Overview: Aperture Data Studio: Improving operational efficiencies for Speedy Hire
Committed to operational excellence, Speedy Hire identified data quality as a critical enabler for enhanced decision-making and efficiency.
Seeking a more modern solution to their current tool, they adopted Experian’s Aperture Data Studio to address their challenges.
When Speedy Hire first implemented data quality management, they were using an older tool from Experian primarily used for data validation during system migrations. As the tool was reaching its end-of-service life, Speedy Hire needed a more modern solution to handle data quality checks, especially during their migration from their legacy ERP system to Microsoft Dynamics 365.
Additionally, Speedy Hire faced several data quality challenges, including difficulties in tracking the location of hire equipment, errors in contract details, ensuring accurate and complete HR data, and inconsistencies in the application of fuel charges. These challenges highlighted the need for a more robust and modern data quality management solution.
Speedy Hire is the UK’s leading provider of tools, equipment, and plant hire services, supporting a diverse customer base—from major infrastructure projects like HS2 to DIY enthusiasts. Committed to operational excellence, Speedy Hire identified data quality as a critical enabler for enhanced decision-making and efficiency.
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Industry: | Retail |
Established: | 1977 |
Employees: | 3,300+ |
Customers: | 46,000+ |
Speedy Hire adopted Experian’s Aperture Data Studio to address their challenges. The solution provided several key functionalities:
Migration reconciliation: Ensured accurate data migration from the legacy ERP system to Microsoft Dynamics 365 by validating data consistency between systems.
Stock count management: Implemented checks to identify and resolve issues with the location of hire equipment, improving inventory management and stock count accuracy.
Contract accuracy: Speedy Hire uses contracts to formalise agreements with their customers and clients for the hire of tools and equipment. Details were manually entered by employees, with contact details, addresses, and other information sometimes entered inaccurately. Errors might be picked up late, so they automated hourly checks to validate contract details, reducing manual input errors and improving data quality using Aperture Data Studio.
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