you only need 5% or or 10%. So, you know, sometimes it may be more incumbent, at least from the perspective of building trust and establishing credibility, and ultimately building momentum. Start small, focus on one or two or three critical business questions.
Solve those questions, engender the trust through that process, repeat that and build that credibility and momentum through that in that fashion. And once you have that, you can invest in the lodge, boil the ocean initiatives. But you know, I see too many times where data leaders or technology leaders say, you know, we need a wholesale investment in these type of capabilities, and the organization makes those investments.
But then what I hear over time is the business leaders say, oh, not another data project, because they've seen so many with such great promise. But it hasn't been a magic bullet and there are no magic bullets. So there's a lot of great capabilities that are out there, but should never lose sight of, you know, the reason why everybody's here and basically who's paying the bill as well.
[00:26:20] Jonas Christensen: There's a lot to unpack in that. And Randy, so this is kind of the, the essence of the question at heart, which is, the CDO role and its justification to some extent, and the teams that sit underneath their justification in an organization, and you talk about some businesses where, where people are succeeding with data and analytics, and then probably the lion's share of organizations where, It's not living up to its full potential.
And data science has been touted as the sexiest job in the 21st century. And we're all lapping it up like a cat drinking milk. But the challenge is the business doesn't see us marketing our wares and walking down the runway, looking that sexy. They're, they're not seeing the results necessarily, or they're not actually absorbing the results.
Right? So there's potentially a production problem of not producing the rights. Analytical outputs, there's potentially a consumption problem of the stakeholders not being able to actually consume that, or there is something in the middle, which is a sales and marketing problem of not being able to communicate that, to link those two things up. Where is the issue? Where, where is most of the issue in that sort of end-to-end production line of work and what do you see those few organizations that do it as well, what do you see them doing differently both the, the business, the non -analytics people, but also those analytics leaders?
What is the magic fairy dust that they're sprinkling around in their businesses that makes it all work so well?
[00:27:53] Randy Bean: Yeah. You know, as noted, I could kind of go on and on on, on these topics, but one of the things that I'd say is that, The CDAO role being a new role in that, you know, organizations haven't had clear expectations in terms of not only what they wanna achieve, but what skills and capabilities they need in a person in that role.
As, I think that as a consequence of that, there's been a number of individuals and organizations that have elevated people into those roles because they, if you will, had been strong contributors as subject matter experts. But that doesn't necessarily equate with being a C-Suite executive, particularly when you're operating in a C-suite with others that have been in those roles and have become seasoned in those roles for a long period of time and have developed the communication and the persuasion skills and the sharp elbows and know how to pick their battles, et cetera. And I think picking the battles is an important point. So, you know, to a certain degree, what I've seen is you've had people elevated into the C D A O roles who have been kind of advocates and proponents and say, you know, we, we have like a solution that's gonna transform and propel the organization forward.
And, you know, these are big organizations, so it takes time. So I think that understanding the culture is critical relative to the receptivity, the pace that an organization matures, its ability to adopt new capabilities and integrate those capabilities into the organization. So it's really, it requires that degree of understanding of the business, that particular company, the industry, and understanding how data and analytics can play a role in that context.
Where there is receptivity because you, you know, you can't force these things down people's throats. You can't preach that, hey, you know, we should all be data and analytics driven if an organization isn't ready to do that. It's funny because you spoke about the sexiest job of the 21st century. You know, from my colleague Tom Davenport.
There's, I think, one of the best chief data analytics officers and I spoke with her yesterday. As a matter of fact, she's gonna be on a panel that I'm doing in two weeks, and I said to her, because we have this kind of ongoing inside joke, I said, so how's things in the coal mines? Because, you know, she had described her job to me a few months ago, as you know, meeting with the business leaders and on the operating committee of the company.
There's perpetual dissatisfaction in terms of, you know, we need more data, we need this type of data. You know, we need these data to make these decisions. You know, we're not getting it in a real what, whatever the questions are, she sits there and feels like, oh, you know, how, how should we be using generative ai?
What should we be doing with, uh, AI in our business that will propel us forward . So there's so many aspects that she feels, you know, overwhelmed at times and she's very focused on working with the business and delivering business results. So she often feels that it's, as a matter of fact, the most unglamorous job in the world, and that it's akin to working in the coal mines because she goes back down and, you know, is chipping away at things and it's dark and dirty and tedious and, and, and hard job and, and anything but, uh, glamorous and sexy in many respects.
And plus, there's the other side of that. If you're doing things that become glamorous and sexy and also become a, a target as well, because you've raised your profile to a degree that people say. Okay. You know, if this is so glamorous and this is so sexy and we've created this new role and we've taken people and elevated them, and now we're paying them significant sums of money and we're gonna sit back and we wanna see things delivered.
And so there's pressure that goes along with that as well. So, you know, there's many things that contribute to the challenges that CDOs face and I think that one of the things that's happened, and, you know, I participate in these events and. Basically speak to one another about things that they're doing where they may be gaining traction and so forth, but they're speaking to, what's the expression, preaching to the converted.
They were sitting there with a series of business leaders that knew nothing and data about data and analytics and it might be a much more skeptical audience with people sitting there with their arms crossed or you know, in some type of pensive mode. So, you know, it's great that we've gone from 12 years ago when there was roughly 12% of organizations that had appointed A C D A O to roughly whatever it is, 84, 85 % that have appointed them now.
But the job's not getting any easier, and that's evidenced by the considerable turnover. You know, some of the major banks are on the sixth or seventh, chief data and analytics officer. Only a third of organizations say that they're, that the CDO role is well established within those organizations. Only 40% say that the role is well understood.
So, you know, when you step back, all of this is good in the sense that this is progress over 10 years ago or 20 years ago, or 30 years ago. It doesn't mean that you know, you are broken free on the field and you're running for the touchdown or the goal in soccer. It's a battle each and every day to show the value, to incorporate new capabilities, and to figure out, you know, where those fit and do so in a way that doesn't put the organization at risk. You know, I could just kind of ramble on indefinitely.
[00:33:38] Jonas Christensen: I think it was Bill Schmarzo, who is the former guest on the show who said something like, the, the quicker you realize you're not doing the sexiest job in the 21st century, you're just a data janitor, the quicker you will realize what it's all about and the quicker you'll, uh, figure out how to add value.
[00:33:56] Randy Bean: I love that quote .
[00:33:57] Jonas Christensen: Which was a sobering point.
[00:33:59] Randy Bean: Yes. Data, data janitor. I'm gonna incorporate that forward.
[00:34:03] Jonas Christensen: Please use it. But of course we should have lots of ambition for this. Now, Randy, so we've outlined that there is a problem here. There's a significant challenge for data professionals because, The chief data officer is kind of an umbrella.
It's a, it's a, it's a senior leadership role, but it, it affects everyone else that sits underneath because it's an organization that is the data organization inside an organization that has a job collectively to, to do with this stuff. The senior leader, of course, has to be able to influence at that executive level, but they also need everyone else to to feed, feed the work up and to do their bit to influence, et cetera. So we should be glass half full here and there's a problem, but we need to fix it and we can fix it because this is not the first time something like this has happened. There was a time where marketing didn't sit on the executive committee. There was a time where risk didn't sit there. There was a time where technology didn't sit there, like you said, the CIOs. So in that sense, it's not something that hasn't been done before. What should data leaders and their teams do to overcome this challenge?
[00:35:11] Randy Bean: Yeah, I'd give a few recommendations. One is I, I've come to be a big believer in keep it simple. I sometimes joke that when I write an article for Forbes or Harvard Business Review, you know, I have an audience in mind, and that's the CEO of a Fortune 1000 company . I describe it as, I say I'm writing at the third grade level, and people say, oh, you know, that's very funny. And I say, I'm like completely serious.
Because if you don't keep it simple and if you talk over people's heads, you, you lose them. And not only do you lose them, But depending upon the context, it can generate some level of resentment because if people feel that they're constantly being, their heads are being talked over, that that starts to annoy them and bother them.
And it gets to the point where they, they, they don't like it and might not even like the people that are doing it. So keeping it simple, communicating effectively, particularly in business terms. I, you know, I know, I don't know how many conversations I'm plugged into where people say, well, The business doesn't understand and you know, they have to become more data literate and they have to do this, and they have to do that.
And you know, my answer would be that no, they don't. You do, because they're the ones that are running the show this, they're the ones that are paying the bills. And you have to go the extra mile to meet them where they're at. That's just the reality, like it or not, and that they may not even be, they may be difficult in that regard, but you know, it's really incumbent upon you to to go that extra mile if you want to be successful and help the organization as fully as possible from a data and analytics perspective. And then, you know, along those same lines, I'd say, please tone down the jargon. There's too much data meshes data, fabric, data democratization, data literacy, et cetera. I mean, all those notions capabilities that the, the intent is good.
The intent is noble but it seems that each and every few months or every few years, there's a new capabilities that have come along. You know, the, the shiny object, you know, data lake, data lake houses, et cetera. You know, I noticed some question about data products and six months ago wrote a piece in Harvard Business Review because a lot of people were asking me about data products, but just in the past few days, some people have said like, so this data products, you know, we just like read all this, talk about it for the past year, but we haven't seen anything change. So it's almost better to talk about simple things like how data is produced, who consumes it, who touches it, why it matters in the jobs that they have within an organization.
Because you know, many years ago, Was involved and, and again, this is another term at the time it was called Data lineage. But the point was was working with a large organization showing all the points where data originated and showing all the people that touch data along the way, and then showed the end customers and how they benefit from the data.
And when that roadmap was outlined, the CEO said, you know, this is really the first time I've had an appreciation of how important data is to the organization and important to everyone and everyone, and it's really everyone's job. So the more that things can be phrased in ways that people see the impact and benefit to them and their customers, and how it can make the organization more successful in, you know, serving its customers or operating more effectively. I think that that's more important than jargon. And, and I know that vendors who have products and services, they need to differentiate their capabilities, and so it's important to come up with new names and so forth, but often those names become separated from the, the business value that's being provided.
[00:39:18] Jonas Christensen: If you start talking to your CEO about Federated data Lakes or whatever the latest term is, unless they've got shares and Databricks or Snowflake, I don't think they're at all interested in that. And this is really the problem to a large extent. So, Randy , I've sitting here thinking about the last, say, five years of conferences I've gone to that have had some title of, uh, data analytics or AI in it, in the title.
And it's, it starts with some sort of technical topic, but it always ends up with, the business doesn't get it. They don't listen to us. They're not data literate enough. They don't appreciate it. We can't sell our ideas in, and they are legitimate problems that the business is not data literate. But we have to change that because the major problem, the bigger problem is that analytics teams are not business literate half the time.
And when you see other departments like finance, they have a finance business partner. They go out there and they don't say, here's the balance sheet. You have to understand exactly how this works, and then I'll tell you how we can help you. And they say, no, no. You need to make that number go up and that number go up.
And I'm gonna tell you exactly how that's done. You've gotta sell more and reduce your cost or whatever it might be. But they're also technical people and not salespeople. Uh, I could also use marketing as an example, but, but them being marketing, they're much better at marketing than anyone else. Finance is not normally good at that, but they're still better at business partnering.
So, so there's, there's something here we have to do. How do we grow up? You've mentioned a lot of things here already. But how do we grow up as a, a community of, of data professionals?
[00:40:58] Randy Bean: I think that there's a wonderful opportunity for data professionals and data leaders because basically you, we, us, you know, we're empowered to, to make that change.
In other words, if we see that we, or you know, or others are, Ineffective at, at making the case or ineffective at building support. You know, we have the opportunity to change that if we want to, and that means stepping back and saying, you know, what are we doing that people are understanding? What are we doing that people are not understanding, and how do we do a better job of helping people, uh, understand and not overwhelm them?
To your point earlier, reminds me it was about. 12 years ago now that a data leader came to me and told me a story, and I was kind of like, uh, like, uh, no kidding. But they went to the, uh, c e o of the company and they asked for $25 million for an M D M investment. And the, uh, C E O looked at them and said, I have no idea what M D M is.
So therefore I'm not investing $25 million in it. And when you can come back to me and maybe describe something that, and say, you know, I'd like you to invest $25 million because it's gonna help us improve the ability to serve customers in this way, or it's gonna increase our return on, uh, Various products and services, you know, then we can have a conversation.
But, you know, don't come to me and say Invest $25 million in some acronym that I have no idea what you're talking about. So, yeah, I mean, I think that data leaders have a great opportunity if they are, are serious in and want to step up, and that is to really get inside the, the minds of business leaders to understand what it will take for data for business leaders to see how data and analytics can make their life easier, or can provide them with insights that they don't have today, or provide them with key pieces of information that would help them make a better decision at a particular, uh, point in time.
I think, you know, it's like you talk about the, the battle or the war. It's one step at a time. You have to kind of pick your battles. You have to demonstrate some value in those situations. So I think that data lead is need to learn how to be exceptionally good listeners, and I know that's easier said than done, but they need really need to practice at listening.
So that they can find out what they hear consistently and that, and they also need to practice how they play back. In other words, say, you know, is, is this what I understand? Is this what I heard? You know, if I was to do this, would this be helpful And just, Trying from a communications perspective, really going the extra mile to work with business leaders to, to, you know, win their hearts and minds basically.
And I know that's all, you know, very general type of language, but you know, that's, that's often how, uh, successes are achieved. That doesn't have anything to do with who has the best technology or the highest iq, you know, maybe in a greenfield opportunity in Silicon Valley, but, You know, 200 year old legacy companies.
[00:44:23] Jonas Christensen: So I subscribe to everything you said there. Do you have an example of someone you think has done this really well? You don't have to mention them by person or company necessarily, but perhaps what they did and how they did it?
[00:44:38] Randy Bean: Yeah. You know, I'm gonna use an example, even though I can't say whether that company's still doing it, but it, it's the, it's the mindset and the philosophy, and that is, In banking in the US , Capital One. Capital One is roughly a 30, 35 year old bank, and what it was, as I understand it, was the founders were basically data and analytics people, and they developed an approach which would help basically market credit cards more effectively and market them to underserved or under underutilized segments of the marketplace.
They put that into practice and it worked very effectively and they became a leader in credit card marketing. And then they said, well, you know, just let's expand it to the full range of banking capabilities, loans, deposits, et cetera. But the thing that I love about Capital One is that they're never satisfied.
So they have this, you know, I, I will talk to other organizations and they'll say, oh, you know, we have everything under control. Yeah, we're doing this, we're doing that. You know, we're on a good trajectory. And Capital One is always like, you know, we think everybody's gaining on us. We think we're gonna be surpassed.
What should we be thinking about, you know, what our other organizations are doing? What are fintechs doing? What are. New startups that aren't even in the financial services space. What are they doing that's analogous that could be applicable for financial services? So they have this culture that's the opposite of complacent.
It's driven to always be thinking that the competitors gaining on you, that there's no sitting at the top of the hill. You have to kind of fight each and every day to sustain your position. So that mindset is something that I see that distinguishes those firms that have the best fighting chance from those firms that don't.
You know, I would say at the same time that over the course of my career, I positioned myself where the mainstream of companies are, and the main mainstream companies don't need to chase every single trend. All they need to do is look and wait and see when particular trends pan out in a way that they start getting adopted by the majority of companies, and then they can take them very seriously.
So they can scout things, but they don't have to be reacting too quickly. So my point in all of that is that I think that organizations need to be vigilant. They need to fight complacency. They don't have to chase every shiny new object, but they do need to be thinking about are there things that are coming along such as generative ai.
That could make a difference in our business. Let's not freak out overnight because everybody else may be, but let's seriously think about how this could play a role in our business from our vantage point of five years, 10 years, and what are the things that we need to be doing to build the capabilities, structures, human resources and skills that will allow us to be well positioned in terms of integrating this capability for the long term.
[00:47:44] Jonas Christensen: So that sounds like role number eight for the chief data officer just come up with one of these ChatGPTs but for us. I remember what maybe five, 10 years ago when Facebook was still Facebook and not Meta and it was at the height of it, everyone was saying, well, Uber, we went through the Uber phase as well, but it was the, can we build the Facebook of banking or the Facebook of utilities or the Facebook of, of whatnot, and the executives were flying to Silicon Valley from everywhere in the world to learn how they did it and what they did. Often, uh, that is, well guess what? We were in the legacy company to start with, so, uh, we are already, we're already ahead in that, in that sense.
Hi there dear listener, I just want to quickly let you know that I have recently published a book with six other authors called Demystifying AI for the Enterprise: a playbook for digital transformation. If you'd like to learn more about the book, then head over to www.leadersofanalytics.com/ai. Now back to the show now, Randy, we are coming towards the end. I'm interested in your point of view on, we've outlined the biggest challenges for chief data and analytics officers right now.
What do you think they're gonna be in the future? And I think we can, we, we should imagine a future where we, we start to overcome some of the challenges we have now, but then what does it look like after that? And how do we keep building?
[00:49:15] Randy Bean: It's impossible to predict the future. You know, I think we are in a stage of maturity, but will the CDAO role, or the CDAIO role, will it look the same in 1, 2, 3 years. It, it's hard to say, you know, obviously those companies that are digitally driven or greenfield companies, you know, the, the Facebooks, Googles, et cetera, you know, they don't really have chief data officers because it's so inbred in the d n a of, uh, people throughout the organization.
So, and I, and I've heard Fortune 1000 companies that say, yeah, we've come to the realization that, you know, If we have a chief data officer, it somehow implies that, you know, it's not everybody's job, it's not everybody's role, so maybe we're gonna get rid of that role. And those same companies two or three years later have rehired a chief data analytics officer.
So, so it's kind of like, the point is, is that back to that, Main thing that there, there, there's no one path, there's no magic bullet. You know, each organization has to figure out what works for them. And it may be that the C D A O role is an interim change agent role and maybe it comes in and out at various points in time and maybe it's reconfigured a lot of the people or some number of the people that have the titles.
Now that there's variations on the titles, there's chief analytics and insight officers. There's. Chief data, digital and AI officers. So it's whatever works for for each organization. And so in the same way that there's been no single blueprint for the CDO role over the past dozen years, I don't think that there will be, or needs to be necessarily going forward. Organizations need to learn what's worked for their organization, but it's tackling something that's happening and new and developing. So it's not, it's not a stagnant thing. So the role needs to continue to evolve again, create the job description and put it on the shelf, it need to continue to adapt it based upon new developments.
[00:51:23] Jonas Christensen: So in summary, more volatility coming our way, which is not necessarily a bad thing that spells opportunity as well, but we gotta be clever about how we, how we pick that. And maybe it means not just staying in one lane, but actually broadening the capability a bit. It sounds like, you know, if you, if it's starting to mix digital into it or, or other functions as well, it becomes much more of a broader remit.
Randy, we are coming towards the end. I have two questions left for you. One is for you to pay it forward and to tell us who you would like to see as the next guest on Leaders of Analytics and why.
[00:52:02] Randy Bean: Yeah. You know, actually there's somebody who I have in my MIT panel next week who I think is really good. She actually just got named the DataIQ number one data influencer. Diana Hoskins Schildhouse . She's the Chief Analytics and Insights Officer for Colgate, Palmolive . And one of the reasons why I liked her and recommended her was I had her on a panel last year with a number of CDOs and I asked the question about how much time everybody was spending on defensive activities versus offensive activities and went through all the, uh, banking executives financial services and they were roughly, I know we're up to. 30% in offensive activities, 40% in offensive activities. Things of that kind came to her. She said, we're 100% on offensive activities, and the audience cheered. She said, you know, we're, we're all about using data and analytics every day to figure out how we can serve our customers, grow our markets, et cetera.
So she's a very forward-looking, progressive chief data officer, focused on how data and analytics can be used to change the business.
[00:53:04] Jonas Christensen: Brilliant. You have recommended the right person, but also the right topic for that conversation I can hear, so we should definitely get her on the show. That would be very, very interesting.
Lastly, Randy, where can people find out more about you and get ahold of your, your book and other content?
[00:53:20] Randy Bean: Yeah, so on LinkedIn, I'm there under / randybeannvp and I have a website set up for my range of personal activities called randybeandata.com . The book Fail Fast, Learn Faster is available on Amazon and it's also available for discounted bulk copies through Porchlight Books, which is a distributor.
So they sold bulk copies to a number of organizations that are looking to, you know, provide a little perspective on the evolution of data and analytics to their business leaders and data leaders.
[00:53:53] Jonas Christensen: Brilliant. And I will link to all those resources in the show notes. So everybody go and check them out.
Randy Bean, thank you so much for being on Leaders of Analytics today. It has been really, really interesting and I think we could have talked about this for hours and hours and hours, but we're out of time. I hope that everyone listening to this has learned as much as I have. And I think we have a lot of the reflections to take away as to how we as a community, not just think about the data, but also how we sell it into organizations and actually change the trajectory that we're on for the better.
So all the best with that and your new book sales as well.
[00:54:31] Randy Bean: Thank you, Jonas. It was a pleasure being here. Great questions, and you know, there's, there's a great opportunity. People just need to think fresh every day and, and think different.
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