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Bol.com improves its product every day by measuring user behavior and identifying opportunities for improvement. They were using an expensive external tool to track and analyze user behavior. The tool worked, but not perfectly. They wanted to switch to an in-house tool based on Apache Kafka. It offered more possibilities, but it was much more complex to use. Our role? Make it easier.
ASML builds extremely advanced machines called scanners. These machines produce wafers, the core product in semiconductor manufacturing. ASML wanted better insight into the performance of these machines to support a new type of service contract. The idea is simple: higher machine performance means more wafers produced, which creates more value for the customer. With this model, ASML aligns the interests of both the company and the customer. But what exactly is performance? It is the connection between machine uptime and machine productivity. In the past, this connection was made manually by a domain expert with more than 20 years of experience. To understand performance across the entire fleet of machines, this process needed to be automated.
ING is committed to equal opportunities and equal rights. They wanted to better measure and address the gender pay gap (GPG). While they had a proof of concept and an annual script-based tool, it was not flexible or always reliable. The goal was to develop a robust, user-friendly tool that provides faster and more accurate insights.
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