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CDAO first 100 days – Felipe Flores – S1.5

For this episode I am joined by a well-known data leader – Felipe Flores – who is talking about things you need to do as a data leader when you start a new role.

Felipe Flores – Data Futurology

“Felipe is a data science senior executive with almost 20 years experience. He has worked across data engineering/warehousing, reporting, business intelligence, analytics, data science, machine learning and artificial intelligence. He is currently the CDAO at Healthcare AI company, and is the founder of Data Futurology.”

Data Futurology is one of my go-to places for data podcasts and events and is worth checking out.

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Hi folks, and welcome to the next episode of Data Revolution podcast. Today. My guest today is Felipe Flores, who is the Data Science senior executive. He’s got a lot of experience. He’s worked across data engineering, data warehousing and bi and related stuff for many years, in particular in AI and machine learning. And he’s currently Chief Data and Analytics Officer at Healthcare AI Company and is the founder of Data Futurology, which there’s a bunch of stuff on LinkedIn if you’re looking for it. Welcome, Felipe.

Felipe Flores [00:00:36]:

Hey, Kate, thank you so much for having me on the show. I’m so excited to be here with you and yeah, get to talk all things data. Thank you so much.

Kate Carruthers [00:00:45]:

Yeah, well, I’m really interested in your topic, so why don’t you tell people what we’re going to talk about today?

Felipe Flores [00:00:50]:

So I thought, yeah, today we could have a discussion around what it’s like coming into a new executive role. So what do the first 90 days as a CDO look like? What we’re seeing in Australia is that there’s a continuing growth of maturity in the data analytics space, and more and more companies are having and creating CDAO positions. Some companies are onto their third or fourth CDAO, others are creating that position for the first time. So as a result, we have many people in the industry, many people in our community going into these positions, sometimes for the first time, sometimes for the third time. And I thought it’d be really good to kind of distil some of the learnings that people have had, give some tips and help people kind of have a smooth transition, kick some goals early and ease those nerves.

Kate Carruthers [00:01:42]:

That is a great idea because I’ve been in this job for many, many years now, so I’ve almost forgotten what it was like to start off with.

Felipe Flores [00:01:50]:

Right. It’s crazy. One of my friends described it as kind of like building up fitness, that you get to a point that at the beginning you might be totally finding it really difficult, really overwhelming, having to think really deeply about kind of every step that you take. And then once you do it for some time, you develop that fitness that it becomes a lot easier to do. And I think it’s good to sometimes reflect, look back. Hindsight is always helpful and particularly helpful to other people that would be stepping into the role, into these type of roles for the first time.

Kate Carruthers [00:02:28]:

Yeah, well, because I can literally remember when I was appointed in 2014 and data governance was part of my remit and sitting down and googling data governance and finding all these articles going, yeah, it’s a really great idea, you should totally do it. And nothing that said, here’s how to do it. So that’s how I developed my data governance website because I was like, you need to know.

Felipe Flores [00:02:54]:

That’s the thing that it’s funny how as seniority increases, the breadth of the remit increases. So much, and it’s almost counterintuitive as you’re coming up to go from an area where you feel like you’re such an expert in a domain that you totally get and understand. And then as you become more senior, you have areas that you may not have worked in before or may not have looked after earlier, and you’re having to kind of learn on the job and become this leader, really, of experts in an area that you’re not an expert and that definitely requires new skill sets. And I think one of them is the rapid learning and getting into the area as you’ve done as you did back then with data governance. I think that’s an awesome way to get into it and be able to add value to the teams and still develop and lean on the leadership skills that are required to lead teams where the leader doesn’t know the full details of everything that is going to be done.

Kate Carruthers [00:04:05]:

So where should people start? Where should new leader who’s got the job and is walking in the door start? What are they going to do?

Felipe Flores [00:04:20]:

I’m very quickly going to close this code in 1 second, sorry. So it’s really interesting because a lot of things that I see of people when they say they just get a CDO role, the good thing is that the people in our space, they want to be prepared. So there’s generally a fair amount of research about the company and the industry that is done and people do that I think usually very well. I think one of the areas that could have greater focus is particularly the commercial model of the organization. If it’s a for profit organization, focusing on what is the mechanics of the business model for that company, having clarity about that as early as possible is going to be extremely helpful. And I’ve definitely been in situations where I’ve gone into new exec roles and I’ve kind of pulled out my playbook that worked for me last time and then sometimes it doesn’t work in the new organization and part of that is because I didn’t take enough time in understanding the commercial model. So for example, when I moved to healthcare where I am now, I came from a background of consulting and finance and banking. So I came into this new role and I go great. I know it’s about customers, it’s about retention, it’s about marketing and it’s about providing that value to customers from an analytics perspective and be able to target them better. And in healthcare it’s much more about the outcomes that we’re looking to make people healthier and so targeting comes into play in a different way but the retention doesn’t necessarily play in the same manner as it would in financial services. So things like that is around what is the commercial model of the organization, what is the aim that the organization, the difference that the organization wants to make. Having clarity on that very quickly I think is super important. The other one that I see a lot of people not taking enough time on, and I’ve definitely made this mistake as well, is understanding the culture of the organization and having the time to really see and feel how things are done there. I’ve seen this in other people and I’ve seen it a lot in myself, that sometimes you start a new role and you think, all right, I’m going to go in, I’m going to kick some goals, I’m going to really make a difference quickly and often. While that has all of the right intents, sometimes we need a little bit more time to understand and absorb how the company operates, how the decisions are made, who are the key influencers.

Kate Carruthers [00:07:24]:

That’s the most important thing you need to understand because a lot of the time the formal hierarchy is not the influence hierarchy in an organization.

Felipe Flores [00:07:34]:

And understanding that, it takes a bit of time and then through that you get to uncover what are the key problems that people really see as the ones that you could make a big difference, that not every problem in the organization is going to have an analytics solution and vice versa. You’re not going to be able to solve everything under the sun, but being able to understand what are the problems that the organization has and sees as very important and then what is a good overlap between the ones that analytics can provide a solution and then start working. Once you get that sense and you get the who’s who in the zoo, start working on, I would say be very focused and start working on very few initiatives that some are going to deliver you some quick wins where you’re making a difference early and that’s going to give you momentum around your position, your new leadership. It’ll make the team feel good. There’s a lot of benefits in having quick wins. It’s obviously going to be adding value to the organization early on, have few of those and then set some time apart to work on the strategy on what data analytics could do for the organization in a broader sense.

Kate Carruthers [00:08:57]:

Do you have a view on people coming in and doing some sort of maturity assessment to assess the stack that you’re using and the data literacy across the organization?

Felipe Flores [00:09:10]:

Yeah, I think overall it’s a great idea because it helps regardless of the scenario or the type of environment that you’re going into. And I think that the scenarios, at least in my mind, are you could be going into a startup or a greenfield company where there’s no analytics can be ability before, so you’re setting it up for the first time. You could be going into a sustaining innovation. So analytics team that has been adding value to the organization, that needs to continue to do that, that’s kind of a sustaining innovation type of scenario, there’s a turnaround. Sometimes there’s teams that have been seen from the organization’s perspective, have been seen that they are not adding as much value as they could, and they’re looking for kind of like the refresh. So having kind of like a turnaround story. Sometimes organizations bring a new leader for that, and then the other one, which is I think one of the more spoken about is doing a transformation, a digital transformation within the organization that they’re looking to do. Kind of like a sweep across the board for customer experience through process automation and bring in a lot of data analytics through that. So regardless of the and the different scenarios will have some different perspectives that you need to take into consideration. But across the board, I think having a maturity assessment and a data literacy assessment, I think is always helpful.

Kate Carruthers [00:10:53]:

Yeah, because for us, we realized we didn’t have a data literacy problem because most of our people have master’s degrees or PhDs at the Uni. We’ve got a digital literacy problem where people’s first choice isn’t always digital. They have a real strong preference for printed out pieces of paper. So understanding the organization, when you’re coming to an organization, you might not understand that about it, that kind of thing about it.

Felipe Flores [00:11:21]:

Right. And that’s so interesting and kind of unexpected, or at least I wouldn’t have expected.

Kate Carruthers [00:11:28]:

I didn’t realize it until later, they’ve all got PhDs. They’ve all done stats. They know this stuff. And then it was like, oh, my God, they’re not digital native people yet. They’ll come through eventually.

Felipe Flores [00:11:44]:

That’s it. That’s it. No, that’s really good. I like that. How do you see the differences in how people get to the role, to the executive role, that some people are promoted up, some people are kind of promoted across, and other people are new to the organization. They all have kind of slightly different approaches to take. And maybe I’m biased, but I think that the more challenging one is promoted up, that you kind of have to leave a lot of your previous responsibilities, strike a different dynamic with your team. You have obviously a lot of knowledge of the organization and the stakeholders and the way that things are done. You might have a lot of ideas that you have been working on or thinking about while the predecessor was at the helm. And now you have your opportunity to solidify those relationships, step into a more senior role, and then start to make your mark. But I know that the people promoted across, they feel like they’re moving into an area that it might not be their bread and butter. And sometimes people come from marketing background or customer digital, and then they move into data analytics leadership, and they feel like they a little bit not out of depth, but not in their comfort zone.

Kate Carruthers [00:13:13]:

And there’s a bit of impostor syndrome sometimes.

Felipe Flores [00:13:19]:

Yes. And the impostor syndrome I think we all struggle with it. It’s something that I think everyone, at least, at least in this field, I think everyone in this field has. And I started thinking about it as more kind of to work through it more as like the ability to make a contribution instead of like, am I being totally perfect in this role or in this capacity, or living up to my own kind of inflated expectations of where I should be. It’s kind of like, am I making a contribution here that’s helping people and making a difference.

Kate Carruthers [00:13:59]:

Well, the thing I always say, when people say they have impostor syndrome is it means you’re not stupid because you’re conscious, you don’t know everything, which is the definition of not stupid.

Felipe Flores [00:14:13]:

I love that.

Kate Carruthers [00:14:16]:

A long time ago where I was like, I can’t know everything in this field. And it was like, okay, that’s good, I can’t know everything. And so that was a good moment for me where I let go of this thing of having to be the smartest person in the room and it was okay for me to go, yeah, I don’t know about that. Tell me about it.

Felipe Flores [00:14:39]:

Great. And I think taking that weight off allows you to become so much more effective. And I know that a lot of people throughout their career, when they look at executives, sometimes they feel like the executive is not afraid to ask the stupid questions. And I think it comes with that transition that you just mentioned, that it’s like, I can’t know everything. And almost like the more stupid questions that I ask, the better I’m going to be at my role, the more effective I’m going to be able to be. I’m going to get greater clarity, get better alignment, get to the bottom truth of what’s really happening. So I think it’s almost a must have in the steps towards roles like.

Kate Carruthers [00:15:29]:

This one when you’re talking about somebody coming in in their first hundred days or so. So we’ve got that they are going to have a look, have a listen, listen to people, understand the organization, understand the money flows, understand where they’re at, do a maturity assessment kind of thing, what other things do you think that they need to do then?

Felipe Flores [00:15:52]:

As long as you’re able to get some momentum in your role and your leadership with some of the things you mentioned, like knowing who’s who in the zoo, understanding the problems, but also starting to get some early wins. And that will get momentum with your boss, with your peers, or at least some of your peers, and then with the team that they’ll start to feel good about the transition, where they’re being valued and they’re being productive and making a difference to the organization. All that kind of helps cement the short term jitters that people might feel that they want to be seen as adding value. And throughout, you also have to carve out some time for the longer term perspective where you want to start building out a strategy that can make a difference in the organization. And in that case, the strategy from a data analytics perspective needs to be completely aligned to the business strategy, to understanding where does the organization want to go. And my kind of like one line of a strategy is understanding where we are now, where do we want to be in a period of time, say three years and then what is the path for us to get there. So having the understanding of the organization’s strengths and weaknesses currently and painting as clear as possible a picture of where we want our end state to be and devising a stage plan to get there, understanding that in order to get there, it’ll be iterative. But having kind of the main areas and having some design around that I think is great. So working on that online, that strategy looks like is an area that needs to have some time carved out. And I’ve seen that one, just one question.

Kate Carruthers [00:17:53]:

Sorry to interrupt, but increasingly now, especially with Chat GPT, everybody wants AI and kind of the future of digital is data. So how do you recommend that people weave those stories into this strategy piece?

Felipe Flores [00:18:14]:

Yeah, that’s where the capabilities that we have are to power the pillars of the strategy of the organization. So for example, next week, next Friday, I think we’ve got a session literally on generative AI with a health insurance client where they asked for it and they said come and sort of tell us what Generative AI can do for us. And the aim is to go. These are the pillars of the business where you have your customer, you have your marketing and sales, you got your service and customer, you have your provider or hospitals and doctors to liaise with, you’ve got the market. And all these have a number of processes or functions, some of them that are more visible than others. Which ones of those does it make sense to start to plug in some of the more recent capabilities like large language models, for example. So bringing in customizing, for example, one of the typical applications, customer service responses based on previous human generated text responses is kind of like an easier win. But then taking it to a step where a customer can interact with a large language model to understand their products and their contracts. And in the case of health insurance, like what are they covered for, what are they not covered for? Does the cost cover the out of gap payment? Where could they go to? What type of specials could they see so they don’t have an out of pocket payment? Those type of more details, that is information that sometimes it’s not as easy to get as people and customers would.

Kate Carruthers [00:20:18]:

Like that type of information handy for summarizing stuff. Such a really useful feature of it. I love it.

Felipe Flores [00:20:26]:

So good, right? Yeah. And I saw an application recently of people wanting to get answers and summaries based on their internal documentation, but they didn’t want to put kind of like all of their internal documentation through the API at this stage. So what they did was for all the internal documentation, they created embeddings for those. So then they have kind of like the summarized vector of that. And then for the questions going into the large language model, they also got an embedding. And then they found the embedding of the documentation that most similarly aligned to the question and then put only that documentation through the large language model along with the question to say, here’s some background on this question. Now here’s the question and try to answer it based on this documentation. And yeah, I thought it was a really nice way to kind of control the amount of information that might be leaving the organization at this stage. Obviously in areas that are less sensitive, while there’s developments into having LLMs that are more be able to be built within your infrastructure or VPN, that’s the really interesting space.

Kate Carruthers [00:21:53]:

Hey, we’re almost out of time. So what would you like to tell people who are about to start a job in the data space as a data leader? What are the top three things you’re going to tell them to make sure that they do?

Felipe Flores [00:22:06]:

Yeah, I think that from a mindset perspective, it’s that what got you here won’t get you there. And some of the things that at least I had to learn the hard way was that throughout my career, I was focusing on being kind of better and better at my craft on data science, data analytics, and didn’t traditionally place too much importance on other areas like data governance or program management and things like that. And those are all structures that you need to create in order to be successful at roles at this level. So you need to definitely expand your horizons and take in kind of like at this level, you are an organizational architect and there are multiple areas that need to have a structure that interacts with the organization for that’s a really.

Kate Carruthers [00:23:06]:

Great way to conceptualize it. I love that.

Felipe Flores [00:23:10]:

Yeah. So for the capability to be the most effective it can be, I would say, yeah, what got you here won’t get you there. Think more broadly, be an organizational architect, make sure that you’re getting those early wins, thinking about the strategy and make sure that the capability is making a difference on the commercial model of the organization or the mission of the organization. And that can be or most of that can be quantified in a way that it really hits people. And for problems that you need to solve that might be a bit more hidden, find ways to make it real for people. And I’ve seen executives, for example, go to the boardroom with four different versions of the report, and instead of saying, all of these reports have different numbers, they turn it around and they have it as almost like a quiz or a game show and say they had the question up front to say, how many new customers did we get this month? Was it option A-B-C or D? They’re all different numbers. And the answer was, they’re all correct because they’re all in a different report. So it’s kind of like an innovative way to highlight the problem and then get some support for fixing them.

Kate Carruthers [00:24:27]:

Yeah, they’re really good tips. Thank you so much for your time. Felipe.

That was Felipe Flores. He is the meister of data futurology. An amazing podcast. They run webinars and events, too, and he’s an all round data guru. So thanks so much for your time.

Felipe Flores [00:24:45]:

Thank you so much, Kate. This was so much fun.