Information Quality & Master Data Management?

Master Data Management is the process used to create and maintain a “system of record” for core sets of data elements and their associated dimensions, hierarchies and properties which typically span business units and IT systems.

Master Data, often referred to as “Reference Data”, may in your organization take the form of Charter of Accounts, Product Catalogue, Stores Organization, Suppliers and Vendor Lists but to name a few.

In his article “Demystifying Master Data Management”, Tony Fischer uses Customer as an example of Master data and how, if not understood and managed appropriately, can cause all sort of headaches for a company, in this case the CEO himself!

“Years ago, a global manufacturing company lost a key distribution plant to a fire. The CEO, eager to maintain profitable relationships with customers, decided to send a letter to key distributors letting them know why their shipments were delayed—and when service would return to normal.

He wrote the letter and asked his executive team to "make it happen." So, they went to their CRM, ERP, billing and logistics systems to find a list of customers. The result? Each application returned a different list, and no single system held a true view of the customer. The CEO learned of this confusion and was understandably irate. What kind of company doesn't understand who its customers
are?”

So what are the typical barriers that hinder organizations from addressing their master data management problem? My colleagues and I typically encounter four primary barriers:

Multiple Sources and Targets: Reference data is created, stored and updated in multiple transactional and analytic systems causing inaccuracies. Synchronization challenges between disparate systems

Ability to Standardize: Most organizations cannot agree on a standardized view of master data. There are a lack of audit policies that comply with federal regulations

Organizational Ownership: Disagreement within the organization as to who takes ownership of master data management, business or IT. Assignment of accountability with cross-functional processes is difficult

Centralization of Master Data: Organizational resistance to centralizing master data since there is a sense that control will be lost. Challenges to find a technology solution that supports existing systems and the lifecycle of master data management

Organizations that are addressing such barriers typically have a successful master data management process in place that contains the following components:

Data Quality: Focus on the accuracy, correctness, completeness and relevance of dataIncorporate validation processes and checkpoints. Effort is highest in the beginning of a MDM initiative to correct quality issues.

Governance: Cross functional team formed to establish organizational standards for MDM related to ownership, change control, validation and audit policies. Focus includes establishing a standard meeting process to discuss standards, large changes and organizational issues.

Stewardship: Assignment of ongoing ownership of MDM stewardship. Typically MDM stewards are business users. Accountable for the implementation of standards established through MDM governance

Technology: Create an architectural foundation that aligns with the other three components. Implement a technology that centralizes reference data. Align processes with the technology solution to synchronize master data across source and analytic systems

As we can see, master data management is not a one-time initiative but rather a long-term program that runs continuously within the organization. To be successful organizations need to instill an iterative approach that helps develop a program that continuously monitors, evaluates, validates and creates master data in a consistent, meaningful and well communicated way.

What is your organization doing about Master Data Management? Have you had success in establishing a Data Governance program? Who own the process in your organization, IT or the business?