Data tells consumer stories at Unilever

People have rekindled their interest in asking questions.

Tableau: What excites you most about Tableau?
Rishi Kumar, Director of Analytics: It’s true that Tableau is a fantastic product and it gets better all the time, but really it's the promise of innovation, the promise that they're going to take us on a journey to become a much better, much more analytically-minded organization that I think is absolutely the most important, the most fantastic part about it. With their products comes the promise of innovation.

Clearly they're taking a very active interest in their innovation funnel. They're listening to what customers have to say, and they're informing their innovation choices by how people are actually using the product.

Tableau: How do you use Tableau at Unilever?
Rishi: Unilever is a fantastically complicated business from a global perspective. We have products in 170-plus countries. Tableau helps us look at our information and bridge the gap between the global perspective and the local perspective. It enables global managers to drill down into the level of detail that they need to in order to understand the business and make the business decisions they need to make. The beauty I think really is that you're enabling decisions that would not otherwise be available. There's a sort of higher quality of decision-making.

Tableau: How does Tableau help Unilever understand its customers?
Rishi: Tableau's definitely a big enabler of really being able to understand what it is that's driving a consumer to make purchases and how those drivers are changing over time by blending all the data together. Tableau is fantastic at drilldown capability, and it's also really good at providing different perspectives. So people can group products or competitors as they see fit. The flexibility in rolling up from that granular level is also fantastic. You also get, you know, scalability, so we don't necessarily need to invest in many different IT infrastructures globally, we can invest in just the one.

Tableau: How does Tableau compare to the way you did analysis before?
Rishi: The most compelling feature of Tableau to me that as somebody who's analyzing data that really changes the game is data visualization. A lot of the things that could be done with complex mathematics can be done simply with Tableau’s data visualization. Instead of relying on computers and complex mathematical modeling to process information and describe those relationships, we're able to see that data and allow the human mind to process that information and understand the relationships. I really see a shift in the requirements from people who really get the mathematical side of statistics and analytics to people all around the company who just can see pictures and become more analytically minded.

Tableau: What has changed since you started using Tableau?
Rishi: The first major change is that people have rekindled their interest in asking questions. Especially in a big organization where the wheels are turning and turning all the time, we have a tendency to follow process. We're not really questioning necessarily what's really happening in the situation, what's really driving it; we're just looking at the numbers and saying this is how the situation unfolded, pass the report on—step B, step C, step; going through the motions.

I think because Tableau puts the capability in everybody's hands to get answers to their questions, people have rekindled their interest in asking questions. We see a resurgence of that sort of interest in analysis.

The second thing we see is that ability to describe complicated situations in a much simpler way, that removal of the complexity. For example, with Tableau we can easily group all the stores which have a high Hispanic population associated with them or group all the products which are fast growing products.

Tableau: How did Unilever get started with Tableau?
Rishi: The Walmart team in Unilever in the U.S. is quite a data-driven team, people who know how to ask the right questions and are relying on data every day to answer those questions. The story goes they went to their IT department and asked, “Can you guys bring in some tools for us to help us have better access to the data, help people with questions get answers to those questions?” After trying Tableau for 10 minutes, IT knew this was a game-changing tool. Tableau was brought in on a trial period there; they reached success, and it spread quickly throughout the U.S. business. A colleague introduced it to me knowing that I really loved tools. He said, “If you're an Excel geek, you're going to be a Tableau fanatic.” He was right.

Tableau: Can you talk about Unilever’s data architecture?
Rishi: So with the complexity of the business comes complexity of our architecture. We have a lot of companies which were equipped locally in terms of their IT infrastructure, and when those companies come into Unilever through acquisitions or other synergy programs, we have to find a way to incorporate their local technology into a global framework. I've seen more types of systems than I ever thought were possible. So it's quite a complicated landscape from a data, data acquisition and IT infrastructure standpoint.

Tableau: How is the role of analytics changing over time in consumer goods?
Rishi: The consumer goods industry is quite a complicated one, so Unilever is by nature a complicated business. We participate in different categories, sell lots of different products, and there are different competitors of different natures. We've got local competitors who produce specialty products in a single market, and we've got global competitors like ourselves that produce really great products, quite frankly, across the globe. I think that more and more people are looking to data, not only to cut the complexity out of the business at a global level simply by providing a simple aggregate view, but they're also looking to understand consumer trends at a far more granular level.

Tableau: Can you give us an example of the questions you answer with Tableau?
Rishi: For example, deodorant roll-ons are outperforming deodorant sprays. Why is that the case? I think it is a source of competitive advantage to really be able to understand the momentum in the business in terms of its tiny constituent parts particularly in consumer goods—because ultimately it's consumers and their behavior and consumer trends that are really driving performance at an aggregate level. Tableau's role in this case is the ability to bridge that local, small, consumer-based trend to a global sort of momentum-defining trend for the business.

Tableau: How has being able to blend data impacted the way you answer questions?
Rishi: One of the interesting parts about being in consumer goods is that you get a rich variety of data—you get qualitative data about the sentiments of your brand, but you also get really concrete quantitative data about purchase behavior, so what people are putting into a basket through loyalty cards. You also get broader market perspectives through ACNielsen and IRI and so on. It’s important Unilever is to be able to blend all this data together to understand why people are entering the shop, ultimately filling their basket with Unilever products, and determine based on those drivers what are the likely products or trends that we need to take part in as an organization.

Tableau: How does Tableau help you communicate your findings?
Rishi: One of the things that comes with Tableau is definitely the ability to tell stories -- partly because the content is engaging, so people are able to see things they never saw before. They can see what our average prices were all across the globe; they can see which competitors have popped up in certain markets; that’s all there.

With Tableau, there's a phenomenal amount of information being displayed visually that would be almost unmanageable if it were in a PDF of numbers. So II certainly see a lot more information and a lot more interest coming through, and really it is because you're able to use these really information-rich visuals to tell stories.

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