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[Radar Recap] Building a Learning Culture for Analytics Functions, with Russell Johnson, Denisse Groenendaal-Lopez and Mark Stern

In the session, Russell Johnson, Chief Data Scientist at Marks & Spencer, Denisse Groenendaal-Lopez, Learning & Development Business Partner at Booking Group, and Mark Stern, VP of Business Intelligence & Analytics at BetMGM will address the importance of fostering a learning environment for driving success with analytics.
Apr 2024

Photo of Russell Johnson
Guest
Russell Johnson

Russell is the Chief Data Scientist for Marks & Spencer, one of the UK’s most trusted retail brands and part of the FTSE100 Index. He leads the AI & Data Science team which has helped to unlock seven figure cost savings across the enterprise and eight figure incremental revenue through online personalisation. Prior to joining M&S, Russell held leadership roles at Meta including heading the data science organisation for Meta’s Workplace product and as the Global Head of Strategy & Operations for Meta’s Reality Labs. Russell’s academic background is in behavioural neuroscience and has active side interests in history, organisational behaviour, sailing, and surfing. Originally from Atlanta in the USA, Russell has called London home for over 23 years and is a proud dad to two teenagers.


Photo of Denisse Groenendaal-Lopez
Guest
Denisse Groenendaal-Lopez

Denisse manages the learning programs for Booking.com staff. She is an expert in using technology, data, and modern HR practices to identify and solve learning needs. Denisse is a DataCamp admin, and has been heavily involved in the Booking.com data training program. She was previously a learning manager at Dakar Solar and Philips.


Photo of Mark Stern
Guest
Mark Stern

Mark has over 20 years experience managing business intelligence and analytics teams. He is an expert in building data and machine learning capabilities to inform decision-making and deliver profit. He previously ran business intelligence departments at Entain, Gala Coral Group, and BetFred.


Photo of Adel Nehme
Host
Adel Nehme

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Key Quotes

How do you build a learning culture? Understand your audience. Make it relevant to them. Understand their internal challenges and career framework. Meet them where they are and speak in their language.

People won't adopt what they don't understand or fear. How do you overcome that fear? Education. If you're not leading with education and understanding, that fear is going to hold people back from adoption.

Key Takeaways

1

Leaders should promote a workspace where trial and error are not only accepted but encouraged, to foster innovation and creativity within analytics teams.

2

Align learning initiatives with strategic business objectives to ensure that continuous learning directly contributes to organizational success, making analytics adoption and upskilling a key component of the company's growth strategy.

3

Implementing structured learning paths that still allow for personalization and self-directed exploration can significantly enhance skill acquisition and engagement in analytics.

Transcript

Adel Nehme (00:00):

All right. All right. I think we are live. Hello. Hello everyone. For those who are joining us right now, I see 500 plus people in this session. Tons of people in the chat, people from Ottawa, people from Greece. Let us know where you're joining from. Give us some love in the emoji, people from Australia, India, all over the world. Yeah, the chat is going to get flooded shortly. Belize, San Francisco, Mexico, London, uk, Kenya, Colorado, Romania, ua, Philippines, Seattle, Lisbon. Okay, all over the world. We can keep going on and on. We were speaking backstage about Ted Lasso. Let us know everyone on the chat, any Ted Lasso fans do let us know. We'd love to hear your thoughts. So yeah, I've welcome everyone to the session on building a learning culture for analytics functions. As we know DataCamp, we can't stop talking about learning data scales, and the sessions definitely right up our alley. As organizations continuously invest in upskilling, whether for analytics teams or not, creating a culture of continuous learning isn't just beneficial, it's essential. So how do you build a culture of continuous learning? How do you sustain it over the long haul? And how do you measure a learning culture? So well, there are no better guests to answer these questions than today's panelist. I'm going to start with Russell Johnson, chief data scientist at Mark and Spencer Russell. Good to see you.

Russel Johnson (01:30):

Hey there. How are you? Good

Adel Nehme (01:31):

A... See more

fternoon. Good, good. Awesome. So Russell is the chief data scientist for MNS, one of the UK's most trusted retail brands and part of the Fortune 100 Index. He leads the AI and data science team, which has helped to unlock seven figure cost savings across the enterprise and eight figure incremental revenue through online personalization. Anyone who checked out the building ROI session from the previous one, that's definitely an example of building RI. Prior to joining m and s, Russell held leadership roles at Meta, including heading the data science organization for Meta's Reality Labs. He has an academic background in neuroscience and has active side interest in history, organizational behavior, sailing and surfing. He's originally from Atlanta and the USA, but he's joining from London. Next up is Denise Ronal Lopez. Denise, good to have you on.

Denisse Groenendaal-Lopez (02:21):

Hi everybody.

Adel Nehme (02:23):

Denise manages the learning programs for technical audiences across booking.com. She's an expert in using technology data and modern HR practices to identify and solve learning needs a data account for business administrator. She has been heavily involved in the booking.com data training program, and she was previously a learning manager at the car, solar and Phillips. Last but not least is Mark Stern, VP of BI Analytics at BET MGM. Mark. Good to see you.

Mark Stern (02:50):

Yeah. Hello everybody. Good morning, good afternoon, good evening.

Adel Nehme (02:54):

Awesome. So Mark has over 20 years building and managing business intelligence analytics teams. He's an expert in building data and machine learning capabilities to inform decision making and deliver profit and cost saving. He previously ran BI departments at ent, gala, coral Group, and be Fred. Now, before we get started, just a bit of housekeeping. We'll have some brief time for q and a at the end of the session, so do make sure to ask questions in the q and a section of the chat. And if you have any questions, make sure to ask them. We're also going to be live posting on social media. So if you use the hashtag DC radar, we'll make sure to amplify your messages and we highly encourage you to fill out your profile and engage in the conversation. So I'm going to set the stage for today's conversation by deep diving maybe into the why behind building a learning culture. You're all actively engaged in the upskilling agenda of your organizations. So maybe help us set the stage behind the motivation of why a learning culture. So what does a strong learning culture within an analytics function looks like or even broader within the organization, and why is it important? Russell, I'll start with you.

Russel Johnson (04:03):

Yeah, thanks, Adele. Yeah, I think when we talk about a lot of the stuff that's been happening in the last year or so, especially around ai, people won't adopt what they don't understand. So I mean, we always talk about how the first sort of AI use case that we launched at m and s was an educational use case, bringing people up to speed with something. I think it's really clear from history. People don't adopt new technologies if they're afraid of it. And the best way to counter that fear is through a bit of education. So if you're not educating people first and foremost as your primary use case, as your initial use case in any new technology, whether it's printing presses or looms and factories or ai, then people are going to be, that fear is going to hold people back from driving that adoption.

Adel Nehme (04:56):

Yeah, I couldn't agree more. And Denise, maybe let you add here as well on top of what Russell said.

Denisse Groenendaal-Lopez (05:01):

Yeah, absolutely. And I think data is just a fundamental nowadays. So I cannot think of any department [email protected] that does not have a business analyst or data analyst. It's just everywhere. It informs our decision making. We are better at making choices because of their insights they have. So it's just a new reality for us. And more and more of these data rules are just coming, right? They're proving their value every day. So it's to see even more of these coming.

Adel Nehme (05:32):

And Mark, explain maybe the motivation behind building learning culture at BET MGM.

Mark Stern (05:36):

Yeah, so in my mind, I work on a performance triangle and each point of that triangle has a word. One word is enjoyment, another is delivery, and another is learning. And all three have got to be balanced. And if they're not, then you have to address that, the fundamentals for performing at an excellent level, I think. So learning is part of one of those three points of that triangle.

Adel Nehme (06:01):

That's great. And we've uncovered the why. Maybe let's dig deep into the how and the what. So maybe learning cultures are not built overnight. Any culture change program, any large scale change within the organization does not happen overnight. And many leaders today are here trying to get started maybe with building their own learning culture. So maybe as a first step, how do you assess your current organization or team's learning culture? Denise, I'll start with you here. This is I think a very specific HR question probably to think about at the beginning. Yeah,

Denisse Groenendaal-Lopez (06:37):

Yeah. I think for booking.com, we're in a very specific situation that learning or learn forever is one of our company values. So we really leave up to those expectations. And also we do a great effort in upskilling our managers. So they're supportive, they understand how important development is, but this is just development that gets us to get the objectives that we are doing. On top of that, we have a very fostering community of learning from each other. We have a great pool of internal trainers. That's also how you get recognized for your expertise because you get to share it with others, but also we incorporate mentoring portals. So you really get to know more people in your role in other areas that are having similar challenges. So you can also increase your network, but solve stuff at the same time. So we're very rich and on top of that, we're a tech company, so we have a great culture of experimentation from failing, from learning from your failures, but also quite open communications. There's a lot of stories and testimonials shared in our internal social media channels. So it's just so organic, so embedded into our daily work that I think it's something quite unique, I would say. So it's just a pleasure to be part of it.

Adel Nehme (07:55):

And maybe I'll double down here and ask you an additional question, Denise. When you think about the formula, because you mentioned it's really deeply embedded in booking dot com's culture, what do you think are the main ingredients that make it so, and I'll jump back to you, Russell and Mark after that.

Denisse Groenendaal-Lopez (08:10):

I think that it doesn't feel like the traditional learning that you have to do or that is heavy. I think as part of the topics and as part of how engaged specifically this data science analytics craft, how we call it internally, it just seems so organic, so fun. It's very collaborative, so it just seems like you are achieving something together and learning from each other. It's less of a burden, so to say, right? You're just doing it with colleagues with like-minded people. So I think that's what makes it a real success, to be honest.

Adel Nehme (08:43):

Okay, great. And Russell, maybe what was the first step at MNS when building out the learning capabilities for analytics early on in the journey? When you think about assessing the current learning culture and how you think about scaling it?

Russel Johnson (08:57):

Yeah, I mean, just to up upload what Denise just said, I mean it's that peer-to-peer aspect that's really different about code of analytics and data science learning. I think when you take an organization as big and as sort of diverse as Marks and Spencer mean, we have over 70,000 employees, all but 5,000 of which are frontline employees, colleagues that we have in store. Obviously the training and educational needs for those colleagues are very different from what we would think about data and data science, although there is a lot of overlap. So how do you do upskilling for data science analytics for those individuals in the course of doing frontline type of work? That's important, but that's more of a traditional L and D type function for a retail organization, how it's different for what we do for people within digital and technology, for example, is a little bit more along the lines of that peer to peer sort of aspect that Denise was referring to.

So building things from the ground up. We actually have a separate l and D function within digital and technology, which is the organization that I roll up into that does all of, as the name suggests, digital and tech within m and s. And we have the Beam Academy that we built from scratch in partnership with data camp and yourself ade. So having different sort of methods and motivations and outcomes that we're trying to drive with that bespoke educational organization that we have in Beam Academy, I think that's helps us sort of be more successful than just a broad based generalized l and d function.

Adel Nehme (10:33):

Yeah, that's great. We're definitely going to talk about the Beam Academy and yeah, maybe Mark let you expand here on what Russell and Denise said.

Mark Stern (10:41):

Yeah, I think for me, we measure it every quarter. We have an engagement survey in the whole organization. I think if you're not learning, you're probably not engaged. My team for the last six quarters have been in the top percentile of that organization survey. So it's keeping that, look, I encourage people to try new things. If I trust someone in my team and they're in their team, they're trusted, they trust 'em to fail. And so in order to stretch themselves and to learn, they've got to try new things and sometimes fail. So that's also important.

Adel Nehme (11:17):

Yeah, that's really great. And a lot of you have mentioned a few things, right? Peer-to-peer learning, community and culture, embedding learning as part of the daily work and the culture. And Mark you just mentioned here, something really important, encouraging people to learn and experiment. And maybe as a follow up here, I'd love to see some examples of how your teams or organizations are embedding learning in daily work. What does that look like in practice? Mark, I'll start with you.

Mark Stern (11:44):

So a number of things. So first thing that my team get when you join my team, everybody gets a complimentary data camp license for everybody encouraged to use it, their technical skills. So they're really encouraged to make time and space for it. And we share time with data camp. We've been to your offices in the Empire State, we've had you over here in Jersey City, and we've watched a game together in our bar. We're a sports company at the end of the day.

So part of that is again, having fun and enjoyment, but also we run hackathons with you. So trying new things, just stretch, stretching the minds. We also do a lot of stuff. We also brought in a whole week where we did data consultancy skills presentation and stuff, and the 20 people that went on that, we encourage that to filter it down. So that happens. And today we've had everybody in the office and we have three or four presentations where people who want to share some of the work they've done. And so all of that encourages people to learn from each other and collaborate and stretch your minds.

Adel Nehme (12:47):

Yeah, that's great. And maybe Denise Russell, how is learning look like in the flow of work for [email protected] and MS? I'll start with you, Denise.

Denisse Groenendaal-Lopez (12:57):

Thank you. Yes, I think it's building up what Mark said right here at booking. Hackathons are also a prominent format, and I would say there's no escape because we have so much formats and platforms for them to explore that we are really catering all their preferences and really formats of how they like to learn. So we also measure quite often engagement on different platforms. We take also monthly meetings with data cam to understand the data, what's the data telling us. We also have a lot of this group actually creates their own internal conference, so they're super engaged on top of that. We allow them to go to external conferences as well. So it's just really plenty of formats for them to explore. Like I said, they can even be mentors and internal trainers. So I would say there's no escape, right? There is everywhere a learning opportunity. We have books everywhere. So it's very present, very embedded here in the physical environment here at the campus as well.

Adel Nehme (13:58):

I feel like a tagline for a learning culture, there is no escape really sets the scene for the wider organization. There is no escape from learning. Russell, maybe share with us how does the learning and the flow of work look like for m and s?

Russel Johnson (14:15):

Yeah, I mean to double down on a couple of different points. Number one, the hackathon concept is great. I mean I've had the privilege of seeing that work at a couple of different companies when I was at Facebook where that sort of culture comes from. I think originally I certainly do the same sort of thing over at m and s. I think it gives visibility and some time and a safe space for people to basically not just produce ideas, which is sort of the core part of the hackathon culture, but also just to meet other like-minded people that are sort of movers and shakers. Those thousand points of light, those peer-to-peer sort of interactions that Denise was talking about earlier. I think that's really a lot of the positive value. And we also do a couple other things on the team. All of my heads of here, we all have presentation sort of parts of our KPIs or goals very much in each one, each one kind of mentality. We're expected to be evangelists as much as we are expected to be data scientists. I think it's an important part of the role. It's no good being in the back closet somewhere, crunching up models, spreadsheets and dashboards. I mean, you've got to be out there educating and sort of inspiring people to get excited about not just data, but what it can do in an organization.

Adel Nehme (15:35):

And I want to touch upon that. Russell, you mentioned the term evangelizing within the organization. I think that's such an important element of any learning culture. Maybe diving a bit deeper there, A big thing that we think about is how do not just get executive sponsorship for a learning program, but how do you get executive excitement for a learning program? How do you lead by example as a leader when trying to establish a learning culture within the organization? Mark, you also mentioned this, you alluded to this when you mentioned you encourage your team to learn to experiment, to try new things. Maybe what would be advice that you would give leaders or would-be leaders here on the call, on how they can set an example for the team on how to embed learning as part of daily work or the team's culture essentially? Mark, I'll start with you.

Mark Stern (16:21):

So it is important to promote your team, the new work that comes out. It's important to get it surfaced, help them present it. I think, look, we talked about these hackathons not only just doing the hackathons, we also got, and the team arranged this. I didn't, they set it up and I just encouraged it, but they even got the chief executive, the CRO to judge it. So they're not only that, there's a high bar in terms of present, they're getting good feedback from those sort of people and they're seeing people, the company who really, really show by putting their time and effort towards it, it is valued, I think. So yeah, it's about, as a leader is just stand at the back and try and promote and when people have ideas, encourage it, encourage it to happen.

Adel Nehme (17:12):

Yeah, that's great. And then maybe Russell, we've worked quite a bit. We're going to touch upon the Beam Academy. One thing that I'm always impressed about with Marks and Spencers is how much excitement of a culture there is around learning how much effort there is. So maybe walk us through that bit, the executive sponsorship and how leaders have set an example for a lot of different folks within the organization to approach learning.

Russel Johnson (17:35):

I think mean last year in 2023, we certainly, a lot of the technological advances in AI kind of threw us a bone here, a natural experiment in how we can do better executive engagement. Because unless you're working for a big tech company or something like that, most CEOs were not sort of ready for that. It was suddenly I'm on the back foot, what kind of CEO am I am the CEO that has good people in place that can sort of help to inform and educate about a new technology that I myself might not understand, or is this something sort of scary that I need help understanding, but don't have the right people in place? So putting those events together I think is really, really important. Getting people in and saying, you need to be a leader as a CEO. You need to be an executive sponsor of this, even if you don't necessarily understand it.

And by coming up being a judge at a hackathon or participating in some of these events that we run, like our AI events that we did last year, Adell that you participated in, this is a great way to basically say to a CEO, look, you can lead on this even if you don't really understand what it's all about, you don't have to understand what it's about. You can be a leader by simply participating and judging and then just having a curious mind about it. It's that culture of curiosity that we talk about. First principles, we're talking about education here on this particular webinar, but even before that, you need to instill this culture of curiosity. And that's what we're sort of leaning into executives with. Be curious and then we can help you sort of be educated.

Adel Nehme (19:14):

Yeah, that's great. And Denise, maybe learning is a big part of the booking.com culture already. So maybe I'll reframe the question for you. How did the early executive [email protected], from a leadership history perspective, how did it initially forge that as a cultural value? What were the behaviors of the leadership team that got codify as part of the culture that it became such a strong cultural value?

Denisse Groenendaal-Lopez (19:43):

And I think thinking about what you both said, it's also the habit of sharing, right? In qbr, in nbr, quarterly business reviews or monthly business reviews, the impact, what are you doing better as a result of this? How is the initiatives that we are putting all these formats, how are they allowing you to do your work better or to actually reach your objectives? So that sharing also brought in perspective from other teams to say, I'm going to give it a try. I was quite hesitant, but after seeing the success of this team, I may give it a try. So that also helps unlock the resistance and also be more open to consider, right? Again, it's a lot of sharing of, okay, is this really giving us the results we want? Are we also serving our customers better as a result of this intervention of this program? So I think ultimately the results and the testimonials are actually doing the job. You're basically getting your job done, so then you get more prompt into what else can we try? Can we do it faster, more, I don't know, in a fun way or more scalable, but it's always based on those results, the impact of all these programs and all these efforts.

Adel Nehme (20:54):

Yeah. Russell, mark, I'm not sure if you want to react to that as well. Maybe walk through us how results oriented, a results oriented approach also feeds into the learning culture. So Russell, maybe I'll start with you here.

Russel Johnson (21:08):

Yeah, I think on some of our certification programs, when we talk about things that happen in our Beam Academy, like our l and d function that's specific towards digital and technology, we talk about the number of certification. When we do events, we talk about the reach we have. It's very, very sort of campaign driven, metric driven. We look for outcomes. So I think that's sort of what distinguishes it from a lot of other L and D type programs. I mean, when you've got an L and D program that that's trying to advance the course of data, it only makes sense that you use a lot of data in order to evaluate the success of it.

Adel Nehme (21:49):

Yeah, that's great. And Mark, maybe walk us through how results factor in here

Mark Stern (21:53):

Thinking to tie this together. So one thing we do, so this is about just learning as part of your job and as part of the organization and does ultimately data driven, but it means actually you've got to learning culture within your organization. So one of the things we have set up is a causal laboratory. And so a causal laboratory means that anybody, any customers that come on a randomly selected. So I get a small percentage of every customer, they belong to me, not marketing and my team. So you don't get any marketing. And my job is to therefore experiment and understand and demonstrate lifting performance and demonstrate I can perform better than the marketing team, the CRM. So there's a big challenge. It's a learning, not only is it a nice competition, but actually we are creating value and we're all learning in the process. So coming through and often people say that they're learning a day driven when they've got a report that's not learning, you've got to take risks and you've got to allow to give to gain something very precious.

Adel Nehme (22:56):

Yeah, that's great. I love that as a challenge. Definitely there's no escape and challenge are both great kind of taglines and motivators here. Maybe one thing that, sorry Russell, I'll let you interject. I was going to

Russel Johnson (23:09):

Say, mark, by the way, I'm writing this down actually. I mean, if I can steal 10% of M and S'S marketing budget and divert it to data science,

Mark Stern (23:17):

Yeah, I'm not sure they knew what they were signing up to initially. You have to give me

Russel Johnson (23:23):

Some notes on how to do that.

Adel Nehme (23:27):

That's great. And there's one question actually we got in the question section that I was planning on exactly asking it myself. So actually I'm going to let Ani ask it himself. So initial enthusiasm for learning is common, but how do you maintain momentum over time? How do you prevent learning initiatives from becoming just another checkbox? I was going to talk about how big of a challenge it is to sustain learning momentum over time, over the long haul. Russell, you've been at the Beam Academy, at least to my knowledge's, been a few years now, right?

Russel Johnson (24:04):

Year now, yeah.

Adel Nehme (24:05):

So maybe walk us through how you've built approach building and keeping momentum, for example, behind learning what best practices you have. I'll also relay this question to Denise and Mark. So yeah, walk us through how do you sustain learning momentum over time?

Russel Johnson (24:18):

Yeah, I love the question, right? Because I mean, I think we've all been through the little box checking exercises of taking a health and safety or an anti-fraud sort of l and d type of quiz. These are not the things that anybody willingly signs up for and rebels in spending their free time doing, right? I

Adel Nehme (24:36):

Love security IT training.

Russel Johnson (24:39):

I love my security badge as much as the next person spending 30 minutes on a survey to do that. So I mean, if we take that as sort of the example of what bad looks like and then flip that on its head, how do we make that a little bit more alive and make people want to do that? Nobody wants to take a health and safety test all the time, but we want people to have a lifelong interest in evangelizing both their own learnings and helping others to learn things around data and data science. So I think as I mentioned, we have the Beam Academy here, which is our DNT, our digital and technology learning and development function. I think from the beginning it was sort of set up to do something really different. Educate, we have 75,000 employees, including a lot of frontline colleagues working in stores.

(25:28):

The digital skills necessary in order to do your work as a colleague, in store, as a store manager, as a regional sales manager for Marks and Spencer, that's what Beam Academy is there to support you doing. And there's lots of certifications where people can do that. But it also caters towards people that are interested in upskilling themselves and other things as well. Everything from Excel technology to data analysis. We have quite a few L seven graduates as well and data clients. So all of these are sort of now embedded in the business. And so we have that thousand points of light kind of thing that the Beam Academy is helping to create. And then how do you fan the flames? How do you keep those embers going rather than just separating all those embers and scatter them away from the fire and suddenly everything dies out and stops producing light and heat. You've got to bring the embers back together in these events. And we do a lot of events with Beam Academy, Adele, the, well, we had the privilege of having you into one of our, let's talk,

Adel Nehme (26:31):

It's my privilege.

Russel Johnson (26:33):

You added a bit of excitement to it. So thank you again for that. Events like that where we have a lot of people in the company that are attending remotely and in person. I mean our Let's Talk AI event where we basically talked about here's the AI technology and here's what it means for the future of Marx and Spencer. We did that fairly early last year, and I think we broke all the records in terms of internal events of any kind that we did it m and s last year. That was the big thing. And I think Dell, most of that was you were driving the attendance there.

Adel Nehme (27:08):

I wouldn't say so myself, but yeah, a lot smarter people on that panel than me. But yes, but we had

Russel Johnson (27:14):

A really, really good time. And I think more importantly, we really got the attention of executives, Hey, what's going on? Let me understand how you're framing this, how this works for the company. But also it gives everybody a chance who's really interested in it to come in and then participate and the evangelists create future evangelists through that program.

Adel Nehme (27:37):

Yeah, that's great. I love that point. The last point at the end of the ambassadorship of that effect that you see when you build up excitement. Denise, mark, Denise, I'll start with you. How do you sustain learning over the long haul?

Denisse Groenendaal-Lopez (27:51):

Yeah, so part of my job is to really create a monthly newsletter of everything that is new, but also we tailor that newsletter to the audience, but also what's going on in that season? What are people naturally thinking about? For example, January is all about building better habits, for example. So how do you support also the personnel need that this person have and then just try to leverage that. On top of that, we do a lot of communication quarter monthly on acknowledgement as well, who has completed what, some sort of leaderboard in some programs, but acknowledgement of the effort, the behavior, we want to role model. So those who are doing it, we're trying to celebrate it. And I think we've done a very data-driven approach already. So we're able to understand what are the natural peaks and what's the natural flow. So we already know Q3 is a very strong quarter for people to learn.

It's also a bit of back to school of what's happening outside work. So we try really to build campaigns somewhere in September with WinCo prices or we try to celebrate or find an excuse depending on the audience to try to just bring that excitement and help them think also how can that relates into the work and the programs that we have. But it's really data-driven, understanding the audience that we're catering, but it's a lot of communication of what's new, what's popular, give it a try, also hear how it's helping other people, but it's constant acknowledgement as well. Even at the end of the year, we sought emails, those internal trainers that help us drive learning how many sessions they did, was it well received? So all this really makes it as part of, once you close the year, you are able to see, okay, here in this quarter we did this. Quarter two, we add that. And just sharing that with the actual learners or colleagues, they already are waiting to hear what's going to be the next event in September type of thing. So yeah, we also tried to give prices or gamified in a way so that they just build up the excitement on this, but acknowledging the efforts, it's also really a good effort, whether it's from the l and d team or the manager itself or the team. It's something that's also part of the campaign and the communications that we run.

Adel Nehme (30:18):

I couldn't agree more, especially on the acknowledgement side. Mark. Yeah, I'll let you expand on how you approach building a learning culture over the long haul at be MGM.

Mark Stern (30:28):

I think Denise, that's a good point. The acknowledgement. I think that's important to keep the encouragement going. When we got feedback, I got feedback. It was less about acknowledgement from me or more senior leaders or people on the side. It was more the contemporaries that they wanted acknowledgement from. I think that, so that's a key for me for getting 'em to share their work with their contemporaries. But I tried to hire natural curious people, and then your job is just to feed that curiosity as a leader to feed and try and create new data sets, find new data sets more difficult, interesting problems, new techniques, or something we've never tried before. So just encourage it and open that up.

Adel Nehme (31:16):

Yeah, that's really great. And in a lot of ways, a lot of what you're discussing here, especially Denise and Russell, when you discuss kind of the Beam Academy and what you do with the campaigns, is that the learning leader, data leader, whoever is in charge of the analytics upskilling program, needs to think a lot of times like a marketer rather than just a traditional learning and development professional or data leader. Maybe walk us through what skills you think from that marketing hat you need to adopt to be able to succeed at building a learning culture for the long haul. Denise, I'll start with you.

Denisse Groenendaal-Lopez (31:53):

Yeah, I think it's also a lot of understanding your audience. Who are they? What tools are used, what formats they use even to communicate, because I think you need to mirror and be where they are, meet them where they are, try to speak their language, acknowledge the challenges that they have, give them some hope that we are trying to work on the same goals. That's why we're trying to expose them to different alternatives or different formats. But that's always a joint effort that we're trying to get something for. What is it that we're trying to reach our goal, like server customers better, but jump in the same collaborative spirit by speaking their language, just posting or writing in the channels where this community is active. And that's quite a good step in understanding who your audience is. Just be part of it as much as you can. Right?

Adel Nehme (32:49):

Yeah. And Russell, what are some great marketing tactics that have worked at m and s?

Russel Johnson (32:54):

Yeah, I mean, like Denise mentioned, I mean it's a lot of internal marketing. I think about somebody who does this really, really well. I'll just give a quick name, shout out to Lindsay Marshall, who runs our Beam percent,

Adel Nehme (33:06):

Hundred percent,

Russel Johnson (33:07):

And I know Lindsay really, really well, but I mean Lindsay is, in my mind, an expert within a fairly solid organization like m and s. You can just imagine different business units, all sort of contributing d and t, digital and technology is sort of a partner to all somebody like Lindsay. In order to do that job really, really well as she does is you've got to tailor that message to the audience, and that means doing something somewhat different for clothing and home that you might do for foods within MS. I think Lindsay does that really, really well. And then basically be able to put those different sort of marketing messages in different ways of talking tailored messages, but still be able to synthesize the whole so you can see the entire outcome

Adel Nehme (33:55):

And mark marketing tactics that worked at BET MGM.

Mark Stern (33:59):

Yeah, it's a large part of my role, a huge part of my role to people don't realize that I'm an analyst at heart, but actually I spend less and less time in the data. But it's about, look, we have once a month, we have analytics steering group was chaired by the CEO and the C-suite. My job is to present what's going on. Are we getting in the right direction, the priorities, the direction of the team. We pushed the engagement stuff. Then more recently we've just done a roadshow with the product leaders, sharing with them for two hours, everything we do. So pulling together that insight and that presentation and putting it isn't a straightforward task. It takes days. It sometimes takes weeks to pull that together and take that through. So yeah, it's an incredibly important part of my job. Really important

Adel Nehme (34:51):

Part. Yeah, I couldn't agree more. It's an additional skillset to have as a leader that is extremely important that no one tells you need to have. So I do want to take questions from the audience, but I'll ask one final question from my side before we get started. As we close out, what is one single piece of advice you would give to analytics leader or a learning leader or any leader on here on the call for that matter when it comes to building an effective learning culture? Denise, I'll start with you.

Denisse Groenendaal-Lopez (35:23):

And I think it goes to understand your audience. What is burden for them, what's important for them? And just really bring that awareness also, not just for their unit, but what are we trying to achieve as a function, largely, what are the challenges that we have, broadly speaking, but also internally, where do you want to start? Have some really alignment with maybe a career framework that you have different skill sets or levels, but I think it's really about being with your audience, understand what's top of priority for them and just stay super close to them.

Adel Nehme (36:04):

Yeah, that's awesome. Mark, your single advice,

Mark Stern (36:08):

Just keep checking in with yourself that you are continually learning and continually driving forward yourself and you're continually curious and share that enthusiasm with the people in your team.

Adel Nehme (36:21):

Great. Russell, your final advice

Russel Johnson (36:24):

To sum it all up? Yeah, I think just I mentioned just like last year, I mean sort of history kind of threw us a bone with AI suddenly becoming top of mind for everybody. I would say for organizations that are, if you really find that you're struggling to create an L and d type of function that can advance skills in data and data science, don't be afraid of using those pain points or that misunderstanding or things that people are worried about in order to say, Hey, I'm doing something more than just creating a general l and d program. I'm solving a particular business problem or a particular business fear or a particular business pain point. And then get as specific as possible with your executives and say, this is what I'm trying to do. I'm going to solve this problem. And then use that to springboard yourself and your program into a broader l and d function for data and data science.

Adel Nehme (37:13):

That's great. So we're going to get a lot of questions from the audience. Please, everyone do use the q and a feature. There's already a lot of questions shown, so I'm going to have a question from Reen, which I think is going to be really relevant. How do you build a data literacy culture from scratch when a large proportion of the workforce are unfamiliar with data literacy? Where do you start, Denise, I'll start with you here.

Denisse Groenendaal-Lopez (37:36):

Yeah, and I think we did that a couple of years ago with some topics, and I think this is great when we build some foundational programs and you try to put cohorts of people or business units, but you are really driving a lot of communications into let's build this together. We want to build this foundational level because of this always tied to the relevance, why now, why these? But I think if you do it as part of, you're not alone with this, right? You're more, you're one of those who want to build this foundational knowledge. If you do it as a group, always thinking what is going to be the benefit for yourself, but also for your team? That's how we did it and how it really paid off.

Adel Nehme (38:20):

That's great. And maybe Mark Russell, do you want to expand on that? Okay. Russell, I'll start with you. I'll pick one. Yeah. So Russell, yeah. Oh

Russel Johnson (38:33):

Yeah, sorry.

(38:36):

I love the question and thank you for the person that asked it, right? I mean, what do you do if a large proportion of your employees are not familiar with data literacy? I would turn that on his head and say, well, there is still a proportion of people that are familiar with data literacy within your organization. Find them. We keep talking about peer to peer over the course of this conversation we're having today. Find those people, get them together. And then you've got small embers. You push those together and you can get some light and heat from it, and then use that as the foundation. These are the people that are interested. These are your future evangelists. And then look at where they're in the organization. If they're confined to one fairly specific part of the organization, that's one problem to solve. But if they're more generally spread, then you're closer to that kind of transformation than you think you are. You just need to push those embers from a common fire back out into the organization and sort of just add oxygen.

Adel Nehme (39:33):

That's great. Mark, your final note here on this one.

Mark Stern (39:36):

Yeah, look, there's always going to be a large portion of the company for the people you work with who aren't data iterate in some ways or form. Our job is to try and to get that data easy accessible for them, but also help 'em understand it, interpret it. That's tough. Sometimes it's tough, but you have to spend time and effort weeks, months with people to help 'em. But your job is, as a data analytics expert, is to build up your own credibility, your own brand. So people start coming to you for help and advice. That's the best thing I do. And that takes time and most good things. It takes time.

Russel Johnson (40:23):

So

Mark Stern (40:23):

True. It's well worth the effort when it happened.

Denisse Groenendaal-Lopez (40:27):

And I would add one final remark that it's also a lot of communication because this is basically a building block that is going to allow you to continue right into really becoming better and achieving what you want to achieve faster. So that's also a very powerful message to give them hope to acknowledge it's going to take you time, it's going to take you effort. But I think if you focus the communications on that level, it's also a nice powerful statement. Right.

Adel Nehme (40:53):

Yeah, I couldn't agree more. Another question here from Katie, it's a pretty strong question. It was mentioned in a previous session about change management. How can we encourage senior members of the team, so leaders to upskill their data literacy instead of passing it off to junior members as they assume we are more tech savvy? So yeah, maybe a broader question, how do you approach the data literacy of senior leadership rather than the broader organization? Denise, I'll start with you here as well.

Denisse Groenendaal-Lopez (41:27):

Yeah, it's an interesting question because I think if you got to be senior, it's because you've demonstrated some behaviors. That's what we want. And you also are curious and you're learning and you're being part of the learning culture. So I don't think we've had that particular challenge here, but I think even if we do, like I said, there is no escape that you're going to be involved. And whether it is your direct reports asking, can I go to this conference? This is going what? I'm going to get knowledge internally, there's plenty of opportunities. So eventually you end up being part of something, even perhaps a bit of peer pressure in a way if you want. But I think it's just so natural just to hear if someone is having the results that you also wanting to achieve. Yeah, I think it's really, you're going to give it a benefit of the doubt and at least try it. So yeah, I don't think that's a particular problem we [email protected]. But yeah, if we had, we'll tackle it that way. And also, everybody understands their role in development here. You as an individual, you drive it, so you're also able to push your manager for more feedback or insights, but you as a manager also understand what is your role into driving and menting knowledge as well. Right?

Adel Nehme (42:47):

Yeah, that's awesome. Mark, maybe how do you approach building the data literacy of leadership profiles?

Mark Stern (42:55):

Well, I'm not unsure what that means, but I don't know. Yeah, I don't understand the question, sorry.

Adel Nehme (43:10):

So no, maybe how would you approach building a learning culture when it comes to data literacy for more senior people within the organization rather than more junior folks?

Mark Stern (43:22):

Understood. It was also about route change, right? And so for me, we have a team philosophy and a part of that team philosophy, and it was built by members of the team and myself, is that is our job to change people's minds with data and analytics. That's one of our key roles.

And so that includes me and includes the whole team. And so the way you present the way, you have to understand the political environment as well. So some people may firmly believe that something is right, even when they don't know they've invested. You have to know that they've invested a lot of effort and stuff. And if your analysis is going to show the opposite, then you need to be aware of that and communicate accordingly. And so today we had two pieces of analysis that was presented, one, which was to do exactly that. It was such a difficult piece of analysis to do. A lot had been invested, and basically it said it didn't work. That piece of analysis changed the people, changed the minds of the people and changed the actions. They actually reversed what they did. And then the other thing was really nice, a piece of analysis around someone called Caitlin Hanks who's actually changed betting behavior.

And she showed that, and suddenly that sparked ideas and sparked change within the organization. So two very nice piece of analysis that are driven, actual, actual change. And so that happens at every levels of the organization. It's my job to help do it at the senior level, but it should ripple down to if you learn it at the lower levels, and actually it will ripple up to when, if that's where you choose to be, if you want to be a data leader at the end of your career, then that also will be an important part of your learning process.

Adel Nehme (45:16):

That's excellent. I'm going to ask one more question, but I'll only direct at Russell since he spoke quite a bit about hackathons for hackathons, unique people who like to share and are good team players and are engaged within the organization. What's the best approach to encourage these individuals in the team to share their knowledge with others? So what worked with you in the past Russell and creating kind of engagement for hackathons?

Russel Johnson (45:38):

Yeah. Yeah. I mean, maybe just push back a little bit on the question actually. I think the presumption in the question is that you need to be an evangelist in order to even participate in a hackathon. And I think a good hackathon isn't necessarily that way. Some people are volunteers, some people are voluntold, some people are smoothly incentivized in order to participate. Call it what you will, right? Something we did when we had a hackathon around ai, the whole thing was generative ai. That was our second hackathon from last year, I believe it was in October. We had a lot of great ideas, really broad base of support and entrance from around m and s. But because of the generative AI aspect of it, one thing I really pushed back against was we had a lot of great ideas within the data science team. We've got a team around 45 people here, and they just wanted to create their own teams.

And I'm like, we can't be like the, what was it, the 1988 US basketball entrant into the Olympics. We have all athletes competing against non-professional amateurs around the rest of the world. So what we did is basically say we can't have that kind of one-sided evangelism. Don't just get the people who know facing off against the people who want to evangelize and have actual business problems to solve. So we integrated the two. We asked every single person on the data science team to go out and find somebody in the business who wanted to be part of the hackathon and then support them directly as their personal data scientist for that particular team. And what we found is there's a lot of people on the data science team who probably wouldn't have been that comfortable getting out and sort of becoming that evangelist. But because of that sort of volunteering, we had a much broader base of support, better technology on display, much more rigorous measurement programs in place, and pairing the evangelists with what do they the willing with the worthy, right? Yeah.

Adel Nehme (47:42):

That is awesome. I couldn't agree more between there's no escape and being voluntold. These are all great taglines. I want to say a huge thank you for everyone who attended this session. A huge thank you as well for Denise Mark Russell for joining us and sharing these insights. Everyone do give our speakers a lot of love with the emojis, with the chat, as we can see, it's all blowing up. I really, really, really appreciate everyone who's joined us so far. And everyone tune in for the last session of the day on data governance and then we're going to have an A MA with the data camm founders at the end, and very excited for the next session. Thank you so much everyone.

Russel Johnson (48:18):

Great. Thank you. Thank you. Thank you. Thanks everyone.

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