Nike's $25 Billion Blunder: A tale of misusing data

In this episode of the Definitely, Maybe Agile podcast, Peter Maddison and David Sharrock discuss a fascinating case study of Nike's digital transformation gone awry, resulting in a $25 billion loss and 32% market share decline over three years. They explore the pitfalls of over-relying on data-driven decision-making while neglecting other crucial aspects of business strategy and customer engagement.

This week´s takeaways:

• Data-driven decision-making is valuable, but you need the right data. Companies need to balance quantitative data with qualitative insights and intuition.
• Optimizing for existing customers isn't enough for growth. Businesses must also focus on attracting new customers and exploring adjacent markets.
• Organizational culture plays a critical role in transformation efforts. Companies need to foster an environment where employees feel empowered to speak up and challenge prevailing narratives.
• Not everything that matters can be easily measured. Organizations should find ways to understand and manage important factors, even if they are difficult to quantify, rather than ignoring them in favor of easily measurable metrics.

Resources_ 
Nike’s $25B blunder shows us the limits of “data-driven-  https://uxdesign.cc/nikes-25b-blunder-shows-us-the-limits-of-data-driven-ad30b6e3d938

Chapters

• 0:04 Data-Driven Decision Making
• 6:59 Challenges of Data-Driven Decision Making
• 16:46 Cultural Considerations in Digital Transformation

Transcript

Peter: 0:04

Welcome to Definitely Maybe Agile, the podcast where Peter Maddison and David Sharrock discuss the complexities of adopting new ways of working at scale. Hello Dave, how are you doing Very?

Dave: 0:14

good. You caught me in like I was just about to get all worked up about the topic we're going to talk about and you said hold on, we've got to record this. Yes, I know what are we talking about. What are we talking about? What are we talking about? Let's pick up the energy again, okay.

Peter: 0:28

Well, so there was a. There was an article, uh, that I shared a little while back with you, and we were just uh re-reviewing it and I thought it was a very interesting article, partly because I thought it was very well written. So I'll definitely uh add this to. It was on medium and uh, and we'll put the link in the show notes, and the article was about Nike and it was about a set of decisions that effectively led to a $25 billion loss and 32% of their market share, and it's interesting how this came about. So why don't you give your take on it?

Dave: 1:04

first, and I just wanted to add in three three years.

Dave: 1:06

Yes, like when you know, and and it's not. It's not market dynamics, it's, it's really. And so so the the story behind this is data-driven decision making and I think this, you know, we talk about digital transformations, we talk about data-driven decision making versus sense making and that sort of you know, the talking to customers and understanding how they view things and so on, sort of that empathetic, not data-driven but gut feel, intuitive conversations versus real data. And both of us academic background, we can come in and we can do maths when we need to. Data-driven decision-making hugely important. We need to be able to make decisions based on real data. So, on the face of it, nike's push to digital-only focusing, you know, sacrificing the wholesale business moving away from a whole range of different product categories to be about shifting.

Dave: 2:02

Let's call it footwear for the minute, but shifting their product digitally and online driven by marketing that can be proven to be working from a data-driven perspective.

Peter: 2:13

There's a lot of things there that if we sat and wrote those down, we might be resonating with yeah, you'd end up with the traditional strategy that, from an executive perspective, we want to streamline, we want to reduce operational costs, and, in fact, I think this was the advice that one of the large consultancies was coming in and giving them, which was rationalize all of your operations, make this simpler, and you've got way too many specialists who know far too much about all these different types of products you've got.

Peter: 2:38

Let's just simplify it all and just have one consistent product stream, and I think there's also a moment in time that this is happening. So, consistent product stream, and I think there's also a moment in time that this is happening in right, like so 2020, they're like oh, we got a shift to digital online, so that probably had something to like drive them towards this direction to make it sound attractive too. Um, but it's the the consequences of that and what it led to wasn't the intent, but it why that is the case Because, as you say, data-driven decision-making is something that would typically come in and promote this. I mean, data is critical. Understanding your baseline of where you are and working out how you're going to measure as you move forward so you can see how you're progressing those are valuable things to have.

Dave: 3:19

And I think so we'll talk about the sort of segregation of when to use really heavily focused on data, and when not to later on in our conversation. I'm sure I think what you're saying is absolutely correct is if you're in an, if your business right now doesn't have lots of data at its fingertips, get lots of data at its fingertips right. Make sure you've got access to lots of data real time. You know, really see what's going on. Things are moving very, very fast and we need to see that happening. I think what's much more intriguing is if you think about this huge push to digital. We've talked a lot about digital transformations and how to do them, but there's also this element of you know what does push to digital mean and I think this is something that we're seeing in lots and lots of organizations which is the push to digital mean and I think this is something that we're seeing in lots and lots of organizations which is the push to digital is a cost reduction strategy. It's we don't need X, we don't need Y, we don't need Z. If we do this digitally, we start leveraging technology. We're going to save a whole bunch of headcount. We're going to save. You know, we're going to cut through and go straight to the market.

Dave: 4:25

What was interesting when you look at this story is you know it's like the beginning and the end. They've got that optimized there, but they're not thinking, you know, upstream and downstream. And what struck me as I'm thinking about that is, I think, of a user story mapping. We've done this all the time. I think you were saying you were just coming from a session. This week.

Dave: 4:44

User story mapping, creating a customer journey, makes the same mistake which is the very first post-it note on nearly every user story map I ever see is download the app or land on the web page and so automatically. Now we're optimizing for existing customers or prospects coming into our buy flow, and so now we're looking at how can we make that experience as great as possible while reducing the cost. All of which makes sense, but what we're missing is how do we get those individuals for the very first time to land on our website?

Peter: 5:22

slash open and the reason mean. This is where we can look at things like why is nike a household name? I mean part of it, and I know netflix made a uh documentary on this not too long ago. I think it was netflix around uh sort of michael jordan and the air, and it's like that people were bought into the idea of I too could jump as high as a michael jordan. I could like is a. This makes me as like, gets me into his shoes, so to speak. So there's a, there's this whole buy-in to that feeling of being a part of that, of being part of something, and they I think some of one of what they were sort of missing there is that they threw all that away. It's like, well, we don't need to understand, like, where our customers come from, from why customers might like us or how we buy them into that. Um, we can get rid of all that we. So they got rid of product categorizations, they got rid of sort of, and they just streamlined everything. That it's storytelling.

Dave: 6:18

I mean nike is is, this is. I think, before we started this, this recording, this is what I was getting like. Ah, because it's about the mystique of nike is is is. The storytelling is these incredibly inspirational moments that were being created with no intention of selling a product I mean of course there's an intention of selling a product but it wasn't, oh and by the way, you can get these ten dollars off, or anything like this.

Dave: 6:44

It was hey, you want to be a part of this community, this mystique that we're creating and, of course, that generated. Now we follow through and we all understand what the swoosh means and we all have at least, you know, in the last. Those of us who are exposed to nike in the last few years maybe don't see it that way, but those of us us who've been around Nike for decades recognize it as this different iconic, like a mystique around an experience, and I still am struggling to understand how that could get given up because of let's call it, the data geeks and the quantitative, like we've got to do all of the maths right.

Peter: 7:23

Let's call it the data geeks and the quantitative like we've got to do all of the maths right, yeah, and that's actually what I quite liked about that article as he was going, because he really did dig into some of the things that he believed would be some of the reasons behind this. And there are things that we encounter quite a lot when we go in and do change within organizations. There's things like, well, people don't feel like they have the power to speak up against the prevailing narrative. So there will have been people inside of nike going like this is stupid, like you're, you're throwing all this organizational knowledge away, this isn't going to work, but I want to keep my job and especially at the moment in time, this is happening over the last three you can see be like. People are going to be like, well, I'm not going to speak up against that. I'm like I want to get paid.

Dave: 8:09

I almost feel I think there's, like you know, I think both of us are huge fans of good data-driven decisions. Yes, but the data-driven decision-making is an element. It's something that I bring to the table and we kind of validate our ideas. I also think there has to be plenty of room for the other side of the equation, and not just occasionally. It's almost a 50-50. There's that fantastic quote from 100 years ago, 100 plus years ago 50% of our marketing spend earns us nothing.

Dave: 8:45

We just don't know which 50% it is, and I'm paraphrasing there, but that is actually as true today as it's ever been. 50% of our decision-making should be data-driven that we can measure and we can see the benefit of, and 50% should probably be much more open to interpretation or a sense-making type of mindset. And again, there's lots of reasons why we may want to support that sense-making, but we can't shut it out.

Peter: 9:12

Yes, exactly, and that innovation piece right. One of the problems of the data is you're looking at what's happened, right, and if you've got really good real-time data, you're looking at what's happening now, but that's the best you're ever going to do with the data. What you look to do with that data is to try and start to be predictive about what might the data be telling us about where we go. Yeah, but that's how gambling works, too right. We're predicting the future.

Dave: 9:43

What are the odds? Well, I kind of see two different fields here. So, going back to that user story map of once, we have somebody coming through the door, how do we optimize their experience, their journey, so that they come out with a super fantastic experience and, by the way, they've got our shoes tucked into a bag as they walk out of the store or whatever the journey is? I think data plays a huge role in that whole experience, because that is something that we can measure very closely, we can observe, we can see what's going on and so on. So there's a lot of benefit and this is the sort of low hanging fruit. It's cost optimization, not necessarily as aggressively as we've seen in some conversations that we've had or discussed before, but there is. There is very definitely an optimization argument there, heavily skewed towards data-driven decision-making, but that's not the strategic element of digital.

Peter: 10:44

And that's where you need to have also a conversation. You need to go and talk to people, find out like well, why did you come to us in the first place? Why didn't you go to the competitor? Why did you download the app? Why did you go to the website? Why did you like? What were the causes behind that?

Peter: 11:03

And you're not going to get that from the data. Well, you could potentially get it if you ask the survey at the end, but not everyone will fill them out and stuff. And if you really want to start to get good, you're going to have to do other things, and I'm sure Nike was doing focus groups and other pieces like this and going out. They must've been like to try and capture that, that sort of that feedback, but were they? Was it just not being fed back into the system as a and not in correlation with the data they were getting from the system that was driving that? Was it that because they got rid of all of the specialists who really truly understood the different areas and spaces, they didn't have the people who understood that they needed to go out to different places or experiment in different areas or weren't thinking about this in a broader sense that that was kind of potentially driving them in the wrong direction.

Dave: 11:53

Well, I'd also argue that there's even the exploration side of things, which is not everything that you're describing. There is still quite intimately connected to, you know, customers in our ecosystem, if you like, or prospects in our ecosystem. And what I also wonder about is how do you explore adjacent industries? How do you explore industries which are totally different to whatever the space is that we work in, but that have similar ingredients? And I find that those are the really interesting ones. This is where those leaps forward in terms of understanding. You know how to either merge different technologies together to create a different experience, or changing the business model. And when we talked in previous um podcasts, we've talked about, like the key different digital transformation sort of plays, if you like. Well, some of them are business model play changes, like significant business model changes, and they don't come from data analysis of who you have today. They come from what are we seeing in the outside world. What can we learn from that? How can we maybe leverage what we do brilliantly well and then add in something?

Peter: 13:05

unusual, and so you need those people who understand what you do brilliantly. Well, yeah, because if you don't have those anymore, if you've optimized your system purely based off the data, then you're not going to have the people who understand to start to ask the right questions right and to start to think about what is going on. It's a fascinating situation that they managed to put themselves into. I thought there was this, the whole conceptual piece of what it sounds like they did. They took data, optimised everything for efficiency, purely focused on who comes to us and started to ignore everything else outside and, as a consequence, people stopped buying.

Dave: 13:50

Well, I found it quite interesting. I think the consequence is they're optimizing existing customers and you don't get growth through optimizing existing customers. You increase sort of you know basket size, lifetime value of your existing customers potentially, and one of the other things they were attacking their margin, because moving online is their discount driven culture. So you've kind of got these different pressures at play.

Dave: 14:13

Yes it's a. I mean it's also one of those things which, with hindsight, very easy to kind of look at and I'm sure when you're in the middle of that whole process maybe it's not as clear. Maybe there are many different kind of you know drivers that can come to that. The drop off of online perhaps was much steeper than it was expected, but the post-covid who knows there could be a number of different trends coming through yeah, and it's fascinating, like from a perspective of the organizational piece here around.

Peter: 14:49

How did they? They did do a lot of the right things in some ways, but they're the entire conceptual idea that the where I I don't know if it looks like it now, but the removing product categorization I found like kind of an interesting thing. Concept, concept, so effectively, our products are the same for everybody. It's one size fits all, which that's? That's an interesting concept in itself, because you're, you're now basically saying that whoever you are and you're not special to us, kind of there's a yeah, there's an element of that. You look at it from the customer perspective the other way. It's like, yeah, you go and say, well, you don't have what I need, that you, you're not speaking to me anymore, right? You're. It's, um, because if you get rid of all categorization, I know how do I find the thing that I want that you have? Right, because I'm not. There's no way of me easily going through the system to find it even. It's like, and if everything looks the same for everybody, then what am I going to do?

Dave: 15:47

so you've made it hard for the customer yes, absolutely yeah, and it and it's a kind of against the grain for where many organizations are going. It's this sort of micro communities or micro uh perspectives on that.

Peter: 16:01

So yeah, like trying to, you've tried to form the community around the thing that it is and buying people into that. That viewpoint to capture all of our very limited attention spans.

Dave: 16:14

How are we going to summarize this? I think we've talked around this quite a bit. How can we summarize it?

Peter: 16:20

Well, I think one of the key points for me is that data-driven decision-making is very, very important. You do need to gather your data. You can't just look at your data, though, because it is only giving you predictions of the past. You need to have other things in your system of knowledge and understanding beyond just collecting the data and looking at the past. You've got to as simple as that. I think that's one of the really, really key points.

Peter: 16:46

One of the other points was in the article, and we didn't quite touch on this, was the, the whole conceptual idea that you can't manage it if you can't measure it. Yeah, and which isn't true. Like it, just because something is difficult to measure doesn't mean that you shouldn't find a way to understand what that thing is, and so. So that's another piece as well. Which was kind of thrown out of. That is that it's not enough. Don't try to just don't ignore something just because it's difficult to measure it, and then, if you focus only on the easy things that are easy to measure, that'll almost certainly drive you in the wrong direction. Yeah, I agree.

Dave: 17:26

I think I'm gonna add something into what you're just describing there. I don't know if this uses our third one up or it's just an additional one. If you had a third but.

Dave: 17:35

I just wanted to come back to that. There is optimization and kind of the quick wins and improvement of how do I make our process, our experiences better, very much driven by data plus those anecdotal sense-making type of input, but a lot more data-driven. But strategically, I think we need to be much more aware that you're unlikely to really understand because the pool of where you pull the data from expands dramatically when you start looking at strategy, at what's the purpose of us becoming digital. So there are a whole bunch of digital transformations which are really cost cutting, slash efficiency transformations. There are a much fewer number of digital transformations which are actually digital shifts in strategy or strategies shifting towards a more digital experience slash organization.

Peter: 18:32

And I think that's a beautiful lead into what I would do as a third one, which would be around or fourth now, I guess. But here's around the cultural elements of this. Like if your culture isn't designed to allow people to speak up, if you're transforming and changing and significantly going in a different direction, but you have a culture where it's saying hold on a sec and having the comment isn't allowed, or even if there are external drivers that are making that harder to do, you're putting yourself massively at risk at that point.

Dave: 19:06

So really, you really take a very close look at your culture as you go through these types of changes and think about that and I just because we should probably have another chat about that one but it's almost like how do you make sure you've always got somebody being devil's advocate and making that voice visible, like if you heard audible.

Peter: 19:27

Yes, yeah we could definitely have another one. We could talk about the Disney game game talk about disney, perfect.

Dave: 19:34

Well, thanks again, great article.

Peter: 19:36

I really love that article so, yeah, we'll make sure to include it. Awesome thanks everybody. You've Definitely Maybe Agile maybe agile, where your hosts, peter Peter Maddison and david David charrock, focus Sharrock the art and science of digital agile and DevOps at scale.