[4893] Data Analysis and Reporting

Start date: April 2025

Clearance: NATO Secret

Location: The Hague

Effective business performance tracking ensures NDWC has clear visibility and control in the execution of its strategic objectives and covers business topics such as: financial health, resource allocation, cost management and other quantitative business assessments. These insights are essential for strategic decision-making, aligning financial & human resources with business priorities and ensuring we stay on the right course. The scope of user stories will cover, amongst others, the following areas:

• Budget analysis and monitoring
• Cost management and tracking
• Resource management and optimization
  
  
  

Product Portfolio Monitoring and Control:

Monitoring and controlling the product portfolio provides a structured approach to evaluating SLA compliance, project outcomes, and service performance. This ensures NDWC meets business expectations and enables NDWC to match the correct resource allocation, both human and financial, with the right priorities. The scope of user stories will cover, amongst others, the following areas:

• SLA (Service Level Agreement) tracking and reporting
• Project performance tracking and reporting
• Service performance tracking and reporting
• Resource leveling and utilization
  
  
  

Maintenance and Quality Control:

Maintenance and quality control underpin the reliability, availability and accessibility of data and reporting outputs. It ensures accurate insights and adaptability to changing business needs, thereby supporting effective monitoring and control of both the business performance and the product portfolio. The scope of user stories will cover, amongst others, the following areas:

• Creation and delivery of repeatable and automated reporting outputs
• Execution of repeatable technical tasks (e.g., data model maintenance, data refreshes)
• Addressing repeatable data-driven tasks (e.g., follow-up on data quality issues)
• Managing user access and control
• Conducting user training
• Implementing incremental improvements
• Developing automated data quality checks
  
  
  

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