Customer Success Story - Bayer AG
Smart and efficient S2P through change request automation
Key results
fTime in SAP MDG reduced from 28 to 14 hours
with reliable data quality rules
Instant risk-based approval instead of 2-day SLA
The challenge
Vendor Master Data process at Bayer comprised over 144,000 change requests annually. With 50 Data Stewards spread across 5 regional shared service centers (SSC), this was both labor-intensive and costly.
The organization confronted dual pressures: the need to showcase cost savings through master data management and to improve data quality in legacy systems and its lifecycle.
With their data governance maturity and an innovative spirit for data quality, Bayer set off on a journey to digitize the process with an ambitious goal to introduce automation, reduce manual effort and enhance data quality simultaneously.
Bayer recognized a significant opportunity as they realized that nearly 80% of SAP MDG requests were straightforward and required no human intervention.
The experience
This sparked the idea of a "decision-making robot" to handle at least a portion of this workload, and eliminate the need for additional analysis.
To digitize their expertise in vendor management, Bayer made use of CDQ data quality rules to create a smart knowledge graph, and established a shared resource that both humans and machines could access.
The "decision-making robot" was smoothly integrated into SAP MDG workflow to approve low-risk, good quality data standard requests.
Collaboration with CDQ Data Sharing Community and access to shared community data empowered Bayer to further automate routine decisions like address validation as well as fraud prevention services to check bank account data for fraud risk and ensure compliance.
The results
The approach led to transformative outcomes.
Standard, low-risk request processing accelerated remarkably, reducing the time from 2 days to just 2 seconds. This not only streamlined the Source-to-Pay workflow but also relieved cost-saving pressures.
Trust in automation grew, with a remarkable 40% automation rate. This optimization freed resources for more complex tasks, enhancing workforce efficiency.
The gains were substantial with SAP MDG process time cut in half, from 28 to 14 hours.
By blending automation and data quality focus and with enhanced data governance capabilities and, Bayer set a new data management standard, achieving speed, trust, and efficiency improvements.
About Bayer
Bayer AG is a global life sciences leader specializing in pharmaceuticals, crop science, and consumer health. Operating in over 90 countries, Bayer drives innovation in healthcare and agriculture, leveraging advanced digital solutions to enhance efficiency and sustainability.
How to detect the 80% ‘good’ requests automatically across 150k change request per year? – this was the question driving us.
Extrapolating early numbers, we have an automation rate of ~40% and a workload saving of 25%.
