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003 - Selling Data services to your Stakeholders
274 Plays1 year ago
This week I’m joined by Leon Tang the VP of Data from @fresha. Leon shares his unique career, from frying fish and chips to building and leading data teams at some of the world's most well-known tech companies.
Leon stresses the importance of relationship building and business understanding as a key attributes to success in data.
We speak about how to make sure your data team is a driver of the business and not a support function.
I dive into how to excel in your data career and have impact on the business everyday!
🌐 What You'll Learn:
How to break from a “Senior” into Leadership
How to build your toolkit to succeed in data
How to foster a data driven culture to set your team up for success.
Top tips for interviewing and a successful career in data!
The Stacked Data Podcast isn't just about technology; it's about the stories, experiences, and lessons that drive innovation in the data landscape. Whether you're a seasoned data professional or simply curious about the future of data, this conversation offers a wealth of knowledge and inspiration.
Please give us a follow as we have lots more episodes coming!
We are always looking for feedback or topics you'd like to hear about. Please reach out!
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Transcript
Introduction to Stacked Podcast
00:00:02
Speaker
Hello and welcome to the Stacked podcast brought to you by Cognify, the recruitment partner for modern data teams hosted by me, Harry Golop. Stacked with incredible content from the most influential and successful data teams, interviewing industry experts who share their invaluable journeys, groundbreaking projects, and most importantly, their key learnings. So get ready to join us as we uncover the dynamic world of modern data.
00:00:34
Speaker
Hello everyone and welcome to the show.
Introducing Leon Tang at Fresher
00:00:36
Speaker
This week I'm joined by Leon Tang. Leon is the VP of Data at Fresher, a fresher of the number one software for Salons and Spahls. They provide a simple, flexible and powerful booking software for businesses and it's subscription free. Today we discuss about the importance of making sure your data function is a driver and not a support function.
00:00:59
Speaker
how to effectively communicate and align with the business needs, and the most important skills for a modern data professional. I hope you enjoy our conversation.
00:01:09
Speaker
Hi, Leon. Thanks for joining me today on the show. How are you doing? All good, Harry. Thanks for joining me in The Fresher Office. How are you? Yeah, I'm really good. It's great to be in The Fresher Office just off of Waterloo. And today we're going to be going through how to navigate the modern world of data.
Leon's Background and Work Ethic
00:01:24
Speaker
But before we jump in, it'd be great just to get an overview of your background and your position here at The Fresher. Yeah, sure. Well, coming from like an immigrant family, it's quite different.
00:01:34
Speaker
Right. And so my parents came to the UK at a young age and didn't have my brother, me, and led to my sister. Like a lot of Chinese immigrants, they opened a fish and chips shop, surprisingly. You wouldn't typically make fish and chips with Chinese people, but here we are in a small town south of London called East Princeton. It's near Gatwick, for those of you who know, which I was forced to work in, right? So growing up, I had to play quite a lot of different roles. Potato peeler, chip fryer,
00:02:03
Speaker
fish and chip rapper, fish deboner, but also cashier. Honestly, as a kid, I absolutely hated it. I had to work on Friday nights and Saturdays, which meant that instead of socializing with my friends, I was stuck at home. But kind of looking back, I don't think I would have had the same success in my career if I didn't play those roles.
Career Journey: Deliveroo and Fresher
00:02:22
Speaker
And if you said to me, right, to that potato peeling kid, you'll one day be building and leading teams at some of the most well-known tech companies in the world, like Deliveroo, to end up leading their data-shoot diligence in Series F, where we raised $485 million, or even working with businesses like Burger King to help them launch their dark kitchens globally, I would have never believed you, right? And now I'm actually the VP of Analytics at Fresher, which I know you mentioned. Just for those of you who haven't heard of us,
00:02:50
Speaker
We're one of the largest beauty and wellness software payments and marketplaces in the world. And during COVID, we grew 200%, right? And imagine that with all these places closing down, how do we grow 200% in those two years? And because of this growth,
00:03:08
Speaker
I guarantee that you have been to or have a store near you that uses Fresher. And I say this because for the past six years that I lived in Angel, I have always booked online at Barbara Smith's in Camden Passage. I just never knew I was booking a Fresher.
00:03:26
Speaker
Well, it's a couple of things to break down there. First off, it seems growing up, your work ethic has transpired into the real world and has held you well. And as for Fresher's Grove over COVID, I think it's just evident of digitalization and the power it's bringing to companies that probably didn't have the infrastructure or the knowledge of how to build a platform like you guys. Exactly.
00:03:47
Speaker
It's all about freshness, like how you make lives of the beauty and wellness industry, shop owners, a lot easier, a lot simpler. So they can focus on the good stuff, right? Like working with their customers, upselling products. Yeah. I mean, you should always focus on what you're best at, right? Exactly. Play to your strengths, not your weaknesses.
00:04:04
Speaker
Brilliant. So you've had an interesting journey into data. You've already sort of mentioned a bit about your background. What made you jump into the world of data and how did you deal with the change into an industry so technical and business focused as data?
00:04:19
Speaker
Let me give you some background on this, because if you look eight years ago, when I first started as one of Deliveroo's early employees, my journey does feel quite surreal. To me anyway, I started initially in customer service at Deliveroo. We kind of dealt with the usual CS stuff, answering calls, replying to emails, giving refunds. Not exactly what I call fun. For me, it was quite boring.
00:04:44
Speaker
And an opportunity came up when I saw refunds were costing us quite a lot, and I really wanted to look into it. Like in around two weeks, I learned SQL and Python, and I actually presented to the team and the analytics from you actually in a route at that time some data and some analysis around how do
Transition to Analytics and Learning Challenges
00:04:59
Speaker
we reduce these refund costs.
00:05:01
Speaker
And essentially, after the presentation itself, guys from analytics came up to me and were like, why are you in customer service? Counter analytics will give you a full-time salary and also some functions. And I was like, man, I can't get off this. Because full disclosure, in customer service, I was earning eight pounds an hour. I was working 12 hours a day, six days a week, and traveling two hours up from London and two hours back from London.
00:05:27
Speaker
So as you can imagine, my life was just completely work related and not very fun, also very steep deprived. So working in analytics really gave me that path out, which was awesome. And I guess your second part of your question was all about how do I deal with the change in the industry, right? And I guess for me, the main difference between analytics and CS was pretty large, right? In CS, I already had the skills that I needed as a working food retail before.
00:05:51
Speaker
But in analytics, I was required to skill up super fast, learning concepts that I hadn't learned or seen before and trying to provide value as quick as possible. It was kind of like being placed on an alien planet and trying to make a living without
Stakeholder Management and Communication
00:06:05
Speaker
learning the language. So pretty hard. I'm not going to lie that it was really tough. I made a lot of mistakes along the way.
00:06:12
Speaker
But I kind of feel like you've got to dust yourself off and keep moving forward. When you're asking about how to deal with the change, I think resilience is key, right? Just be comfortable with making mistakes and know that you're going to make mistakes, but learn from them.
00:06:24
Speaker
Yeah, I think that's such a powerful message. And I think even now what we see in the modern data world is no one has the right answer to everything. Everyone's trying to find their own way. And by making mistakes and failing is how you learn and progress. So it's a great lesson to take forward. You mentioned, obviously, you had no prior technical backgrounds.
00:06:47
Speaker
How did you upskill in that environment? Did you do extra courses? Was it the team? How could someone else go on a similar journey to you like that? That's a good question. I guess I've always been quite mathematical. I mean, growing up in Asian households, maths was a really big thing. But also when I was saying I was working as a cashier in that fish and chip shop, you weren't allowed to use calculators or anything. You calculate all the price in your head, and then you type it out, right?
00:07:14
Speaker
which is crazy. Imagine someone comes in or there's like six or seven portion of fish and chips with two bad sausages on the side of a mush of peas. You've got to do that in your head straight away. Take the money, right? And you've got to be precise and correct. So that's one thing. And the other thing is I also study physics at university. And in physics, there's a lot of stats.
00:07:31
Speaker
There's a lot of theoretical work, but there's a lot of like problem solving as well, which kind of translates to analytics as a whole. But in terms of like the actual hard skills, which are necessary, like learning SQL and Python, I just looked on what the skill course era or coded caveat, one of those anyway, to re-understand exactly. Okay.
00:07:49
Speaker
How do I start writing out code? How do I understand it and conceptualize it? But then also working on problems that actually allowed me to produce this analysis. I found
Specialization in Data Roles
00:08:00
Speaker
that the key way of doing it, just learn by doing. Yeah, it's been a common theme actually with some other guests. Learn by doing is definitely the most powerful and it comes back to their mistakes. So that brings us nicely on to the next question around what skills you think are the most important
00:08:17
Speaker
in data to excel, what is your approach in developing them and how do you think you can best apply them to real-world data analytics?
00:08:27
Speaker
That's not a good question. So there's three things I really think are important to excel in data, but actually kind of overlap within the general business world as well. And the first one is stakeholders management, right? If you are good in your stakeholders, you won't get anywhere, right? There's only a certain point where your hard skills take you, right? And then afterwards, you need to understand how to work with people and work for them well. Make sure they like you and actually build those relationships.
00:08:57
Speaker
Because it's very easy to be the best at SQL. Well, easy-ish. Or the best like Python. But when it comes to working the stakeholders, understanding what they need before they even need it, that's essential. Or understand how to work for them in terms of the best way for project management, the best way of communication, the best way of following up. All these things are completely vital, especially when they progress.
00:09:22
Speaker
The second one, I would say, is being very business-focused. What I find is that a lot of people are very technical, but they can't relate it back to business or to commercials. So they made this amazing model, and they're like, oh, yeah, but does it actually solve the business problem they're looking for? Oh, no? Well, what are you making in the first place? And it kind of ties back into the stakeholder management model as well, because I didn't know a unique bit to sell the thing that you're making. If you can't sell the model you're making or sell the analysis that you're doing to your stakeholders,
00:09:51
Speaker
You're going to get nowhere because I guess it's very different to how people think about analytics teams. Some people think about analytics teams like a support function, but the way I see it is more like a steering function. And in order for you to steer those business units or those stakeholders in the right way, you need to be able to
Data as a Steering Function
00:10:07
Speaker
sell. You need to have that relationship in the first place and you need to understand the business.
00:10:11
Speaker
And I guess the last and most important thing is, I would say it's all about communication, right? How do you communicate something which is very technical, very simply to your stakeholders? Because if you can't do that, they'll understand you. Again, it's very hard for you to sell that to them.
00:10:27
Speaker
I mean, they all link perfectly into each other. And I think your emphasis on the softer skills is so important, isn't it? Because you can build, as you mentioned, all of this amazing stuff, but if it's not being used by the business, then what's the real point in building it? And I think that's an interesting point that you made about.
00:10:45
Speaker
the data team not being a support function but being a steerer. Is that how you would maybe look at an organization of the data team when you join them? And if they are seen as more of a support function, how would you approach turning them into a steerer and a driver rather than that support function? Because I think that's something that maybe quite a lot of leaders might be in an organization where they're seen like that and maybe you'd like some advice how to get there. For sure.
00:11:09
Speaker
I've worked in a few companies where analytics has been a support function, and actually we have transitioning out to more of a steering strategic function. So I'm just going to quickly explain to you what I mean by a steering function. So the support function is very similar to CX.
00:11:24
Speaker
It's similar to, I guess, how data engineers are working with analysts. They help them get to where they need by giving them the support, the tasks, or the projects they need to actually fulfill that in the first place. A steering function is slightly different. And the way I see it is kind of like being an internal consultant.
00:11:44
Speaker
like McKinsey, like people from Bain, working with the different verticals to help them achieve their results and help them implement different strategies and actually even processes to get to that required result, right, hitting a certain KPI or increasing their growth or improving their EBITDA. That stuff that analysis should be able to do because they should be able to pull the data together, come up with a strategy by working with different stakeholders and then actually implement it with them hand in hand. I think that supports stuff anyway.
00:12:13
Speaker
So that's what I see as a steering function. And when you say how to get to that, I think it's depending on a few things. One is that analytics can't be reactive all the time. You have to think about how to start being proactive in certain things, certain issues that come up, and actually just take something or project by their hands, be like, hey, look, I see there's a problem here. Let me bring all the data together and actually go out to those bit functions and be like, hey, this is some of the interests I found, how about work together on this?
00:12:42
Speaker
which actually relates really closely to what I said before about stakeholder management and building those relationships. Because if you don't have those relationships in the first place, it's so hard for you to push those genders. And I guess the next thing, which I feel like a lot of analytics teams are missing, is clear processes, clear projects,
00:13:05
Speaker
and also business understanding. So I'm going to cover the first one. So when I say clear processes, I have seen a lot of analysts being stuck in the support function because people would go up to them like, hey, can I get some analysis? And if the first analyst is busy, they'll go to the second one, the third one, the fourth one, the fifth one for exactly the same thing.
00:13:29
Speaker
And obviously, that's very destructive. So you need to be able to set up processes to protect and shield your team from ad hoc requests and from people just bugging them all the time. And one way you do that is with projects. And the way you think about projects is like, how do you work across the business? Again, building those relationships in the first place and quickly understanding what do people care about and what problems do they need to solve using data.
00:13:57
Speaker
Because if you can't figure that out, then you actually shouldn't have projects in the first place, right? But once you have these projects in place, then what you do is you say, OK, here's the quality projects that analysts are going to work with. These are going to be affected by with the rest of the wider business, with the senior leadership team, the sea levels, whoever it is. And they say, we're going to work on these for this quarter, right?
00:14:20
Speaker
Obviously, don't overburden yourselves because I see when people put too much in, they kind of burn themselves out. But once you have these projects in place, then you can say, hey, look, these are things I'm working on in this quarter. Any ad hoc things that come up have to go through a separate process. And we recently, for sure, implemented a ticketing system. So tickets will go through this process into Notion, where all of our other stuff is. And we would review that once a week or once every two weeks, depending on what people department is.
00:14:49
Speaker
on priorities regarding ad hoc tasks versus the projects. So if they want us to work on certain ad hoc tasks, then we say, actually, you're going to push your project by two, three weeks. Are you happy with that? So we have a conversation around that. And this also means that all the requests are at one place. That allows us to make decisions in the first place.
00:15:07
Speaker
So as a leader, you prioritise your team's workload, take the burden off of them and empower them to work more effectively by creating open communication and a single source of truth when it comes to ticketing and ad-hoc requests. Allowing your team to do what they do best, like what pressure does, you don't need your team being overwhelmed with stuff which is...
00:15:30
Speaker
They need to do, but you have removed the blockers for them to be able to do it. Totally agreed. Perfect. And I suppose on that you have these different roles, your data analysts. There are so many roles within the data space. What's your advice for someone who is looking to choose to focus in on one? And do you think that is the best approach to focus in on a specific role?
00:15:53
Speaker
It's hard because it really depends on your end goal. But generally speaking, you need to stand out. And you do this by specializing and also realizing what you're good at. So you need to focus on your strengths and your weaknesses, like we mentioned before. And I guess a good story for this is when I was working at Deliveroo, I really wanted to be a data scientist. Because it was like the new shiny thing. You're doing all these machine learning algorithms. It sounds super cool.
00:16:23
Speaker
And then I was quickly thinking, I see all of these new graduates come out with their master's degrees, and data science, with their stats degree, with amazing skills in Python. And then I paired up to myself, and I was like, yeah, that's not me. How do I compete with these guys? And the thing that I had compared to them
00:16:45
Speaker
was that I was very good commercially. I knew exactly what the business needed. I knew what investors wanted. I knew how to actually get to that strategy. I knew how to pull my data and actually do the whole thing. I was good with stakeholders. And if I compare that, if I went, actually, if I thought about going down the data science route using those set of skills, yeah, I probably could have done well, but probably not as well as thinking now. So focus on your strengths, guys. It's so, so important.
00:17:10
Speaker
Yeah. Now it's a running theme and it makes sense, doesn't it? Play to your strengths and excel in them and upskill in your weaknesses where possible. So exactly. Or you just hire for the right people to cover those weaknesses. Yes. Yeah. Well, that's what a strong leader does, right? Find someone when you can't do something, you find someone who can.
00:17:28
Speaker
Exactly. And remove blockers in their way to enable them. Exactly that.
Early Career Mistakes and Advice
00:17:34
Speaker
So I suppose on that it's really been really interesting for you as a leader, what mistakes do you see professionals make in their early career or as they progress and what advice do you have for them? Let me bring you back to delivery once again because that's where I started and like I said I made a lot of mistakes and one of them was very early on I was focusing on hard skills
00:17:54
Speaker
all the time that I need to learn this language, I need to be the best at SQL, I need to be the best at Python, right? I need to be the best at making these dashboards or the best at geospatial analysis. And yeah, great, it got me to like a senior analyst, but then I found it really hard to move faster, right? And that only changed when I moved into corporate strategy to lead the day-to-day diligence with fundraising. And then I realized that hard skills are great, but what makes teams work is the ability to work with people across the board.
00:18:24
Speaker
And then I guess the other thing which is really important for me is not trying too much at once. And I have a caveat here. So I would try to do as much as possible when you're a very junior and an entry role. Do as many projects as you can, really understand what it is that drives you, what you're passionate about, what you like doing. And I guess that's the whole point of being in a startup, you get to wear loads of different hats. But as you grow more mature,
00:18:52
Speaker
and you grow in your career, you're ready to focus on what you'll get out. So what we said before, always focus on your strengths. Everyone's going to have their inherent weaknesses. You can round yourself off if you want, but without focusing on your strengths, you're never going to differentiate yourself from everyone else. And that's related again to that business awareness, which is obviously so
00:19:12
Speaker
So tuned with what data teams need, I think, particularly now in what's happened over the last six, nine, 12 months with the scrutiny on data teams with the economic situation. There's a lot of data teams that are trying to really try and prove their value within the ecosystem. So that realignment of business and commercial awareness is so important, I think, for no matter where you are within data, whether you're an analyst or a platform data engineer, I still think you need that domain knowledge. Exactly.
00:19:39
Speaker
Because what's more interesting is that analytics don't really have the KPIs. They're very linked to business KPIs. Honestly, how do you show that your teams help to drive 56% growth? It's by working with these other teams across the business, and they need to help push and promote you with the analysis that you've done. That's the important thing.
Aligning Analytics to Business Strategy
00:20:00
Speaker
Yeah.
00:20:01
Speaker
You know, it's all great us saying you need to have commercial awareness. You need to think about the business. But what's your advice for practitioners and leaders to actually gain that and to actually gain that experience and that awareness? Because it's easier said, maybe harder to execute. That's so true. Understanding is very important. Understanding before you make any decisions as a company, the people, the business strategy, different projects you're working on,
00:20:29
Speaker
the different relationships around the business, what's important, what's not important, what's been done. Like without understanding the whole scope of things, it's very hard for you to make the right decisions. But also you just come across as a bit of a dick, right? You come in like hell and make all these changes, but you don't even understand what's been changed and what's important.
00:20:47
Speaker
and you lose trust. And then the second most important thing then is like how do you work alongside different teams to actually build this analytics roadmap once you understood what's important in that company, right? Understood the capacity that you have because again you don't want to overwork your team.
00:21:04
Speaker
And then the last one is like, how do you start thinking about refining these projects once they've been launched, right? Does the scope change a little bit? Do we care about this anymore? Does it still align with the business strategy? If it doesn't, we've got to fix and change it, right? Yes, you have got to be a little bit like agile or flexible with these things. And sometimes you work on something for a month and it doesn't turn out to be as important as it once was. That's fine, right? We just need to make sure we don't make that same mistake again and actually understand, OK, what do we work on next, which is important.
00:21:33
Speaker
And I think from this, then you can get that alignment between business teams and data teams, because everyone understands what that one goal is, what that one vision is, and how to get there. Yes, it's about constant alignment, constant communication, understanding their pain points, and making their problems your problems, and you're giving them solutions. Exactly. And it's what we try to do in our industry in recruitment as well, understand your pain points and provide a solution. Exactly. So it's all about asking a question, you know? Yes.
00:22:02
Speaker
Yeah, the right questions, pull out the right answers, and then you can all be aligned on. And everyone's on the same road and the same journey rather than you just saying, this is what we're doing. Exactly. You're coming along for the ride, and then they're not. Whenever you tell someone to do something, they're always a bit more hesitant. It needs to be them driving it. Exactly. It's like when you're choosing a BI tool, right? You don't want to choose one that you've used before.
00:22:26
Speaker
only because you're real familiar with it. You need to think about from the business perspective, what do they need, right? And also how data literate are they? Because that completely dictates what to eat for. Yeah, yeah, that's brings us on nicely to our next question.
Technology Stack and Data Culture at Fresher
00:22:43
Speaker
Actually, tech is obviously a huge enabler. And it's so important to marry your technology with the culture and the DNA of your organization. So
00:22:52
Speaker
What is the fresher tech stack and how do you maximise the most out of the tech and the potential that it has? So we use Netblade dbt5 from Prefect. Right, it's similar to the reigning stack. We still use Periscope and that was a relic of the past, let's say, and that's something we aim to look at renewing and changing. What I find is really important
00:23:15
Speaker
to, you know, one maximize its potential across the business is actually to make sure that there is a data-driven culture, right? Because without a data-driven culture, then at the end of the day, what you're making doesn't reflect on that as actual usage or as actual benefits to the white team, right? I guess our fresh
00:23:35
Speaker
pretty lucky with a data-driven culture because it was already there, right, when I joined. But also, reporting into the CEO who loves data as well definitely helps, right? It helps push four different initiatives really quickly, whereas sometimes it would be hard to push through either a CTO or a CFO or a CEO, right? Or even a CPO, which is a bit strange, finally to suit.
00:23:59
Speaker
Important too, but sometimes it is like that. And what this means is that reporting to your CEO and also having a strong data-driven culture ready means that I didn't actually have to push to enable this. But now I have the responsibility of like nurturing, growing it. And honestly, I guess it's very similar to growing a data-driven culture, right? And you do this by giving people the skills and tools to use data easily.
00:24:26
Speaker
So firstly, like I mentioned just now, you need to assess the data literacy of the team. Do they understand how to pull their own data? Do they know how to use Excel or even analyze their own data? If not, I would typically think about Excel training classes, SQL classes, or even like data case studies to help them understand how to look at data. And then from there, it's all about giving stakeholders the correct tools to self-serve their own data. This typically means like a curated data map for each team, which we can train them how to use.
00:24:56
Speaker
but also work to them on how to curate this. So what types of granularity do you want? What data points do you want? What columns do you want to look at? What columns do you have to hide from specific team members? All that we should be doing alongside the different verticals. And then on top of that, they should be a very easy to use BI tool. I've seen some BI tools, I won't name who, but they're very hard to pick up. And the retention rate on them is just super, super low. That's something you don't want. You want something which is very easy for everyone to pick up.
00:25:26
Speaker
and answers straight away. Otherwise it means more ad hoc work for you. And I guess, yeah, that's my few cents on this. Yeah, no, that's really interesting. I think it's so important to have that ease of use on the front end. I think there's lots of talk of the future of BI with AI and natural language. I think that seems to be a really strong use case if you can have business users
00:25:48
Speaker
able to have natural language, ask natural language questions and get data and analytics back is definitely seems like the most easy to use solution for the future. Exactly. And imagine your stakeholders saying, Hey, I want the sales for Manhattan in the last three years, split by month, right? Compared to them writing now in SQL, it's a lot easier, right? You're kind of enabling them, but you just have to train them to make sure they're looking at the right data sets. Because otherwise what could happen is that different people can bring different numbers to a meeting and that's something you don't.
00:26:18
Speaker
Then you lose all that trust and that data culture starts to crumble a little bit. Exactly. Okay, well that's great. That brings us I suppose near the end and to the final question we have a quick fire round which we've asked all the guests and I suppose the first question is quite relevant to you because you're quite new to Fresher. So the first question is how do you assess a job opportunity and how do you know it's the right move in your career?
00:26:44
Speaker
Good question. A few things. So I guess the first one is, if you join a startup, you need to understand the equity. Is it going to give you a good enough, let's say, bonus when they do eventually IPO, or if they're IPO, and they have to calculate and understand one, the business model, second, the growth, third is the profitability, and then the potential payout at the end.
00:27:08
Speaker
Because joining a startup is kind of like getting shares, but you just pick the right one. You're spending four years of your life to get fully vested. And if you don't pick the right one and they never IPO, you just waste those four years. That potential money is zero. So something to look into. And then on the personal side for me is, am I going to find a place which always pushes me and always pushes me to learn more? And then last year's, do I like the team?
00:27:36
Speaker
and do I like my manager, right? Are they going to get me to that next level or am I going to be stagnant?
00:27:43
Speaker
Yeah, makes perfect sense. You know, that's one of the big drivers of a staff staff is the equity. And I think given recent situations, profitability and making sure that there's a clear roadmap for the future is so important. And I suppose the last point is all about culture, right? You have to enjoy the people you're working with and hopefully they're the ones pushing you and you're not just another cog in a machine, which can exactly where you can stagnate. Exactly. And it's always nice to be able to make changes when you want to.
00:28:12
Speaker
If you're in a place where it's very bureaucratic and things are moving very slow, I mean, it might work for some people, but for me, it just doesn't excite me, right? I want to be able to make these big changes. I want to be able to hire who I want. I want to be able to use data to help people around the company. And without all these things, I think it's very hard. Yeah, freedom is definitely a massive part and something people should look for when making their choice to the next world.
00:28:36
Speaker
So I suppose that links nicely to the next question. What's your best piece of advice for people in an interview you've obviously recently been interviewing, I imagine, and I imagine you've interviewed quite a few people over your time.
Interview Tips and Authenticity
00:28:46
Speaker
Wow, quite a few. I built a whole data team out of reef technology from zero to 26, without any recruiters, because we're into the same bit of life. So you can imagine how much time went into that, right? Yes. And I guess,
00:28:59
Speaker
There's advice for interviewer and an interviewee. Let's start with interviewee. And honestly, just be yourself. Because at the end of the day, an interviewer is a two-way thing. You need to sell yourself, sure, but they also need to sell their company to you, right? And then for the interviewers, just be nice. You need to create a setting where the interviewee feels comfortable and can open up. And please, for the love of God, don't go over the usual boring interview questions like,
00:29:29
Speaker
tell me about your time in X or tell me about your three biggest strengths, all of that stuff, right? You want to make it as engaging as possible and not rehearse because they're very easy to rehearse and you don't get to know the person. Yeah, I know it makes perfect sense. I think that being yourself is so important and you should tap into the things you're passionate about, really talk about them in detail. Just on you hiring with no recruiters, you clearly probably spent quite a lot of time interviewing
00:29:55
Speaker
Do you ever think about the cost it takes of interviewing that many people? Because I know that's something that some companies really have strain on, right? If you're interviewing X amount of people who aren't qualified, that's a lot of cost of your time as a data team. Is that something you often consider? That's something I definitely consider. But getting the buy-in from the wider company typically is quite hard, right? Final question. If you could recommend one resource to the audience to help them upskill, what would it be?
00:30:25
Speaker
Okay, so the thing that I recommend everyone up skills, not only in data is selling. And I feel that as the most valuable skill anyone can have.
Recommended Reading: Selling Skills
00:30:34
Speaker
Like I said, not only in analytics, but in life. And recently, I think two years ago, I read this book called Never Split the Difference. And I've always recommended it to anyone who wants to succeed in the world, in the business world, I should say. It's written by an ex-FBI negotiator. Chris Voss. Correct. And Chris covers the communication skills he's used to save many people from very dangerous situations. It's such a good read.
00:30:59
Speaker
Yeah, I've read the book as well. It's great. It's incredibly insightful. And it just talks about how every interaction you have, it can be in a negotiation. Exactly. And trying to change someone's mind or just help them see it from your side or your point of view, which is so important. Exactly. And also the way that you speak, your pitch, your tone, your speed, your cadence, but also the language that you use, like using little butts is not good.
00:31:27
Speaker
It doesn't feel like a big change, and it feels quite strange at the start. And honestly, it really works. Yeah, no, I couldn't agree more. And definitely something in data, you're trying to change people's minds. You're trying to keep them inside, trying to show them what the data is saying. So yeah, the ability to sell that and sell the value, especially to people that might understand and be as data literate, is so important. So I think that's an excellent resource to look at. 100%. There's actually another really good book by Bob Iger.
00:31:56
Speaker
who was the ex-CEO of Disney, but now the CEO of Disney again. He wrote a book called Ride Over Lifetime. It's just incredible. The stuff that a guy has done, the teams that he has built, the achievements he's done. Absolutely incredible.
00:32:11
Speaker
I'll be sure to add that one to my list. And that brings us to the end of the show. Thank you so much for your time, Leon. It's been an absolute pleasure. And yeah, hopefully people will enjoy everything. They're going to enjoy hearing your approach. And yeah, hope you will speak to Ken soon. Thanks, Harry. Speak to you soon. Bye, guys. Bye.
00:32:30
Speaker
Well, that's it for this week. Thank you so, so much for tuning in. I really hope you've learned something. I know I have. The Stack podcast aims to share real journeys and lessons that empower you and the entire community. Together, we aim to unlock new perspectives and overcome challenges in the ever evolving landscape of modern data.
00:32:51
Speaker
Today's episode was brought to you by Cognify, the recruitment partner for modern data teams. If you've enjoyed today's episode, hit that follow button to stay updated with our latest releases. More importantly, if you believe this episode could benefit someone you know, please share it with them. We're always on the lookout for new guests who have inspiring stories and valuable lessons to share with our community. If you or someone you know fits that pill, please don't hesitate to reach out.
00:33:18
Speaker
I've been Harry Gollop from Cognify, your host and guide on this data-driven journey. Until next time, over and out.