This case study shows how we helped Delhaize’s logistics department build a single source of truth for its reporting, giving teams a common, reliable foundation for their data.
Context & Challenges: Fragmented Logistics Data Undermined Reliable Reporting
Logistics teams generate a constant stream of data across warehousing, transport, and delivery operations. For Delhaize, a large retail organization, that data lived across multiple systems and reports, with no shared reference point for the numbers behind daily decisions.
Data & Reporting: Inconsistent KPIs and manual reporting created bottlenecks
Before the project, the logistics organization had no single source of truth for its data. Reports relied on inconsistent KPI definitions, which made it difficult to compare figures across teams. Reporting itself was manual, time-consuming, and dependent on a single business user, creating a bottleneck and a key-person risk. The data available also had a limited scope, with no visibility at the warehouse level, and covered day-to-day operations only, without historical retention for trend analysis.
Governance, security, and coordination added complexity
Beyond the data itself, the project had to navigate a complex organizational environment. Multiple stakeholders held diverging reporting needs, and the team depended closely on source system teams for data access. High security, GDPR, and access-control requirements added further constraints, and cross-team coordination had to happen within a Scaled Agile Framework (SAFe), involving business, development, and governance teams working in parallel.
Our Approach: Aligning Business Needs with a Secure Azure Data Platform
We addressed these challenges through three parallel workstreams: aligning business requirements, enabling secure technical delivery, and managing the project within a SAFe framework.
Aligning business needs and standardizing KPIs
We started by collecting and aligning requirements across the entire logistics domain, bringing together the diverging needs identified during the initial assessment. From there, we structured and standardized the logistics KPIs, replacing the inconsistent definitions with a shared reference. We also ensured end-to-end traceability, connecting each business need directly to its corresponding data output.
Enabling secure, compliant data delivery on Azure
On the technical side, we coordinated with source system teams to enable the data extractions the project depended on. We produced detailed analysis and data documentation to support ingestion into Azure. We also ensured the design of a secure network and access architecture, covering security, firewalls, and connectivity, and worked with compliance teams to secure full GDPR compliance and security clearance for the solution.
Managing delivery within a SAFe Framework
We defined the delivery scope and built the budget and timeline plans together with the Product Managers and Product Owner . We presented the project proposal for board approval, then led the project kickoff. Throughout delivery, we provided weekly follow-up, unblocked issues as they arose, and maintained continuous alignment between business, development, and governance teams.
Key Benefits: A Reliable, Scalable Foundation for Logistics Reporting
The project delivered measurable improvements in reporting reliability, analytics capability and long-term value.
Measurable savings and efficiency gains
- 20% savings on driver route optimization
- 25% savings thanks to improved planning and delivery
- 80% reduction in time spent on report preparation and analysis
Consistent reporting across the organization
The project established a trusted single source of truth for logistics reporting. KPI definitions are now consistent and reliable across the logistics organization, and manual effort and dependency on individual team members have been reduced. Reporting now covers warehousing and logistics operations in full.
Historical data and self-service analytics through Power BI and Databricks
Teams now have access to historical logistics data, supporting trend and performance analysis that was not previously possible. Self-service, scalable reporting through Power BI, connected to Databricks, gives teams direct access to the data they need. Data quality, transparency, and stakeholder confidence have all improved as a result.
A scalable foundation built for future use cases
The new analytics foundation is scalable and reusable for future use cases. The project also put in place a clear governance, security, and compliance model, and strengthened the collaboration model between business and IT teams.
Teams and Technologies Used to Build the Single Source of Truth
The project was delivered by a Data Functional Analyst, who also took on the role of Project Manager during the second delivery phase, over two and a half years with a budget of over €500,000. She worked in close collaboration with business stakeholders, IT project managers, data architects, and a scrum development team.
The solution relies in particular on our partners to collect, process, and highlight logistics data:
- Azure Data Platform: used to ingest and host logistics data, providing the infrastructure for the single source of truth.
- Databricks: used to process and prepare the underlying data for reporting.
- Power BI: connected to Databricks to deliver self-service, scalable reporting to business teams.
