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Welcome to the Data Strategy Gurus podcast. In this show, we bring together the brightest minds in the world of data strategy, data management, artificial intelligence, and disruptive technologies.
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Thought leaders and experts share their insights, knowledge, and experience on how to stay ahead of the game in an ever-evolving data landscape.
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Whether you're a data professional, a business leader, or simply someone who is passionate about the power of data, this podcast is for you.
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So sit back, relax, and join us on a journey to explore the world of data, analytics, artificial intelligence, tech, and beyond. Hi, and welcome to the Data Strategy Gurus podcast.
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Today, we have, uh, Christopher Chin with us, and we're gonna throw it on the side from data storytelling.
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Uh, Christopher, maybe you can tell our audience a bit more about yourself, and, uh, what is your key topic that excites you? Sure. Thanks so much, Yves. So I'm a communication coach for tech professionals.
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I spent the majority of my career working in the data industry, but recently I realized that what I could uniquely give to the community is this focus on communication and presentation.
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Often, what happens in our industry is that there's a lot of focus on technical training, so how to learn certain programming languages, how to learn certain tools, but not so often is there training when it comes to soft skills like communication, which is the last mile of the typical data workflow, but one of the most important in my opinion.
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Because if you can't communicate the value of your work well, then it won't have as much value as it could have for your business users.
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So what I do is I conduct one-on-one personalized coaching and also trainings for teams when it comes to data storytelling and presentation. So you're talking about the end of the part. You do the implementation.
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You built a solution. You have to sell it. But I understand there is a big issue as well in the beginning, in the part of building the solution with the soft skills, trying to understanding critical thinking.
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These are soft skills as well lacking from a lot of, uh, technical people, which are very proficient in, in doing the technical stuff, but trying to understand what an end user or what a con- a consumer needs as a solution, that's very often pretty hard as well.
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Is that something you take into account as well in your coaching? Absolutely. What I've found is that we as technical prof- professionals, and myself being a technical professional, we like solutioning.
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So we like fixing problems, but what sometimes we're not as good at is identifying what the problem is to begin with that we're trying to solve.
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So I've seen what happens with when we're interacting with stakeholders is we immediately jump to, "Oh, this is how I can solve that with this technology, with this tool."
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But not so often do we take pause and say, "Wait a minute, what is the actual problem you need solved? What is the actual pain point that you're facing challenges with?"
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Because if you don't identify that well up front, you'll create a solution that doesn't actually solve anything.
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So what I recommend in my coaching and working with teams is really that practice of active listening, making sure that when you are communicating with that other person, you take the time to listen to what they're saying, to think beyond what the points they're making are to actually what the meaning of them is, and then only speaking when you have reached that understanding.
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Yeah, exactly. Like you say, the active listening, we, we tend to, and it's-- I think it's a human behavior if I, I talk to other people, we tend to jump into solutions.
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Typically as well, uh, they think in a, in a, in a, in a product as well.
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So [chuckles] having the, the, having the requirements, uh, specified in a very, uh, easy and understandable way, that's, that's pretty hard because we say, "You know, this how-- Yeah, I want this module in SAP."
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But no, tell me what your problem really is, like you say. Are there any, um... Like you say, active listening is, is one of the skills that you can, uh, use. Are there any other, uh, advices that you can give?
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The other advice would be to communicate consistently.
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So, and I liken this, an analogy I like to use is if you were to hire someone to build a house for you, you would want them to communicate consistently with you throughout the process, not just at the beginning to collect requirements, and then they create the house, and then you're not happy with it.
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But rather, you would want them to tell you as they're going along the process, how is it looking, maybe have you take a look at what they're building, and then you can iterate and make adjustments as you go.
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So the same should apply for the data teams in the business. If you're interacting with the business, you should communicate consistently with them.
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So not just at the beginning to gather requirements and at the end to deliver the product, but throughout on per- perhaps a weekly or biweekly cadence to make sure that everyone's on the same page all the time, and that there are no surprises at any point in the process.
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Yeah. In fact, that's-- most, most of the time, that's the role of the, of the project manager. Mm-hmm.
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Estates a, a communication plan so you understand how you will communicate, when you will communicate, what, and so on.
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But it's a, a very good skill to have as well as a technical person if that communication plan is not in place, if I understand what you are saying, and then, uh, regularly communicate what you are doing and, uh, just informing the people on where you are, maybe some, some issues you had and, uh, trying to solve that together in, in, uh, in such a way if I understand where you say this is an important thing on the communication plan then.
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Mm-hmm. Absolutely. And building off of that idea of consistent communication is even when the product is done and you hand it off to the person, it's important not to just end the relationship there, but continue it.
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Make sure there's ongoing support.
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For example, if you built a dashboard, make sure that they understand how to use it, not just that you've completed some fancy bells and whistles on it, but that they can actually use it to solve their pain points.
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So here is where maybe demos come in handy. Make sure they, that you demonstrate the capability to them. Make sure that they can actually use it and you're in interactive sessions.
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And make sure that there's good documentation, so later down the line, if you're no longer working with them, they can refer to it and understand how to do it themselves.
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So that's exactly the customer success manager, [chuckles] what you are referring to.
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The people just making sure that the adoption of what you have built, uh, really lands within the organization and is used, uh, at its, uh, full potential.Exactly.
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So there's often different roles at play, but if those roles are missing within the organization, it's important to take that step to make sure those gaps are filled.
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And is that something that, that, uh, technical people can learn a bit better as well, where you say certain roles are not in place, and it's harder to communicate?
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Uh, normally it's an implicit, um, requirement where you think this is a role that a project manager won't-- uh, is not taking up, where you expect him, uh, or, or her to take it up, and these things are not happening.
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So that's very, very often a frustration for the team to deliver the, the, the solutions in time, within budget, and within scope.
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Uh, how do you-- would, as an, as a technical person, how would you solve that or communicate that, uh, there is an issue around it?
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I think one of the things that we focus on as technical professionals a lot is order taking, because it's the path of least resistance. We just accept what people tell us to do.
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But what's harder to do but more meaningful to an organization is when you can champion data, and it's what it can deliver to the organiz-organization itself, when you can take that leadership role and be proactive about initiatives that can solve business problems.
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So in one organization I worked in, that product manager role was vacant for a while.
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So the technical team, including myself, had to step up to the plate and fill that role, communicate with the stakeholders, make sure we gathered requirements well, make sure we delivered the product well, make sure we communicated consistently throughout the process.
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And it's important at that stage not to step back and stay within the role that you were assigned, but rise to that occasion and make sure that you can not combine your technical expertise with business acumen so that together you can have business impact.
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Yeah, and are there any special things in a data-related project? We were referring to more technical roles, data, and, and data engineering. Building the solutions is very technical as well.
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Is it-- But here you have the aspect of data on top of your technical solution. Is there something more involved, would you say, in the communication and, and adoption of your solution?
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And could you clarify that a little more? So do you mean when we're creating technical solutions with data on top? Yeah. I'm, I'm thinking about a technical solution. It's an application, what you're building.
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It's entering, uh, information into a system. It needs to trigger some actions. If you're working with data, you start with, with the data in itself. The data in itself sometimes is not of a quality data.
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So you have a data quality issue which comes on top of building the solution and giving the insights. So it's an extra dimension which comes into place to, uh, to build the insights and, and help, uh, solve problems.
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Yeah, that's a huge issue, and has come up in my career as well. I was working with data that wasn't of the best quality.
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And because of that, when I found what I thought were important insights, it was good that I checked with my fellow colleagues because it turned out they weren't so important insights because it was just because the bad data was bad quality that they appeared that way.
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So it came down to me talking to the teams that were providing the source data and figuring out what, what went wrong in this process? How can we make sure this doesn't happen again?
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So data quality is of paramount importance at the very beginning of the process in any data project.
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And it comes down to talking with the people who are producers of that data early on as much as possible, because often what happens in addition to it not being bad qual-- not being good quality, is that it's not in a form that's readily accessible.
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So you wanna make sure the producers of the data can work with you to put the data in a schema or a form that you can later on use efficiently.
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So communication, again, is key throughout this process to make sure everyone's on the same page. Yeah, really understanding what the data means, but on top of that, uh, yeah, having it clear what, what they were after.
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If we then go back, well, back, go forward to the end of communicating the storytelling of your data, what are important things where you need to, um, well, um, well take care of that you communicate it in a correct way?
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What I like to focus on is the real purpose of a presentation is not to just give information, because if you're just giving information, you could easily just email someone about it.
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When we're giving a presentation to someone about our insights for data storytelling purposes, what we need to focus on is not the information part, but the action part.
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So what action do we want people to take based on this information? It's only when we focus on that, that the information becomes meaningful.
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'Cause I can tell you all these statistics about how our company performed, but unless I give you a recommendation for how we can improve performance or cut back on things that weren't giving us such good performance in the past, not until then can we actually do something that will change the business for the better.
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So the interaction then again is very important.
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I mean, from a technical perspective, you completely understand how Google Cloud works, uh, how the ETL pipeline needs to be built, uh, the versioning, all the technical aspects of your data platform.
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But you need to understand, if you, say, need to make recommendations on the insights that you found for your data, you need to understand the business as well to make those recommendations and say, "Hey, this is what we've built.
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And with this solution, we can scale it up to different departments, to different regions, to different countries," for example. That's the technical part where you, especially as an expert, can take care of.
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But you have-- need to have that business acumen as well to communicate it, how that works in relationship with your technical part.
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Uh, is that what I'm understanding what you are saying now in, in the last part of giving the advice, the suggestions? Exactly.
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It really comes down to knowing your audience is what I always recommend as even the first step that goes into preparing a data story.
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Because one of the worst things to do is give the same data story to every single audience that you speak to. The best thing to do is to make sure you personalize it to the audience.
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So if you're taking this data story, these insights you found, and you're presenting it to marketing, make sure you focus on marketing's goals, marketing's KPIs, marketing terminology.
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Don't use a lot of jargon that they wouldn't understand. Same goes for finance. If you're talking to finance instead, make sure you use finance analogies, finance terminology, finance KPIs.
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Make sure you always-Ensure that your story is focused on the audience and their goals, and not just on the information you want to give to them. Yeah.
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It's, it's-- it needs to be relatable to what they want to, uh, achieve, and based upon that, you take the technical part and then, uh, translate it into something what, uh, the receiver, the, the business user understands.
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Exactly. What I've also experienced is that sometimes when you're working with stakeholders, they'll express what they want, but it may not actually be what solves their problem.
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And what happens is they're actually really relying on you and your technical expertise to guide them in the right direction.
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So again, this comes down to the idea of not just being an order taker, but being proactive and questioning, digging deeper, asking those probing questions, and really getting at what the problem actually is so that you can solve their problem.
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Yeah, again, the critical thinking, not the expected-- well, accepting what you've been told, but always not criticizing, but challenging it and to have the best understanding of what you're after in fact. Exactly. Yeah.
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It's-- it really comes down to knowing your audience. And what I've also experienced is that a lot of us, when we're working on these data stories, often don't perhaps give enough context around the issue.
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So we focus on the big insight that we found, but unless you give the audience sufficient context, we won't understand why it's important.
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So at the very beginning of a presentation for data storytelling, it's important to give sufficient context, make sure everyone's on the same page.
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This is where the company was before, this is what the big insight we found now is, and this is where we can go in the future.
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So it's this framework of what, so what, now what, that's commonly used in these kinds of presentations.
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Make sure you talk about what's going on, what can-- why, why does this matter, and then what can we do from this point? So making sure you have all those pieces in place.
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Action at the end, the most important part, but also enough context in the middle, at the beginning, and then this big climax insight at the-- in the middle of the presentation where you express to them why this is so important to do.
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Yeah. And then as well, what I hear in what you're saying, um, you need to understand the business strategy as well. Where do we want to go with the business to be able to connect that and, and give the insights?
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If you say, "This is where the company is right now, and this is where we can go," you need to understand as well and know, uh, what is the strategy for the company, what do you want to achieve.
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And that's, for me, I see that very often time in projects, it's very hard to get that information out of the business users.
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You need to talk to the C levels to get that information, but they're not always available- Right... to help you or just get you started on a project to share that type of information.
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So I think there's a, a lot of miscommunication, uh, to, uh, to, yeah, to build, uh, successful data stories and successful data projects as such. So what, what is your experience on that? Absolutely.
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When I talk to a lot of aspiring analysts who hope to enter the field, they think it'll be all technical. They'll just be behind the screen coding all day, creating dashboards and reports and pretty visualizations.
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But the reality is you have to be a business person, because in an organization, every single activity that occurs needs to deliver value for the business in some way.
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It can't be just something you're doing for fun on the side because you enjoy it technically. So what I always recommend to analysts is to spend the time to develop that business acumen.
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Talk to as many people as you can within your organization. Talk to your boss. See who they can refer you to to better understand, how does the business make money?
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In fact, one of my previous managers, what I really appreciated was when I onboarded, they gave me time to understand the business.
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They said, "I really want to make sure you understand how the business makes money, because then as an analyst, you can help us make more money."
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So, uh, they gave me the resources, they gave me the trainings to understand, how exactly does this company make money? And then I can start thinking of the bigger questions.
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When I'm analyzing data, how can I provide recommendations and insights that propel that forward?
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So my biggest recommendation to aspiring analysts or any analyst at any stage of their career is to focus not just on the technical part, but also the business part, because that's integral to success.
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Yeah, I think that's, that's a nice wrap-up where you say don't only focus on the things that you really like to do, the technical part, but really understanding the business, because in the end, it's creating that business value.
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How can we improve the business to run, make more money, less costs, uh, just be more competitive or, or any other things that is really business-related as such.
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Previously, uh, Christopher, you told me as well you've been into the music scene. Yeah. Data connects us all, but music connects us all as well. So what is your favorite band or, uh, type of music?
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I used to do film scoring, and my big aspiration was to become a big, famous Hollywood film composer one day. So film scores are one of my favorite genre to listen to.
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And I love music by John Williams and Hans Zimmer, some of the big names in the, I guess, the US Hollywood film composing scene. And that music is just spectacular. So that would definitely be my favorite genre.
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And I believe that music has really informed the way that I approach communication and presentation even to this day, because alluding to what I mentioned before about presentations not being just about information, but being about action,
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I always try to think about presentation and communication about the audience's experience of the information.
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So the analogy I like to use is, why would people pay to go to a music concert when they can listen to the same music on YouTube?
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And the reason is, it's not just about the information or the raw data that's you're consuming, it's about your experience of that information or raw data that makes you pay money to go to this kind of concert.
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So in communication, it's important for us to not think about information, but about experience and inspiration.
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Yeah, and then we come again to who, who are you talking to and then, uh, aligning your communication to the receiver, uh, of your, uh, information, what you're sharing.
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Uh, Christopher, thanks very much for your time and being a guest on the Data Strategy Gurus podcast. Uh, it was really fun talking to you. Thanks for your time. Thanks so much, Yves. It was a pleasure.
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Thank you for joining us on this awesome podcast. As senior executives, data and analytics architects, and AI professionals, your time is valuable and we appreciate you choosing to hang out with us.
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If you liked what you heard, please give us a thumbs up, hit the subscribe button, and leave a comment. We love hearing from our audience.
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Don't forget to spread the word on social media and let's continue to drive innovation in the industry together. Thanks for listening, and we'll catch you on the next episode. [outro music]
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Welcome to the Data Strategy Gurus podcast. In this show, we bring together the brightest minds in the world of data strategy, data management, artificial intelligence, and disruptive technologies.
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Thought leaders and experts share their insights, knowledge, and experience on how to stay ahead of the game in an ever-evolving data landscape.
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Whether you're a data professional, a business leader, or simply someone who is passionate about the power of data, this podcast is for you.
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So sit back, relax, and join us on a journey to explore the world of data, analytics, artificial intelligence, tech, and beyond. Hi, and welcome to the Data Strategy Gurus podcast.
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Today, we have, uh, Christopher Chin with us, and we're gonna throw it on the side from data storytelling.
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Uh, Christopher, maybe you can tell our audience a bit more about yourself, and, uh, what is your key topic that excites you? Sure. Thanks so much, Yves. So I'm a communication coach for tech professionals.
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I spent the majority of my career working in the data industry, but recently I realized that what I could uniquely give to the community is this focus on communication and presentation.
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Often, what happens in our industry is that there's a lot of focus on technical training, so how to learn certain programming languages, how to learn certain tools, but not so often is there training when it comes to soft skills like communication, which is the last mile of the typical data workflow, but one of the most important in my opinion.
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Because if you can't communicate the value of your work well, then it won't have as much value as it could have for your business users.
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So what I do is I conduct one-on-one personalized coaching and also trainings for teams when it comes to data storytelling and presentation. So you're talking about the end of the part. You do the implementation.
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You built a solution. You have to sell it. But I understand there is a big issue as well in the beginning, in the part of building the solution with the soft skills, trying to understanding critical thinking.
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These are soft skills as well lacking from a lot of, uh, technical people, which are very proficient in, in doing the technical stuff, but trying to understand what an end user or what a con- a consumer needs as a solution, that's very often pretty hard as well.
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Is that something you take into account as well in your coaching? Absolutely. What I've found is that we as technical prof- professionals, and myself being a technical professional, we like solutioning.
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So we like fixing problems, but what sometimes we're not as good at is identifying what the problem is to begin with that we're trying to solve.
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So I've seen what happens with when we're interacting with stakeholders is we immediately jump to, "Oh, this is how I can solve that with this technology, with this tool."
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But not so often do we take pause and say, "Wait a minute, what is the actual problem you need solved? What is the actual pain point that you're facing challenges with?"
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Because if you don't identify that well up front, you'll create a solution that doesn't actually solve anything.
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So what I recommend in my coaching and working with teams is really that practice of active listening, making sure that when you are communicating with that other person, you take the time to listen to what they're saying, to think beyond what the points they're making are to actually what the meaning of them is, and then only speaking when you have reached that understanding.
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Yeah, exactly. Like you say, the active listening, we, we tend to, and it's-- I think it's a human behavior if I, I talk to other people, we tend to jump into solutions.
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Typically as well, uh, they think in a, in a, in a, in a product as well.
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So [chuckles] having the, the, having the requirements, uh, specified in a very, uh, easy and understandable way, that's, that's pretty hard because we say, "You know, this how-- Yeah, I want this module in SAP."
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But no, tell me what your problem really is, like you say. Are there any, um... Like you say, active listening is, is one of the skills that you can, uh, use. Are there any other, uh, advices that you can give?
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The other advice would be to communicate consistently.
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So, and I liken this, an analogy I like to use is if you were to hire someone to build a house for you, you would want them to communicate consistently with you throughout the process, not just at the beginning to collect requirements, and then they create the house, and then you're not happy with it.
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But rather, you would want them to tell you as they're going along the process, how is it looking, maybe have you take a look at what they're building, and then you can iterate and make adjustments as you go.
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So the same should apply for the data teams in the business. If you're interacting with the business, you should communicate consistently with them.
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So not just at the beginning to gather requirements and at the end to deliver the product, but throughout on per- perhaps a weekly or biweekly cadence to make sure that everyone's on the same page all the time, and that there are no surprises at any point in the process.
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Yeah. In fact, that's-- most, most of the time, that's the role of the, of the project manager. Mm-hmm.
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Estates a, a communication plan so you understand how you will communicate, when you will communicate, what, and so on.
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But it's a, a very good skill to have as well as a technical person if that communication plan is not in place, if I understand what you are saying, and then, uh, regularly communicate what you are doing and, uh, just informing the people on where you are, maybe some, some issues you had and, uh, trying to solve that together in, in, uh, in such a way if I understand where you say this is an important thing on the communication plan then.
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Mm-hmm. Absolutely. And building off of that idea of consistent communication is even when the product is done and you hand it off to the person, it's important not to just end the relationship there, but continue it.
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Make sure there's ongoing support.
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For example, if you built a dashboard, make sure that they understand how to use it, not just that you've completed some fancy bells and whistles on it, but that they can actually use it to solve their pain points.
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So here is where maybe demos come in handy. Make sure they, that you demonstrate the capability to them. Make sure that they can actually use it and you're in interactive sessions.
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And make sure that there's good documentation, so later down the line, if you're no longer working with them, they can refer to it and understand how to do it themselves.
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So that's exactly the customer success manager, [chuckles] what you are referring to.
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The people just making sure that the adoption of what you have built, uh, really lands within the organization and is used, uh, at its, uh, full potential.Exactly.
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So there's often different roles at play, but if those roles are missing within the organization, it's important to take that step to make sure those gaps are filled.
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And is that something that, that, uh, technical people can learn a bit better as well, where you say certain roles are not in place, and it's harder to communicate?
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Uh, normally it's an implicit, um, requirement where you think this is a role that a project manager won't-- uh, is not taking up, where you expect him, uh, or, or her to take it up, and these things are not happening.
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So that's very, very often a frustration for the team to deliver the, the, the solutions in time, within budget, and within scope.
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Uh, how do you-- would, as an, as a technical person, how would you solve that or communicate that, uh, there is an issue around it?
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I think one of the things that we focus on as technical professionals a lot is order taking, because it's the path of least resistance. We just accept what people tell us to do.
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But what's harder to do but more meaningful to an organization is when you can champion data, and it's what it can deliver to the organiz-organization itself, when you can take that leadership role and be proactive about initiatives that can solve business problems.
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So in one organization I worked in, that product manager role was vacant for a while.
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So the technical team, including myself, had to step up to the plate and fill that role, communicate with the stakeholders, make sure we gathered requirements well, make sure we delivered the product well, make sure we communicated consistently throughout the process.
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And it's important at that stage not to step back and stay within the role that you were assigned, but rise to that occasion and make sure that you can not combine your technical expertise with business acumen so that together you can have business impact.
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Yeah, and are there any special things in a data-related project? We were referring to more technical roles, data, and, and data engineering. Building the solutions is very technical as well.
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Is it-- But here you have the aspect of data on top of your technical solution. Is there something more involved, would you say, in the communication and, and adoption of your solution?
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And could you clarify that a little more? So do you mean when we're creating technical solutions with data on top? Yeah. I'm, I'm thinking about a technical solution. It's an application, what you're building.
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It's entering, uh, information into a system. It needs to trigger some actions. If you're working with data, you start with, with the data in itself. The data in itself sometimes is not of a quality data.
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So you have a data quality issue which comes on top of building the solution and giving the insights. So it's an extra dimension which comes into place to, uh, to build the insights and, and help, uh, solve problems.
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Yeah, that's a huge issue, and has come up in my career as well. I was working with data that wasn't of the best quality.
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And because of that, when I found what I thought were important insights, it was good that I checked with my fellow colleagues because it turned out they weren't so important insights because it was just because the bad data was bad quality that they appeared that way.
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So it came down to me talking to the teams that were providing the source data and figuring out what, what went wrong in this process? How can we make sure this doesn't happen again?
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So data quality is of paramount importance at the very beginning of the process in any data project.
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And it comes down to talking with the people who are producers of that data early on as much as possible, because often what happens in addition to it not being bad qual-- not being good quality, is that it's not in a form that's readily accessible.
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So you wanna make sure the producers of the data can work with you to put the data in a schema or a form that you can later on use efficiently.
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So communication, again, is key throughout this process to make sure everyone's on the same page. Yeah, really understanding what the data means, but on top of that, uh, yeah, having it clear what, what they were after.
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If we then go back, well, back, go forward to the end of communicating the storytelling of your data, what are important things where you need to, um, well, um, well take care of that you communicate it in a correct way?
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What I like to focus on is the real purpose of a presentation is not to just give information, because if you're just giving information, you could easily just email someone about it.
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When we're giving a presentation to someone about our insights for data storytelling purposes, what we need to focus on is not the information part, but the action part.
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So what action do we want people to take based on this information? It's only when we focus on that, that the information becomes meaningful.
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'Cause I can tell you all these statistics about how our company performed, but unless I give you a recommendation for how we can improve performance or cut back on things that weren't giving us such good performance in the past, not until then can we actually do something that will change the business for the better.
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So the interaction then again is very important.
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I mean, from a technical perspective, you completely understand how Google Cloud works, uh, how the ETL pipeline needs to be built, uh, the versioning, all the technical aspects of your data platform.
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But you need to understand, if you, say, need to make recommendations on the insights that you found for your data, you need to understand the business as well to make those recommendations and say, "Hey, this is what we've built.
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And with this solution, we can scale it up to different departments, to different regions, to different countries," for example. That's the technical part where you, especially as an expert, can take care of.
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But you have-- need to have that business acumen as well to communicate it, how that works in relationship with your technical part.
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Uh, is that what I'm understanding what you are saying now in, in the last part of giving the advice, the suggestions? Exactly.
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It really comes down to knowing your audience is what I always recommend as even the first step that goes into preparing a data story.
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Because one of the worst things to do is give the same data story to every single audience that you speak to. The best thing to do is to make sure you personalize it to the audience.
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So if you're taking this data story, these insights you found, and you're presenting it to marketing, make sure you focus on marketing's goals, marketing's KPIs, marketing terminology.
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Don't use a lot of jargon that they wouldn't understand. Same goes for finance. If you're talking to finance instead, make sure you use finance analogies, finance terminology, finance KPIs.
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Make sure you always-Ensure that your story is focused on the audience and their goals, and not just on the information you want to give to them. Yeah.
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It's, it's-- it needs to be relatable to what they want to, uh, achieve, and based upon that, you take the technical part and then, uh, translate it into something what, uh, the receiver, the, the business user understands.
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Exactly. What I've also experienced is that sometimes when you're working with stakeholders, they'll express what they want, but it may not actually be what solves their problem.
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And what happens is they're actually really relying on you and your technical expertise to guide them in the right direction.
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So again, this comes down to the idea of not just being an order taker, but being proactive and questioning, digging deeper, asking those probing questions, and really getting at what the problem actually is so that you can solve their problem.
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Yeah, again, the critical thinking, not the expected-- well, accepting what you've been told, but always not criticizing, but challenging it and to have the best understanding of what you're after in fact. Exactly. Yeah.
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It's-- it really comes down to knowing your audience. And what I've also experienced is that a lot of us, when we're working on these data stories, often don't perhaps give enough context around the issue.
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So we focus on the big insight that we found, but unless you give the audience sufficient context, we won't understand why it's important.
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So at the very beginning of a presentation for data storytelling, it's important to give sufficient context, make sure everyone's on the same page.
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This is where the company was before, this is what the big insight we found now is, and this is where we can go in the future.
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So it's this framework of what, so what, now what, that's commonly used in these kinds of presentations.
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Make sure you talk about what's going on, what can-- why, why does this matter, and then what can we do from this point? So making sure you have all those pieces in place.
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Action at the end, the most important part, but also enough context in the middle, at the beginning, and then this big climax insight at the-- in the middle of the presentation where you express to them why this is so important to do.
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Yeah. And then as well, what I hear in what you're saying, um, you need to understand the business strategy as well. Where do we want to go with the business to be able to connect that and, and give the insights?
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If you say, "This is where the company is right now, and this is where we can go," you need to understand as well and know, uh, what is the strategy for the company, what do you want to achieve.
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And that's, for me, I see that very often time in projects, it's very hard to get that information out of the business users.
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You need to talk to the C levels to get that information, but they're not always available- Right... to help you or just get you started on a project to share that type of information.
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So I think there's a, a lot of miscommunication, uh, to, uh, to, yeah, to build, uh, successful data stories and successful data projects as such. So what, what is your experience on that? Absolutely.
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When I talk to a lot of aspiring analysts who hope to enter the field, they think it'll be all technical. They'll just be behind the screen coding all day, creating dashboards and reports and pretty visualizations.
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But the reality is you have to be a business person, because in an organization, every single activity that occurs needs to deliver value for the business in some way.
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It can't be just something you're doing for fun on the side because you enjoy it technically. So what I always recommend to analysts is to spend the time to develop that business acumen.
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Talk to as many people as you can within your organization. Talk to your boss. See who they can refer you to to better understand, how does the business make money?
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In fact, one of my previous managers, what I really appreciated was when I onboarded, they gave me time to understand the business.
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They said, "I really want to make sure you understand how the business makes money, because then as an analyst, you can help us make more money."
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So, uh, they gave me the resources, they gave me the trainings to understand, how exactly does this company make money? And then I can start thinking of the bigger questions.
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When I'm analyzing data, how can I provide recommendations and insights that propel that forward?
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So my biggest recommendation to aspiring analysts or any analyst at any stage of their career is to focus not just on the technical part, but also the business part, because that's integral to success.
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Yeah, I think that's, that's a nice wrap-up where you say don't only focus on the things that you really like to do, the technical part, but really understanding the business, because in the end, it's creating that business value.
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How can we improve the business to run, make more money, less costs, uh, just be more competitive or, or any other things that is really business-related as such.
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Previously, uh, Christopher, you told me as well you've been into the music scene. Yeah. Data connects us all, but music connects us all as well. So what is your favorite band or, uh, type of music?
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I used to do film scoring, and my big aspiration was to become a big, famous Hollywood film composer one day. So film scores are one of my favorite genre to listen to.
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And I love music by John Williams and Hans Zimmer, some of the big names in the, I guess, the US Hollywood film composing scene. And that music is just spectacular. So that would definitely be my favorite genre.
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And I believe that music has really informed the way that I approach communication and presentation even to this day, because alluding to what I mentioned before about presentations not being just about information, but being about action,
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I always try to think about presentation and communication about the audience's experience of the information.
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So the analogy I like to use is, why would people pay to go to a music concert when they can listen to the same music on YouTube?
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And the reason is, it's not just about the information or the raw data that's you're consuming, it's about your experience of that information or raw data that makes you pay money to go to this kind of concert.
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So in communication, it's important for us to not think about information, but about experience and inspiration.
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Yeah, and then we come again to who, who are you talking to and then, uh, aligning your communication to the receiver, uh, of your, uh, information, what you're sharing.
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Uh, Christopher, thanks very much for your time and being a guest on the Data Strategy Gurus podcast. Uh, it was really fun talking to you. Thanks for your time. Thanks so much, Yves. It was a pleasure.
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