1. / A Fortune 10 Automotive Company Eliminates Data Errors by 98%
Overview

Large organizations need to create structured relationships for complex data to manage it and unlock its best value easily. The customer, a Fortune 10 company that designs, manufactures, and markets vehicles and vehicle parts, generated an immense amount of data. They needed a master data environment that would treat all hierarchies and push a correct version of truth downstream for processing.

Problem

The customer’s data deluge presented a host of problems.

  • Lack of a robust hierarchy management system hindered downstream processing
  • Difficulty in dealing with complex global hierarchies used in various planning and accounting applications
  • Lack of clarity regarding past acquisitions, streamlining data, and picking a master golden record became bottlenecks for various business applications
  • Difficulty in coordinating processes, leading to tedious manual activities for the same on the last 13 days of each month
Solution

After analyzing the customer’s requirements and existing systems, Apexon delivered a cutting-edge solution.

  • A pipeline to collect new data feeds, change requests and build a complete hierarchy management system with match-merge and fuzzy-match-driven criteria
  • A custom asset workflow to allow users to map the governance system attributes to MDM systems
  • Automated validations to ensure smooth month-end processing 
  • Staging versions to enable processing of future-dated requests
  • API-integration with MDM systems to run validations, build staging versions, view changes, and automate the month-end MDM maintenance process
Impact

The new automated pipeline solution created for the customer delivered various benefits.

  • Reconciled data standards between governance and MDM tools
  • Reduced over standards and key-man risk
  • Eliminated 60% of processing steps, 40% of processing days, and five days of month-end work
  • Eliminated 98% of accounting report generation errors that could occur due to data anomalies or redundancy (The remaining 2% of business data updates will be taken care of by data stewards).
  • Delivered values-adds beyond the original scope

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