McKinsey lessons & How to become a proactive Data Analyst
Updated: May 17
MindSpeaking Podcast Episode 14 - João Sousa , Practitioner & consultant at McKinsey
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Timestamps:
00:23 Introduction
02:10 How does speaking another language help you in the data world?
04:22 Who is Joao Sousa?
07:23 What have you taken from your experience at McKinsey?
10:44 Do you have any questions that you often ask or prepare before meeting someone?
12:06 Are there situations where a structured approach is not beneficial?
15:50 Do you see a gap in data and business? What are the problems you see?
18:52 What type of communication skills are most important for people working in data?
21:13 How can we develop empathy in data world?
23:35 What does it mean to be a trusted advisor?
25:36 What is the best way to handle quick questions?
31:32 What is something you are curious about right now?
33:09 What have you learned so far?
34:29 Challenges as a data analyst
38:49 What have you learned about creating a narrative?
40:42 Different types of approaches for capturing the attention of the audience
44:05 What is your number one place to go for learning?
45:40 What are the best decisions you've made in your life or career?
46:51 Why does curiosity help with learning?
48:52 Takeaway
50:07 Where can people connect with Joao?
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Introducing João Sousa
Gilbert Eijkelenboom:
Today's episodes is the reason why I started this podcast because I love conversations driven by curiosity. And that's what we did today. Curiosity was a main theme because today's guest is João Sousa. Build a career in data analytics in different roles as a practitioner, as a consultant at McKinsey, and also more recently, as a director of growth of a modern data stack vendor. As mentioned, we talked about curiosity a lot. And I got very curious about his ideas, his ideas about how leaders can develop a more proactive data team. The mindset he learned at McKinsey, and what he sees is the most important communication skills and how to develop them. So I've talked about how to tell stories with data and grabbed the attention of your audience, and how to make people more open for your ideas. And this, of course, is a very important skills skill in the data world. So I hope you enjoy today's episode, and I hope it feeds your curiosity and joy.
João Sousa:
Thanks, thanks for having me.
How does speaking another language help you in the data world?
Gilbert Eijkelenboom:
Yeah. Thanks for Thanks for joining today. We had a initial conversation a few weeks ago or months ago, maybe already and I really enjoyed that. And I think there's so much more to explore about about you about your vision on data analytics and the gap between data and business. So I'm very excited and what is special about your profile, if I look at your history is that you speak several languages right? You're trilingual, so you speak English, Portuguese and Spanish. What does that teach you about? I know speaking different languages. How does it help you in the data world?
João Sousa:
It's a good question. I think, first of all, thanks for having me. Really exciting to be here. I think at the end of the day, data is kind of another language. So I think the fact that one when one speaks different languages, on the one hand, it makes us kind of adapt to different situations and and kind of adapt to different audiences because usually, we're not so comfortable in foreign languages as we are in our mother's mother language. So it kind of forces us to adopt different audiences in different situations. And on the other hand, I think data is also a new language to some extent, in due to the whole technical jargon and specific terms. So I think it's just the fourth language on my on my skill set. So I think that definitely an interesting comparison.
Gilbert Eijkelenboom:
Absolutely. And even four languages now and you live in Berlin, right in Germany. So the next question is, when will you add the fifth one, the German one, when are you going to be fluent?
João Sousa:
That one is hard. This one is definitely harder than then than any of the other four but I'm definitely working on it. Yeah, so trying trying to improve that as well. But I guess it's the out of this one out of the four. Yeah,
Who is João Sousa?
Gilbert Eijkelenboom:
I mean, it's so such a difficult one, right for people that come from Portugal, from Spain for from France, it's so hard to to learn German for us is pretty, pretty easy, relatively easy. My girlfriend is German, so I had to learn it a bit better than in high school, because in high school, it was pretty pretty bad. So I took some courses. But I agree with you, if you learn a new language, it's kind of uncomfortable and you need to try to understand their position. There's a lot of cultural differences that you need to take into account. So much we can we can learn and that's also what I took away from the last conversation we had, which was not recorded. But I really saw you as a person with an open mind and curious and to understand the other side. And that's also what I want to talk about today a lot. But first, let's talk about a bit about you. So can you tell us a bit of about yourself? How you grew up?
João Sousa:
Yeah, absolutely. So I'm originally from Porto, Portugal, and I spent most of my life there. And my background, so I'm industry engineering by training. And then I've been working in the data analytics industry across different roles. So right out of right after university, I started to work as a data analyst slash data signs kind of a mix between both and and back then is what I really started to realize, okay, there's definitely a gap between the technical side of things and looking for this, this, this gap between data and business, which kind of got me triggered back then. And I also wanted to learn more about the business side of things. So back then I shifted my career into strategy consulting, where then I joined McKinsey and Company so I was based in Portugal work across different industries, different business functions. So in terms of industries ranging from hospitality to telecommunications, in terms of functions, ranging from procurement to marketing and sales, so I did a lot of different things. I was working mainly in Portugal, Spain, a bit of Latin America as well. And yeah, after some time, I wanted to go back to data analytics world because at the end of the day, that's really my passion. I did have the chance to work a bit on data analytics project that will again see but was not the core. So I wanted to go back to data analytics, also the startup scene. So I came across this opportunity that the cows the mission, the value proposition resonated with me a lot as a former data analyst myself. I guess we're going to explore this throughout the call, but in a nutshell, so basically, augmenting data analysts so that they can focus on what's inherently human specifically, generate these generating insights, interpret the results, communicate with stakeholders influence decision making, and that's basically my vision for the data analyst role. And this is something I'm really passionate about. And I also write a lot about on LinkedIn how to elevate the data analyst role now I envisioned data analysts role and I saw in Carrozza, a way to enable this transition and to support this movement. So that was my major motivation when joining calls already, one year and four months ago. And yeah, so I joined because in the beginning, it was all about figuring out to go to market strategy, working a lot with with data leaders, data protection practitioners, and that's been the ride so far. So I'm on the commercial side working very closely with with data leaders and data teams.
What have you taken from your experience at McKinsey?
Gilbert Eijkelenboom:
Wow, that's that's really interesting to hear your background and so many things come together there with your background and McKinsey and your data work as a data scientist, data analyst. So many things come together and before we dive into the data world, and the gap between data and business and these kind of topics, what what have you taken from your experience at McKinsey, because McKinsey is a very famous company, of course, where a lot of smart people work. What have you learned that there? Have you learned any skills or mindsets that you still apply today?
João Sousa:
Yeah, great question. I would I would emphasize three points. So I think that McKinsey learn how to learn fast. In any new project. One is usually out of the comfort zone because it's a new interest in your business function. So I think one of the key learnings from me or a key development points was really about whenever there is a new project or something that we're not familiar with, how can one learn a lot in a short period of time and kind of absorb all this knowledge from other people, industry experts or from more experienced people, and how to prioritize so what is essential to learn and kind of not get lost in all the details and all the noise and just focus on the car and what's actually required to proceed and be successful in that. So I think this is the first one. The second one is the importance of communication skills. While as in management, consulting one spends a lot of time doing research and doing quantitative analysis to make the best recommendations possible. But as this is crucial, of course, but as important is to spend enough time thinking how to communicate these insights and how to make sure that your audience will understand these insights. So we have to put a lot of emphasis on communication to make sure that our audience understands what we're trying the message we're trying to convey. So this I think it's the was the to the to the second main learning. And the third one was the main learning I think was about being structure. So every time there's a complex problem, approach it in a very structured way and breaking down a big complex problem into smaller components and smaller chunks that we can tackle and solve piece by piece to then bring the puzzle together. So I think that to wrap it up, I think it was all about learning how to learn fast. How we second how important the communication skills are, and, and third, being structured in approaching complex problems.
Do you have any questions that you often ask or prepare before meeting someone?
Gilbert Eijkelenboom:
Awesome. And of course, I like the emphasis on communication because that's what I'm trying to preach. to too many people are important it is but also like the fact that you say the first point is learning how to learn I think it's such an important skill, maybe even the most important skill we can learn right in this world that's changing so fast and you constantly need to gain new knowledge and work with new people and and if you have this learning mindset, I think you can do everything.
João Sousa:
Absolutely, absolutely. I think this is crucial in in for today's world. As you mentioned, change is faster than ever. And I think like for me personally, I realized that my time in management consulting that I learned best from other people so I really learned best by being curious asking questions, drilling down, going deeper, talking to people that are way more experience and kind of prepare some questions in advance and then also show interest in going deeper in topics. That's personal to me what works best when I know other people prefer maybe reading on their own or or exploring on their own. But I think kind of I would really recommend and emphasize a combination of both because I think learning from others and also brainstorming together in it's a great way to just be curious. It's a great way to just keep learning every single day
Gilbert Eijkelenboom:
Absolutely. Do you have any questions that you often ask or that you often prepare before meeting with someone or the jokes and ask to dive deeper and to understand more about what the other person is thinking or saying?
João Sousa:
Yeah, it's a quick question out what what I usually like to do in the beginning is quite kind of try to frame the discussion points or the structure, because from my experience when there isn't a clear structure or points to cover, I think sometimes one gets a bit lost in the conversation, especially when we have a lot to cover in a short period of time. So I usually like in the beginning to kind of lay out what I would be interested in knowing more about and making sure that we start with the from the high level details. So first, cover the basics, the high level perspective, and then try to break it down into several components and then cover one by one. So for instance, as an example I was I was the other day discussing with data leaders, how to measure or assess the data maturity of a team. And we came up with a structure based on four key elements so people processes, tools and culture. And then once we frame the discussion this way, then it ceases to go factor by factor or element by element and really discuss what this means and how to assess it. So that we usually like to go about it.
Are there situations where a structured approach is not beneficial?
Gilbert Eijkelenboom:
Right. And I see a lot of benefits for using such a structure and the question that pops into my mind while we're talking about this is are there situations where such a structured approach is non beneficial or whereas there's this is actually an obstacle for for getting anywhere? What do you think?
João Sousa:
It's a good question. I do think in some situations, less structure is actually positive. So I think when the goal is learning the most in a short period of time, I think structure is critical, because we have to make sure we're focusing our time on what matters the most and kind of layout destruction then go deeper, it's the right way to do it. On the other end, when it's something more creative, specially for Team brainstorming, actually going bottom up so kind of writing down some ideas and then find the structure later. To kind of tie back everything together, I think might actually work best for more creative for more exploratory work streams. So for instance, if we bring norming something that's very Greenfield or very new or or where there isn't a clear structure yet I think then it might make sense to kind of forget the with the structure and and be a bit more not so structure. Yeah.
Gilbert Eijkelenboom:
Right. I've been thinking about this, this topic quite a lot lately because I'm constantly trying to improve my training as well and the training is consistent at least for in my training consists of 10 participants, and they all have different needs, right? But you always need to get kind of a structure that fits for everyone. But I try to keep the flexibility to so that people that are curious about one topic are able to explore that right? without distracting the whole group. So there's these kinds of dynamics are very interesting to me.
João Sousa:
Yeah, absolutely. I think that's challenged man. It's such a group where they have different starting points. What have worked really well for you. I'm curious. Yeah. What
Gilbert Eijkelenboom:
what I tried to do is a few things first of all, assess the skill level of people. So to understand what skills people have, for example, if you're talking about data storytelling, are they just starting out no idea how to structure a narrative, or do a visualization make a visualization, or are they maybe more advanced? Are they really good data? visualizers and can they craft a story from their from their insights? So I tried to group those people together. There might also be benefits to group to mix them to have the advanced nature and junior students. But I think there's also quite a big downfall where the finance person doesn't learn as much. But it's still useful in a kind of mentor role, but in training, I try to have everyone to at the same level. What I also ask is, What what are you interested in so before you start a training program, the three sessions the three month program I asked people, what do you want to learn? So I tried to not just tailor the content to their preferences, but also to make them accountable, you know, to motivate them to work towards that goal, and to coach them in that direction. Because if I know there's one person wanting to become better at persuading other people with their data, then if there's an opportunity for them to do a roleplay or an exercise, I might invite them or stimulate them or remind them that they have this learning goal so that they move closer in the direction.
João Sousa:
Now that makes a lot of sense yet it seems like a good approach.
Do you see a gap in data and business? What are the problems you see?
Gilbert Eijkelenboom:
Thank you. So we have talked a bit a little bit about the gap between data and business and later I also want to talk more about the data analyst role, how you evaluate that role and what's your what's your vision, but first of all, the gap between data and business. What do you see a gap and talk to us about it? What is your vision? What are they the problems you see?
João Sousa:
Yeah, I think it's a very interesting question that can be seen from different different perspectives. I think on the one hand, there's definitely a decision gap so like 90% of the data was generated over the last few years. So that is growing exponentially, both in volume and complexity. And at the same time, businesses are changing faster than ever, as you mentioned, like things in general, everything is changing faster than ever. So what's the implication business have to make decisions faster than ever, and they have to be a child, otherwise they fall behind their competition. So this puts pressure on the data side because business stakeholders need insights fast at the speed of business. However, due to this increasing complexity in terms of data volume, and and data complexity, by itself, so more more types of data, and new data collected and so on. They don't usually struggle to provide all the sites at the speed of business. And I feel so basically, the data teams struggle to meet the expectations of the business stakeholders. And this is something that definitely I see on many data teams by speaking with with many data leaders. This is definitely a decision gap. On the one hand, just to kind of cover gaps from two different dimension so I think this is kind of a decision gap. So the expectations are not met. And that is not living up to the expectations what the business requires. On the other hand, there is definitely a gap when it comes to communication skills. So data teams usually struggle to adaptive communication in a way that business stakeholders understand. And business stakeholders like the technical expertise and experience in data to also communicate with with the data colleagues. So there's usually that a lot of misunderstandings, sometimes data people find something that they think it's interesting in the data but they struggled to communicate and then get frustrated because the business stakeholders don't see the value in the insights. So I see I see gaps in these two dimensions. And I think at the end of the day, the implication of these two gaps, these businesses are not leveraging the data to the maximum expense and there's a lot of hidden value in the data and in the insights that data analysts finds and the business doesn't appreciate. I know it's been a long answer, but I definitely I definitely see the gaping from these two angles.
What type of communication skills are most important for people working in data?
Gilbert Eijkelenboom:
Right. And imagine you know if, because I believe as well there's so much undiscovered or unfulfilled value right now. So imagine the size of the data market, right and five or 10 years when we maybe not solve this issue, but maybe narrow it down and I see that the two dynamics that you that you mentioned are the two the two problems. You mentioned communication skills what what type of communication skills do you see most important for for people working data?
João Sousa:
Yeah, great question. I think I would emphasize three main skills. The first one is in terms of communication, the first one is the ability to zoom out and focus and speak from a high level perspective is not only communication skills, also the ability really to zoom out and forget all the details. Forget all the technical things. Forget how the sausage was made, and just focus on the sowhat and communicate from a high level perspective and then to then go down to the details if needed, if not, no one really cares how the sausage is made. Because I think it's the first one. The second one is the ability to understand the audience. So the ability to take a step back, develop empathy. For the audience that we're targeting and say, Okay, this is what my audience cares about. So this is what I'm going to focus on and really cater for the audience. The third one, I think it's difficult to get to the structure when communicating. From my experience, usually data people kind of communicate in a very detailed way and not so easy to follow for business stakeholders. And I think the usually it's missing some structure.
How can we develop empathy in data world?
Gilbert Eijkelenboom:
Yes. And about the last point I love that you often speak in three things right, three bullet points, you're announcing what you're about to say and then you say it and sometimes you even summarize it. So without you saying it explicitly, I think is a fantastic example in this podcast already how you can structure your answers or your your conversations. Because by announcing what you're going to say and what three points it's very structured, and for me as a listener, it's very easy to follow even though all the thoughts are new. So this is a great tip for listeners who want to communicate more clearly. announce what you're going to say and then say it and maybe even summarize, for for clarity. You mentioned develop empathy and do the ability to understand the audience. How How do you do that? Because some people working in the data space they might think about empathy is something you have with your spouse or your girlfriend. Or your boyfriend. How do you see empathy in the data world and how can we use it or develop it?
João Sousa:
Great question. So the best data analyst I've worked with and I've been seen in the industry, I just the most curious, I think the way to develop empathy is by sitting together with the business stakeholders and just asking questions, just asking, like, what are top priorities for you? Just maybe sitting there once a week funny. Let's say I'm a data analyst that focus on marketing. I know marketing data analysts as an example. The best ones I see they sit together with their marketing colleagues, and they just absorb all the knowledge and just asked questions. Okay, what does this metric mean? Why is this important to you? Okay, you I share this insight with you. What are you going to do? What actions can you take? How does this help in your job? What's most relevant for you? What do you struggle most? I think it's all about being curious and all about immersing oneself into the stakeholders world. I think, especially when people come from very technical backgrounds. The natural tendency is to over focus a lot on technical details and discuss a lot of technical details while I think of technical skills are definitely useful and and data analysis very definitely a technical profile. I do think that they would benefit by just going for lunch with their business colleagues, for example, and just absorbing the communications and asking questions. I think there's a lot that can be done. My main recommendation from what I've been seeing is just be curious and immerse yourself in in your stick into your stakeholders world.
What does it mean to be a trusted advisor?
Gilbert Eijkelenboom:
I like that approach because while you were speaking, I was thinking that makes total sense. And of course, you can learn questions by heart and you know, thinking okay, I'm not going to ask these questions. But if you just become very curious, then it's so easy, because then the questions will come automatically, right? Just like in the conversation here, we're having now of course, I prepared a few topics. But what I'm mainly interested in is what questions are popping up in my mind and how can we dive deeper spontaneously, and I think older data analysts can take similar approach with business stakeholders, but they do have to have time and sit with those people otherwise that conversation never happens. You integrate, but you also mentioned to talk about the role of a trusted advisor that data analysts need to become a trusted adviser. What do you what do you mean with that?
João Sousa:
First of all, yeah, I think that's that's, that's also I think, the critical point when the finding and trying to elevate the data and install oftentimes, data analysts are perceived as people that are responsible for pulling data for updating dashboards. So it's basically a support function. When it comes to everything data related. I'm not saying this applies to every company. I say this applies to fair amounts of data of companies and data teams. And I do believe in what I've been seeing that this is changing. I think it's still the reality most companies so what I'm referring to is every time dashboard is down. We asked the data analyst every time a stakeholder needs some data, the data analyst is there. Every time there is a question the business stakeholder asked this typical, quick select question that sometimes is when an asset takes week. So I think the data teams and specific data analysts have been perceived as a support function. And the way I envision this position is to shift from reactive to proactive and basically become trusted advisors, powered by data of course. So if I'm a business stakeholder, and I want to optimize my back marketing budget every single day, I have my trusted advisor next to me, the marketing data analysts that proactively comes to me with recommendations powered by data and we work together. So I understand that if I'm a business to go then in marketing understand more about marketing that data analysts understands more about data, but we need to collaborate very closely. And the data analyst plays this role of trust advisor that proactively shares insights instead of just reacting and answering tickets or answering Quick Select questions.
What is the best way to handle quick questions?
Gilbert Eijkelenboom:
Yeah, because I think many people can relate to those quick questions right, that turned out to be a month or a week long, long work out. And if that if that happens, because I see why you want to move to a proactive approach but these quick questions might still come to read. So how, what are your suggestions to how to deal with that?
João Sousa:
It's not easy. I have to be honest, I've been working with many teams and it's not easy and there isn't. I mean, they they at least can only do a part of it. At the end of the day, tying back to our initial discussion about data analytics maturity, I think these requires work across the four key elements, people processes, culture and tools. So by people, I mean the roles have to be well defined. And these role of trust advisor has to be spread out across the organization's right so that's it, we need to educate the business stakeholders in the whole business. So they understand that they cannot simply shoot questions to data analysts and ask a lot of requests is the first one. The second one from a culture perspective, businesses need to work on data literacy, need to work on educating business stakeholders on how important data is and how we should handle data and what the roles should be doing. also requires a really good team data team leaders who also know how to push back and prioritize requests. So that's also critical. So we've covered people and culture. The other two are processes and tools right in terms of processes and this ties a bit back to the data leader role. I think data leaders need to develop processes that avoid these situations or at least protect partially data analysts from falling into this support ticketing endless so I think processes are also keen terms of streamlining work and making sure and avoiding these kind of situations. And the last one is tools. And by tools, I mean everything, any tool that can automate what machines can do the best. So it can be in the data quality. So that the data teams are proactive in identifying data issues instead of business stakeholders saying oh dashboard is down and then the data analysts spend hours firefighting. This is one dimension. Another dimension is also tools like augmented analytics, for instance, like 1000s. So automating the manual slicing and dicing required for root cause analysis. So finally, save a lot of time. And then you can focus on partnering up with business stakeholders and influencing them and and communicating because to your point, I mean, while I see that most data analysts should improve their data communication skills, they also need time for it. If they spend most of the time firefighting. They don't really have the time to influence business stakeholders and communicating sites, right. So that's also a requirement for them to excel in the jobs. Yeah.
Gilbert Eijkelenboom:
Like did you bring up that point? Because it's, it's often what what people say Right? Adding more training or more things. To or they're all already existing, huge plate of work. It's, it's hard and I think there's a big role of the the team lead or the data leaders to to make sure they, the whole team develops a more proactive mindset in that sense and also that business stakeholders know what type of questions to ask and not just if they have a question, hey, how many products that we sell between 13th of August and 14th of July? So almost all year then it's probably not very valuable to just know that number. It might be worthwhile to sit down and see what they actually want to find out. You so you're talking about a trusted adviser. Do you know this this book, I'm not sure about the author. There's also a book called trusted advisor. Do you know about it? No. But I'm curious. Yeah, it's it's a pretty good book. It's by Robert Gulf works, and two other authors. So it's called the trusted advisor. It's from last year. So it's a pretty recent book. It's it's quite insightful, and I think it's not a book about data. But of course, you can get knowledge from it. And you touched upon a lot of points already that are in the book. So maybe you secretly wrote a book. But there's there's a lot of good insights in there. Also, there's the trust. equation. So they tried to kind of frame this the concept of trust, which is very vague and abstract into an equation and maybe you know about it, that is credibility, reliability, intimacy. So those all make they build trust, if you show them and self orientation day, the breaks trust. So there's credibility, reliability and intimacy on the top, all divided by self orientation. So to what extent do you care about the goals of the people in front of you and I think that's, again, related to the empathy story that you mentioned. How to understand their will their perspective.
João Sousa:
Absolutely. I think I mean, I'm glad you brought this distress equation, so I don't I don't know the book. I just wrote it down. I'm curious, but I've heard about this equation before and it makes totally sense to me. And I think, again, tying back to how to build empathy, as you just mentioned, if you want to build intimacy, and also reduce your your self orientation, you need to spend time with business stakeholders. And that's that's the way to go not only to build trust, but also to read as you mentioned, to really understand their world and then adapt communication. So that's so that data analysts can communicate effectively to influence decisions and increase the value of their work. So totally, yeah.
What is something you are curious about right now?
Gilbert Eijkelenboom:
I'd like to, to zoom out a little from from the data world and ask you a different question, because you mentioned curiosity a few times or several times, and also in our last conversation, and I always like it, the topic of curiosity. So I'm curious, what is something that you're curious about right now? In your work, or in your life or whatever?
João Sousa:
It's a great question. I'm, I've been exploring a big topic. So I'm curious about learning how to make people more open to new ideas to something that they they either never consider, or they never saw as, as important to them. So why why is this relevant just for your context? So I for context, I speak with towards really the leaders usually a day, and most of the times when when bringing up counsel for instance, since it's a very new technology, people don't know yet about the solution. And oftentimes, I feel like the initial reaction is oh, there's just another tool. I mean, there are so another two days we don't need it, which which is fair, because most of them actually, in fact, might not need it right. But I'm curious about learning more how to, to create an healthy tension in a way that prompts people to take a step back and reflect Okay, to what extent is this might actually be helpful or valuable. So wrapping it up. So in a nutshell is how to communicate new perspectives, and how to try to challenge existing assumptions or preconceived ideas. So that's something I'm really curious about. Also, that is a bit of psychology, I assume. And it's very complex topic. Yeah.
What have you learned so far?
Gilbert Eijkelenboom:
Absolutely. And what have you learned so far while thinking or learning about this?
João Sousa:
So it's a tough it's a complex topic, but I think what I've what I've learned so far is empathy goes a long way. So being able to actually in the beginning, phrasing in their own words, how they think about a specific topic or what they're struggling with. I think that goes a long way because it makes people feel he or she understands me, he or she understands my world. And this makes people become more open to new ideas. So this is this has been my major learning. So actually, making people open to new ideas is crucial and, and communicating their own words and show empathy. I think it's really important. Then I think the second one and last one is kind of how to ask a thoughtful, provocative question that makes people take a step back and oh, boy, okay, I never thought about these in these way. Is something new to me. This is something I'm still learning, but I'm definitely passionate about and I do see a lot of value, for instance for data analysts. So these I think it is a very hard communication skill to master.
Gilbert Eijkelenboom:
So tell it, tell us more about it. I'm very curious.
Challenges as a data analyst
João Sousa:
Yeah. So I think I think the challenge here, and I assume it will resonate with your audience because I think data analysts also face these challenges. So when people have been doing certain in a specific way, certain activity or they go about, for instance, they go about decision making, in a certain way for years, it's very hard to change these habits, right. Or when you when you for instance, as an example, when you see or as a business stakeholders when you perceive the data team as a dashboard factory. So just there to support requests. It's very hard to change these mindsets. So how to go about it. And I think the domain learning is the beginning. I think it's all in this stuff, conversation. It's all about showing some empathy and and making sure that the other person feels okay. He or she understands me and kind of creating some common ground. And then it's all about me, like creating a trigger that makes people take a step back and reflect. So for instance, what if their analysts could be become your trusted advisor that proactively deliver insights what would be the impact on your activity? And this is such like an open question that makes people think twice right and take a step back. Or also think of you are also phrased it in a different way. Have you ever considered X, what would be the impact of x? So from my experience so far I think these prompts people to take a step back and and approach a question in a more thoughtful way.
Gilbert Eijkelenboom:
That's that's very helpful. Also, taking notes of the conversation because I think you bring up great, great points. And by prompting these these questions, right, you make people think and imagine a situation and what would be the impact for them? And I think you learned so much about their goals as well in their world by talking about the impact and especially if you know about their goals, and you know, the impact of your proposed solution is going to be them reaching their goals. It's got to be one plus one is two, right? It's going to be very easy, and that's why that's why I like the question so much. What I've also learned is that the word imagine is very powerful. So imagine a situation where you do this or that because bad people actually use their imagination turns on and and when they see it and feel it. It's so much easier to bring them to the place you want them to be.
João Sousa:
I love this. I think I totally resonate. And just to build on what you mentioned, I think this imagination also works really well when when one tells a very compelling story, but for the story to work, so a story about another data team or another data situation for this story to work. Our audience needs to see themselves in the story. So for this to work, it requires a lot of empathy and a lot of homework. But if our audience if they see themselves in their story, especially in the beginning, this is I think, is the best way to drive change. But the story is to be told lots of homework, it requires empathy, and the story has to be very well conveyed. So short, concise, and to the point that this can work really well.
Gilbert Eijkelenboom:
Great that you bring this up. I would love to talk a bit more about storytelling. Which direction do you want to take it?
João Sousa:
It's also a broad topic. Maybe I'm curious what what usually what is your audience or data analysts in general, most interests are what they struggle most with. Maybe we can try to cover that.
What have you learned about creating a narrative?
Gilbert Eijkelenboom:
I think they relate very much to what you said in the beginning of our conversation about being a bit frustrated that they do have the insights but people are not using them or they do create a dashboard. But they see the statistics that people are not using it are really little. So they really resonate with that, that challenge. So what is the because storytelling sometimes is a daunting example. So first of all, I I don't think storytelling is just visuals visualizations. That's what many people think. But I disagree. I'm really with Ben dykes there. And I think you're also a fan of his work. Yeah, that that narrative is also important, of course, the data but the data is fairly easy for most people to creating a narrative. What have you learned about creating a narrative to work question?
João Sousa:
I think. So creating a narrative usually, especially when presenting to more senior stakeholders. I think the key and I think most data analysts struggle with these is grabbing their attention the beginning you have to grab their attention in the first and second that but I also learned a lot at McKinsey. And I think for these you need to you should start with the key takeaway, or the key implication or consequence or business impact. So instead of saying we did these, or we apply this method, we found that no, like, so let's start with the so lots and then, and then start to have like different layers. So I think depends on the audience. But I think for very senior audiences, this is crucial to grab their attention in the first 10 seconds and make the whole story concise and to the point for for very senior audience, especially business the goal there would be my my main my main point, I would say,
Different types of approaches for capturing the attention of the audience
Gilbert Eijkelenboom:
Yeah, because usually have so little time right for for senior stakeholders to grab their attention. They decided a few minutes or one minute if you're worth listening to. What I because of what you're referring to is kind of imperative principle, the principle pyramid a pyramid principle, very difficult word. So starting with the the most important first so the key the key insight. Brand dikes always says okay, I sometimes it can help for for very senior stakeholders who have very little time what he says you can also have kind of a data trailer to show a few of the insights or build some tension so that they know it's worth listening, and then still tell the whole story because if you give give away everything upfront, the tension is gone, right? There's no tension. So what are your What are your thoughts on that? So for more executive, more executive audiences, pyramid principle or starting with the most important first or hooking people and then slowly build up to the main insight, what do you think?
João Sousa:
It's a good question. I think it depends on the context and the audience. So if it's more executive audience, and especially a shorter meeting with many different stakeholders, I do believe that the pirate pyramid principle works better. The reason being, if you start if you if you try the other approach and start to try to build some tension in the beginning, you might lose people throughout the way before hitting the main the main points. So that's I would go with this one, but if it's either not executive or if it's maybe a longer meeting us to explore some ideas and not kind of an executive meeting. I definitely see the value in the second approach you mentioned, because I think it's more like it's actually more telling a story and you definitely build some tension and you make people curious about what's the main conclusion and then you just present Yeah, so I think it's all about adapting to the audience and to the context as well. Something I do want to emphasize also from my experiences, executive, when communicating with executive leaders when should communicate very simple. And to the point, the reason being, they have so many things in their head, so many topics are always switching topics. So there's so many meetings. I think sometimes one likes to use fancy words and complex and complex things to try to impress. I actually think that's counterproductive. I think it works way better to have a simple communication, plain language to the point focus on what really matters short, concise, because the end of the day they have so much in their head that they struggle to absorb complex things because I mean, at the end of the day, they cannot they also humans and they cannot absorb things so fast.
Gilbert Eijkelenboom:
Exactly what and I see this quite a lot with data scientists and data analysts who want to include all the details or technical methods they used or or how how significant it is, you know, what, what are all the all the details around that? But most most people are not so interested. You know, if you're presenting there I hope they trust to because you're in that trusted advisor we talked about and they trust that you did the work right that you're capable person who's not telling telling BS and and if you're in that place, then you don't need to prove yourself by its trying to sound smarter, including all the methods because that's what people will will distract people instead of focused on your next step.
Unknown Speaker 43:36
Absolutely, and like maybe a few people will be interested in the methods but they can ask afterwards, right? Maybe 10 people will be interested in knowing more or if they are interested they will ask so Exactly. As you mentioned, focus on what's what's most important and the technical details of how the sausage is made. Leave it for the q&a, or maybe no one asks and they trust you. Yeah.
Gilbert Eijkelenboom:
Exactly. Probably no one asks, maybe you can even include in the appendix if people ask about it. You can have the conversation when the executive leaves.
João Sousa:
Exactly, exactly.
What is your number one place to go for learning?
Gilbert Eijkelenboom:
We talk a lot about curiosity about about learning and I'm curious what is your number one place or thing or person you go to? You go to for your for learning? Question.
João Sousa:
I think for simple things. My best friend is Google. For quick questions. I'm kidding. I think I tried to create some time to exchange thoughts. We will experience people in different fields. Apparently one of the initiatives I'm running and I organize data leaders roundtables, please least once or twice a week, where I bring together six to eight data leaders to discuss to discuss strategic topics is for instance, one of the initiatives where I actually learn a lot and also try to contribute to the community. So as I mentioned before, I learned mostly from people exchanging thoughts with other people sharing my ideas, asking questions, being curious. So I tried to create opportunities to enable these basically so it can be as little as roundtables or just depends on the topic but at the end of the day spending quality time discussing ideas and sharing knowledge with with other people.
What are the best decisions you've made in your life or career?
Gilbert Eijkelenboom:
Awesome. That's also something I really enjoy and the conversations like this I you know, when we hang up when we close this recording, I've I have a lot of new ideas and a lot of inspiration. So I'm happy you're also facilitating that for other people and thereby earning yourself. Absolutely. You. You talked about the decision gap in the beginning of this conversation, mainly with data and business, but what are some of the best decisions you've taken in your life or career?
João Sousa:
Who would quit question. So I would say in my life, the one of the best decisions was getting out of the comfort zone, and both studying and then working and living abroad. I think so I was born and raised in Porto studied there the whole school system and then also University. And then when I went on Erasmus to abroad to Sweden, and then also then I moved to Germany, one one and a half years ago, more or less. I think this was one of the best decisions in terms of personal life. The reason being one is exposed to other cultures. It makes us reflect and see in different things, see how other cultures approach different topics, learn from other people. And there's also understand that while we're all different at the core, we're all very similar. So that very, that's very interesting. That more of the personal life, I think workwise Yeah, I think I mean, it's a good question. I mean,
Why does curiosity help with learning?
Gilbert Eijkelenboom:
let me let me respond to what you're saying. And then you can think in the meanwhile, I love that you bring up that we seem very different but on the other hand, we're all very similar, right? Because from the outside, we might seem very, very different. I mean, we both have dark hair, but we have a totally different background. We speak different languages. We have a different background from studies, friends, family, everything, but still we have so many things in common and I think it's such a powerful way to look at the world and look at other people and see that they're different than think hey, that makes me curious instead of a this guy, or girl or men or ladies is different than that why I will keep a distance and I think again, it comes down to just curiosity because that's will drive so much of your learning and also the empathy with people not just understanding what their goals are in the business world but also connecting with them on a personal level. So I love that mindset. Because I think that mindset brings everything we talked about in this conversation.
João Sousa:
Yeah, absolutely. And I think we're in a world where lots of people talk about diversity, and that's what I see diversity playing a key role, right? It's also by having a diverse team of people from different backgrounds, and different cultures, different ways of approaching issues and by just being curious about our other approach is questions the topic these issues, whatever the challenge is, when also learns and develops oneself, and we can we can kind of leverage the best of each of each person so definitely nothing. I think so far what's what the one word that's that we're emphasizing a lot of this curiosity, and I can just double down on that.
Takeaway
Gilbert Eijkelenboom:
Yeah, fantastic. We're nearing the end of the interview. I know you write a lot on LinkedIn, and I follow you and I read your posts. I'm always very inspired just like in this conversation now. So I would definitely recommend following you on LinkedIn. I will ask you more about where people can connect with you or follow you but also want to, to know what are what is one big takeaway you want listeners to get from the episode? Maybe you shared it already or something else you want to emphasize
João Sousa:
Yeah, I'm gonna double down on curiosity. Just be curious about the people around you. And if you work in data, it's natural. And it's really good that you're interested in data and understanding new data tools, improve your technical skills, but at the same time, be curious about the business side of things. Be curious about the business stakeholders. Were you curious about what's important them? Because I think while art skills are a requirement, and are super important in a data role, or any data break for any data practitioner, soft skills is what moves the needle in closing all these gaps we've discussed and enabling you to deliver more business value and also have more fun because at the end of the day, we all like to feel we're valuable, and we're helping other people and we're basically bringing value to the table and soft skills communication skills, empathy and less when at least curiosity are key for these and I kind of lost my enclosing this last mile and, and nailing analytics, I believe.
Where can people connect with Joao?
Gilbert Eijkelenboom:
I believe so to where where can people connect and follow you? Because I'm sure people want to know more and learn more from from you in the future.
João Sousa:
Yeah, so as you mentioned, I do post a lot on LinkedIn, usually three times a week I cover these topics about data analyst role, how to elevate it, how to increase the value of analytics, so I think LinkedIn is the best source. I'm getting started also on Twitter and if it also interest in participating in any data event by to organize in person events in Berlin, but also other events remotely. So which will presume so please feel free to reach out and if you have any suggestions feedback, or you just found something really interesting from this conversation I would love to hear and yeah, LinkedIn in general is definitely the best channel.
Gilbert Eijkelenboom:
Fantastic. So I hope many data minded people will connect with you. Some data leaders will connect with you to learn more and talk, talk about curiosity, talk about data and talk about how to get bigger in business impact. I really enjoyed this conversation and then we could go on for hours. I think and I love that we took such a spontaneous approach and we actually we what we did is follow our curiosity right. That's what I did. I think also what you did. So I think it was a big episode about curiosity and learning. And thanks. Thanks for making the time for for coming on the show. I really appreciate it. And maybe we do in our next episode someday.
João Sousa:
I would love to thanks really appreciate I think it was really interesting and inspiring for me as well. So I'm really glad thanks for having me. Appreciate it.
Gilbert Eijkelenboom:
Thanks, man.