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The business need
DHL's Expedited Max premium service required timely visibility into process, quality, routing, and logistics issues that could cause packages to miss a 2–3 day service expectation. The business knew the general outcome it wanted, but the detailed analytical product still had to be defined.
Turning a concept into a product
I worked closely with the head of Quality to convert that high-level need into practical business rules, causal classifications, data requirements, and reporting functionality. My prior distribution-center quality experience and years of quality-focused work gave me operational context that was explicitly requested when we worked through how the report should function in practice.
How the solution evolved
- Initially built the reporting in Excel, with SSIS-driven updates and automated PivotTable refreshes.
- Later transitioned the reporting into Tableau.
- Ultimately helped move the solution into Power BI as the BI environment evolved.
- Stayed involved in the data and reporting development throughout those technology changes.
Data engineering
- Integrated package-level and performance data from multiple Oracle sources into SQL Server.
- Developed SSIS ETL packages, SQL Server Agent jobs, staging and historical tables, stored procedures, validation logic, and analytical views.
- Built a historical reporting foundation capable of supporting service-performance analysis over time.
Cross-functional validation
Worked with Quality, Product, Operations, IT, Master Data, Transportation, and Postal teams to validate classifications and reporting logic against actual network behavior.
Impact
The solution gave Operations, Quality, Customer Service, and leadership visibility not only into packages that had already failed service, but also into packages at risk of missing SLA, helping teams identify emerging issues and intervene before customer delivery expectations were missed.
What this demonstrates
Long-term analytical product ownership: shaping requirements, applying operational expertise, engineering the data, and evolving the same business capability across Excel, Tableau, and Power BI.