A leading financial services company embarked on a project to develop a workflow enabling individuals to customize their dashboard. The goal was to create a dashboard facilitating anomaly detection and model mapping, empowering users to efficiently identify the most suitable model.

• Accurate performance summaries needed precise financial data, particularly due to the unique calculations required for each user.
• The definition and collection of metrics were hindered by limited available information. This limitation affected the project's progress, particularly in understanding user requirements and optimizing the workflow.
• The volume of data involved reached terabytes, necessitating optimizations to ensure efficient data access within the required latency. This challenge added complexity to the development process, requiring careful consideration of data management strategies.

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Through data analysis, the team pinpointed spikes, trends, and weaknesses across various stages of the business process, enabling them to propose precise improvements. Also, they streamlined operations by decreasing SPICE capacity and associated costs by 20%, optimizing efficiency without compromising analytical capabilities.

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• Detection of spikes, trends, and weak points at various business process stages
• Reduction of SPICE capacity and associated costs by 20%.