Business Intelligence Elevates Decision-Making in Software Engineering Teams

As digitization accelerates, making fast, informed decisions is essential for organizations to stay competitive. However, many still rely on intuition rather than structured, data-facilitated processes. Business Intelligence (BI) offers powerful ways to transform raw data into insights that support better decision-making. While software engineering companies are especially affected by digital transformation, BI is an understudied area in this field.

Master Programme in Digital Business Management Thesis research by Péter Ivanics titled ‘The Impact of Business Intelligence for Data-Facilitated Decision-Making in Software Engineering’ examines how BI can enhance decision-making within Webstar Csoport Kft., a rapidly growing Hungarian software engineering agency. Through a detailed single case study, the research highlights how BI can enhance strategic business practices, especially when adapted to measuring progress towards a defined company-level strategy.

Results

The research found that success with BI depends much more on process design, collaboration and change management rather than the utilizing and integrating the selected tools. Key challenges during the development work included technological complexity, data quality, and the need for ongoing employee engagement. BI implementation at the case company led to clearer performance baselines and improved decision-making. DevOps methodologies, particularly DORA and SPACE frameworks, were adapted to help define meaningful metrics specific to the needs of the case organization.

Measuring and visualizing focus areas

Two focus areas—Team Happiness and Software Delivery Performance—were measured over 1.5 years using tailored metrics. An anonymous survey gathered 108 responses across 15 projects, offering leadership insight into team morale and identifying a need for better feedback mechanisms. Software delivery data from over 100 projects pinpointed strengths and inefficiencies between teams, providing guideliens to the management of Webstar Csoport Kft. to target improvements.

All collected metrics were visualized using Metabase, a BI system. Two dashboards—one at company level for upper management and one at team—enabled real-time insights and easier correlation analysis based on the collected data easily on a time-series basis. This unified view helps reinforcing a culture of data-facilitated decision-making across the case company. Over time, the dashboards can be expanded to include additional focus areas such as financial performance or customer satisfaction, providing an even more comprehensive view of organizational health to support continuous improvement efforts.

Tailored BI and performance metrics create meaningful insights

The findings are applicable to any organization working on complex, knowledge-intensive projects. Structured measurement of both people and performance metrics supports responsiveness, transparency, and alignment with strategic goals meanwhile providing an objective view at what is happening inside the organization. By tailoring BI and DevOps practices and adapting industry-standard metrics to fit the context, software engineering teams can create meaningful, actionable insights even in areas traditionally seen as difficult to quantify, such as team well-being and delivery performance. The case study of Webstar Csoport Kft. demonstrates that success depends not only on technical implementation but also on cultivating a culture that embraces data-facilitated decision-making across the organization.

Contact information

Péter Ivanics
Chief Technology Officer, Webstar Csoport Kft.
ivanics.peter@webstar.hu   
Master Programme in Digital Business Management