“As a middle aged Englishman, by definition, I know nothing about fashion or beauty.” So says Tim Carmichael, Chief Data Officer for Chalhoub Group, a luxury retailer in the Middle East and Gulf Region. In this episode, you will hear from a leader who brings everyone to the table and serves his team and organization with great humility and grace, leaning on his experience in the public and private sector and notably as an officer of the British Army. Tim and Jesse delve deep and talk about having a talented team, managing data, and handling a few of life’s personal challenges.
Welcome to the Soda Podcast. We're talking about the Data Dream Team with Jesse Anderson. There's a new approach needed to align how the organization, the team, the people are structured and organized around data. New roles, shifted accountability, breaking silos, and forging new channels of collaboration. The lineup of guests is fantastic. We're excited for everyone to listen, learn, and like. Without further ado, here's your host, Jesse Anderson.
Hello, and welcome to the Data Dream Team podcast. My name is Jesse Anderson, and welcome to our first guest of season two. We have Tim Carmichael with us. He is the CDO at the Chalhoub Group. Tim, would you mind introducing yourself a little bit more?
I'd be delighted, Jesse. Thanks very much for having me on the podcast. As you've said, I'm Tim Carmichael. I'm the chief data officer at Chalhoub Group, which is a leader in luxury retail in the Gulf region and the wider Middle East and an area that was completely new to me when I came to this organization.
As a middle aged Englishman, by definition, I know nothing about fashion or beauty. And so the good news was, I've been employed for what I do know about: data. And that's what I do at the moment. In terms of background, it's my third attempt at being a chief data officer or chief analytics officer. And my previous experience has been in the public sector and in the private sector.
So, Tim is being very shy right now. He's actually dressed like Elton John. You may not see it if you're just listening, but Elton John would be jealous right now of the outfit that Tim is wearing. I mean, it's just blinking. I'm having a hard time looking at him right now. Thank you, Tim, so much. Thank you for coming. Before moving to Chalhoub, you were in the British military. And I find the military very interesting, because you're very results oriented and very mission focused, and I find that that helps with working in IT. Do you find that as well?
Yes, certainly. I had a really enriching and challenging career as an officer in the British army, which kept me going and kept me interested and motivated for quite a long time. But, towards the end of that career, I ended up as the British army's first chief data officer.
And the idea behind that was a one line remit from the head of the army, who said, "Tim, I want you to enable data driven decisions, because we're really good at judgment decisions and experiential decisions, but not necessarily at consulting the data beforehand." And I thought that was really quite a humble insight from the leader of an organization that likes to be good at a lot of things. So I enjoyed being its first chief data officer and setting that up from scratch, but in doing so, I was leaning on a range of experiences that I built up over the years, where I basically flipped between more technologically driven roles and operationally driven roles and bounced between the two.
So by the time I got to that stage where it was something I could take on board as a responsibility, I was probably best placed to have that conversation that allows a meaningful conversation between technologists and what we now call the business side but at that stage, I guess would've felt like the operational sharper end of the army. And I think that's how I got going in this role.
That's interesting. So would you tell me more about how you staff that? Because I think you're probably the first public servant I've been able to talk to about this who can actually talk about it.
I'm entirely happy to talk about it, and there are no state secrets at stake here. So if you think of any military in a professional military, essentially, they're happily schizophrenic. On one side of the coin, you have an organization of the kind of the images you'll see on TV and on news and on film, of men and women in camouflage pajamas, running around with rifles and weapons and doing what only professional soldiers can do, which is a very tactical way of fighting. And that's, of course, quite an extreme lifestyle.
But on the other side, it's still a corporate existence. You can think of the British army as a $15 billion a year, corporate global non-for-profit and therefore has to have all of the governance you'd expect in place and then some more. Because of course, it's spending taxpayers money, and therefore to make sure there is as little wastage of that money as possible is very much part of the remit. And therefore the linkage to business is quite close. Now how we staffed it, to finish my answer, is essentially a threefold mix of military personnel, of civil servants - so permanent employees of the ministry of defense - and of contractors to fill in some of the skills gaps that weren't able to be filled at that time by our sort of organic workforce.
And what was the breakdown approximately, percentage wise?
Well, I would say about 50% military, about 30% civil service, and about 20% contractors. And the contractors were people who allowed that endeavor at that time to get going and generate momentum whilst we grew skills in the background, because I'm sure as you appreciate, some of the specialist skills associated particularly with data engineering, data science, and to a certain extent, the art of data visualization were in rarer supply.
And there's a rather unique character about the military, which is that they grow their own. So they don't buy in capability or skills sideways. They grow it from the most junior soldier up through the ranks, and therefore, if you don't have the foresight to recruit those skill sets, it takes a generation to develop them. You can't just buy them in laterally like you would in a commercial endeavor.
And in a similar question, what was your breakdown of data engineers, data scientists, percentage wise?
It was many more engineers than scientists, essentially. And I relied on some really close colleagues in the IT setup to help us with that data engineering and software engineering approach.
What did you carry over from your military experience, and what did you leave behind?
I left behind as many of the stereotypes as I could. I didn't really subscribe to them anyway when I was there. So occasionally, I'll meet people who think that you are an army officer, therefore you made a living by shouting orders and telling people what to do. And that was rarely my style anyway. And it's certainly not a style that will translate into any other meaningful endeavor outside the very rare occasions where an order is the right thing to do. So I certainly left that behind, or any vestiges of that behind.
What I took with me is the idea of service to others. And I don't mean that in some sort of holier than thou altruistic way, I mean that that's the best way to get the best out of other people. To set them up for success and to do all I can to make other people as good as they can be, and to bring together the component parts of a jigsaw team with multiple skills and to bring that together into a cohesive whole greater than the sum of its parts.
So now let's go to your next position. Could you tell us more about this business?
Yeah, so my current role in Chalhoub Group is to run its data endeavor but the Chalhoub Group is a family business that started in the 1960s with an amazing husband and wife team from Syria. And they progressed a business, literally starting selling out of a suitcase, but with a taste for selling into the luxury market, which was growing at the time.
And through a series of migrations via Lebanon, Kuwait, and then into Dubai, and you can imagine the kind of historic events that forced them away from Lebanon, forced them out of Kuwait. The family showed amazing resilience and landed in Dubai some time ago, at a time when Dubai is not the metropolis it is now, and so made a big bet on the future of that emirate in particular but also all of the UAE and the Gulf region as being the region they wanted to market to. Because there's a hunger for luxury items, and Chalhoub Group sells beauty and fashion items.
So, items around makeup, around face care, around clothing that you can only imagine that some people would want. Dresses, shoes, and so on. And I think the way I would define it, at its heart, the definition of luxury of course, is something you don't necessarily need but you really want. And that's the itch that Chalhoub Group tries to scratch in a way that really delights our customers.
That's interesting. I think when we first talked about it, I said, the next time they move, tell me, so that I know not to go there.
Come to Dubai, my friend. It's great.
I do want to, so that actually reminds me, if we have any listers in Dubai, I actually want to go. That is on my list. Please invite me in some fashion. So let's talk about your journey there. Could you talk about where you are and where you want to go data wise for Chalhoub?
I was one of the luckiest men alive, because I got to take over a going concern set up by the amazing Ryan den Rooijen. And for those of your listeners who have come across Ryan, he has a heritage in Google and Dyson, and he came as the single person data team towards the end of 2019. And he set up a team, and he set up the backbone of the team and of the data platform that we use, of our big data platform. And then about a year later, he invited me to join him, shortly after which he transitioned across to leading our e-commerce endeavor inside Chalhoub.
So Chalhoub has an ambition, which it's already realizing, to be a genuine hybrid retailer. Both bricks and mortar retail, but also online, web, and app retail. So the idea is, we delight our customers wherever we find them. And therefore, I inherited that and got to take over from Ryan as the CDO.
So I inherited something that was already up and running, and whilst not a hundred percent fit for purpose, certainly good enough to be getting going in the early use cases, around understanding our customer's behaviors and understanding how we link our customer understanding to those transactions, the orders that those customers make. A key linkage. And also understanding all the detailed data about our stock, where it is, and where it is throughout the supply chain. Those were two big pain points that the company was quite blind to before, as it started out in its data journey.
And now we've expanded into data that covers the whole breadth of a modern business that you would expect to see. So data associated with our customers, as I've said, with our upstream supply chain - so demand planning, and ordering, and dealing with our suppliers and our franchisees - but also downstream, whether it's a distribution model or a direct to customer model. So we're talking about the fulfillment in warehouses or in stores and the downstream supply chain, the last mile delivery to customers, so that we provide them with the goods that they've asked for as promptly as we can, given the logistics of the area. Plus of course, all that finger on the pulse analytics, as I would call it, of understanding sales and understanding gross margin and sell-through and markdown rates and all of the other really important business metrics that are the beating heart of the business.
And where are you on your journey to AI and ML?
We're at a very early stage of maturity, and I'm entirely unashamed about that. I find AI is used as a bit of a buzzword, and for me personally, I set the bar of artificial intelligence quite high. It has to be intelligent to qualify as artificial intelligence, not just, shall we say, a bunch of nested IF statements in a spreadsheet, which can happen. And people say, hey, I do AI. Not really. And so for us, we're nowhere near AI, and that's fine for the moment.
Now, there are accelerants that we're trying to put in place associated with the use cases that can be satisfied through machine learning, and the ones that are fairly obvious are the ability to forecast with confidence, to predict what's likely to happen next, to recommend great products to our customers in a way that makes them feel if not personalized then much more relevant to them on a journey towards personalization, and to really sort the attribution of all of the moving parts of the business and how they contribute to business success. None of those can be solved in a simple fashion, and those are our early machine learning use cases.
I appreciate you being unashamed, I think is the word that is used, about not having AI. I think that more companies, even companies that are saying that they're AI driven, are actually not. And it's a lot of buzzwords, unfortunately. So going a little bit technical, tell me more about the technologies that you're using or trying to move off of.
We are a happy user of the Google stack. So we use Google cloud platform and Google BigQuery as our data warehouse. And on top of that, to be able to harness that data and surface it as products to our user community and our stakeholder community, we use Looker, which as you'll know, was not so long ago bought into the Google stable as their analytics tool.
And I think there are three really quite important strengths to that. So the first one is that you ingest multiple source data into a big data platform. And the legacy landscape was all of a single system with a single purpose. So our CRM system, for instance, or our sales system or our warehouse management system were all silos. And the idea of course, by using a big data platform is you can ingest those as multi-source data and integrate them all into one place. That's the first significant advantage, because then you get to see some lateral insights that wouldn't show up with siloed approaches.
The second one is you can set this up to work in an automated way. And I think we all know the fairly standard productivity use case when someone says, "Hey, it takes me four days to produce the weekly report, and it's painful, and I make mistakes every week and I try to cover them up or I try to address them, but it's hard" or even worse, I worked in an organization once that took nine days to produce the weekly report, go figure. Well, of course, now it's one touch, wait 10 seconds, there's your answer. And so there's a huge productivity gain for those people who were previously trapped and handcuffed in the churn of dealing with routine reporting. And now they can deal with what that reporting tells them, so it takes them much further forward in their insights. That's the second advantage, automation.
And the third advantage is that the whole process is set up to default for self-service. Now, actually, this has proven our biggest challenge, because the culture of the business was one where analysts did the analysis and would explain to business leaders. And now what we're inviting business leaders to do is to change their reflexes and have a different approach to self-serving on their own data and on their own insights that come from that data, so they can make better decisions in a more prompt way and therefore drive value. So for me, those are the three significant advantages of doing it this way. There's integration, automation, and self-service baked into our approach.
One thing I really like about you, Tim, and I think you can even hear it just even the podcast listener so far, is the humility you have around this. For example, when you were saying, "I don't bark orders," you could have barked orders when you were in the military. You didn't need to. You didn't feel that need. So you also talked about the need to recognize help in getting the team set up. Where did you go for that help?
I rely on a lot of other people in our wider ecosystem, not just the people inside my team. So when you're looking at setting up a team, of course, we have a really capable in-house talent acquisition organization who put their feelers out into the local, indeed, the global market to look for a rare talent. And I'm sure it won't need me to explain to any of your listeners quite how challenging it is to find really skilled practitioners. But it's one of the areas where we laid down a red line where we said we won't compromise on talent. We won't compromise on the real skill sets of our people, because we are on a voyage of transformation, and you can't have people who are just good at one thing to help you there.
You've gotta have people who also have the imagination and the willingness to learn and develop, to learn new things as they go. And therefore, you can't compromise on the talent. And I'm really fortunate that the talent acquisition team has helped us. I also rely on some of my colleagues around us to do that kind of coarse filtering that takes a long list down to a short list where we can really focus on making sure that if we recruit a certain individual, we would be doing so to set them up for success. We wouldn't be doing so to set them and therefore the business up for failure, because that's in no one's interest.
And what I'm really pleased about is the survival rate, if you like, and indeed, the thriving rate beyond a short probation period that we have in this organization, in the data team, precisely because of the due diligence we do in that selection process. It doesn't mean it's perfect every time, but it does mean that we get more hits than we do misses, and that's thanks to the help I can get from the wider talent acquisition team in setting up the team. And we're still growing.
Good. One thing I was surprised about is that you aren't outsourcing. Is that something that you took from your time in the army, to not outsource anymore? Or why did you make that choice?
No, I don't think it's a military choice, but it was certainly a deliberate choice. And that deliberate choice was one about owning our own intellectual property. We are firmly of the belief, and it's at the heart of our data strategy for the next three years, that you have to own your own intellectual property and be a master of that or a mistress of that, so that you can generate competitive advantage from that.
Now, what do I mean by intellectual property in a data sense? What I mean is, at every point from the point of ingestion or creation of data, to the point of consumption or destruction or disposal of data, we should be able to lift the lid on that pathway across all those transformations and understand exactly and intimately what's going on. Why? Because we created it. I say "we" - clearly, it's hugely talented people in my team who are doing that creation, and I'm really grateful for it, because if it was just me, it would be a disaster. But the point is, it's not a contractor or a consultant who came in for six months or a year, set it up, and then departed with a few residual notes left behind of how this works that then atrophies over time. So the initial setup and creation, the design, develop, and delivery of those data pipelines, and the products that come out of them. And then all the evolution as we respond to the needs and anticipate the new needs of the business, that's all done by us, created by us, and delivered by us. And I think that gives us a huge advantage, because we are never at a loss as to what's going on.
It's tough sometimes. And one would argue that it might be cheaper to do that elsewhere, but we've taken a deliberate decision that we want to own that intellectual property. And the second part of the decision is a really important part. We like everyone who's playing in this space to be vested in its success. And when you are an employer of the Chalhoub Group, you're a member of the wider Chalhoub family, and you subscribe to the success of the group and it's constituent parts. And I think people are more motivated to do that if they know that they're employed in that space and it's up to them to make it successful.
All right. If there was a better advertisement for going and working at the Chalhoub Group, I haven't heard one. So those of you listening, tell us, what open positions do you have? What are you looking for in people?
We are currently recruiting. We are hiring, as they say on LinkedIn. And we're looking for really capable data scientists, which is a new endeavor for us - proper data scientists, as opposed to people who also have data science in their background, knowledge, or skills. We are for data engineers, both pure-play, let's say, data engineers, but also platform engineers and software engineers.
We're also looking for people who can help with the products that we provide in terms of product management. And people who can help at the coalface of where we interact with the business, more on the analyst side and on the creation side, because we want to act as an accelerant for our business partners and our stakeholders. And therefore, sometimes, we do the heavy lifting of creating that basic lifeblood of information flow for them through reporting and dashboarding. And then we take them further in the maturity of their data journey.
So, we are recruiting skills across the whole spectrum of data skills you would expect to see. What we're not yet recruiting is people who design artificial intelligence, because I don't have a use case that's compelling enough for it. That'll come in time, but not yet.
What is your breakdown percentage wise of data engineers, data scientists, software engineers?
We have a team at the moment that is about 35 strong. It changes frequently on an upward curve, so today's figure is 35. Next week's figure could be higher. We have about 50% of that endeavor doing the heavy lifting backstage, if you like. So doing data engineering and platform engineering.
We have a single software engineer at the moment who is satisfying an approach for designing APIs, for instance. We have a single data scientist who is a hugely talented colleague called Loveleen with a PhD in data science. And she has waited very patiently for us to get to the point where we're ready to use her skills. And until then, she's been doing some excellent work elsewhere in the data quality space.
I have some really talented people who do data product design and development and offer what's termed in Looker as explorations for the business to use so they can harness their data. So it's about 50% heavy engineering work in the background, working the pipelines and designing the models, and about 50% delivering the products and then surfacing them and engaging them with the business.
And if I could amplify what Tim just said for the listeners, your data scientists, if they're waiting in the wings like that, they're being very patient. And you should thank them. Because oftentimes, data scientists will leave after six months if they're patiently waiting for that data. You mentioned that talent market, and how tough is it to recruit right now in Dubai?
Well, Dubai's always a challenge, because it's an ecosystem of its own, and there's a huge ambition to this city and to this country. It's an ambition I love. I think it's a credit to the emirates, the way that they have come up with a vision and then walked the talk on that vision. But it doesn't mean there's any spare capacity going around. And therefore, we tend to recruit internally where we can, but also we are prepared to reach wider afield.
Chalhoub Group today has 108 different nationalities working for, out of about 12 or 13,000 employees. So I think the diversity of thought of our workforce is really important and a strength, and the data team is a microcosm of that, because we recruit for diversity. And there are a number of ways, of course, one can measure diversity. The most important for me is that people feel empowered to bring their thoughts and their perspectives to the equation when it comes to designing products for our customers and stakeholders.
So you were talking about bringing the people internally. How do you get them up to speed and upskill them so that they could be part of your data team?
Well, it's not as simple as just internal. I'll try and break it down a little. So we have a central data team with these skilled specialists that I've described already, and then out embedded in the business in the various business units and the various business functions, there are also data analysts serving that business who have a level of detailed, contextual knowledge about that business area that is really important to that business area and are able to harness the data products that we surface for the benefit of the business. And to be the champions of self-service, so it's kind of three levels of literacy, if you like. The central team, the business analysts, and then the non-specialist users and consumers of data.
And for all of those, we are on a journey of upskilling in terms of data literacy and data awareness. And creating a community amongst those analysts is one of our initiatives for this year, for instance. But our recruitment casts wider, and our presence is also wider than just Dubai. I have a really talented, small but growing talented offshore team in Thailand who we employ at the moment, because there are plenty of skill sets there to be attracted to the company. And in terms of gender diversity, there's an equal balance, which is rare in other communities, between and female people in data engineering, particularly. And we value that diversity and what it brings for us.
That's interesting. I think you're the first person I've talked to who is outsourcing to Thailand. How is that going? Is that something you'd recommend?
It's going great. I'm not gonna recommend it to anyone else. I'd like to corner the market, please.
Okay. Best kept secret then. Okay.
Promise not to tell anyone.
So all of you listening, forget what Tim just said. We may even have to take that out so that nobody else knows. You mentioned a bit about servant leadership. Would you mind defining that for our listeners?
I'll do my best. It's quite ephemeral. Servant leadership is where others matter more than the individual, and certainly matters more than the individual's ego. So for me, the definition of servant leadership is the default setting where I am there to serve my team and set them up for success, rather than have the team report to me in a more traditional line management structure. And yes, of course, line management still exists, but the whole focus of the leadership within the data team and elsewhere across the whole of Chalhoub Group is on making sure that we do the best we can for the people who work alongside us and with us and for us, to set them up for success. And that changes the whole perspective then.
It's a bit like the old cliche of taking the wiring diagram and flipping it through 180 degrees, so the leader's at the bottom. But it's a lived version of that, where selflessness matters, and putting yourself out for others matters. Now, it's one of the things that attracted me to Chalhoub Group, because that's very much one of the things that I did try to retain from my military service, because the motto of my alma mater at Sandhurst, at the Royal Military Academy Sandhurst, is, "Serve to lead." And that's something that is in my DNA now, if one can assume things into one's DNA.
And so I do my best every day to be an effective leader for the benefit of others and not for my own benefit. That will come as a byproduct of that, and that's fine, but it's important to me that no one feels left out or dropped by the wayside because of one of my many failings. And therefore my role is to help people be the best they can and bring the best they can to work.
That's inspiring. And so who inspired you to do that? You mentioned the military, but who inspired the Chalhoub Group to do this?
Well, there are several people in Chalhoub Group who came up with this, but primarily, let's be really clear. Patrick Chalhoub, the leader of our organization and the chief executive, is the one who has championed this from the outset, because he has people at heart in his organization. Customers and his own employees. And that is a lived behavior, not just a corporate logo on the wall. Now he brought in some very talented people to help him on that journey, and I would call out Lou Clarke, who's one of my colleagues in our People & Culture department who is leading and championing the cultural change that comes with a switch to servant leadership.
Because of course, with 108 different nationalities and that many different cultural backgrounds, it's not apparent if you haven't experienced it before, what good servant leadership looks and feels like. So there's a deliberate transformational change program that's underway in the group about educating around that and deliberately taking the time to educate people. What does it look and feel like, servant leadership? Why is there a benefit to it? What is the business benefit to be had? And what are the behaviors and values that we espouse that can be demonstrated through servant leadership? And so, what does good look like when you see it? And what does not quite good enough look like, so you can aspire to be good enough? And I think Lou and her team have done an amazing job in putting together a meaningful package and then insisting on the accountability that goes with that. I think that's the crucial, additional step beyond just education and learning.
And now, applying that to data teams, what is the one thing that you've seen be really interesting as applied to data teams with servant leadership?
I think the phrase I would use is empowerment. And ironically, as someone who sees himself as a servant leader, I was corrected earlier this week, quite rightly, by one of my colleagues who pointed out that we weren't empowering enough of the team to have a voice enough of the time. And I take that really seriously, because I can sit here in my ivory tower and believe I'm getting it all right, but what I felt really encouraged by that is that that individual - and I'll name her, she's my colleague, Carli, and she's an amazing professional - but she felt confident enough or to have the remit to come and speak to me and say, hey, Tim, there's a problem here, and I think we need to fix it, and I think you are part of the solution in fixing it, and I'd like your help, please. And she didn't feel that she couldn't have that very frank conversation.
We welcome feedback as part of our culture, in the team and in wider Chalhoub, and she chose to give me some feedback, which was, I found, super useful and I need to enact. So, empowerment is one of the facets of servant leadership, where you empower people to have an opinion and to be as good as they can be. And my colleague and friend Carli used that on me just this week. And I'm grateful for it.
That's living it. Let's switch up a little bit. It's somewhat related, but you are obviously from England, and you're living in Dubai. What is it like living and working internationally?
Well, living and working internationally is something I've done throughout my professional life. My first existence living in another country was when I was still 19 and I lived in Germany. Actually, it was West Germany then, which tells you how old I am. Before Germany, reunified. I've also lived in other parts of Europe, in France, in Belgium, and for periods of time in perhaps less hospitable or welcoming parts of the world, for obvious reasons. And I won't dwell on that.
So living in another country is something I always enjoy, because it brings a cosmopolitan and a more eclectic mix to life than living in just one society. Much as I love and appreciate my home country, there are other things on offer in the world, and I've really enjoyed experiencing them. Dubai itself, there's only one word for it. It's bonkers! I love Dubai. There is an optimism and an ambition about the place, and it's a city of opportunity. Someone said once, a wise person, I think it was Oscar Wilde, "Whoever's tired of London is tired of life." I think whoever doesn't seize opportunity in Dubai is simply closing their eyes. And for my relatively brief experience here so far, of the last 18 months, I've loved it.
That's awesome. One thing I found interesting, your LinkedIn profile, and I think it's the only time I've ever seen somebody do this, you said, "There are three things I've learned." I wanna go through each one individually. "It's not just about data. It's about culture, too." What do you mean by that?
I think what I mean is, I've learnt to start the conversation not mentioning data. I've learnt to start the conversation by mentioning what are the business challenges an organization faces, and understand by understanding how they're currently dealing with those challenges, where the business unit is in its relative maturity associated with data. And where I'm most effective is in organizations who have a relatively modest level of maturity but aspirations to grow that maturity.
But there is still a cultural change required in that. And cultural change is the hardest change to land, because you're challenging embedded behaviors - not in an aggressive way, but you are asking people to question, ultimately, by adopting data, to deliver insights that drive value. You're asking them to maybe change the way that they have worked before. And in Chalhoub Group, there's a very specific context to that, of course.
There are some really talented business leaders there who are steeped in how fashion and beauty as industries work, and particularly, the luxury end of that. So they will tend to be very creative types and very imaginative types - I don't wish to stereotype - but they're not necessarily, therefore the closest bedfellows of technology or data. But they're certainly not slow to see an opportunity, either. And what I love about therefore that is that you can push at a door that's at least half open, but pushing it all the way open requires cultural change, a change of a willingness to consult the facts, that's data, before making a decision, rather than just going with an experiential or a judgmental decision.
And the next one was, "Keep the message simple and compelling."
And I think by my previous answer, I failed to do that. As a leader in data, I have to also be a communicator. In a previous life, I was an interpreter. I interpreted between French and English, so I know what it's like to be in a room where you have two parties to the conversation who can't speak directly to each other. And therefore, it's really important to enable that conversation. And therefore, keeping the message simple - data’s tough to imagine, so you use analogies and metaphors and help people understand something that otherwise will feel quite nebulous to them.
And the last one was, "Data is most relevant when it is exploited to generate business value."
Yeah. If you can't answer the question, "What's in it for me?” - which, any reasonable business person will ask themselves, "Why should I follow you down this road, Tim?” - if you can't answer that question, then people won't play. And then all that happens is that the data endeavor looks and feels like a big fat cost center, and it will eventually wither on the vine. So data has to be worth its own money. In fact, it has to be a generator of profit and of value and a multiplier of profit and value. Otherwise, there's little point in starting on that endeavor.
Yeah. CDOs, managers listening to this, Tim is exactly right. It will die on the vine. There's a limited time. So, please don't bide your time. Just make sure you're generating that value. Can't echo that enough. So we've talked a lot about teams, but we haven't talked about how your team is laid out. Could you lay out how the team is laid out, and maybe any changes that you'd make to the team, organizationally?
Yes. We've evolved the team into three pillars. The acronym we use is API, sorry. So, A for assets, our data assets, that's our architecture and engineering team. And they do, as I mentioned earlier, the heavy lifting associated with the design of our data ingestion and our extract, transform, load, and the workings and the modeling inside our big data platform, inside Google BigQuery. So that's the architecture and engineering team known as our data assets team.
Then we have the data products team, that's the P. And they take all the potential now surfaced into Looker from the big data platform and turn that into data products. And anybody who understands about Looker, and many of the other analytics tools out there, will understand that you can surface a product that essentially acts as a blank sheet of paper, metaphorically, from which people can draw and design their own business intelligent type insights, in terms of insights through dashboarding and reporting, for instance, at a basic level. And so this data product team surfaces the potential to do that, either for users to be just a consumer, I'll just take that in consumer and not do anything, or for other users to also be creators and designers, and those are called explorers in Looker.
And that's the data product team. So they will surface products around a 360 degree view of our customer. They'll surface products around understanding our last mile performance, for delivery through our third party delivery partners. Products associated with stock and sales, stock coverage, and so forth. And as I've previously described, the whole spectrum of products that you would wish the company to be well sighted on are delivered by that data product team. As part of that data product team, we also have a small and very talented group of onboarders, and a shout out to our three onboarders who take users by the hand and help them with the clockology of the software. And finally in that team is also a team of data quality people who, we are doing our very best to measure and articulate the challenges in data quality, which is inevitable when you take it from any source system that's been around for a while. And here's a vanity stat for you. We run now 288 million automated data quality checks every day. At the start of last year, before we put that team in place, we ran zero automated checks a day.
So that's the P, that's the products team, and then the I is analytics impact. And that's the team that helps land the value of all of that potential in the business. So they will work with the business to understand their business challenges, decrypt those and present them as requirements to the product team to develop products to satisfy those needs, and also act as sparring partners and internal consultants for the business on how they can derive insights that give value to them from our overall platform. So in summary, we've got a team around architecture and engineering, a team around data products, and a team around landing insights for the business. API.
One thing you mentioned was the onboarders. Are they onboarding for technical, or are they onboarding for business, or both?
Both, but the main focus is for business, because as I mentioned earlier, one of the strengths of the approach we are taking and using Looker as our tool is its default setting for self-service. And so if you're asking non-specialists to self-serve on a data tool or on an analytics tool, they really need to know their way around it. And after a little while, it's as intuitive as using a spreadsheet or intuitive as running a PowerPoint deck. But people don't have those reflexes yet, and so we have to help them with that. You can't just throw the tool at them and give them a login and say, "Over to you."
So definitely, the focus is on scaling up the number of subscriptions we have with our business users. But then there's also a special focus on the data analysts who are embedded in the business, in our community of analysts out there in the business, who will have further questions and answers to be had over the best tips and tricks to use. And our onboarders and others help them with that.
That is interesting. I'm gonna have to keep on looking out for that. That's kind of the missing piece with the whole self-service. How do people actually self-serve? We need somebody to help them self-serve and teach them. We need to teach them to fish.
Because if you can't teach them to fish, they're gonna revert to what they were doing before. And the pre-fishing version in data is, I'm gonna go back to my pet spreadsheet, please. And that doesn't feed enough people reliably enough.
Very good. Would you mind sharing the greatest team or story that you've never told?
I'd be delighted to. I have a story about a colleague of mine, and I know, because I've asked him, he won't mind me mentioning his name. His name's Hisham, and Hisham has had problems over the last couple of years with mental health and with a sense of wellbeing. And he's at times struggled with his mental health. And very sadly, last year, Hisham lost his father. And so on top of his challenges with mental health, he was also faced with that body blow of grief when you lose a loved one. And especially there is no shortage of people, of course, recently, who have done so in the pandemic, but when it's your father and you are the son, in this culture, that's such an important relationship.
And that almost knocked Hisham out, but he had the courage to put his hand up and say, I'm struggling here. I'm really struggling here. Not just a bit. Help. And what I was hugely encouraged was the way that the whole team, even people who don't routinely work alongside Hisham, stood up to be counted and said, how can I help? Let me do what you were doing, and I'll pick up that burden. Let me help with this area. Let me make a phone call with you every now and again, just to check how you are. So a range of different helps, which played to people's strengths, whether they were gonna be good to pick up the workload that Hisham had previously had, to give him the breathing space, or to care for Hisham as a fellow colleague and as a human being.
And I found it, I have to say, hugely touching with the way people responded to a very personal crisis there. And of course, that's not a story that's specific to data. It's not a story that's specific to this region or to this company. It's a story that's much more common, I think, than people understand. But what is a measure of success here? I'm gonna put it in Hisham's own words. Hisham said to me recently, "It's still difficult. There are still challenges. But I'm no longer afraid to fall when I know there's a team behind me to catch me." And I think we've taken away the fear element for Hisham. And that makes me just so enthused for the power of humanity and looking after other people. And I think it's important that people acknowledge that it's okay not to be okay. And we have tried in our very modest way to make that part of our culture as a team.
Well, Hisham, if you're listening, there's even more people rooting for you now. And those others of you who are experiencing similar mental health issues, we're rooting for you as well. We will get through this. What do you never compromise on?
Work life balance. And that's a selfish act, and it's a selfish act because I know I get more out of people if I insist that they don't compromise on their work life balance either. It's very easy for anyone to say, work harder, work longer. Clearly, working smarter is the more intelligent thing to do. But also, knowing when to stop. There's the old phrase, "When the work's done, stop." Well, our work is not really ever done, but we should stop anyway.
And one of the things I like to think that I have offered my team on a personal level is, again, that freedom to say, no, I'm taking my time off, and it's my time off. And I'm taking my weekends, the majority of my weekends, and I'm taking my evenings, the majority of my evenings, and they're mine. And that's fine. And that's entirely legitimate. And why do I think that's a selfish act on my part? Because I get more motivated, refreshed people who when they come back from their leave or when they come back from their weekend away, are enthused about their work. And they're not exhausted the whole time.
One of the members who came to our team, and I won't name this individual, came to us at the end of last year from a stint of eight months where he had worked every day for eight months with not a single day off, including weekends. And he was truly exhausted. So the first thing I said to him is, hey, look, the first thing you're gonna do on our dollar is take some leave. Take a break, and we'll get you back when you're refreshed. And that's paid dividends. So work life balance I won't compromise on.
That's amazing. What is something that would surprise everyone that has worked with you in a team?
Oh, I'm a bit of an open book, so I don't suppose there's many surprises left. But maybe I'll talk about imposter syndrome. It's a facet of leadership, and I think that more people who are in a leadership position have it than possibly admit it, but there are still times when I'm waiting for someone to come and tap me on the shoulder and say well done, Tim. It's been a good run, hasn't it? But yeah, we've found you out now. You can go home.
And who knows, maybe that'll happen one day. But, I think, for any leader who has any self-awareness, they'll also be aware of their failings and their weaknesses. I'm not one to over dwell on those. I prefer to play to my strengths, 'cause I have the confidence to believe that my strengths are helpful to the organization and to the people I work with. But still, occasionally, there's that imposter syndrome, and there's a little voice that everyone has inside of their head saying, they're gonna find you out soon. And I just have to acknowledge that that's part of who I am.
I have that imposter syndrome, too. I always thought, I guess, growing up that somebody would dub thee. I dub the CDO. And the queen comes out, and she dubs thee, and then nobody could ever say, oh, Tim, how are you a CDO?
Yeah, you're a fraud.
That doesn't happen. Thank you so much, Tim. I think this has been a really interesting show. I really appreciated how openly you shared. I actually found the Chalhoub Group's ethos and corporate culture to be very interesting, so, definitely something we'll wanna look at. Thank you so much, Tim.
You're welcome. Great to be here.
Another great story, another perspective shared on data, and the tools, technologies, methodologies, and people that use it every day. I loved it. It was informative, refreshing, and just the right dose of inspiration. Remember to check dreamteam.soda.io for additional resources and more great episodes. We’ll meet you back here soon at the Soda Podcast.