Jonas Christensen 2:52
Murli Buluswar, welcome to Leaders of Analytics. It is so good to have you on the show today.
Murli Buluswar 3:00
Jonas, good morning. My pleasure. Such a delight. Thank you for making the time for us to have this conversation. Looking forward to it.
Jonas Christensen 3:07
Yes, it is late afternoon on the East Coast in the USA and it is early morning in Australia. So we do analytics at all hours of the day, and this is no exception. Now, Murli, I have done an introduction to you already. But we want to hear it straight from you as well. So let's start learning a bit about you. Could you tell us about your background, your career to date and what you do?
Murli Buluswar 3:31
Certainly Jonas, I run the data and analytics function for Citibank on the consumer side in the US, which is the vast majority of the consumer business. My team's mission is to deliver faster, wider and deeper data driven insights to achieve superior financial outcomes and to make better decisions.
Jonas Christensen 3:57
So you've obviously thought about this a lot, because you're so well defined in your answer, which is rare. Have you come to such clarity in your role and the clarity of the remit of the team?
Murli Buluswar 4:08
Hmm, good question. The opportunity that I see Jonas, not just within my context, but even across industries is this this ability to think about this capability as being an enabler function of capability, working shoulder to shoulder with partner functions to be able to drive change. And at the same time, also a function that is a little bit more on the leading edge of innovation and sort of guiding a particular firm or a particular function within a larger firm, to be more innovative in a way that is material and meaningful. And why I care about that mission statement that I just alluded to Jonas is that for me, the ultimate power is in being able to measure what positive scale change did you drive. And that change could be a financial outcome that manifests itself in your P&L or your balance sheet in, again, a measurable, tangible way. Or that change could be a set of capabilities that you've delivered that are driving better decision making more sophisticated decision making, in a way that is obvious, even though it might not be measurable directly financially. So for me, the power is in thinking about that sort of full virtuous cycle of how do we define success? Why does it matter in a profound way to the C suite? And how do we ensure even if we don't have accountability for every piece of that, that we take responsibility to ensure that the questions we're asking the data driven insights we're providing are driving measurable scale, financial outcomes, and are materially improving the calibre of decision making.
Jonas Christensen 5:58
There is so much to unpack in that. And I actually want to just take a step back. And so listeners don't where we are going to unpack all that. But I just want to spend two minutes. And this was this was me jumping ahead. I want to spend two minutes just learning a little bit more about you. Before we get to the answer on that. Murli, how did you end up in this sort of role in the first place? How did you become such an analytics professional that you are today?
Murli Buluswar 6:23
Gosh, So believe it or not, Jonas, math, and quantitative thinking was never my strong suit, when I was in high school. But as I went through my college years, I decided that I, at that point in time wanted to pursue a PhD. And I needed to be able to build strong quantitative aptitude in order to gain a PhD. And I ended up making a little bit of a pivot to pursue a master's in statistics. And that was a foundation that has guided my career. Now, I've had the fortune of always being in roles that didn't exist before. So roles that require someone to bring fresh thinking, and challenge the existing norms. And think about ways in which we could drive superior outcomes through data driven insights. So this notion of being able to connect the data, to curiosity and to strategy, and then making sure that we also solve for that last mile problem of being able to drive into and change and being able to measure that and know why it matters and how it matters. And when it matters, is that it has been a core thesis of my career. And what I realised fairly early in my life was that while I enjoyed the statistical modelling, getting sort of my fingernails a little bit more dirty, so to speak, with the data and such, I really quite liked being able to step back being able to zoom out and think about the more conceptual problems and play that connective tissue be that connector between the strategy and the operations and the power of what data driven insights could drive.
Jonas Christensen 8:04
And looking at your resume. It starts with data roles back in the 90s. So I'd say you've been doing analytics way before there was anything called analytics. So you're very well experienced in this. And you've held some big roles across some pretty big organisations. So not least the one you're in now. But also, actually, maybe you could tell us a little bit about that, rather than me doing it, what your sort of career trajectory through analytics has been?
Murli Buluswar 8:32
Certainly, certainly I started off in the mid to late 90s. at Capital One, which is a bank that here in the US is well known for having data driven insights in its core DNA when it was created in the early 90s. And quickly decided that I wanted to make the leap to complement my technical capabilities with more commercial acumen and conceptual problem solving, and abstract reasoning skills. So I ended up getting an MBA, and have been in a couple of industries. Insurance for many years, where my last role was the Chief Science Officer for AIG. And then, of course, currently here, at Citi where it's really been in roles that are the intersection of where curiosity meets strategy meets insights meets change.
Jonas Christensen 9:20
And now you are, as you said, the head of analytics for the Consumer Bank at Citi. And that's a pretty big role that we'll unpack in a minute, but could you please tell us about what this role is actually about and how you help directly move the organisation forward, and perhaps give us a bit of a sense of just how big the organisation is and how you intersect with it?
Murli Buluswar 9:42
Yep, yep. To give you a sense of scale of the business, Jonas, we have an the US Consumer Bank, about 30 million plus customers. It generates revenues that are multibillion in the range of anywhere from 16 to 25 billion, so to give you sort of a sense of scale, so it's a big business that spans the credit card and lending business, the mortgage business, the retail bank business, that is all of the consumer deposits and the branches, and so on and so forth, as well as a business unit that we called City retail services, which is our private label, store branded cards business as well. And if you think about all of those businesses, there's a lot of data that is generated, because banking is a high touch, high interaction, sort of sector, so to speak. And the question really is, in a fast paced world, where consumer expectations are not just guided by what they expect from their bank, but what they expect, as consumers across all sectors, the gold standard is no longer your peer group within banking, it's the best of the best of what we as consumers experience. And so our mission is to think of ways in which we could harness all of the data from the interactions and transactions, to understand consumer behaviour to be able to infer their needs, even if they're a little bit latent, and to be able to communicate and connect and engage with them in the context in the timely way, in a way that sort of mirrors that radical empathy, and gives the customer the recognition that we understand them. And we are here to be of service to them for them data and data driven insights, particularly when you sort of begin with sort of the questions that you should be asking, and answering through the data is a linchpin and being able to live that objective on a day in day out basis.
Jonas Christensen 11:49
So to be specific here, so your main thesis, as a department is really to help with the way that the organisation engages with, with consumers. As in it's less about all the other analytics opportunities that there are, because there are so many in an organisation like that there could be operational analytics, or how you optimise your call centre, how you help the finance team, build better models, etc, etc, etc, is the main focus that that consumer interaction?
Murli Buluswar 12:19
There are definitely elements of those other pieces that you just alluded to Jonas, the most important thrust of the team is how do you go all the way from being able to understand prospective customers, and being able to reach out to them what offer what channel when, and to what end, beginning from that all the way through to all of the intelligence and analytics that guides the onboarding experience, and the ongoing engagement that cuts across channels and products and myriad of customer journeys? Being able to draw meaning from that data and being able to know how could we build more relevance in a timely way with each of those consumers, based on again, data driven insights. So that is a huge component of it. But as is often the case, with teams like this, you definitely have operational or operations related analytics, so to speak, being in the banking space, we also have things around risk and controls and a variety of other areas that are complementary.
Jonas Christensen 13:29
Right, so we're gonna get to later on in the show how you actually execute some of this analytics and interact with customers. But before we get to that, I want to just drill into how your team's structured, the size of the team and all that because you have a very big team, you have hundreds of professionals in it. And it's actually rare to see an analytics organisation of that size. So could you tell us what does it what does a week look like in your job? And how do you lead such a large analytics organisation internally?
Murli Buluswar 14:03
Happy to. How well I lead it is probably still sort of the jury's out on that. But I can tell you how I try to lead it on a day in day out basis. So the team Jonas is somewhere between 500 to 600 people strong, spread across a couple of continents here in the US and in India as well. And to put it sort of, in the in the simplest way I can, they're largely speaking three categories of roles. Role number one, and this is in no particular order of criticality. Role number one is what I would call the business partner or the business analyst category of roles. And their goal is to bring that abstract reasoning conceptual thinking, critical problem solving skills, and to be that connective tissue with the different operating units, understand their needs, and be that bridge in a way that that sort of allows the broader analytics team to be the most in impactful in its service for the different functional areas. So that's bucket number one. Bucket number two, I would call data analysts or data and technology, data engineering, call it even tool and software development and such. So the goal there is to play that enabler role in being able to stitch all of our data to make it fit for purpose. And to understand what tools and solutions we need to build in order to integrate the analytics to be able to achieve a set of and financial outcomes or to be able to achieve decision making in a way that is materially improved over historic. And then the third skill is data science course, which is the predictive modelling the ability to think about algorithm generation, the ability to play with the data do all the feature engineering, and to understand how do you blend the science of data science with the art of modelling what is the context in which those predictions will be implemented? How do we think about methodology and the input data and the implications of false positives and false negatives? And how does that impact our algorithms. So those are, broadly speaking, the three roles and please recognise, of course, that I'm sort of oversimplifying it. And in terms of what a typical week looks like, I try and sort of break down my routines into broadly speaking three buckets. The first bucket is people & culture, specifically within my team, the intent there is to give, to try and be the best that I can be in challenging my team to have a sense of individual and collective identity of what our mission is, why it exists, how that connects to maximum impact for the team, and how that relates to individual career growth, and promotions, and fulfilment, and so on and so forth. The bucket number two that I focus on is projects, specific material problems, alpha initiatives, in particular, but not just limited to Alpha initiatives that my team is leading the charge on and understanding what are the insights, what's the status, what is the pathway to realisation of full scale value, what are the impediments and things of that nature. And then the third category is, I'd put it in the bucket of enterprise leadership, trying to take a more expansive view of the firm, not just a functional data and analytics view, engaging with my peer group, thinking about the business issues, challenging my own understanding on what we could be doing differently, better as an analytics function, given the challenges that the business has, and really trying to listen to the different functional partners we work with, understand their needs, and being able to be a thought partner for them, and have their experiences also guide, how we might shift a little bit the portfolio of work that we're doing in service of the broader business objectives.
Jonas Christensen 18:12
Murli, one of the things that I often say to my teams is, I want you to think like you're the CEO. I don't want you to act like you're the CEO, but I want you to think like you're the CEO, because you are the only people in the organisation that have access to all this information. And you're the only ones that have the technical ability to slice and dice it in any way. And therefore you need to have the CEO hat on when you do that. So that you can, I think use the words art and science that you could combine the science of, of manipulating data with the art of thinking about how to manipulate that data. And I gather from what you're saying that this is you phrased it in a different way. But it's very much the way that you drive the team. And you are kind of the CEO of this organisation within the organisation, which is this quite a large analytics team. So that's great. On a day to day basis, you would have 1,000,001 questions coming from all angles of seemingly helpful, seemingly worthwhile and least questions that are not directly part of the larger mission. And but they seem like, oh, we could just spend a week on this and it''' the organisation here and it'll enable this group over here to do something. How do you keep this large organisation on the straight and narrow and focused on on the on the core purpose to somewhat then I suppose, cast away the work of all the other things you could also be working on?
Murli Buluswar 19:43
Gosh, that's a terrific question Jonas. First thing I'll point out is that there's never any patently right answers and your thinking and approach for any leader in the space could be a little bit different from month to month, week to week. Number one is having the openness to recognise that some of what we do will not be perfectly scripted. So questions arise on a weekly, monthly basis that we need to play an important role in tackling. At the same time, what you don't want to do is spend your entire year reacting to questions that someone else is asking. So as a rule of thumb, depending on the level of seniority and such, I think how much of one's time is spent on what I would think of as reactive versus proactive can vary the the more junior you are, perhaps the larger portion of your time is spent on being a little bit more reactive. But even there, it's important, I think, to have a set of objectives on what success looks like in terms of specific outcomes, and in terms of the culture of responsiveness and adaptability. So I have a scorecard that I'm very, very fixated upon. And my objective is, when I do reviews with my team, I connect that to that scorecard so that there's a clear understanding of what are we looking to achieve? What does success look like over the 123456 months? And how is this in service effect. So drawing that connectivity is, I think, very important. The other thing that I would say Jonas is I don't have a desire to control exactly how people spend their times, that would be an exercise in futility. And I really want people to have a very strong agency around how they spend their time in a way that makes sense, given what we're looking to accomplish recognising competing, you know, priorities. And for me, the thing is culture and giving people the sense of identity, having them have a clear sense of what a success look like, over a medium term. And knowing when to follow when to partner and when to lead is important, because that allows you to toggle across times when you need to be reactive times when you need to be solving problems by going shoulder to shoulder with some partner functions, and times where you need to lead because you're actually thinking of issues and asking questions that people might not otherwise be asking.
Jonas Christensen 22:13
So it's all in the leadership to a large extent here. So Murli, you're making me think here, but what types of skill sets you have in your team to actually do this, and one of the things that you often see in analytics teams, and I have to be careful to paint everyone with the same brush, but I'm gonna do it a little bit anyway. Which is people who like to sit in and, and deal with that or a more introverted, typically, there may be less of that sort of driver personality that go in and tell people what to do. And here's what we want from you, and so on, they're actually there to help other people. That's kind of what the role is. Yet, you are also driving a lot of the commercial outcomes in your organisation. And that is exactly the way it should be. Because this is what we're saying this whole function is, is actually has the potential to do right, we're going to change the way we operate businesses in the 21st century using data. So therefore, the people who are the data professionals necessarily have to step into the driver's seat to do that. So you have this team, you must have hired some very particular skill sets in that to do those roles and to actually make sure that the organisation interacts in the right way. So could you tell us about how you drive the right decision making in the organisation specifically, and how you engage and collaborate across the organisation? And then thirdly, what kinds of people you have to get that job done?
Murli Buluswar 23:50
Yes. So the way I think about this Jonas is there's a skill set, which is your data scientist or your business analyst, and so on and so forth. And then there's the mindset. The mindset for me is how do you sort of see your identity? And how does that sense of identity and sense of collective mission or purpose, allow you to collaborate across different parts of the organisation in a way that hopefully gets you to be the best version of yourself, for the organisation, for the teams that you manage, as well as for your peers and most importantly, or equally importantly, for yourself as an individual? So for me, I don't necessarily think of it as a skill set as much as a as a mindset. And yet one of the quotes that I've heard from a coach before is that in many large organisations, people can easily fall trap to confusing motion for progress and organisations are by design or by happenstance, more susceptible to lot of movement without necessarily having that clarity around being able to to define success, and so any act of progress has to be very intentional and has to be driven by an awareness of what someone's looking to accomplish. For me, the way that manifests is I've got a set of principles and values that I've defined, that I think are important not only for our own individual development as people, but also for the success of the team. And I've connected that to the mission statement that I alluded to earlier. And the way we think of our goals, Jonas is in five categories. Category number one, is financials realised. So alpha financials realised these are numbers that other functional areas can attest to and say yes, indeed, we've been able to deliver these outcomes from a financial standpoint, category number two, is alpha financials identified. So they're a little bit more early stage in the sense that before you can actually realise the outcomes, you need to be able to make the business case. And you need to bring people along in being able to agree that we think the size of the price of this particular effort is this. And now let's actually collaborate and figure out how we're going to execute on that and keep score, so to speak. The third category is non financial outcomes. This is related to tools and solutions that we've developed that we're not going to try and force $1 amount associated with it. But nonetheless, the benefit of these things is highly material. And being able to measure is this working the way it was designed to is important. In this instance, from an adoption standpoint, category number four, Jonas is a New Frontiers of Innovation. These are a little bit more exploratory. But I don't want to say exploratory in the sense that they're not wildly open ended. They're still innovating within what the firm does. But nonetheless, these are ideas that we've conceptualised that are a little bit earlier stage in development. And the question is, can we do the baseline analytics to be able to sort of see the promise before we started exposing it to a broader set of functional partners. And last, but not the least, is our operating deliverables, which is the things that we do on a day in day out basis, to ensure that we are meeting the organization's financial objectives, where we are one part of an ecosystem, we're not necessarily leading in that example, where either following or more often than not, we're actually partnering in that follow up partner lead spectrum of things that I alluded to.
Jonas Christensen 27:40
So there are a few lessons here and what you're seeing, in my opinion, and one of the things that I'm gathering that you do really well is you provide a lot of clarity for your team, on what they are meant to do and what the purpose is, and what within that purpose are the deliverables that make that purpose a reality. But you also do that well with the consumers of your output, which is the business. So there is a team's ability to produce something and then there is the business's ability to consume what you produce. And both have to be really good for it to be a success. And, for me, if someone wants this sort of capability to be a C-suite capability, they need to be really good at communicating that. And you're obviously following that up with measurement of outcome within those five buckets. So I think there's a lesson for for anyone listening here, whether they are an aspiring analytics leader wanting to move their function into as the C-suite, or they are some other business leader wanting that role or function to be lifted in the organisation. This is kind of where that the Nexus is for this stuff. You got to be able to communicate around your what you produce, not just produce the stuff. Then you have your five categories, which are really good. So let's talk about those. Do you have a sort of a proportion of work that should go into each portion of how much time or effort you spend? How do you make sure that that each category gets just the right amount of love?
Murli Buluswar 29:20
Oh, gosh, tough question. I don't know how to think about whether each category is getting the right amount of love, because that answer might not be quite as easily knowable. But I will say this, you always start with that fifth category. And they were certainly not designed to be as I articulated them in order of significance in any form or fashion. But delivering on our operating commitments to achieve in your outcomes where we are an important cog in a bigger wheel is absolutely essential. And that's something that we do not compromise on. Everything else builds on top of that.
Jonas Christensen 30:00
Could you tell us what sits in that category? Specifically?
Speaker 2 30:03
Yes, absolutely. So there are projections around financial outcomes that the firm has, whether it is customer growth, or revenue per customer, or adoption of digital channels, or improvement in net promoter score and things of that nature. So there's a myriad of metrics that you could imagine that cut across new customer acquisition, engaging existing customers, there's a channel view, there is a risk and controls view, and so on, and so forth. So there are very specific metrics that the firm has. And analytics is an important enabler to achieve those outcomes. And that is easily the largest of those five buckets by a substantive amount. And then the other four, are, we think, critical, because that's the differentiator between being an enabler and being more at the tip of the spear, and being able to drive change. And that to me is asking and answering those other four categories are largely asking and answering questions that people have not necessarily conceived of, that we think will matter in a big way. And that requires our competency of data driven insight. And our ability then to sort of think about how will these insights be absorbed and decision upon? What do we need to do and able to in order to bridge that gap, whether it is from a culture or change management standpoint, or whether it is from a tool development standpoint.
Jonas Christensen 31:36
So you got to do your operations well before you get the ticket to play in the other four categories is another way to think about it?
Murli Buluswar 31:47
Jonas Christensen 31:48
So Murli, you've managed to, in this role and in a previous role, sit in the C suite, so you're you're an executive that reports directly to the CEO. And on this show, and many other places, we talked about how analytics, data science, machine learning, AI, anything data driven, is going to reinvent the way we run our society and the way we do business as well. But it's actually a little bit rare to see what you have - that you have such a large function and that it is a C suite role. Why do we have this gap in what seems to be the reality versus what we think it should be? Could you talk to us about that?
Murli Buluswar 32:38
Yes. Oh, goodness. So you know, what is of course, pretty obvious. Jonah says that this capability is profoundly reinventing society as we know it. And in many large organisations, it's still sort of seen as a pure enabler function, maybe not quite nearly as potent and influential as it should be. Or I think we would say it should be, or is it could be. For me, the way I think about it, Jonas is there's sort of three gears I think that people get stuck in sometimes in roles like this, and then I'll share my view on how to sort of be able to get the sand out from those three years. Gear number one is a reactive gear, ie. one where we say, we're here to be of service, you tell us what questions you want to have his answer, whether that's business intelligence, or some sort of an algorithm or some form of a business analysis, we'll deliver that to you, and will do a diligent job of it. But there is not real connectivity to saying well, why are you asking that question? What is the end outcome? And how can we not just think and act like a functional player, but rather be able to think and act horizontally the way a CEO or a CFO or a head of audit might. So that's sort of gear number one, to me that I've observed to be a bit of an inhibitor. gear number two is in the space of infrastructure, let's face it, no organisation that we are a part of any of us or any of the listeners are part of will have a perfect data ecosystem. It will be a continuous motion in progress, sort of a capability. And gear number two, in my view, is getting stuck and saying, Look, I need to be cloud native. In order to be cloud native, I've got to make all of these investments in my infrastructure. And that's a three year four year effort. And in those three to four years, our measure of success is only related to the infrastructure development. It's not related to driving outcomes in the here and now. And the challenge there is then you're not relevant to the problems that the organisation is tackling in the here. and now. It's not to say that you shouldn't focus on the infrastructure is to say that you cannot exclusively focus on the infrastructure. And gear number three is reacting, innovation du jour. We all know that the latest one is generative AI ChatGPT. And I think it's fascinating and the possibilities are absolutely endless. And I do think it's incumbent upon us to develop that curiosity and connective tissue to say, how could this transform or enable a particular business or industry, we're part of - 100%. However, if we were a year ago talking about blockchain and crypto, and then we switch somewhere to Metaverse, and now we're in generative AI, not to say that those conversations and those insights aren't important, but to say that they're not necessarily actionable in a way, in the here and now. And so how do you kind of juggle where you spend your time in a way that allows you to have a balanced portfolio that is toggling time value and certainty to build strategic and operational relevance? In the short, medium and long term? That, to me is the key that I believe that unlocks the potential of being a functional service provider to being a capability, that's the tip of the spear.
Jonas Christensen 36:13
So there is a lot of leadership, self leadership and team leadership in that there is technical aspects. And basically, time management in a central don't get distracted. Your middle one was one that I hadn't thought of actually, the one about the technical capability, not when I say that sort of, of course, I thought of it, but I hadn't put it on the same pedestal as the leadership. But I think you're right, if I look back at my career, there are many, many warehouses that were the perfect solution that ended up in the graveyard because we never quite finished it. And, and so it's been a massive distraction for me and all the people that I've worked with in many organisations throughout my career. So that is a really good lesson. So there is here an element of what the analytics function has under their control, to some extent. But there's also the business's ability to to consume the output, which is called analytic literacy, or what have you the organization's adoption of the output, but also the organization's as opposed to willingness or vision for what what can be done, right? So there's a chicken and egg thing in this. Well, when you report to the CEO, it's a lot easier for you there to permeate the organisation with analytics, because you report to the CEO. But conversely, before you start showing that you can permeate the organisation with this, and it makes a big difference, you don't get to report to the CEO. How does one influence that outcome as a leader? But also what are the elements that need to be in place in the organisation for that to actually be a success?
Murli Buluswar 37:55
Because this is another question Jonas, where I don't think there's a perfect scripted answer, it really probably depends on the cultural context of a particular firm. I'll share with you a couple of nuggets. Number one, one of the phrases that we use within my team is who will be providing unaided advocacy for a particular effort. So if you sort of think about brand resonance, there's this notion of aided awareness, then there's unaided awareness. And we use a phrase unaided advocacy. And why that is important is you need to be able to sort of create a movement, where you're not a soul soldier, you're not an individual soldier fighting an uphill battle. And in order for you to be able to do that, in order for you to sort of create that sort of wave, you have to be able to be radically empathetic, you have to be able to understand how somebody else sees the world, what's important to them, Why is it important to them? And how do you connect what you are working toward, in the context that they can engage with, which means that you also have to allow yourself to be influenced by them. So it's not just about how do I understand this person to best influence them? It's also about saying, How do I understand this person in a way that I can challenge my understanding and my thinking in order to be most effective in being an agent for positive change with this person or with this functional area? And I, if you don't mind, so challenge, something that you said a moment ago, in terms of the reporting structure, yes, reporting structures matter, but they sometimes can be a minimum, but insufficient condition, meaning that at the end of the day, a capability like this does typically not own a P&L. It is by design a horizontal function. And as a horizontal function, its ability to exercise soft power, its ability to influence and its ability to recognise that just because you've got the perfect answer does not mean that it'll get deployed exactly at the speed and with the granularity and clarity that you might like, and to have that humility to recognise that it's going to be iterative. And to have the depth of thinking Jonas, in my view to know, how will something specific be implemented? I'll give you an example to make it real. We all know that we're in a remarkably high interest rate environment that news sort of has hit home even more powerfully in the last 48 hours with the stories in the financial services space. The question is, how do you think about your pricing strategy for the consumer deposits, that you offer savings accounts and CDs and things of that nature? Now, in order to solve that problem, it's not just an analytical problem. It's actually a process problem of how are those decisions made today? And how do you go build out the analytics, but just because you've built the analytics does not mean that it can be consumed in a way that decisions are made today. So in order for you to be effective, not only do you have to crack the nut on the analytics, where you take, you know, couple of decades worth of data and model out all of the money flow movements, and so on, and so forth. But you then need to say, I know how the product managers make decisions today. And I want to enhance that with this intelligence embedded, which means that I need to build a software solution or a tool that allows them to simulate and do scenario analysis, and to be able to understand what the Pareto optimal outcome is, and things of that nature. And those tools may not exist in the marketplace. So then you've got to figure out how do you build those tools. And when you build those tools, you have to get the specs from the users. And once you build that, in deliver that you cannot just sit back and say mission accomplished. Because the next level question is, well, what outcomes did a drive that it made 5, 10, 20, 30 people happy and their roles easier, which is good, but again, an incomplete answer, or did it materially move the needle on how we were able to drive growth without compromising the net interest margin? Or how we were able to improve the net interest margin for the same growth? And how do you measure that, that's changed management. So for me this notion of thinking like a CEO and a CFO, a head of audit, and having this notion of traceability that end to end is really what is important and knowing when to push or challenge and how much and with whom, and knowing when to back off, recognising that as long as you're not working on random problem statements that don't have material relevance, sooner or later, you will have the opportunity to push home that advantage with your colleagues, for your colleagues.
Jonas Christensen 42:46
So can we dig into this a little bit more at this specific example here? So here's the thing, right: analytics teams, they produce analyses that produce models, statistical models, machine learning, whatever. At the end of the day, if we're really frank, no one cares, what's inside that, they care about the outcome. But we're very excited about what we produce. Look at this. It's very cool. All the numbers, here's how we did it. It was really complex. And it was a big effort. But what's the business value? Right, show me the money. And you've outlined what is actually the thing or the couple of things that make analytics teams impactful in an outsized way, which is actually being able to create solutions to there's solution design and is there's experienced design, and there's technology meeting and the data is a data is the connective tissue underneath that. So you need, you need a data science skill, but you also need the experience design skill, if you call it that UX design, whatever you want to call it. And you need the raw technology side. Do you have that in your team? And are they the same group of people or are small? Are they do you have individuals that have that span that sort of full stack? Or do you have that skill set across many people in your team? Or do you have, say, a product department and a an IT function helping you enabling and if so, how does that kind of mesh happen?
Murli Buluswar 44:21
Yep. One thing I might point out before I answer your question, specifically, as I think about your reflections, Jonas is, in order for this to be full potential, we as data and analytics professionals have to teach ourselves to engage in outside communication and thinking and I think that a majority of human communication is inside out, which is I'm going to tell Jonas what I am thinking of based on my own analysis and my own worldview, versus reflecting upon what is the question that he is seeking to answer. Why does that matter to Jonas and how do I meet Jonas where he is? So I'll just park that is a thought if I may. And getting back to the crux of your question, we don't necessarily have all of those competencies within my team in scale. We have some of those competencies, 100%. And being in financial services, oftentimes, you can't necessarily just go out and build your own tools and, and such that creates downstream operational complexity. So we work very closely with our technology partners. But we really bring in the end users, and we design it with the end users with our technology partners in a way that meets the needs of the users today, but with much more amplified intelligence, and in a way that can be sort of sustainable and deployed into our architecture in collaboration with our technology partners. So it really does require this combination of skills and functional lenses in order to achieve that complete outcome.
Jonas Christensen 45:57
Great. That's clear to me. And the last bit here is you've talked about it a bit throughout the show, is the measurement of outcomes. How do you do that specifically across the categories that you've mentioned? So what are the frameworks that you have for it? What does it look like day to day.
Murli Buluswar 46:17
So going by category, the first category was financials realised. And we have a series of line items based on particular bodies of work, that we put a dollar amount on sometimes in a range, because point estimates are always incorrect. And we have functional partners that agreed to those numbers at the beginning of the year. And as those numbers materialise, we publish those in our business reviews. And we ensure that our functional partners are able to validate and attest to that, and that the numbers are showing up in our financials in a tangible way. The second category was financials identified, there, we have a hypothesis on what the size of the price would be. And we develop the business case through MVPs and POCs in the course of the year, in order to gain confidence in that sizing, recognising that the full scale deployment and value realisation might actually happen, say, on a run rate basis toward the end of the year, which would then move it into Financials realised category. The third category was non financial outcomes. Typically, here the measurement is on two fronts, number of active users for tools and such that we've developed. And or if we built capabilities that are a little bit more horizontal. What are the 3, 4, 5 most business critical applications of that, and how do we measure that, so that we're not resting on our laurels saying we developed this and somebody's using it somewhere, but we're not able to answer the question through the lens of a CEO, CFO and athehead of audit on why did this matter? And how did it matter. The fourth category was New Frontiers of Innovation. And even within that, we have measures of things that we're aspiring to understand and identify and build confidence around so that very rarely do we meander through the proverbial forest, hoping to find a pot of gold, we tried to be very intentional in where we're focusing our energies in service of wealth, a reasonably well defined business problems that we think we can actually solve. And that will matter materially to the organisation. And that last category was operating deliverables. And that manifests itself in the P&L that the myself and the rest of the executive team is privy to reviewing on a monthly basis.
Jonas Christensen 48:44
Uh huh. So you might sit down with the stakeholder, the person with the P&L responsibility for mortgages. And you identify an initiative, and you say, we think this could improve for a subset of the customers that we're targeting with this initiative, the net interest margin by one to two basis points, and then you sign you kind of sign up jointly to delivering that upfront, and then time passes in other 6-12 months passes, you deliver this thing, the Feds moved interest rates a couple of times, and the's 1-2 basis points have sort of gotten hidden a bit in there all the movement in the market. How do you tie back to that?
Murli Buluswar 49:31
Very good question. There's two ways to do it. In some instances, we'll have tests and control. In other instances, we are able to show that we can actually predict with a high degree of accuracy, what different decisions will yield different outcomes. And so that itself can also be a validation of are the predictions working. And if you're using that software tool to simulate and optimise, we can actually say hey, you know what, this is sort of the best possible outcome. So if we make this decision, this is what we think this is how it'll influence the growth or what have you in the retail deposit business. And that is something that we can predict. And because we can actually predict it, we can quantify it as it happens. And to the extent that the sands under US have shifted, while the predictions changed a little bit, but the algorithm is still the algorithm, even if it is sort of a machine learning algorithm. So we're able to still tease out partially, and we're not looking for perfection in our answer. In that instance, what we are looking for is ensuring that things that we've built that have material value to the organisation do not slip through the cracks because of inertia, or because of our inability or unwillingness to solve for the last mile problem of adoption, or because of things that we didn't understand in terms of the whole process of the how the decision making process works.
Jonas Christensen 50:58
Yeah, great. And it often does fall off the cars when it is that last mile problem of actually getting people to adopt stuff. So that was a great example. And Molly, I get the sense that you spend can put a time or effort on you, maybe you can you spend a lot of time on on measurement relative to actually executing the exercise of the project initiative, which is, I think, a really critical part here. Because the natural tendency for humans is going out, surely this will be a success. It looks so obvious, why haven't we done it already? Let's just go and do it and make it happen. And then there are all these elements that can shift things, last mile problems, etc. How much time do you time or effort as a proportion do you spend on the measurement? And yeah, that's part of the implementation effort of sorts, right. But it's the measurement and follow up of what is actually a success? And should we continue, etc?
Murli Buluswar 51:56
Yes, the biggest time that I ended up find myself spending time on Jonas is upstream, actually, from the measurement in two areas, the sophistication and clarity of the insights through areas actually, the implications of those insights and the decisions we should be making as a consequence, and the engagement with our different functional partners in their critique and challenge and understanding and confidence in what we've developed and their willingness to execute on it, and ability to execute on it. And then the actual measurement at the end of it is an outcome of those three areas that we invest very heavily in slightly more upstream. Because once we know it's deployed, the answer could be x versus 1.1x, or 0.9x. In something, and we don't actually super fuss about that. Because our bigger goal is to say, are we in the right ballpark? Has this been absorbed and deployed? Is this driving material, positive outcomes, and have we effected the change that we want it to, even if the dollars aren't exactly what we thought it would be? But it's a discipline to have to make sure that we hold ourselves accountable to think not just like functional players, but to think like I said, like a CEO, and a CFO and a head of audit, who really kind of think about the scale of a problem, the financial implication and measurability of a problem, and the traceability of whatever change you're looking to drive, the reproducibility of that change is what a head of audit typically does. So having those three lenses allows us to say, you know, what, we're living our mission, we're making an impact. And we are traversing across being a follower, a partner and a leader. And we are shaping the art of the imagination of what could be achieved through the power of data driven insights. And that's a story that we all carry in our careers with us wherever it takes us.
Jonas Christensen 54:06
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.
Murli before we finish off, there's one more topic that I would like to just drill into a little bit here because we've explored how you interact with the organisation and your purpose in how you as an organisation ensure the right outcomes and how to measure them. The banking industry is very data heavy and it collects a lot of personal information but also a lot of behavioural information on its customers. And when you look at that as an outside in a spectator, you go well, this surely should be one of the most data driven industries in the world, and also an industry that really has the potential, at least the building blocks the raw material to create personalization. And this is also what your mission is. Could you tell us about specifically how you're doing that to the extent that you can do that, but also talk about what are some of the roadblocks for banking to really do that well, as an industry?
Murli Buluswar 55:32
I could give you, if we, if I could torture you all day, I probably give you 10 or 12. Examples, Jonas. But I'll give you one simple one : it is important for us as consumers, when we interact with a bank to have an omni channel experience, ie, whether I walk into a branch, whether I call the call centre, whether I log into my mobile app and have some sort of interaction or transaction, what I want to know as a consumer is that the bank is able to connect each of those experiences and understand those customer journeys and engage with me in a continuous way that reflects the intelligence of the prior prior channels of engagement. So what we've executed on is an omni channel decision engine that is essentially able to stitch together all of the data that we have across channels, and allows us to say when a customer logs on to the mobile app, how do we build the maximum relevance with them? What are they there to do? And what is the conversation we have with them, that mirrors to them that we understand their needs, we are inferring their needs, we have all of the data on their customer journeys across channels and products. And we're building timely relevance with them, whether that is cross sell, upsell, or a customer experience or information sharing, knowledge sharing, and so on, and so forth. So that's just one simple example. But in that sort of broad category, to your point about being in a sector that is very high interaction and transaction, particularly on the credit card side of the business, is an enormous opportunity then to say, gosh, you know, what, he made a purchase in category x. And we know that if you've done that there's a very high likelihood that within the next 24 hours, you might actually make a spend in category Y. Think about say hotels and car rentals, for example. How do we connect that? And how do we then give you information or offers with sort of partner merchants in a way that makes that experience a little bit more seamless. So triggers, you know, this notion of being able to take that data and build timely contextual relevance is I think critical. And it is more and more a baseline of what we as consumers expect, regardless of which sector we're interacting with.
Jonas Christensen 57:54
And for me, that is where banking really has a huge opportunity is being that nexus point between what is actually being consumed at the end, because the the banking is a means to an end, not the end in itself. If you go and spend at the supermarket you using your your credit card, perhaps a Citibank credit card, but you're not there to use the credit card, you're there to buy milk, or whatever it might be. And being able to connect that is massive. And you look at some of the companies like Tencent, so WhatsApp in in China that have many years ago now been able to corner, a large proportion of if you call it the interaction market, right. So you can go to a restaurant using your Whatsapp app, you can organise your friends, you can book the table, you can order the food on the menu, and you can pay through their app as well. And all of that happens inside that app, not through the bank itself. But that's the threat. That is also the opportunity. Is that kind of how you think about it. I can see you You're nodding your head a bit here?
Speaker 2 58:59
Well, I mean, I think the regulatory considerations and the competitive landscape vary from country to country, there are obvious sort of choices that the consumer has to have that kind of engagement across apps, we probably don't have a single sort of consolidated view in the US and much of the Western world, the way it is in China with Alipay and such, but the idea is absolutely in that space of look, building relevance and engagement and being of service to the consumer and trying to understand them better based on the signals that they're sending you on who they are, what they are, why they are and when they are and being that sort of that sort of empathetic intelligence machine that is building relevance with them is to me the most critical accomplishment that any consumer facing institution might have, whether that's in banking, or other facets of our lives.
Jonas Christensen 59:57
And I should correct myself here I said WhatsApp I meant WeChat of course, WhatsApp has nothing to do with Tencent Holdings. And you mentioned also Alipay, which is a strong competitor in China. So yeah, this is fascinating the change that can happen Murli in the banking space, the financial consumption space. Where do you see the banking industry being five to ten years from now in this? And who's going to be the winners and losers out of that?
Murli Buluswar 1:00:24
Gosh, tough question. Short answer is, I have no clue who the winners and losers will be. But I do have this fundamental belief system, that the gap between the winners and the alterans will become wider and wider. And that will be based on individual institutions' ability to really be able to harness the data that they have, translate that data into intelligence, and be able to act upon that intelligence in a timely, contextual way. And those capabilities are not ubiquitous across every firm in financial services, they're not even ubiquitous force in within any other industry either. And for me, in order to get closer and closer to that full potential, you have to have this ability to be curious, you have to have this ability to be pragmatic in what you're looking to accomplish. You have to have this ability to think and act integratively in a way that is focused on decisions, material decisions, and scale financial outcomes that requires you then to in my mind, to think and act like a CEO, CFO, head of audit, it requires you to learn when to follow into partner when to lead, and it requires you to engage it outside in communication and thinking to take responsibility for how you measure success through a much broader lens, of which your functional lens is one piece.
Jonas Christensen 1:01:59
Right, I couldn't have said it better myself. So I think this is a good time to start running off things, Murli. I have two questions there for you. One is for you to pay forward. So it's a question but also an ask I suppose. So who would you like to see as the next guest on leaders of analytics, and why?
Murli Buluswar 1:02:18
Excellent question. Gosh, there's so many names that come to mind. I think that sports analytics is super fascinating. The data that they collect, and how they action upon that, whether it's in basketball or baseball, I think that there's some phenomenal work that is happening in, in healthcare, but you put me on the spot, and you asked me for one name. So I'll give you one name of person that I haven't mentioned that he'll probably know about it after my actually giving you his name. It's a gentleman named Dhiraj Rajaram. And here he is the founder and CEO of a firm named mu sigma, which is among the largest freestanding analytics service providers in the world, and was formed about 15 to 17 years ago, and has a super interesting history in how they've shaped the analytics landscape through the lens of India, but really kind of influencing the globe more holistically, I think that he's got some very unique perspectives on the evolution of this space. And what he thinks is the future of this capability and, and what that full potential looks like. And I'd be happy to make the connection.
Jonas Christensen 1:03:25
Awesome. That will be just the perfect guest for this show. So let's make that happen. And listeners, you can hopefully look forward to that one. And if you are interested in sports analytics, I do actually have a previous episode with Ari Kaplan, who in in some areas is called the real Moneyball guy. He was part of producing the manuscript for that movie Moneyball, and sort of checking some of the fact checking some of the the actual approaches underneath. So he's a very, very cool guy. And and that was a fun episode. So you can check that out there, Murli, if you're interested. Lastly, where do people find out more about you, connect with you, and get a hold of you?
Murli Buluswar 1:04:07
The most obvious platform, of course, is LinkedIn. And the other thing that I'd add is that like most people, I've got probably more than my fair share of digital breadcrumbs on conversations like this, I've had a chance to have that is searchable. So if I can be of service and be a thought partner for someone as they go on their own journeys, glad to be a thought partner.
Jonas Christensen 1:04:31
Murli, you definitely have been of great service and have been a very strong thought partner for us today. And I have really enjoyed this conversation. I've learned so much. There's a lot that I'm going to copy from your approach in my day to day so I rest assured that also all the listeners have gathered a whole bunch of stuff from this. So Murli Buluswar, thank you so much for being on leaders of analytics today and all the best for you, Citibank, the banking industry as a whole, and thanks for contributing today.
Murli Buluswar 1:05:04
It's an honour and a pleasure and I appreciate you Jonas. Thank you as well.
Jonas Christensen 1:05:11
Hi, dear listeners. Just a quick note for me before you go. If you enjoyed the show, then please don't forget to subscribe to future episodes via your favourite podcast app. I have loads more great stuff coming your way. Also, I'd love some feedback from you on this show. So please, please leave a review on Apple podcasts, iTunes, Spotify, or wherever you listen to podcasts. Thanks for listening and catch you soon.