Case study

Category Management dashboard for Coca-Cola

Interviewee: Ineke Kuijpers, Sr Category Manager for the wholesale partners of CCEP.

The challenge

We have built many dashboards for the Category Development Management department within Coca-Cola European Partners (CCEP) in recent years. The challenge was to link large datasets together so that they could obtain insights from them on a structural basis. For the assignment to gain more insight into the market share within certain channels, Ineke Kuijpers, Sr Category Manager for the wholesale partners of CCEP, was our contact person and client.

Main role

”As a Category Manager, I work as an independent consultant with our customers to see how we can grow the entire soft drink section. In order to provide them with the best advice possible, we use data that they share with us. It is important for us and for our customers to gain as much insights as possible.”

Tackling the problem

Retrieving data can be a labor-intensive process. The more time you spend on it, the less time you can spend analyzing the actual data. But that is precisely what is necessary in order to pinpoint the sore spot or to spot potential developments. The result is that you can put in many hours and sometimes make decisions based on only 50% of your available data, while the ideal situation would be to do this on the basis of 80% or even 100% of the data.


Linking different datasets in this dashboard helps me to better understand the impact of certain activities as well as to what extent these activities help the customer to grow. I now spend much less time with the “raw” work, I can spend more time analyzing the data and translating the insights into concrete advice. This enables me to proactively manage projects together with the customer.

The dashboard made me realize that you should always look for as much data as possible. During the process, we were asked carefully what information we wanted to see and whether we could extract it from the data. This also continuously challenged me to think about what was important to me. The result is a dashboard with information that is much more valuable than if you were to analyze each data set individually.

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