Adidas

Adidas
We spoke to the Director of Global Digital Analytics at Adidas to talk about all things data and what the Skills of Tomorrow look like
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 1. Please tell me a bit about your role and your key responsibilities 

I am the Director of Global Digital Analytics at Adidas. I work for Adidas in the Global Headquarters, on the e-commerce site.

Adidas built its own e-commerce platform which covers all the markets from Europe to North America, and emerging markets like the Asia Pacific, Russia and Latin America. We have a central template for the structure of the e-commerce experience. And there's a whole team of about 100 people dedicated to doing digital analytics.

The principle of Adidas is to internalise capabilities as much as possible. We've got our own data science team, and we're building all the tools ourselves. In the beginning, we do get some support from external consultants. But then to run the tools and build capabilities is all internalised as much as possible.

We've got a team of four trading entities: marketing analytics, business performance analytics, traffic analytics, and we've got functions within analytics, that are specialised to cover the whole of the e-commerce platform.

And for me, specifically, I've got a small team that is growing because I'm covering the rest of the world. As much as we are a global team, it's very much skewed to the key markets in North America and Europe. And there's very little time for the rest of the world, being Latin America, Russia, Asia Pacific and other emerging markets.
I'm building capabilities or supporting those markets by sharing the global framework and best practices.

Our capabilities are mainly skewed towards experience optimisation. So within the whole of digital analytics, one function specifically is the one driving value, which is optimising the conversion rate on the website, making sure we are delivering the best experience possible so that the consumers buy as much as possible, and they don't encounter any issue during their navigation on the website. I do that for the rest of the world market.


2. So if you look at your specific team and their specific capabilities, what do their profiles look like in terms of analytics skills? What are the differences with the roles? 

We're looking at the typical analytics roadmap, where you start at the foundations, which is performance reporting. Building performance reports, aligning the KPIs with the global team. To regularly show to the business where we are doing well, where we're not.

That's the first basic function. Then we move on to experience analytics. So we look at the experience and what insights can help drive an increase in our conversion rate.

You also have traffic analytics, which becomes interesting when you look at marketing analytics. How can we optimise the channels, the marketing channels that will drive the traffic to the website?

These are the three basic functions. And then there's operational analytics, for which the definition is not so clear within Adidas, there's a lot of people who have different views on that. People think of operational analytics as only looking at the issues and fixing the bugs.

Some see it as more trading analytics, which is a different animal and being defined within Adidas. Trading analytics is more like product analytics that looks at how you manage stock and inventory. The sizes, the size curve, size, distribution. That’s pretty much the basic function for Adidas now.


3. And within the Analytics function, what do you see as the main capabilities or skills that are growing in importance in the near future for Adidas? 

I think it's kind of a similar roadmap as other businesses, we're sticking to the same pattern. We start with the basic analytics for the moment, we crunch the data. And we extract some insights, then we give them to the business.

We're describing the performance, we are describing what's going on with the data, what we see. And we tell our Stakeholders, this is what's happening, the conversion rate is going down in the cart to checkout. And then we can extract some insight, maybe we should change this, move that button here. So it's very much tactical.

What I see happening in the future is that we'll be so good at visualising and showing the numbers, that at some point, it will be automated. It will be available directly for the stakeholders on a dashboard, all the data will be already described, automatically.

That means that we would be able to dedicate more time to extract the meaning of it. Extracting the insights, and start being a bit more prescriptive.
So you go from descriptive to prescriptive. That's usually in an analytics roadmap.

Then as analysts, we will become better at making sense of the data, which is what the business needs. Businesses need people to make sense of the data, someone to translate what the data is telling us.


4. And within your team, do you have roles to help move from being descriptive to prescriptive? Or do you have functions that help act as a bridge between the business and the analytics teams? Almost like a translator role? 

This is something I'm driving at the moment. And that's pretty new. I developed a sort of spokesperson model. So it could potentially completely change the structure we've designed at the moment.

What I'd like to see is having a single point of contact per stakeholder. That person will provide all the analytics support that that stakeholder needs specifically. So people will not be structured per function or speciality, but they will be a dedicated point of contact with the business partner of the business.

And then they will be able to dispatch or centralise or coordinate the whole analytic service based on the demand, whether it's trading analytics or performance analytics or experience analytics, that person would be dispatching and connecting with the right person within the analytics team to provide support on a specific use case.


5.  So there's a big part in terms of automation and in terms of capabilities. And how do you make it more visual, the storytelling part of data?

We're trying to develop our storytelling and make sense of the data. Also looking at productive, prescriptive insights. So what can we give as advice to stakeholders for the next campaign? What did we learn from our previous campaigns and what can we do for future campaigns? Not only looking in hindsight at the post mortem of a campaign but looking forward too. What can we do to equip you with the best features of your campaign that we know work? So becoming more prescriptive essentially. 

7. The strategy of in-housing and making sure you build your own capabilities makes a lot of sense? Or at least, I can imagine you looking for an optimal model? How can you be most effective while building these capabilities in house? 

That's how our app is all internalised. But you need some experience in apps to build that e-commerce, and apps are a different skill set. And we've had lots of bugs and things to fix before it got to a place where it was a good experience. But then we've got all the experts in-house at some point, and we'll be able to see that.


8. And in terms of building everything internally, how do you build capabilities to build those key skills internally? Through training and development? How do you manage the move to a remote way of working and staying on top as an organisation? 

I mean, there's development, personal development - there's more training, not in terms of skills, but of leadership and personal development. How to deal with working remotely, to manage a team efficiently.

But in terms of the skill set, the technical skills, we get Ad Hoc training. For instance, on the analytic solutions, we often get advanced Adobe training, or advanced SQL training, or Python. But I don't think there's a big emphasis on staying up to scratch, in terms of upskilling, it's on-demand. It’s organised by HR, the training is provided by HR.


9. And finally, in terms of skills, you talk about leadership, and technical skills, but what about mindset? How about digital skills, working in agile ways, focusing on experimentation, and innovating, are these topics of focus for an organisation like Adidas? Is it part of the culture? 

When you talk about mindset, there's a big, big emphasis with Adidas on developing a growth mindset versus the fixed mindset. And there's some very heavy training for everyone to develop a growth mindset. So we're trying to be a Growth Mindset Organisation. And I was pleasantly surprised because it's quite a recent theory, I think, this whole growth mindset outlook. But HR has fully embraced it. And they are providing training. And there's a lot of material to make sure that everyone at Adidas, in terms of the culture, moves towards a more growth mindset, which is good. It's very, very modern.

And it's working well, and it's embedded in the value of Adidas, in team culture, and it's being really, really encouraged and fully supported by the business.

So this, along with inclusion and diversity, and I think we're not there yet (with Diversity and Inclusion). We're not there yet, of course. But we are quite advanced compared with lots of other companies.


At Adidas, there is diversity, for sure. Inclusion is the next step. But there's some intention. There is some good intention there.


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