Case Study: Amec Foster Wheeler achieves improved data quality and faster deduplication with Data Ladder's DataMatch™

Mastering and maintaining data quality

Amec Foster Wheeler faced an urgent need to improve the quality and accuracy of its data as it prepared for a large influx of infrastructure and environmental projects and a migration to new finance and HR systems. To address this, Amec Foster Wheeler engaged Data Ladder and its flagship product, DataMatch™, to tackle deduplication and data cleansing ahead of the system migration.

Data Ladder implemented DataMatch™ with fuzzy matching, deduplication workflows and customized training to clean, export and repopulate financial and HR records, eliminating much manual entry and speeding the deduplication process. The solution helped Amec Foster Wheeler maintain the high level of data quality required for migration and operational work; Data Ladder notes its DataMatch Enterprise finds approximately 5–12% more matches than leading competitors in comparative studies.

Amec Foster Wheeler