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IR BERLIN SUMMIT Rajesh Kumar of adidas on big data in merchandising

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Senior European retailers are gathering in Berlin for the first InternetRetailing Summit to debate and discuss the current state and future development of ecommerce and multichannel retail. Today we hear today from Rajesh Kumar, vice president merchandising concept to consumer, at adidas Group. Rajesh will be moderating a session at the Summit on using big data to understand the consumer.

InternetRetailing: At the InternetRetailing Summit you’ll be moderating a session on using big data to understand the consumer, and using those insights to merchandise products. Can you tell us some more about that, and about how you use this at adidas?

Rajesh Kumar, vice president merchandising concept to consumer, adidas Group: I classify data into three: hindsight, insight and foresight. Hindsight for me is historical sales information which you generally use for the future season planning. Now we are trading spring summer 2016 and you might use this data to plan for spring summer 2017.

Insight is information for making the decision today – you see something is selling very fast this week: how can you use that information to make decisions for next week or the coming weeks?

Foresight is information thinking about the future, where the big data spectrum comes. Foresight information for me was classified as social media data, digital touchpoints in the stores, and so on. How could you use the foresight information combined with hindsight and insight to make a better position in merchandising?

We’re now trialling a solution around that in 10 stores including New York, London, Paris. Shanghai, Tokyo, that will help to inform which products are carried in each. This takes out the emotional decision because you have a data-based decision. However, I would not make the business decision only on data – data is the science part, while the art part is what the team thinks, and many other factors. It has to be a combination of them all.

IR: Why is this a particularly important subject to consider at the moment?

RK: Look at Airbnb and Uber. The more you understand your data the more efficient you become. Today’s it’s more relevant because if you’re not efficient, no matter how big you are you don’t have a future. It’s important for everyone in today’s world to be efficient.

IR: One key trend that’s developing in this area is the use of social media analytics. Can you tell us about that?

RK: Today everything revolves around social media. Facebook has a big population bigger than countries, while Instagram is growing fast as well. There are different ways of looking at social media analytics. You might look at a particular product, and see what consumers are tweeting about it. You can look at a data crawling method, just take one location, London, Oxford Street, for example. Or you can go and search for people who have gone in and tweeted from this location in the last 15 to 30 days, and look at their interests, and what they are tweeting and many more factors. The same thing can be done with Facebook, or other social media analytics.

When you do this there is a lot of fluff that has to be carefully segregated. You have to know what you really need, and you have to have a clear picture in your mind of what you are looking for. Then it becomes more crystal clear. It’s a big ocean – when you’re diving into it you have to be very clear that you’re searching for exactly this pearl at the bottom, rather than swimming the entire ocean.

IR: It can be overwhelming – and I expect retailers will be asking you about that in the session. What other big questions do you expect participants may raise?

RK: There’s a saying that big data is like teenage sex: everyone is doing something, so people think we have to do something about it – but noone knows exactly how to do it.

People will say yes, yes, I understand we have to do something, but what do we actually have to do? There’s a lot of fluff around it and I hope questions will come from any direction. As a moderator I expect I’ll hear questions about how it can be used, what can be done, what is the methodology, and so on. How can this be used mostly on product placements and to make decisions on assortment planning? Maybe people will also say how can we get a tangible benefit out of it? Can we get an end result in terms of consumer satisfaction or more sales?

IR: How do you see big data continuing to influence merchandising into the future?

RK: I’ve been in this area for the last 24 years. Historically there was a belief that you have to be in the store, in the region, to do business as a retailer with shops. A merchandiser’s job isn’t just an office job – you should be looking at stores and consumers. In many markets people have believed that you can’t centralise merchandising – you don’t know what the market needs, what the consumer needs – you are making the decision for someone else.

That decision has been challenged in many fields. If you look especially at people like Zara and H&M, they have come with a very centralised model from day one and very successful at what they do. But if you look at brand retailing, adidas, Nike, Calvin Klein, Hugo Boss – they have a very decentralised DNA. The belief was that you need to be in the region to understand the region. But in the future if you want to make efficiencies, you’ll need to centralize. Equally, if you can’t centralise you won’t be able to make effective decisions centrally because there won’t be enough data available.

You can sit anywhere in the world and know everything and anything about the consumer as long as you have the data. This will be a big paradigm shift and you will say you don’t need to be in Timbuktu to know about Timbuktu. You can be anywhere in the world and know anything. That’s a big paradigm shift in terms of how you run things. People will tell you 90-95% of the things you need to make business decisions.

That’s how I see this plays a big role in the future of merchandising. So companies that have not centralised merchandising because they believe they couldn’t centralise because they don’t believe they have enough market knowledge at the centre can now, because by using the spectrum of big data they should be able to have enough knowledge about the consumer in a centralised function.

Rajesh Kumar, vice president merchandising concept to consumer, adidas group, will be moderating a session on harnessing the power of data in merchandising at the first InternetRetailing Summit, to be held at andel’s Hotel in Berlin between June 27 and 29.

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