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The Value of Automation in Master Data Management (MDM)
Manage episode 456161632 series 2304478
In this episode of the SAP Let's Talk Data podcast, host Corrie Birkeness is joined by experts Andreas Seifried (Product Manager at SAP) and Kai Hüner (CTO of CDQ) as they discuss the critical role of automation and data quality in master data management (MDM). They dive into the value of automation in master data management (MDM) and the critical role of high-quality, trusted data in enabling reliable and efficient automation. They explore the challenges of manual data management, such as errors, inefficiencies, and delays, and highlights how automation can improve data accuracy, save costs, and support business growth.
Andreas and Kai also explain how their collaboration integrates CDQ's trusted data services with SAP's Master Data Governance (MDG) solution. They share examples of companies achieving faster processes, reduced compliance risks, and enhanced scalability through automation.
Key Topics of Discussion:
- The Importance of Trusted, High-Quality Data - Trusted data is essential for reliable automation, compliance, and AI initiatives. The concept of "trusted data" emphasizes accuracy, traceability, and verified sources like tax authorities or trade registers.
- Challenges of Manual Master Data Management (MDM) - Manual MDM is labor-intensive, error-prone, and causes inefficiencies, delays, and bottlenecks. Mistakes in master data lead to operational issues like delayed logistics, compliance failures, and rework costs.
- Benefits of Automation in MDM - Automation reduces manual effort, errors, and compliance risks while improving speed and scalability. Examples highlight significant cost and time savings, such as reducing supplier onboarding from 50 minutes to 1 minute.
- Collaboration Between SAP and CDQ - SAP MDG integrates with CDQ's trusted data services to enable seamless data lookup, enrichment, and validation. Simplified setup processes, like value mapping and trusted data sourcing, streamline automation implementation.
- Features Supporting Automation in SAP MDG - Tools like derivation rules, rule mining, and AI-powered features enhance data accuracy and governance. These features help organizations automate repetitive tasks, reduce errors, and enable growth.
Subscribe to The Let’s Talk Data Podcast
Connect With Corrie Birkeness
Connect With Andreas Seifried
Connect With Kia Hüner
Additional Resources:
CDQ Business Value Study: https://hubs.la/Q02YwW-_0
Enrichment of Business Partner Master Data using CDQ blog: https://community.sap.com/t5/technology-blogs-by-sap/mass-enrichment-of-business-partners-with-tax-and-id-numbers-found-using/ba-p/13915206
SAP Master Data Governance product page: www.sap.com/mdg
CDQ on the SAP Store: https://store.sap.com/dcp/en/product/display-2001000790_live_v1
100集单集
Manage episode 456161632 series 2304478
In this episode of the SAP Let's Talk Data podcast, host Corrie Birkeness is joined by experts Andreas Seifried (Product Manager at SAP) and Kai Hüner (CTO of CDQ) as they discuss the critical role of automation and data quality in master data management (MDM). They dive into the value of automation in master data management (MDM) and the critical role of high-quality, trusted data in enabling reliable and efficient automation. They explore the challenges of manual data management, such as errors, inefficiencies, and delays, and highlights how automation can improve data accuracy, save costs, and support business growth.
Andreas and Kai also explain how their collaboration integrates CDQ's trusted data services with SAP's Master Data Governance (MDG) solution. They share examples of companies achieving faster processes, reduced compliance risks, and enhanced scalability through automation.
Key Topics of Discussion:
- The Importance of Trusted, High-Quality Data - Trusted data is essential for reliable automation, compliance, and AI initiatives. The concept of "trusted data" emphasizes accuracy, traceability, and verified sources like tax authorities or trade registers.
- Challenges of Manual Master Data Management (MDM) - Manual MDM is labor-intensive, error-prone, and causes inefficiencies, delays, and bottlenecks. Mistakes in master data lead to operational issues like delayed logistics, compliance failures, and rework costs.
- Benefits of Automation in MDM - Automation reduces manual effort, errors, and compliance risks while improving speed and scalability. Examples highlight significant cost and time savings, such as reducing supplier onboarding from 50 minutes to 1 minute.
- Collaboration Between SAP and CDQ - SAP MDG integrates with CDQ's trusted data services to enable seamless data lookup, enrichment, and validation. Simplified setup processes, like value mapping and trusted data sourcing, streamline automation implementation.
- Features Supporting Automation in SAP MDG - Tools like derivation rules, rule mining, and AI-powered features enhance data accuracy and governance. These features help organizations automate repetitive tasks, reduce errors, and enable growth.
Subscribe to The Let’s Talk Data Podcast
Connect With Corrie Birkeness
Connect With Andreas Seifried
Connect With Kia Hüner
Additional Resources:
CDQ Business Value Study: https://hubs.la/Q02YwW-_0
Enrichment of Business Partner Master Data using CDQ blog: https://community.sap.com/t5/technology-blogs-by-sap/mass-enrichment-of-business-partners-with-tax-and-id-numbers-found-using/ba-p/13915206
SAP Master Data Governance product page: www.sap.com/mdg
CDQ on the SAP Store: https://store.sap.com/dcp/en/product/display-2001000790_live_v1
100集单集
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