Overview
Stedin needed to improve software delivery quality and predictability across its development teams. emagine introduced CI/CD pipelines, DevOps practices and engineering metrics, enabling faster releases, improved quality and a scalable delivery foundation.
The Challenge
Stedin is one of Europe’s major energy infrastructure operators, managing electricity networks that serve more than 2.2 million businesses across the Netherlands.
To support its operations, the organisation relies on a large and complex software landscape, with more than 40 development teams working across critical systems, including web platforms and SAP environments.
As Stedin expanded its agile delivery model, several challenges began to emerge.
Technical debt increased across multiple systems, impacting code quality and making it more difficult to maintain and evolve applications. At the same time, the number of bugs reaching production environments grew. This affected system reliability and created additional workload for development and operations teams, reducing overall efficiency.
Business demand for faster delivery also intensified. Teams were expected to release new features more quickly while maintaining high standards of quality and stability. However, existing development processes made it difficult to achieve both speed and reliability.
Another key challenge was limited visibility. Without consistent metrics and standardised pipelines, it was difficult to track performance, predict delivery outcomes and identify areas for improvement across teams.
To address these issues, Stedin initiated a focused pilot programme. The objective was to introduce Continuous Integration and Continuous Delivery (CI/CD) practices, improve engineering quality and establish a more predictable and scalable approach to software delivery.
The Solution
To support Stedin’s pilot programme, emagine introduced a structured set of DevOps practices and engineering improvements designed to strengthen software delivery across multiple teams.
Phase 1: Assessing the data landscape
The programme began with a detailed assessment of existing data sources, formats and quality.
This provided a clear understanding of the current environment and defined a structured roadmap for transformation and migration.
Phase 2: Migrating to a scalable cloud foundation
The ERP system and Oracle database were migrated to Microsoft Azure using a phased approach.
This ensured continuity while reducing risk, and created a more scalable and cost-efficient infrastructure to support future growth.
Phase 3: Integrating data and automating pipelines
An automated data pipeline was implemented using Azure Data Factory, Databricks and Logic Apps.
This replaced manual data handling with consistent, repeatable workflows. At the same time, data from multiple sources was consolidated into a centralised data warehouse, establishing a single source of truth for reporting and analysis.
Phase 4: Enabling insights, quality and adoption
Power BI dashboards and reports were developed to provide clear, accessible insights across financial and product performance.
Data validation and QA processes were embedded throughout the pipeline to ensure accuracy and consistency.
Close collaboration with stakeholders ensured the solution worked in practice, supporting real business needs and day-to-day decision-making.
Transformation timeline
Phase 1
Assessing the data landscape
Phase 2
Migrating to a scalable cloud foundation
Phase 3
Integrating data and automating pipelines
Phase 4
Enabling insights, quality and adoption
The Results
The new platform improved both how data is managed and how it is used across the organisation.
Faster data processing and access to insights
Data transformation time was reduced by 40%, enabling faster access to accurate and up-to-date information.
Reduced infrastructure and operational costs
Cloud optimisation reduced infrastructure costs by 30%, improving efficiency while maintaining performance and scalability.
Improved reporting and user satisfaction
Stakeholder satisfaction with reporting increased by 70%, driven by clearer dashboards and easier access to reliable data. Teams can now focus on decision-making rather than data preparation.
Scalable foundation for future growth
A centralised, cloud-based platform provides a flexible foundation that can adapt to changing business needs. This makes it easier to integrate new data sources, expand capabilities and support long-term growth.