Material Quality and Cost Variance Reporting for Controlling

Problem & Context

A machinery manufacturing client required two reports to support its material quality and costing processes. The first needed to surface defects across the multi-level hierarchy of a given material; the second had to compare the current material calculation against the last released version and visualize the difference. Both topics were business-critical but highly time-consuming: identifying all relevant defects manually took stakeholders several days per cycle. The underlying data was also fragmented across numerous SAP tables, which had to be joined to bring the relevant information together into one view and one data asset.

Approach & Solution

The project began with a business alignment phase to confirm definitions and reporting expectations together with the relevant stakeholders. A second alignment followed with the IT team to ensure the correct SAP tables were made available in the SQL environment, where data preparation took place. Visualization was built in Power BI, and a Power Apps component was integrated directly into the dashboards so stakeholders could capture their written analysis alongside the figures themselves. Close collaboration with the business continued throughout, with several rounds of quality checks to validate that the data matched expected results.

Results & Impact

The reports replaced a manual process that previously consumed several days of stakeholder time each cycle, delivering the same views instantly. The stakeholder’s role shifted from manually locating errors to only commenting on them — explaining where each defect originates rather than tracking it down. The reporting cycle is now significantly shorter, with the remaining effort concentrated on root-cause interpretation rather than data gathering.

16 hours

reporting cycle time reduced

+50%

more defects and issues identified per cycle

-70%

faster root-cause tracing for material defects

Your Contact

Dr. Steffen Illig
Partner and Expert for Data Analytics
+49 176 579 82284

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