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Volvo Cars

Case study

Client: Volvo Cars
Industry: Automotive industry
Challenge: Obtaining timely, consistent, and reliable information about the performance of their dealers.

Volvo Cars Netherlands makes all operational processes visible and measurable with Qlik

Volvo Cars in the Netherlands is the importer of Volvo passenger cars in the Netherlands. Measured in 2013, Volvo Cars Netherlands had a market share of 5.8 percent with more than 24,500 cars sold. Cars are imported, marketed, and 106 dealers are supported from the headquarters in Beesd. Market conditions in recent years, including the crisis, have forced Volvo Cars Netherlands to make significant efficiency improvements.

Hanneke Brefeld, Manager Business & Process Planning at Volvo Cars Netherlands: "Around 2007, I worked at Volvo Cars Netherlands as manager of the Knowledge Center. In that role, I discovered that there was still a lot of room for improvement in the timely and regular delivery of available information about the performance of our dealers. A report was manually compiled every six months.

A huge efficiency leap at low costs
Hanneke Brefeld
Manager Business & Process Planning

From Excel to Microsoft Word

For this, different people provided information in their own format. It took us a month to collect all performance figures per location and present them in a report format. This also meant that employees visiting the dealers did not always have the most recent information. Additionally, there were no uniform criteria. One employee counted an ordered car as a sold car, while another counted it only upon delivery. This led to discussions about the reliability of the figures.

Volvo Cars Netherlands had already encountered Qlik due to a success story from Volvo Cars Spain. René Traa, IT & Facility Manager at Volvo Cars Netherlands: "Although we were slightly biased, we compared various BI solutions. Our highly fragmented IT environment was decisive in choosing the Qlik platform. With Qlik's BI solution, it is possible to quickly build analytical applications with data from a large number of different sources without the need for a data warehouse.

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