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SheCanCode's Spilling The T
SheCanCode's Spilling The T
Data Insights & Agile Innovations at N Brown: A Journey through Analytics and Career Acceleration
Join us on this episode as we dive into the world of data analytics and agile methodologies with Stacey Hudson, Digital Talent Lead, Laura Sealby, Head of Data Analytics, and Stephanie Ramsdale, Senior Data Analyst - all from the N Brown Group.
Listen as they share insights into their journey within the company, from roles at N Brown to specialising in data analytics. Discover how the data team at N Brown operates, including their major achievements this year. We also explore N Brown's adoption of agile methodologies, its impact on work culture, challenges faced, and opportunities for personal growth.
Looking to start or advance your career in data? Our guests offer valuable advice and discuss the essential attributes they seek when hiring data professionals. Whether you're new to the field or looking to take your career to the next level, this episode provides actionable insights and inspiration.
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Hello everyone, thank you for tuning in Again. I am Katie Bateman, the Managing Director Community and Partnerships at SheCanCode, and today we are discussing data insights and agile innovations at the Enbrand Group a journey through analytics and career acceleration. In this episode, we dive into the world of analytics and agile methodologies, and I'm lucky enough to have three incredible women from the Enbrand group with me today. I have Laura Silby, head of Data.
Speaker 1:Analytics, Stephanie Ramsdell, Senior Data Analyst, and Stacey Hudson, Digital Talent Lead. Welcome ladies. Thank you all so much for joining us on Spilling the Tea, Hello.
Speaker 3:Thank you for having us today.
Speaker 1:It's a pleasure to have you all on here. Can we kick off with a bit of background about each of you, please? Just to set the scene for our ladies Stacey, should we go?
Speaker 2:with you? Yeah, of course. So thank you again for having us here. So my role here at M Brown, I am the Digital Talent Lead, so I am part of the people team and I support all of our digital operations. So that includes everything from data technology engineering, um, data science, digital product, ux and everything in between um.
Speaker 2:I've been with the business for seven years. I've supported data for the majority of that time actually, and it's been really great to see the data the group data team evolve over that time. You know we have data analytics, data science, data engineering and data visualization, but it's been really great to see how data is really central to the decision making across the business. It's a real balance of kind of technical and commercial. So certainly from a recruitment perspective, it's really great when we're looking to hire data professionals into the business because we're always looking for that understanding between customer and business values and that balance between the technical and commercial. So really interesting, ever evolving it certainly makes my role really interesting as well. So, yeah, that's just a bit about me well.
Speaker 1:So, yeah, that's, that's just a bit about me. Amazing, and we've got two incredible ladies who work in uh data data analytics um from n brown with us. So, stephanie, can you tell us a little bit about you please, where you're from, how you landed at n brown.
Speaker 4:Yeah, so I'm a senior data analyst here at n brown and I've been with the company for nearly two years now, working predominantly within the brand's team and working with marketing, and I've pretty much always worked in data. So I did maths and sport at uni and took a placement here doing programming and stats, which basically introduced me to the world of analytics. And then, despite not being a fan of coding at the start, it did show me how I could use my skills and what other things I could do when I left, and I was pretty much worked in analytics ever since, mainly within the retail sector um, health, beauty, office supplies and now clothes so, yeah, I love it when people have a path and they know what they want to do.
Speaker 1:does somebody inspire you to work in data? I mean, we have ladies on here that say I thought that data was going to be quite dry and I actually, when I spoke to people that worked in it, I thought actually I really want to do that. I can actually make an impact. Did you see somebody doing something?
Speaker 4:incredible. I think, just in all of the roles I've had, there have definitely been ladies that have been there supporting me and pushing me and I think they have been quite instrumental into me to stay within analytics and moving around and and doing doing other roles. So no one, no one specifically, but lots of people within my journey, so yeah yeah, amazing.
Speaker 1:And Laura, what about yourself?
Speaker 3:right. Um, so I'm Laura and I've worked at Enbrow now for seven years, so similar time to Stacey been there on that, the evolving journey that she talked about, and it's really good to see the central part that data plays in the commercial decision-making that we do here at M Brown. Bit different to Steph in that I didn't really do didn't do any coding or anything like that at university. I fell into the role. I did econometrics at university. I thought when am I ever going to use this?
Speaker 3:And I was working at a bank at the time and then the role came up, fell into it and I've just loved analytics ever since, always worked in the analytics space throughout my career, like Steph, though different subject matters ever since always worked in the analytics space throughout my career and, like Steph, though different, different subject matters, and so I worked in retail. But aside from that, I've spent quite a bit of time in financial services and insurance as well. But the skills are so transferable it's just you're analyzing different things, a lot of the methodologies and thought processes and the softer skills that you require it. I feel that they're quite similar, regardless of what industry, um you, you were working in amazing we.
Speaker 1:We have lots of ladies in our community that fell into tech.
Speaker 1:Don't worry there are lots just like you who just find their way in the industry, um and that's always good to hear as well um, that so many people don't have to take a traditional path. So we're going to go into a little bit about your roles and what you do at Enbrown. So can you tell us a little bit about what you do and your journey within the company and how you came to work in data analytics? Laura, shall we start with you on that?
Speaker 3:Yeah, sure, so, as I. So, as I've always been in analytics um throughout my career and moved to to m brown about seven years ago. During that time there's been so much change, especially within the data space um, we've had our home in various different departments over that time, which has been really beneficial for me personally within my career. It means I've seen analytics from various different angles within the business and I think that that's helped me become a bit more rounded and holistic in my approach to the questions that we get now. So I head up the analytics team. We are one part of the data family that can perhaps go into a bit more detail later on, but there are lots more data roles within m brown um. But within the analytics space um, we have analysts deployed across various parts of the organization and we get really varied questions a lot about we. We like to thread together the story of the customer, so it could be things like who is buying what? Why are they buying it, what are they buying it with, what's their motivation? How do they go on to trade thereafter? So yeah, lots and lots of opportunities and really varied questions. As I say, we've moved around departments and that's given that different commercial exposure. It's also exposed us to different technologies over the past seven years as well. We've been on an evolving journey there, and one of the things that I've really liked about working at M Brown is that, as well as getting the analytical experience and answering those commercial questions, there have been other opportunities that have helped me personally develop.
Speaker 3:So, as an example, as part of M Brown's move to working more agile and I guess we'll come on to this in a bit more detail later on one of the opportunities was to train to be an OKR coach. So this is setting objectives and key results, which is one of the core foundation pillars of the Agile ways of working, and so I took part in that process, which you didn't have to be in data analytics to be part of that. There was a group of us. We all came from different areas within the business, and that helped me immensely. There was of theory about um how people behave, also theory about the the actual subject matter that we were then going to go and coach the rest of the business but it helped me develop really personally as well. So I think m brown's been really good at making those opportunities available to people that might take them a bit bit outside of the comfort zone within their, within their normal role, so that that's been really good.
Speaker 3:One of the really good things about working here and other things along the way has been, over the course of my time here I've managed apprentice as well, which is a different form of line management and takes different skills and different use of time and how you approach things with that person. So again, help me develop personally there and help the, the um colleague in question, um make it through their apprentice in a really successful manner. She did brilliantly. And then other things I think m brown do um which is really good is that we run a data academy um with an external partner and very various members of the team have been through that and so help support them. But I've also helped support with the actual program as well. So there's a lot here about m brown, about developing the individual as well as um helping the commit, the company, reach their commercial goals.
Speaker 1:So yeah, I've been a bit of a varied time um here at m brown yeah, and then you're kind of guided through it as well, because especially things like managing an apprentice, you're right, it's so different and sometimes it's just, I think, companies think, oh, that's really easy, because it's a young person, it'd be fine. And actually I love what you said about like the OKRs and the different behaviors, because an apprentice, that is just completely different behaviour to somebody else in the workforce. So, yeah, I love that that you're not kind of thrown into things and just said get on with that, we have an apprentice now.
Speaker 3:Yeah, the apprenticeship provider. They were really supportive in that manner, giving me as much support as the apprentice um and help, helping them get through, get through the process.
Speaker 1:Let's say it was a really successful outcome for her yeah, yeah, that, and that's the main thing that they come out feeling like that was worth going through that program. Um, because, uh, you were supported and so were they. Um, I love that. Um, stephanie, what about you? Can you tell us a bit about your role at Enbrown and your journey within the company and how you came to work in data analytics? Out of curiosity, did you think that you would be working with brand in tech? Because, working with marketing that's one of those misconceptions of working in tech you work on your own, you work really siloed, you don't really work across different departments, but you work with brand and marketing and actually make an impact on what customers see and how they interpret that. Did you think you were going to do that when you went into data analytics?
Speaker 4:Yes and no. I think anything's possible within analytics, because I think your reach can be so far across so many different. You can have so many fingers in different pots and make such an impact in so many different areas. So, whilst it might not be something that your mind thinks of straight away, you do tend to focus on different areas because you can help. You can help across the board. If you've got information, you've got data on it, it doesn't really matter which area board. If you've got information, you've got data on it, doesn't really matter which area you know there's, there's some sort of way we can support. So so I think it's not surprising if you're working in that environment.
Speaker 1:Perhaps from the outside looking in, it might be yeah, yeah, you just said you know, I hadn't even thought of that. That actually um data also creeps into brand and Stacey. You mentioned how much data has changed so much at Enbrown. You must have seen data analytics creep into different areas of Enbrown. What, since you've been there?
Speaker 2:yeah, absolutely, um, I think as well. So the role that, the role of an analyst at Enbrown um is very much about solving analytical questions, answering real kind of whether it's problems, whether it's kind of strategic business questions. So it it's not, you know, it can be brand and it can be marketing um, but it could also be, you know, a kind of more um level. It could be, you know, within our financial services division. So I think, because also, I think the role of an analyst is probably different from business to business and if you've worked as an analyst in multiple business, many people will kind of feel that. So I think from our perspective, it's about it is really not just about the technical, it is very much about the stakeholder management and the engagement, telling a story, really trying to understand your stakeholders point of view and what they're trying to achieve. So actually, the commercial, you know um experience and skill is so important um, because you have to think differently, um, and I think that's that's something that we really look for when we're doing our um, our recruitment and our interviewing. It's okay, you know. You know, yes, we expect you to look at this data, but actually what's the data saying? And actually, off the back of that, what would your recommendations be?
Speaker 2:So I always kind of explain the roles kind of like that hybrid.
Speaker 2:It's almost like, yes, we're looking for someone who's got experience of you know Python or SQL, someone who's got experience of you know python, rsql, but actually we want you to be able to tell us a story and figure out and problem solve kind of along the way and work with your stakeholders um to bring that to life, um.
Speaker 2:So I think that's, I guess, maybe um why it's so central to how we operate on a day-to-day um and that that could be we, you know one. One of the things that we say is almost about how, how are we driven by data, how you know and I use it in my role from a recruitment perspective um, you know, yes, you can look at a set of data, but actually what does that mean and what you know? Sometimes you can look at a set of data, but actually what does that mean and what you know? Sometimes you can look at something and think, well, it's saying that, but actually what's the background of it and what are we trying to achieve? So I think that's kind of. I think that for me is like the sweet spot with data analytics across the business.
Speaker 1:Yeah, yeah, I totally agree. We. We track a lot of data in our community here to to help us move forward and and how, um, how ladies are finding us and what they're enjoying and how they're doing. And I completely agree with that, because sometimes there is so much, but you need to look at it and think, yeah, but how do I interpret that and how do we move forward? And you need somebody that can look at data that way, instead of looking at it and thinking it's just a load of numbers to me.
Speaker 2:Yeah, because we can look at a set of data. But actually what does it mean? And what does it mean in the context of our customer, or what does it mean in the context of our business? And I guess that's what this team do really well.
Speaker 1:Yes, yeah, and talking of the data team, can you tell us more about the data team at Enbrown and what are some of the key achievements that you've had this year?
Speaker 3:So analytics, I like to think, has been just one part of the data family that we have here at Enbrown, and I guess it's quite. It can be quite similar to other organisations. I would have thought so. I have to mention our colleagues that we have in visualization, and so they are the people who produce productionized, real quality reports for us. We're an online retailer, so speed of information is critical to us. We're looking at sales and you know an hourly cadence to make sure it's tracking what, what we were expecting it to be doing. So our visualization colleagues really excel in that area. So that's one part of the family. Next part is our colleagues in data science, and so they're building the models and forecasts and all the ml and ai tools that are really helping to power decision making across various aspects of the business. So from our pricing decisioning what price point we're going to charge for a specific item through to marketing and forecasting how much we're going to spend on specific campaigns. So yeah, so they're another part of the family. And then, at the foundation of it all, we've got our engineering team, and then, at the foundation of it all, we've got our engineering team. So they're the people who make sure and provide that that data is there for us in a timely and accurate manner and it's in a format that's accessible and logical to us. We won't be able to do anything without those guys. They're absolutely incredible.
Speaker 3:So then that kind of leaves analytics. So touching on, I think, what you said a lot before, um stacy, but I see us as being sort of like the front door to the business and that blend of commercial um skills versus the actual coding and the data. So our reporting it can't cover every minutiae of detail that we would need to answer all the business questions that we have. So this is where analytics comes in and we're sometimes described as being the detectives. So it could be. We've got this business challenge at the moment. Go and find out what the real nub of it is and, um, uh, that's where my team come into it. So it's asking the why, why, why going that next level down to uncover those insights that can then really help the business truly make a difference and change the way we do things so that we can move forward. So that's where my team fits in.
Speaker 3:We're also responsible for executing and analysing all our customer contacts. So at M Brown we send a lot of emails to our customers to engage with them in a marketing sense, and we also send paper mailings to them. We've got a core base that do still value that type of contact, so we analyze that. And then we've got analysts that are deployed within the technology space as well, answering a whole host of questions there. So that might be more about, um, we've got this piece of technology. Is it adding value to our site as an example? So that's kind of, uh, the rounded view of how I see the, uh, the data family here at m brown.
Speaker 3:And then in terms of achievements, I've been reflecting on this, so trying to pick, pick the top ones. There's loads more as well. So I guess, probably similar to other companies as well, we have had the challenge or opportunity of having to adapt to using multi-platform. So we've got data in various areas now on different platforms. So the team have had to rise to the challenge of upskilling in new coding languages so that we can get the best out of all that technology. We've also had to move to GA4, which a lot of other companies will have done as well, but that's required us all to think in a different way, get used to new data structures, and I'm just so pleased with how easily that has been achieved at Enbrown and that's been through a couple of things. So our colleagues in technology really working so closely with us to make sure that that data is provided in an accessible format to us so that we can use it straight away, and the team being so integrated into that process and rising to the challenge of of upskilling in that area. So so that's been one key achievement.
Speaker 3:Um. Other things that I'm really proud of is the impact that we've had on commercial decisions. So we often work with third parties and our team will get asked the question is it worth the money that we're paying for that thing, that contract? And this is where we often get involved and we have to prove whether we think it is worth it or not, and we can have a real influence on those, those types of negotiations. So I'm really proud of what the team have achieved there.
Speaker 3:Um. Another thing is um, within the analytics team, our female gender ratio. We've got over 50 women in the team, which is well above the, the industry average for for a team that is more aligned in the in the tech space. Um and stacy feel free to to jump in here. I think I think it might be partly due to the skill set that's needed within within the role, um, but I know we do a lot, don't we stacy, to make all the job gender neutral so that we can try and attract the best quality people for for the role. But I'm just really proud of what we've achieved there on the gender ratio and I think it it's really helped the the team be be more holistic in in approach.
Speaker 1:Yeah, I, I think the way that you talk about your role as well must really help with that, because if that, the way that you talk about that, if it's in the job advertisements and by the time you talk to somebody like Stacey about it, the way that you describe data was not like how people would think about working in data, and we get that from a lot about ladies that work in data analytics in our community who you know thought it was going to be you kind of working on your.
Speaker 1:It almost sounds like you know very sort of dusty, like data, very dusty. Brush off all of this dust in the background and it's sort of you don't don't really get to dig beneath the surface. But you described yourself as being at the front door of the business, that you're curious and you're referred to as the detectives, like that sounds super cool. It must attract such a wider pool of talent to want to come and hear about those roles. So, um, it must be the way that you talk about it, and then that goes into the job applications and then, stacey, by the time they reach you, um, it's just the icing on the cake yeah, I think it's um.
Speaker 2:I think as well, data is constantly evolving and the role of someone working in data has is evolving as well. So I think it's, and it's great, obviously, the CEC, the work that's happening in in schools and colleges and universities, um we've got good relationships with with the universities um we've had, uh we've facilitated placement students, we've given talks at the universities um we've ran our own events here in the office in central manchester, manchester, um. So I think, by trying to focus on our local kind of community um as well, as you know, um reaching, you know, just outside of of the northwest um, it gives us a really great range of people, different backgrounds, um, who have had different avenues into data. So, as I say, laura and Steph, very different backgrounds. We've had people who have, you know, worked in academia for years and years and years and then they make the switch to work it in more of a commercial environment and all of those different backgrounds and experiences help with the way in which that team work together and collaborate with the business.
Speaker 2:So, yeah, I think we are really proud of of the, the kind of the gender balance um within the data team and I think, yeah, it's a it's a testament for the team in terms of how how they not only obviously work within the business, but the work that we do outside of the business as well. So, yeah, that's something that I'm really proud of and would like to continue. Um, as as we, as we kind of yeah as we as we go on just picking up on something about the placements um, I think that they're fantastic.
Speaker 3:Not only does it open up other people outside the business into what the role is like, I think it's really good for the individuals who then manage the students within the business. It's a development opportunity for them. They may not have managed somebody previously or had to think about, or, if they have, it's a different type of relationship if you're managing a student. So I think I just think that the win-win really the business gets something both. We get an answer to a question and we develop our people internally and then externally. It's showcasing what working in data is like to to a wider group of people and hopefully gets more of them interested and and roles thereafter definitely yeah, that visibility on what a role is actually like um can really make a difference.
Speaker 1:Uh, to some some people, especially young people, you don't know all of the roles available in tech.
Speaker 2:Sometimes it's going to be coding um, and that you have to be highly technical to come into tech and that's it yeah, I think I think as well is looking at it as skills rather than I'm going to move into that as a career. So we've, you know, over the last few years we've kind of grown um a data academy. Uh, we've had colleagues across the business do apprenticeships. So that could be someone who's working in the people team you know who may be.
Speaker 2:You know, um, you wouldn't necessarily think on the face of it, why would someone in the people team want to do an apprenticeship in data? But actually it's the curiosity about learning about data and how we can use that in our day-to-day work. Um, so, by having people across the business who are maybe in classified non-data roles, um taking up the opportunity to do an apprenticeship or do some learning around it and, uh, it's really great because it expands on your skill set and who knows, like down the road you might be like, do you know, I'd love to work in the data team, or actually it might be. I love doing my job, but actually by using data, it's making me better and more efficient at my job now.
Speaker 1:So you could look at it in in two ways as well yes, definitely, and and we spoke about that a little bit earlier about um stakeholders and I find that sometimes when you want to do something or move forward in your job, if you have data to show why it would work, it's so much easier to get something pushed through. And you kind of notice as you go through your career, you think actually, if I'm going to go and pitch for something or I need budget for something, I need to go and find the data and make a really good case for that and, like you said, stacey, it can really make your job easier by doing that. And it's not necessarily part of your job. You might not be in a data role, but you can definitely draw upon that to help you. We're going to talk a little bit about Agile, so can you share more insight into the ways of working at Enbrown and the introduction of Agile? How does this work?
Speaker 3:now At Enbrown we've been adopting Agile. It's been a bit of a journey for us, but in adopting it we're following a blueprint, so every team that goes through it follows the same process and document, which has so many advantages. So I'll come back to that. But basically, us working in agile really simply for those that might be less familiar with it is that we have a collection of people in either a squad or a tribe and they come from multidisciplinary backgrounds. So they come from different areas across the business with different skills and they're there to galvanize behind a specific um goal. So each squad will have its own vision and mission of what they in particular are trying to achieve and they'll track those against the OKRs. So those objectives and key results that I mentioned earlier on um that are really underpin how we measure success with that. So the blueprint essentially is a document that documents how this process is deployed within the organisation and it's really good in that it sets people's expectations so they then know what to expect in working in that way. So what are they going to be, the ceremonies or the meetings that will happen? And it creates this commonality so that if they were then to move from one squad to another. It should be executed in exactly the same way. The roles and responsibilities will be the same. It's just that the subject matter matter would be different across each of the squads and tribes. And we've got about I think it's about 60 percent of the organization. Organization is now deployed um across our job. Now there are plans to further this within the next financial year.
Speaker 3:Um, and what I love is the fact that it's visible right the way through the organization. So this blueprint. It ladders up so right up to exec and director levels. We're still having the same types of meetings. They're called exactly the same, so there's commonality of language and everybody's speaking in the same tone and using the same processes, same processes, um. So that's so.
Speaker 3:It's really good in that the squad benefits from the different smes that it brings together to achieve that common goal. But we can't forget that the individuals making up that squad they still belong to their um role family, which we call chapter. So in our example, our chapter is the analytics chapter and we'll have our analysts deployed across various parts of the business. But we all have this ring fence time as a chapter together where we regroup and we use it for things such as sharing best practice, supporting each other, doing peer review and developing as an analytics function together and it'll be the same whatever role family that you come from. So I think it's a really nice hybrid approach in that the squad to get that collection of different people coming together and sharing their specific skills, but they still but each individual still belongs to their own role family and gets that support. And so perhaps, if I pass over to Steph now, who can give us a bit more of an insight into what that was like, working in with the, in with the brand tribes- yeah.
Speaker 4:So when we moved to Agile, I was deployed deployed into a brand tribe.
Speaker 4:So, as I said earlier, I work with a specific brand and you're responsible for working with that team and providing insights relating to that, things like the OKRs from the start of conception to make sure things are in place, to monitor the success all the way through to that implementation and providing results.
Speaker 4:So you're very much key member of that team throughout. You're the first point of call for data and you can have that influence to make sure things are set up in a way to help you analyze the results. So that's kind of really a really helpful element of this, and I think some of the challenges is that you're often working with people who are less data literate or, in our example, less data literate. Obviously, other departments, it will be less familiar with things in their team, and so you, from my perspective, I need to be able to highlight why we needed to test the data, why it's important wanting to be in place for this to happen more often, not making sure you have a holdout group and being able to portray the data and results in a way that is digestible for all, because it's no good if you can do all this work, but no one can understand it, and take action from it.
Speaker 4:So I think there are some real positives to working in that agile environment because you are involved, um, within a lot of things, and then you can take those learnings back to your chapter and your analytics and then other areas. Other brand tribes could be like oh they did this in one tribe, could we try this in another? Or you can share your learnings. Quite often, a lot of things would be done across brands so you could actually, um build on what other people had done, so you can share your knowledge as well. So I think there's some really key takeaways from being in that agile environment for sure.
Speaker 1:Yeah, I love that. So that must really help with retaining staff as well, because you have different tribes that all kind of work in similar ways. You can have the thought oh actually I want to try something new, I can go over to a different tribe. You don't have to have the thought of I think I've run out of things to do at this company. I don't need to jump ship. You can literally move across to a different tribe and learn something very new. But it still seemed quite familiar.
Speaker 3:Yeah, we've had lots of experience of that, haven't we Steph, with people changing their tribe?
Speaker 4:Yeah, I think skills are transferable, aren't they? And you can bring your knowledge from different areas and apply it to different.
Speaker 3:Yeah, it has been a real journey and, just touching on some of the some of the challenges, I think everybody's now up to speed with terminology, but it has taken a little bit of time, as expected, to get the whole business talking in the same way and now that more and more people are mobilized and deployed, we've got the really, really strong foundations.
Speaker 3:It's perhaps a bit more challenging when some areas were working in this way and other people weren't, so it's been like what does team of teams mean, and and things like that. But you know, we've we've certainly overcome that and we're on a really strong trajectory with it now. And I think, from the individual point of view it I just love the autonomy it gives the people who are deployed within their squads. They are the face of analytics in that squad. They get to make real impression all on their own. So that's really good and, depending on what tribe they're put in, they might learn new tech skills as well, because some of them are more technically focused than others. Learn new tech skills as well, because some of them are more technically focused than others.
Speaker 1:So we can tailor those opportunities as to where people are in their careers and how they personally want to develop too yeah, and it's always a challenge when you bring something new in as well, and how people um take that on board and whether or not they push against things. But most people um who who work in tech that I speak with, they're up for something new. Tech is always changing so much, so if you implement something like Agile, most people tend to see that as a positive. What about some of the biggest opportunities for self-development as well? Laurie, you mentioned a little bit there about how people can use that for a positive and to move forward, but have you seen some big opportunities for self-development as well during Agile?
Speaker 4:I'm more exposed to different areas of the business and different people that you might not have had exposure to, and I think you can have influence in different areas.
Speaker 2:Yeah, I think one of the reasons we wanted to move to this way of working as well is to break down any sort of barriers or siloed ways of working and be more of a cross-functional working um team. And it will. You've got the right people in the right place at the right time, and then that allows us to get to, to answer quicker, you know, to get plans in place quicker, um, you know. If something doesn't work, you try something different, you move on, you learn from it, and so I think it's made us feel more connected as a business as well, and we're not just tech, we're not just retail. We are, you know it's like a group of like, all working towards the same kind of mission, isn't it? And and and to what you mentioned before, laura, is you learn from different people. You learn different, not just from a technical perspective, but you know you might work with different people who think differently, who come from different backgrounds, who have a different career path. So all of that really helps as an individual to see things from different points of view, which will then help you in your role as you work and continue on in the business.
Speaker 2:So I think that's certainly an area of opportunity and develop for anybody working in an agile business and being able to make decisions and less of a hierarchy approach and so like, for example, steph's in the brand tribe. Steph is the data expert within that brand tribe, so you know everything will go to Steph, so that gives her more autonomy, probably puts you more in a position of that kind of key decision-making responsibility as well, which then will grow your confidence. You know you're speaking to people at all different levels as well, which then will grow your confidence. You know, um, you're speaking to people at all different levels as well, different stakeholders, so, whether you're speaking to a fellow analyst or a director, um, so I think all that's really positive experience, isn't it? Because it's growing you as an individual, both on your soft skills, but also on your technical skills as well yeah, definitely, and it it helps with um.
Speaker 1:You mentioned about, uh, trying new things and if they don't work, they don't work and you try something else.
Speaker 1:When you're a company that allows you to do that, you grow so much, whereas some companies are kind of you just do your day job and that's it, but when it's okay to foul, if things don't work, you know you just do them again. You look at the data and you think, well, that didn't work, we'll try something else that you can really grow, and you can grow really fast doing that, and you tend to stay at companies longer that allow you to do that. Because I wanted to ask you a little bit about the key attributes when looking for, when hiring, a data professional and we've already mentioned a few words throughout this like somebody that's curious and somebody that wants to dig into that data and what are those things that you're looking for? Because you're looking for someone that's fearless in that way, they want to test and they want to get to the bottom of things. So, yeah, what do you think some of those key attributes are when, when you hire?
Speaker 3:well, we often say that we're looking for a unicle on that thing.
Speaker 2:That that's very may not actually, which to then I respond and go oh gosh, this is gonna take me some time um, do you need them?
Speaker 3:by so, um, so we want. Okay, can we want to eat it as well? We're looking for that blend of the storytelling together with the technical coding skills. So, within our role, we can only truly succeed where we can convey our insights to stakeholders and we get it done quickly and we get the message across first time correctly. So that's how we bring about change. So it's distilling those hours and hours that you might have spent looking at the data into that newspaper-style headline, that attention-grabbing sentence that gets the stakeholder supported with some strong visuals that will, um, make change within the business. Um, we, we at m brown, we've got our, our four main key values, um, one of which is curiosity. Um, and uh, I think that's really powerful one. Within analytics, it's that constant seeking the next level of understanding and that asking that additional, why, why, why?
Speaker 1:I love that you you um, describe that as a new story. You're absolutely right. So in journalism you're given sometimes a press release. We have a load of statistics in it about something that's happened, someone's done a report about something, and you might not be given the the breakdown of what the story is or the headline. Or somebody just hands you some really in-depth report and you're literally asked so what's the story? And you're looking at it like I have no idea and it takes a while to be able to pick out that's the story.
Speaker 1:I'm going to go with that angle for that, because sometimes there are so many different ways that you can pull data. But, what's the most important thing, it takes a little while to figure that out and to look at it and say I'm not just looking at numbers, that's the story that I'm going to run with and that's going to be the big grabbing attention headline. You're absolutely right. I love that you made that into a story, because that takes a certain person to be able to see a story within data instead of just thinking it's just numbers. Stacey, any other key attributes that you look for when hiring?
Speaker 2:I think, building on what laura said, so someone who's inquisitive so what are we trying to achieve? What's the business trying to achieve? Um, use that perspective as well. So look at the situations from a different viewpoint, ask questions to understand the size and the scale of of what are we trying to achieve? Um, I think that business partnering piece is really big.
Speaker 2:That stakeholder management piece, that that that ability to really get under you know what you're trying to understand. Um, so that when you're looking at the data, you're looking at it through the eyes of not just a data professional but a. You know that that that seo person, that you know that seo lead that you're working with on this piece of work um, I think, open-mindedness. So that's that's key for me, because our business is ever changing and ever evolving.
Speaker 2:We work in an industry that's so heavily influenced by so many things out of our, our control, so we need to think differently sometimes and consider new ideas and new solutions, and if things don't work, they don't work. If it doesn't work for us, it doesn't work for us, but we've tried it, we've explored it. So I think for me, yeah, those are some of the key things no-transcript doing. What are other analytics teams doing so. That's why I quite enjoy doing things like events and encouraging people to network, and so I think that, for me, is some of the some of the things that I think I hear a lookout for when I'm speaking to people. I think some of the things that I think I hear I look out for when I'm speaking to people.
Speaker 1:I think some of those things are really important definitely and, like Laura said, the unicorn you're looking for yeah, big part, yeah, exactly, I think, yeah, and I think as well.
Speaker 2:I think if you have those types of kind of behaviors, you'll fit really well into the team as well. Being comfortable sometimes with working in a really fast-paced business which we change directs and we have to scale things, we have to slow things down, we have to speed things up so being comfortable in that environment actually is really important as well. Um, I'd never worked in a retail business before I started at m brown. Um, so it was, it's been eye-opening but really exciting, because the business is in a different place than it was a year ago, than it was five years ago. So being able to be on that kind of evolution, um, is really exciting. The business has been around since the late 1800s, so there's a lot of heritage there that we're really proud of. But how amazing is it that you know where we are today, you know so and where we're going to be in the future. So, yeah, that's, yeah, that would be what I would. That would be my view anyway yeah, definitely.
Speaker 1:I tell a lot of people about um Enbrown and the brand, because um that when saying you've been around since the 1800s and people say, oh really. And then when you start talking about the brands and and your story and how you went through even from catalogs through to digital, when it you're right, it's such a an interesting story to be a part of, and when you're part of a company that's constantly evolving, um it's, it's it's so lovely to look back and think you know where we, where we were and how we're growing and what you'll do in the future. Again, it really helps with retaining um staff and keeping. Yeah, um, ladies, we're nearly out of time, but I wanted to ask you one last question and do you have any advice for our listeners who want to accelerate their careers in data but they don't know where to start?
Speaker 2:I suppose I've got one. I think if you are looking to progress into more like, if you're looking to progress into more of an analytical role kind of for what we've explained is how we work, um is really trying to if you've not got a huge amount of experience or you're currently not working in a data role, is really try and think of some examples in your current role where you have used data and used that analytical problem solving ability, um to to answer some questions or some solve some problems. So, yeah, you may not have done kind of exactly what we've done, which is fine, but actually can you demonstrate where you've done something like that and and start to really put together some examples so that if you are interviewing for a role, you've got something to to kind of talk through um? So, yeah, that would be my bit of advice. So think about what you can do within the remit of your current role and then try and build on that yeah, we get asked that a lot of what if I don't have the experience?
Speaker 1:how I move into something about the experience again, it sometimes comes down to that and we spoke about it finding your own story as well, and and the skills that you've been doing in your current role and how they um transfer over to tech or something um new. Like you said, stacey, finding that within your own company sometimes is the best place to start, and we do get asked that a lot from our community. How do you do it without experience?
Speaker 4:yeah, it's really about asking the right questions. Isn't it thinking about the problems you want to solve? Because I think that's really key in our role. I think, something that's also helped me. A couple of things. I know we mentioned podcasts. I found them. Those are really useful. This one, women in stem, careers and confidence, and women in data. I think the perspective of other professional women working in similar environments is really valuable and I know this is easier said than done, but sometimes I think a mentor can really help. I've been really fortunate of being part of the mentoring program here at m brown and I've found the things I've got out of it been really invaluable to me to develop and I think if you can find someone, even if it's just someone, to talk to or ask some questions about their experiences, it can be really helpful yes, definitely.
Speaker 1:Yes, we actually had to bring forward the launch of our mentoring program because we got asked about it so much. You know there are people want to find somebody who, um, they can, sometimes to share their thoughts with, and, um, we in our community, we we kind of made it like a matchmaking service where you match on skills, um, and if it doesn't work out, you can, you can part ways. But there are so many people that want to do that and it became quite awkward as well how to find somebody. But if you're lucky enough to have an internal program like yours, where you can match and say I want to be be a mentor or I'm looking for a mentor, that takes away the awkwardness of having to reach out to someone on LinkedIn and getting rejected yeah, it's fine, anyone.
Speaker 3:Yeah for sure. The only thing I'd potentially add is it depends where you want to go into the data space. So if it is more in the in the coding um remit, then yeah, just get on. Things like um there's, there's some organizations that offer free sample courses. So things like data camp and you may you can get some free courses to start off with. Work out whether it is for you before you take that plunge and invest. If that is the route you want to go down In terms of perhaps more, how you've used data, then take part in competitions like Kaggle, because then you could always show to potential employers your output from that. Or there's things like Makeover Wednesday, where you can take a piece of data and show how you would then present that back. They're really good things to do. If, if you, if you don't have that current exposure within your role, you could take it to an interview as an example of how you would have approached something in a more hypothetical sense that's a great idea.
Speaker 1:Yes, yeah, just that, having to a way to show your practical skills and and how you would have done something. Um, we, we do get asked about that. Like, if you don't have a portfolio, how do you show that you've worked on things and you're right? It just sometimes it's just finding those projects or even meetups where they um can work on projects, and we run hackathons. For that reason, if you've never been to um a hackathon, we don't have to be technical to come to ours. Just we, we throw you into a team of strangers and you get to work on something fun for the day and that's it.
Speaker 1:It's very um, it's not a lot of pressure, but you can take that project with you and say I worked on this and I did this part and this is how I solved these problems. But it's looking for opportunities where you can um show your skills, definitely. I agree, and Udemy gets mentioned a lot to our community because a lot of those courses are free and we always advocate for try something free first. Yeah, don't like it, you haven't spent anything, it's fine.
Speaker 2:Yeah, absolutely.
Speaker 1:Incredible. Well, ladies, we are already out of time. I could keep talking to you for like another three hours on this, but thank you all so much. Stacy, stephanie, laura, thank you so much for taking the time out to have a chat on spilling the tea today. It's been a pleasure thank you so much for having us thank you for everybody listening, as always. Thank you so much for joining us and we hope to see you again next time.
