Matt Elenjickal, the Founder and Chief Executive Officer of FourKites, has pointed out that “data is the raw fuel of a digital transformation.” But it must be quality data! “Just as any chef will tell you that anything less than the best quality ingredients can render a dish inedible, so too, bad data can turn any data-driven IT effort sour.”
When enterprise implementations take longer than expected, almost all do, the amount of time needed to clean up the data is often the leading factor. When the performance of enterprise systems becomes degraded, it is often because the parameters used in the systems are no longer accurate. This is also a data issue. Master data management (MDM) as a critical performance driver for the enterprise.
What is Master Data Management?
Master data management is the discipline in ensuring data is accurate, accessible, and up to date. Unfortunately, for many departments, the necessary data to operate effectively comes from across the enterprise, it is not generated inside that department. APQC and the Digital Supply Chain Institute (DSCI) have conducted best practice and benchmarking research on MDM. APQC is a member-based nonprofit that conducts benchmarking, best practices, and performance improvement research. Part of what makes APQC research so good is that they are able to get large numbers of members to participate and then they have a strong validation process. In this research, more than 1300 qualified respondents participated.
APQC defines master data as the set of identifiers and extended attributes that describe the core entities of an enterprise. These include customers, products, suppliers, and sites/assets. For the supply chain, other core data sets would also include throughput/lead times and global risks. All this data must be kept up to date and clean.
Top performers in APQC’s research engaged in continuous process of organizing, categorizing, synchronizing, and enriching master data records. Typically enabled by technology, MDM requires business and IT teams to work together to ensure uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise’s official shared master data assets.
Effective master data management is not a “one and done” process. It is an ongoing journey requiring clear governance and ongoing attention. Centralized ownership is a foundational requirement.
In APQC’s research, when respondents were asked how master data is managed, only 64% reported that their organization centralizes it in an enterprise-wide function, such as a chief data officer. A decentralized approach – for example, when sales owns customer data and the supply chain owns supplier data – sets an organization up for failure.
Effective master data management is not a “one and done” process. It is an ongoing journey requiring clear governance and ongoing attention. Centralized ownership is a foundational requirement.
In APQC’s research, when respondents were asked how master data is managed, only 64% reported that their organization centralizes it in an enterprise-wide function, such as a chief data officer. A decentralized approach – for example, when sales owns customer data and the supply chain owns supplier data – sets an organization up for failure.
At a time of rapid outbreak of various viruses, there is a growing demand for working from home due to limited travel. As such, companies desperately need a platform that can make it easier for employees to work together and many Vietnam business consultant out there can help them to solve this problem, not only to help you save costs and time, but also improve the productivity of your business.
Forbes
