I’ve been working with Oracle’s Enterprise Resource Planning (ERP) application, now called the E-Business Suite, since 1995.
My first exposure was as the project manager for an Oracle Release 10.5 implementation at a manufacturing company. Later, I was part of the Oracle practices at two different consulting firms, so along the way, I’ve managed a lot of Release 11.0 and Release 11i projects.
I didn’t realize at the time what a great training ground ERP would be for Master Data Management.
Of course, there is some controversy about whether a single global instance of an ERP application qualifies as an MDM platform.
My definition of Master Data Management is “a set of disciplines and processes for ensuring the accuracy, completeness, timeliness and consistency of the most important types (or domains) of reference data in the enterprise – across different applications, systems and databases, and across multiple business processes, functional areas, organizations, geographies and channels.”
There’s a lot of similarity there to Wikipedia’s definition of ERP: “cross-functional and enterprise wide. All functional departments that are involved in operations or production are integrated in one system.”
Bottom line — some companies can use an ERP system as their cross-functional, enterprise-wide “single system”, and others have such a heterogenous IT environment that they require a dedicated MDM platform.
But the organizational disciplines and processes are very similar. Most of what works in an ERP environment is also going to be necessary in an MDM environment. The specifics may differ, but a lot of the same themes will emerge.
Data will still be “king”. The quality of data will be a critical driver to the success of the implementation, as will the depth of and quality of the integration. Enrichment of your internal information with content from a third party will be an important component.
And data governance is probably going to make the difference between success and failure of your implementation.
There’s a great white paper on data governance called Taking Data Quality to the Enterprise through Data Governance. In it, data governance is defined as:
“When an organization views data as an enterprise asset …, it establishes an executive-level data governance committee that oversees data stewardship across the organization. Data governance … exerts control over multiple business initiatives and technology implementations, to unify these through consistent data definitions and gain greater reuse for IT projects and business efforts.
The most critical success factor with governance is mandate. Governance bodies and stewards must exert change on business and technical people—who own the data and its processes—when opportunities for improvement arise. The most effective mandates come from a high-level executive. Without a strong mandate for change and an attentive executive sponsor, stewardship and governance deteriorate into academic data profiling exercises with little or no practical application.”
Conclusion: a lot of the same things that are “critical success factors” to an ERP implementation are necessary in a Master Data Management or data governance initiative as well. Active, involved executive sponsorship; organizational change management; business process and data quality improvement; strong project management – it’s no surprise that the same techniques that work in ERP would be necessary for MDM as well.
In my next post, I’ll discuss MDM best practices that I’ve picked up from clients over the past three years.