Case Study: Cleaning Up Complexity – How MAHLE Streamlined Its Spare Parts Master Data with SPARROW.Clean
About MAHLE
MAHLE is a global Tier 1 automotive supplier and development partner, serving both traditional powertrain and electric mobility markets. MAHLE is navigating digitalisation and operational transformation while transitioning to SAP S/4HANA. Clean, consistent spare parts data is critical to their success.
Overview
In 2020, MAHLE launched a pilot across four business units to explore how startup solutions could address complex MRO data issues. That early engagement with SPARROW laid the groundwork for a broader initiative. MAHLE requested a dedicated rollout of SPARROW.Clean across a business unit, driven by challenges stemming from incompatible data structures.
The Challenge
MAHLE was dealing with:
- Fragmented spare parts data across newly acquired and legacy sites
- Inconsistent quality of data inputs between facilities
- Multiple ERP systems with internal naming conventions
- Multilingual inputs, requiring consolidation into a unified English-language catalogue
- Global SAP S/4HANA transition
The result was a landscape of disconnected, error-prone MRO records—hard to manage, search, or analyse across the organisation.
On the top of that, a key roadblock was change management, particularly at the site level. While the project was organised centrally, it took time for local production teams to:
- Understand the value of SPARROW’s solutions
- Allocate resources to support the rollout
- Adopt SPARROW.Clean as part of their daily workflows
Here is a video about the project.
The Solution
SPARROW.Clean was deployed to:
- Harmonise and deduplicate spare parts master data across 14 pilot sites
- Consolidate multilingual records into a standardised English catalogue
- Prepare clean, structured data compatible with MAHLE’s future SAP environment
- Eliminate redundant records and reduce complexity in ongoing operations
Unlike traditional master data clean-up tools, SPARROW.Clean combines automation with MRO expertise to handle linguistic diversity, legacy formats, and classification inconsistencies. The collaboration was particularly effective because SPARROW.Clean was developed in close cooperation with MAHLE’s teams, adapting the solution to their operational requirements and data realities.
Key Outcomes
- High-quality, harmonised master data
- Accelerated readiness for S/4HANA rollout
- Improved collaboration across business units through shared terminology
- Lower risk and cost for integration projects thanks to clean input data
- Proven impact that positioned SPARROW as a global data partner
