Customer Story
Babcock Marine & Technology Division
Trillium Discovery helped Babcock increase supplier master data quality by 23%
Babcock’s Marine & Technology (M&T) Division is part of Babcock International Group plc, a multinational corporation which specialises in support services managing complex assets and infrastructure in safety and mission-critical environments. As one of the world’s leading marine support businesses, the Division serves defence and commercial organisations in the UK and beyond. They are the Ministry of Defence’s largest single support services supplier and constantly strive to remain amongst the top three in the market sector globally. To retain their preeminent UK position, grow global business and secure future success, Babcock’s Marine & Technology Division drives an aggressive continuous improvement agenda.
Supply Chain Data Optimization
In an increasingly connected business world, data has become a critical currency. A successful business therefore depends on the creation, management, and exploitation of accurate data and information. Data is the foundation on which Babcock’s Marine & Technology Division builds customer and supplier relationships, operates processes and manages people. Data that is not fit for business purposes can increase costs, reduce revenues, and increase commercial and regulatory risks, thereby reducing global competitiveness. Customers and partners expect them to manage data on their behalf with care and rigour. Quite simply, the Division sees effective management of data as key to securing future success.
The Supply Chain function is a critical part of Babcock’s M&T Division, managing all aspects of the supply chain. The Division spends over £500 million a year procuring materials and services from over 3,000 suppliers to enable it to service customers and partners. Data on over 1 million commodities and parts needs to be managed. The supply chain poses complex data challenges, and issues were causing inefficiencies and additional costs across the end-to-end process.
The urgency of this challenge was heightened by an enterprise wide process and system redesign; bringing together variable quality data from disparate systems would cause problems when trying to integrate and match it within a single platform.
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