Winner Bayer: CDL+ "Cinderella Project"
A novel approach to automated Decision Making in Vendor Master Data Management
Bayer's case represents an exemplary data management initiative that implements automated decision-making in their master data workflows based on executable business rules. Their good practices demonstrate the scale and cost savings that are possible by leveraging data sharing and combining community-defined data quality rules with internally defined rules.
Bayer's CDL+ framework builds on a semantic knowledge graph and more than 1,700 Data Quality Rules, defined by the Data Sharing Community, and combines them with Bayer-specific rules. These executable business rules and the validation with external data allow an instant-risk-based approval of master data requests instead of 24h service levels.
The initial pilot scope has achieved a considerable automation rate as well as several secondary benefits in the area of data quality and documentation of data-related knowledge. The utilization of the framework translates into a monetary business case. Moreover, it provides a future blueprint for other data objects (…) and presents a for system enabled Data Governance covering many aspects of the CDQ Data Excellence Model.
Bayers novel approach
In this video, Bayer presents their CDL+ approach: A forward-looking approach to automate master data workflows, and manage the trade-offs between data quality, risks and manual efforts in vendor master data management.
45 min video
CDQ Summer-Must-Reads 2021
The Bayer Cinderella Project is one of our Summer Must-Reads. During the summer months July and August we have clustered some of our most popular pieces (eBooks, webinars, templates, business cases etc) all about Data. You can retrieve these content pieces for FREE. Simply request ALL summer items via the central campaign page to be sent to your inbox directly in the coming weeks.