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Data-Driven Culture: Metrics, Hiring Skills, and Effective Data Presentation


MindSpeaking Podcast Episode 21 - John Thompson , Global Head of AI at EY


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Timestamps:

0:00 - Introduction

0:03 - John discusses importance of data literacy

2:28 - Discussion about book writing processes

3:02 - John's unique writing habits

3:54 - John's early morning routine

4:18 - Reflections on early career influences

5:13 - John's entry into data and analytics

6:10 - Insights on building analytics teams

6:27 - Lessons learned in team management

7:45 - Managing and valuing diverse talents

8:16 - Appreciating and recognizing individual contributors

9:35 - Recognizing potential in team members

11:05 - Essential traits for analytics professionals

11:56 - John's unique interview approach

13:26 - Enhancing communication within teams

15:20 - The role of creativity in data science

16:22 - Strategies for building a data-driven culture

18:35 - Importance of advanced communication skills

20:59 - Engaging the audience during Q&A

21:27 - Strategies for addressing mixed audiences

23:57 - Techniques for engaging audience questions

24:58 - Transitioning from presentation to discussion

26:16 - The art of storytelling in presentations

28:57 - Introduction of "Data for All" book

30:52 - Discussing risks of not understanding data privacy 3

2:17 - Rapid-fire personal questions

34:21 - Recap of key interview insights

35:29 - Closing remarks






Summary:


Key Topics Discussed:

  1. Importance of Data Literacy: John emphasizes the need for widespread data literacy and discusses his involvement with educational institutions to promote data awareness from an early age.

  2. Book Writing and Processes: John shares his approach to writing books on analytics and data teams, revealing his unique nightly routine of planning his writing in advance.

  3. Career Beginnings and Influences: John reflects on how his early experiences and family background influenced his career in data and analytics.

  4. Building and Managing Analytics Teams: He talks about the importance of recognizing and nurturing diverse talents within analytics teams, advocating for a personalized approach to management.

  5. Traits of Successful Analytics Professionals: John prioritizes curiosity, honesty, ethics, and kindness over technical skills in his evaluation of potential team members.

  6. Communication Skills: The importance of advanced communication skills is highlighted, with John suggesting training in verbal, written, and presentation skills to enhance team effectiveness.

  7. Data-Driven Culture: John outlines how to foster a data-driven culture within an organization, emphasizing the role of top-level executives and the use of data in decision-making processes.

  8. Engagement Techniques in Presentations: John discusses strategies for engaging with mixed audiences, including adjusting the level of detail and actively inviting questions throughout presentations.

  9. Storytelling in Data Presentation: He stresses the power of storytelling to connect with the audience and make technical information more accessible.

  10. Data Privacy and Ownership: John introduces his upcoming book, "Data for All," which aims to educate the general public on data privacy, ownership, and the implications of data usage in everyday technology.



Conclusion: The episode wraps up with John advocating for greater data literacy and a stronger focus on the human aspects of data science, such as empathy and effective communication. He encourages listeners to follow him for more insights and check out his publications for detailed guidance on building effective analytics teams and understanding data privacy.

This summary encapsulates the main points discussed in the podcast, providing a comprehensive overview of the conversation between Gilbert Eijkelenboom and John Thompson.






Introduction


Gilbert Eijkelenboom:

Welcome to the mind speaking podcast, where we talk about the human side of data. In other words, data communication, and personal development. My name is Gilbert. I'm driven by curiosity and my aim is to spread insights that you can apply to your life starting today. Let's do it. Let's start mind speaking. Today I'm speaking with John Thompson. You may know him from LinkedIn. He is the bestselling author of two books. The first one, "Analytics: How to Win with Intelligence," the second one "Building Analytics Teams," and I'm recommending it to everyone. I love the book. It's on my desk right now. The next book on the way is "Data for All Sorts." The third book that he will publish, we talk about the writing process and how this book is different compared to the other ones. John has worked for many companies like Dell, Gartner, and now he's the Global Head of Artificial Intelligence and UI. We speak about data-driven culture. So how to measure if your organization is data-driven and what is a good metric to look at. The second, we look at what are the skills he considers and he evaluates when he's interviewing data scientists and analysts. And lastly, we also speak about presenting data to a mixed audience because that's a common challenge for all of us. There are way more topics we also dive into, but these were the most important ones. So I hope you're going to enjoy this episode as much as I did. Today's guest, John Thompson. All right, John, welcome to the show.


John Thompson:

Thanks, Gilbert. Always good to talk to you. I'm so pleased to have the invitation and thank you I expect it to be an enjoyable conversation. I'm really looking forward to it.




John discusses the importance of data literacy


John Thompson:

Data and Analytics has been a field and it continues to be a field and it will grow dramatically. But I think we all need to be data and analytics literate. I spent a fair amount of time working with universities in the United States, and I'm looking to work with universities around the world. And I've spent the last 12 years working with our local high school so we can start to teach students when they're teenagers about the value of data and analytics. So I think we as a profession should work really hard to help everybody be analytically literate.




Discussion about book writing processes


Gilbert Eijkelenboom:

There are many things I would love to dive into. But the first thing I want to ask about is your third book because you're working on your third book. And man, three books. I know what it is like to publish one and how much time it takes and effort and sweat and tears to produce one and alone three, so I guess you have quite some stamina. How, how did you do it? Do you have any writing habits or how do you create books like that?


John Thompson:

Yeah, it's something that I fell into, you know, my wife was saying, John, you should write a book. You have so much to say you should write a book and I was like, No, no, no, no, I don't want to write a book. I'll never do that. I'm too busy. And then the opportunity came to write a book and I did and it was reasonably successful. And then I wrote the second book building analytics teams, which of course, we've talked about, we'll talk about today. And then the third book, I finally figured out what I was doing. And now in the fourth book, I'm well in the groove so we'll talk about the third book and maybe even a little bit about the fourth but my process is a little unusual. And that before I go to bed at night, I think about what I'm going to write the next day. And then when I get out of bed, it's pretty much written in my subconscious. I just have to sit down and tap it out on the keyboard. So I think about what I'm going to do the night before I go to bed I wake up and then I write.




John's early morning routine


Gilbert Eijkelenboom:

Well, and then you wake up and you sit down directly and write down on your laptop or your computer?


John Thompson:

Yeah, I usually get up early. Today I got up at 7:11, but I was at my desk at 4:45 and wrote for two hours and then started my day.




Reflections on early career influences


Gilbert Eijkelenboom:

Fantastic. Do you get up really early or how do you manage your time?


John Thompson:

Yeah, I do get up really early. I grew up in the US state of Michigan. My father was an auto repair mechanic and had his own auto mechanic shop and his idea was that children should work. So I was up every day and I worked a couple of hours before I went to school, and I've never broken that habit. So I get up early. I do things that I want to do for me personally. And then I do my normal day job after that.


Gilbert Eijkelenboom:

Right now, Obama said this as well. That's the most important work will be done before everyone is waking up. It's true. It's true. Yeah. And it gets it helps prioritize the most important work. Yeah. And because you've you've written three books about data, you have a lot of experience in analytics. When was the first moment you started to become interested in data, our analytics?




John's entry into data and analytics


John Thompson:

You know, I've been doing this for 37 years. So I left college, obtained a computer science degree and I started working in a large corporation in the United States, focused on transportation. And I was building systems using assembler and COBOL and RPG and all the languages of the day. And it really struck me about six months into my career that everything that we do focused on data, you know that all the systems were based on data, all the reports were based on data, everything we did was based on data. So I started talking to people about Well, shouldn't we do more with the data? Should we handle data more responsively, more consciously, and more proactively? And people just looked at me and said, What are you talking about? It's just data. You know, there's really nothing there. And I thought that that can't be you know, because everything is based on data. So I don't know I just stuck with that position. And now for nearly four decades later, it's just come to be true.




Insights on building analytics teams


Gilbert Eijkelenboom: Definitely, definitely true. And in your second book, building analytics teams, you also talk a lot about how to build those teams and how to grow them. Where did you learn those first lessons, how to build analytics teams?


John Thompson:

I remember very clearly I was working in a company in England. I was living in Chicago, and I was the CEO of US operations. And I ended up with a couple of people on my team that were had fallen out of favor with other managers in the organization. And, you know, more than likely they were on the autism spectrum. They'd never been diagnosed. But you know, I think they were on the autism spectrum. And I really started to see their creativity and their value and the things that they needed to be successful. And they just weren't, you know, quote, unquote, in the norm, you know, of what other people thought they should be doing. They didn't do well in an office environment. They liked to work at night, they worked in this really thirsty way where they created just huge amounts of value, and then they would be rather dormant. That was one way to say it for longer periods than most people would like. And I just looked at that and said, No, these people are very much like musicians. And artists, they're very creative, and they can create all sorts of wonderful, wonderful value. You just have to treat them differently. So that was the first inkling that you know, there was a different way to build and manage analytics teams.




Managing and valuing diverse talents


Gilbert Eijkelenboom:

You mentioned you need to treat them differently. First of all, I like to point out that I appreciate it that you recognize the value in people right, even though other people might say hey, it's impossible to work with them or they don't perform. Apparently you saw the value appreciated, what they could do, and what was the opportunity and you mentioned you just have to treat them a bit differently. You are what, what has, what are some things? These are things that you have learned how to treat


John Thompson:

It really comes down to treating everybody as an individual, you know, not having expectations or, you know, having just ideas that everybody should conform to a certain way that's just not the way the world works anymore. It's not the way people probably have ever worked. So I tried to look at the individual I tried to get to know them their their life, their families, their mindset, there's a Kadian rhythms and just looking to see because most people want to do good work. Most people have almost unlimited ability to create new and interesting things. You have to be tolerant of how they do it. That's the real issue is it if you get hung up on how people do things, you're going to be disappointed a lot. You know, like I said, this was one fellow that I had the reason that he gave them to me in the end they said was, you know you're an American so you have a thicker skin and you'll be able to fire him faster than any of the rest of us. You're this way you people are, which I thought was kind of rude. Anyway, that was a bit of an assumption that all Americans are ruthless, heartless people. And I just started looking at this guy and I'm like, he doesn't need to be fired. He just needs to be put in an environment where he can succeed.




Recognizing potential in team members


Gilbert Eijkelenboom:

Right? That sounds like you. Yeah, you had a good eye for that?


John Thompson:

I do. I grew up in a very small farming community in Michigan town of 200 people and everybody knew everybody. And you know, there was I was fortunate enough to grow up with quite quite a small place. There was quite a bit of diversity in the town, diversity of thought, diversity of approach, all that different kinds of stuff. I mean, racially, we were all the same. But there were a lot of things in people that I learned about my father as I said, he had an auto repair shop. So I spent a lot of time talking to adults when I was a child. And I was very curious. I'm still very curious. So I would be asking people all sorts of questions and sometimes they were embarrassing to my parents. You know, why do you say things like that? Why do you walk like that? Why do you wear those clothes and why? Do you think that way? And, you know, my parents would just look at me go, Oh, my God, this kid is out of control. But I just wanted to understand why people did what they did.


Gilbert Eijkelenboom:

There's a medicine that has real story there. And when you spoke about those individuals and people you didn't recognize that qualities. It's a nice transition to what do you see as desired? skills or attributes that are traits that people should have when they are working in an analytics team for data leaders? What should they develop or what should they be on the lookout for?



John Thompson:

Well, we've talked about it already. It's another really great question. Thanks, Gilbert. You know, curiosity. That's the first thing I look for people in people's curiosity. And then I look for honesty and ethics, and then I look for kindness and consideration of others. So you know, I really don't evaluate too many people on their tech skills. Most people when they get to me, if I'm evaluating them for a job, you know, they've proven that they've gone to a good university or maybe they've gone to a you know, a second tier university. They've proven that they're, you know, that they can do you know, they can code or they can decompose problems, or they can speak or they can write or they can do all of those things are they're very good with neural networks are very good with generative AI. You know, I really don't end up with too many people that I have to evaluate them from a technical perspective.



John's unique interview approach


Gilbert Eijkelenboom:

So John, you talked about the importance of other types of skills, right? By the time people get to you that an interview or an interview that they have proven that they have the right technical skills, they went to the right schools, and you name a lot of soft skills, or I'm not sure how you want to call them. How do you how do you address that in an interview process? If they have kindness, they have an open mind. They have all these things you mentioned.


John Thompson: I think most people, many people if not most people are surprised when they interview with me because I don't sit down and giving coding challenges. I don't ask about you know, hey, do you understand, you know, do loops and for loops, and do you know what pandas do? And are you good in data visualization? I don't ask any of those questions. I asked questions about life, you know, how do you how do you handle this and what's your relationship wise with your partner and, you know, what do you do in your spare time and what was the last thing you learned? And what books do you read? And, you know, where do you go for fun? And do you like to travel? And, you know, I'm just trying to figure out if they're well-rounded people who I would like to spend time with, that's really what I'm looking for is, you know, do I want to sit in a room with you day in and day out and work together through challenges and problems? I assume you're smart. I assume that you know, you've done different things in your career because, you know, most people do get to me have 10-15 20 years of experience. So I'm really looking for you know, Are you a person that I want to spend time with?




Enhancing communication within teams


Gilbert Eijkelenboom:

Yes, because especially in consulting, right, there are weeks that you spent a lot of time with each other. So it's important. And imagine also in your role at EY right now, with global head of AI, you also spend a lot of time with people working with teams. So definitely, you're in the book, building analytics teams. You also talk about open versus fixed mindset. What do you mean with that video, elaborate?


John Thompson:

Sure. You know, a fixed mindset is you look at things in a certain way. You know, you always solve things in a linear fashion. You start from one and you go to five or you may be different you start at five, and you go to one or something like that. But in analytics, it's always changing. I mean, especially now with generative AI everything is just kind of topsy turvy over the last couple months, but I always look for people that you know, would look at it and say, you know, we've always used our internal datasets to look at how our products perform. But why don't we turn that on its head and bring in our consumer behavior, our competitive information, market information, different factors that are outside the organization that will help us understand this problem from a different perspective. So I'm always looking for people that hey, I personally have solved forecasting problems probably for the last 15 years. But every time I look at one I try to think what else can I do here? What is going to be germane to the problem, what are the kinds of data can I find or what you mean today, you know, with synthetic data generation, what data can I generate? You know, you don't have to just use what's there and what other people have purchased in F F consume. So I'm looking for creative thinkers. I'm looking for people that may have solved the problem 10 times, but they solved it 10 different ways.




The role of creativity in data science


Gilbert Eijkelenboom:

It's interesting. I hear more and more data leaders talk about the role of creativity in data science and analytics.


John Thompson:

More and more. Yeah, it used to be that oh, gosh, you know, you had the your sales data and you had your returns data and you had warranty data, and we had to put that together with a primary key and certain set of foreign keys and we sell through that data and we found out that you know, a certain set of people didn't like what we offered and we should have made it blue rather than red. Okay, you know, anybody can do that kind of stuff. But, you know, let's try to figure out what are the what are the orthogonal directions and data that can bring it in? We have so much data available to us and we and I said we can create our own data. So let's use data to really drive competitive advantage. So that's where, you know, as you said, you're seeing more and more creativity come in. And it's necessary because data and analytics is not just a linear thing anymore. We're looking to create competitive advantage. So the more ways we bring building blocks together and put them together in unique ways, top to bottom side to side. the better off we are. Thanks for those tips.



Strategies for building a data-driven culture


Gilbert Eijkelenboom:

sharing One thing that many people speak about is the data driven culture. And you know how to build it and one of the steps to take the question I'm interested in is what do you see as a good metric to see people or organizations move ahead in building this data driven culture?


John Thompson:

The over that is that is the million dollar question is, you know, as you know, people say they want a data driven culture. And I understand and I love data and I live in the data world and I'm a data geek, for sure. But, you know, it's hard to build a data driven culture you almost need to start with a top level executives. They need to be data driven. They're the ones that hold the investment in, they drive the culture, they drive the organization. So if your executives are not data driven, then it's going to be very hard to be a data driven company. You know, the metrics I look for is when you talk about what's happening in business. Do you refer back to analytics V refer back to do you reference, you know, benchmarks and measurement. Do you say, you know, hey, our customer adoption went up by 3%. And that 3% was driven by this customer segment in this region in this area, which of course, we increased our spending and advertising by this, you know, if you're a data driven company, your language is different. You refer to metrics you refer to a drove those metrics and you refer to what will come in the future from those metrics. You don't talk in generalities. You just don't talk in the concepts. You refer to data. And you talk about why things changed and you understand the programs that drove that change.




Importance of advanced communication skills


Gilbert Eijkelenboom:

Right. I like that perspective, about language. And when I think about language, I also think about communication and what do you see as the the role of communication and also how, how other data leaders who are listening who are managing one or multiple data teams, how can they foster communication skills of the people in their team?


John Thompson:

It's a great question. You know, I I'm on the advisory boards of the University of Texas, Oakland University, Ferris State, a number of US universities, and I work with them on their curriculums around advanced analytics and artificial intelligence at the undergraduate and the graduate level. And I'm sure they're tired of me, may almost sound like a broken record at times that I'm always saying, we need to spend more time teaching the students about communication, and we need to teach them about written verbal and presentation skills, because we spend most of our time communicating with at least we should spend most of our time communicating you know so I talked to my team about you know, their all those skills written verbal presentation in my previous job and CSL and I will be doing any why? We brought in presentation coaches we brought in visualization experts, we brought in writing coaches, and we put people through different different seminars and different training classes that were not demanded by the by the organization. Then what happened after I ran my teams through that is I got consistent feedback from other executives that man I love to have your people show up in meetings, they are so organized, they communicate so well, they're very clear on what they're talking about. And they talk about things in our terms, you know, so, you know, we as analytics professionals have to be kind of chameleons you know, when we sit amongst ourselves, you know, we can talk about data and models and you know, all kinds of things that we're interested in. But I was told, I always tell all my teams, if you're going to a finance meeting, you're going to talk in the terms of finance, if you're going to a marketing meeting, you're going to talk in the terms of marketing in a supply chain, the same thing. You're not going to talk about algorithmic approaches you're not going to talk about data smoothing. You're not going to talk about data management technologies or approaches. You're going to talk about the terms and the metrics they're interested in. And at first people push back they're like, Well, I don't know if I can do that. And I said, Well, then, then you can't be part of this team, because it's not good enough to be a good modeler. It's not good enough to be a good data engineer. You have to be a good professional. You have to be a business person as well. And if you can do that, if you can, you know, expand your world to include those lexicon of communication then you're unstoppable.




Engaging the audience during Q&A


Gilbert Eijkelenboom:

Yes, I completely agree, then you are unstoppable. And what do you suggest to speak the language of the audience right understand what language they speak and talk in their language. What do you suggest when you have a mixed audience of maybe marketing and finance or even more difficult maybe marketing and data people? How, how do you deal with such situations where you have a mixed audience you're talking to?


John Thompson:

Yeah, that's a great question. I've tried this all different ways, and I've made every mistake you can possibly make. So hopefully we can help our audience not make those same mistakes. You know, he doesn't really work very well to try the abstraction approach to move it up to a level where everybody can understand what you're talking about. Because if you do that, then nobody understands what you're talking about. So usually what I try to do is I try to do a presentation about the specific objective that we're working on. And I try, if anybody has been in a presentation or meeting with me, I try to get the point done and maybe seven to 10 minutes, you know, in a 30 minute meeting that gives you 23 to 20 minutes for open dialogue and q&a. And that's where it really comes to a shared understanding of what you're talking about. I really, I really don't like it. When someone presents for 29 minutes of a 30 minute meeting and they go oh, are you okay? It's like, No, I'm not okay. I'm not even sure what you said. You know, so more talking, more communicating. And then you know, while I tried to talk about, you know, the, the objective we're working on, then if someone from the data group asked me question, I talked to them about data type of concepts, and then I'll turn to the other people in the room and I said, does that response make sense to you? Generally, the answer is going to be no. Then I'll answer the question for them using their lens. So I go back and I usually answer questions two or three different times in a meeting. I was I was in a meeting once, probably 25 years ago. And it was a very, very important meeting with a thought leader and someone who had great weight in the industry. And I was talking to him for I did seem like forever. I think it was maybe just under a half hour. And he said to me is I don't know what you're talking about. I don't get it. And my boss was there and some of the board members were there and I thought it was just gonna melt. So I went back at it and said the question is question again. I still get it. And I went back at it. We did that four times. And I took different tasks, took a business approach to operations approach to the industry analyst approach and just kept answering it and finally he looked at me he goes, Oh, now I get it. He goes, I got a little bit out of every time you answered it differently and he goes, finally all made sense to me. We walked out of there in Boston as a CEO looked at me and he goes, That was truly impressive. He goes, I thought you were going to be, you know, just absolutely sunk after the first response. And I'm like, No, I can always go back and get back at it many different ways.




Techniques for engaging audience questions


Gilbert Eijkelenboom:

Yeah, I like that. Thanks for sharing that. Story. And it shows that we need to also be confident and willing to ask the question, right, because it's much safer to just finish your presentations. Talk about what you know, instead of asking a question, are you still with me with the risk of people saying I haven't understood anything so far, and then trying to improvise and work your way but actually, it's the best way right? Because then you keep the connection. You keep the attention of the audience, you make sure that they understand what you're saying. So what I understand from you is that throughout your presentation, you check if the audience is still engaged with you. And also at the end, I guess, I will check with you. At the end. You also lay down some questions or you open it for for q&a or for a conversation. Talking about that last one, how do you do that? How do you transfer from your conclusion the last words you're saying in your presentation to open it opening up the floor?


John Thompson:

Usually, what I'll do is I'll say to people, look, I want this to be a dialogue rather than a diatribe. You know, I would love you to ask questions all the way through the presentation. There's very few things that I have been involved in that would stump me. You know, but if people don't do that, which is often the case, people just want you to do your presentation, and then they'll open it up for q&a, because that's the way nor most people do their presentations. So if I've gone through and I don't get a whole lot of questions, and I've done my presentation, then as you can tell Gilbert, I'm used to telling stories. So you know, I'll tell a story that's related to what we're talking about. And just hang in there for a little while. And then someone will get brave and break the ice and ask a question, or you know, sometimes I even do it where I said, You know what, these are the questions people ask me all the time. So I'll ask a question that I get quite frequently and I'll answer it and then I'll ask myself another question, and I'll answer it and you know, I just go back and forth talking to myself for a while and then someone will break the ice and then after that, and it's just usually a flood. You know, people are then a What about this and what about that, and I've got two follow up questions and how about this, and then it really opens up. So you know, asking yourself questions, because you and I talk to a lot of people. And, you know, there's themes of questions. So that seems to work pretty well.




The art of storytelling in presentations


Gilbert Eijkelenboom:

Right, great tips. You mentioned telling a story right that is related to the content or threat to the presentation. Many people tell me I don't have any stories to tell. Can you share how this what what is the process of the detail process of you doing a presentation and then thinking hey, what would be an appropriate story to tell and you bring us into mind of John Thompson how are you?


John Thompson:

That's a frightening place to be. Well, you know, as I've mentioned a couple times now, I grew up in this small town and my father had an auto repair shop and right next to it, there was a gas station. Funny enough behind his shop was another auto repair shop. And different people went to different places for different things. And often, these guys, they're all old men would be standing around telling stories. So I when I was a kid, I sat around and listen to these stories. Now these embellishments you knew they were just made up? You know, they were for entertainment. Everybody was laughing and enjoying themselves. That's where I learned how to tell stories. You know, I just be sitting in the corner listening to something or other rival stories at times that a seven year old should not be listening to but it was fun. I really enjoyed it. But I really don't. I mean, this is this is truly a peek into my mind. I don't really plan too much stuff you know, when I do a presentation, I'm just listening to what people are saying and how they're reacting. Are they reticent? Are they coming forward? Are they engaged? Are they afraid to ask a question because they might look, you know, they might think that they look stupid, you know? So I'm gauging the the audience that I'm in the environment that I'm in and I may tell a story that makes me look vulnerable, you know, because I want to bring people forward. Or I may tell a story of how we worked on a really hard problem and solved it. I don't think I don't think about it beforehand. I never rehearse anything so you know, usually if you're talking to me, you're getting, you know, right off the top of my head.




The human side of data


Gilbert Eijkelenboom:

Right. And it sounds like it all starts with the human side. Right? Do you talk about vulnerability to about listening into about seeing, hey, are people connected to what I'm saying? And and so that also connects to what you said before? What kind of trade to uniform. In the in the last minutes we have talked about different things also about the book, building steam, so I highly recommend it to everyone. But as I mentioned in the introduction, there's also a new comic a new book out data for all. So what would you like to share about that? How is this book different and what would you like to talk about?


John Thompson:

Now? That's a great question, and thank you for teeing it up. It's so kind Gilbert. Yeah, building analytics teams was for analytics teams. You know, I affectionately referred to it as a nerd book, because I think of myself as a nerd. So, you know, it's all the people who do data and analytics, and that's a small population of the world believing data for all was written for everybody. And it really was a product of the 15 years of conversations at the dinner table with our two children and my wife, you know, because it became clear that most people don't understand what happens when you you know, you pick up your phone and and you go online and you know, you go to Facebook, you use apps, people don't understand what happens to the data. Most people don't. I mean, we generally do, but I take people through the world of data and what happens to your data, where does it go? Who has it, who stores it? Who owns it? Most people don't know that they own their own data. They think Facebook owns their data, or General Electric or Procter and Gamble or Emirates Airlines, you know, they don't realize that they own their data. So what I do is I take him through the history of data, the last 100 years of data. Why do you think about data the way we do today? And then I talk about I know that you're in Europe, I talked about all the EU laws that are coming on to the books, the AI Act, the DATA Act, I go back to GDPR and I talk about what's going to happen in the future, how you're going to be able to control your data, you're going to be able to obtain your data, download it, delete it, modify it, do all sorts of interesting things with it, and then ultimately monetize it. So it's a book for everybody. You know, and I've talked to a lot of people and like, I'm gonna buy that from my daughter or my son or my nephew or my cousin or my wife or my grandpa. You know, it really lays out what happens when you go online with your data and what will happen in the coming years.




Discussing risks of not understanding data privacy


Gilbert Eijkelenboom:

What what do you think is a risk if people don't learn about these things?


John Thompson:

You know, we've already gone you know, down a certain path where people give up their data for free and then they then their their product, you know, they're targeted by advertising. unfortunate people do things with their data, there's phishing scams, and, you know, and all sorts of, you know, fraud and things that go on, and that'll continue and it'll probably even increase over time. So I just want everybody to make the best decisions they possibly can for themselves. I'm not saying don't use Facebook. I'm not saying don't use GrubHub or, you know, any apps or anything like that. I love technology. I love data. You should use what works for you and your life, but you should be aware of what the consequences are and what the repercussions are and where your data is going. And if you're comfortable with that then cool, you know, that's all good. You know, and I did a calculation that said that, you know, just an average person, actually use me as an example. I mean, just doing what I'm doing now, when we get to a point of monetizing data. My Data dividend that I'll get paid should be about $2,000 a year. So why wouldn't I want $2,000 Some people say, Oh, it's not worth it. It's not enough money. It's not. I said, Well, I'm gonna do these things anyway. You know, and now I'm getting nothing. So I'd like to get $2,000 I mean, you know, $2,000 is useful to me.


Gilbert Eijkelenboom:

You're also giving something so it's, it's fair to get something from it.


John Thompson: Earliest truly.




Rapid-fire personal questions


Gilbert Eijkelenboom: I'd like to go to a few quick questions. And then we move towards the end of the interview. So, first thing I would like to ask is, What is something you've learned in your career that you wish you would have known earlier? All About people have upheaval? Alright. Are you early bird or night? Night all? The one in the beginning?


John Thompson:

I'm always apparently always.


Gilbert Eijkelenboom:

What's your favorite book?


John Thompson:

I'm reading a book right now called practical Egyptian magic. And I'm really enjoying that book. So that's the book I'm reading right now. My favorite book of all time was by Viktor Frankl. The title escapes me I think it was the meaning. Man's Search for me to be that I've read that book multiple times. I love it.


Gilbert Eijkelenboom:

Wow wonderful book, really on so many levels. Fantastic. Book. What is your favorite analytics tool?


John Thompson:

That's a really great question. I'd have to say python.


Gilbert Eijkelenboom:

All right. And what is one thing that many people don't know about you?


John Thompson:

Wow, I talk all the time. Feels like people know so much about me. I stopped to help anybody I can I help you know, I help people get across the street elderly people I have returned carts in the shopping parking lot shopping mall.

I already know that I'd be terrible at anything in retail. I worked in a retail job in high school and I got fired from it, so I'm not good at that.


Gilbert Eijkelenboom:

Alright, so we're nearing the end of the interview. We've discussed many things. We talked about traits of data professionals. Not only the technical side, how managers can foster a data-driven culture, how they can teach their people skills that you're talking about and many other things but what is one big takeaway you would like listeners to take away from this episode?


John Thompson:

Data and Analytics has been a field and it continues to be a field and it will grow dramatically. But I think we all need to be data and analytics literate. I spent a fair amount of time working with universities in the United States and I'm looking to work with universities around the world. And I've spent the last 12 years working with our local high school so we can start to teach students when they're teenagers, about the value of data and analytics. So I think we as a profession, should work really hard to help everybody be analytically literate.


Gilbert Eijkelenboom:

Great, thank you. And where can people follow you, connect with you, and find your books?


John Thompson:

LinkedIn is generally the best place, and if you're an analytics or data and analytics professional, happy to connect with you. If you're trying to sell me a franchise scheme, I'm probably not going to connect with you. LinkedIn is the best place, and Amazon, especially for buying my books.


Gilbert Eijkelenboom:

Right? So for everyone. The new book is now available yet. When this is out, it will be. Building Analytics Teams. Definitely recommend it and the other books as well. So what I would like to do is thank you. Thank you for the conversations, it was really pleasant. I learned a lot as well and it opened my mind. So I hope it also opens the minds of other people who are listening, who are working or working in analytics or even outside to think more about the human side to think about hey, maybe the technical skills are important. But there are other traits that are equally important and at least equally important, like kindness, like listening, like communication. And yeah, in that sense, maybe, paradoxically, we need to learn more about the human side to spread more data literacy in the world. So thank you very much for all your contributions, your books, and what you do for the community. So thanks again for today, John.


John Thompson:

Thank you, Gilbert. I really appreciated the invitation. I was anticipating this conversation over the last couple of weeks and I'm really looking forward to it. So thank you for inviting me. I really appreciate it and hopefully we can do it again in the future.


Gilbert Eijkelenboom:

Absolutely. Thank you very much, John, for everyone listening. Thank you for listening and until next time.


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