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Why MDM Vision May Fail
Now that master data management (MDM) is on the short-list for many CIOs, it is worthwhile to consider how MDM projects are spawning in organizations and how an organization can evaluate their potential for success. Recent surveys by some industry analysts recommend what the software mega-vendors such as IBM, SAP, and Oracle have been hyping?that CIOs must look at the MDM effort holistically and embark upon an enterprise-wide MDM initiative. Today, MDM is a seductive vision that is sold primarily to the CIO office. However, the mainstream success of MDM depends on enrolling business as the sponsor?or the master?of such initiatives, because master data is inherently tied to solving business problems. Rather than falling victim to mega-vendor promises, CIOs are now opting for a more prudent approach that enables them to start small with a business-sponsored project to demonstrate the high return on investment (ROI) that can be realized using MDM technology, and then evolve that technology into an enterprise-wide MDM platform over time.
Data Governance in Infancy
The MDM vision being sold to the CIO paints a picture where all information silos within the organization are dissolved and the data is set free to flow among systems in real-time; data that is accurately unified with other data and is transmitted securely and viewed discretely by each business user at their desired frequency and latency. At a loftier level, the IT vision being presented is one that supports a set of universal definitions of all core business data entities?or master data?that are shared across all business processes and systems.
This vision is certainly alluring but also appropriate in order to tear down decades of legacy data silos. However, the first task CIOs face in realizing this vision is addressing data governance issues. Specifically, organizations must determine who defines the customer and standard product description; who knows of the correct relationship between customer and organization; who resolves the conflicts among these data sources, and more importantly, who owns the data? With all these considerations, it is not surprising that settling data governance policies and practices is an enormous, corporate-wide undertaking that has the potential for political strife.
Ironically, the critical assumption underlying the MDM debate today is that IT can manage master data. This implies that IT can anticipate, define, and standardize on a complete MDM technology stack in advance of the negotiated outcome of data governance issues between business and IT. The assumption is flawed and may prove to be fatal for the entire master data management category. Realistically, it could take three to five years at most organizations for the critical data governance issues and organizational priorities to be fully resolved, and for data governance policies and processes to be implemented.
Enter the Business Master
Consequently, it is mandatory for IT to work with business units to identify who the customer is, what the product is, and how products and customers are related?since business owners are the subject matter experts of business entity data. Moreover, if poor data has a negative impact on the business process, it is the business that needs to solve the problem and subsequently, the business that benefits from improvements in master data. This brings to light the new reality?business has to be the master of master data management. After all, who is more suited to answer these and other related questions such as: who is the customer that placed the order; is this employee authorized to approve the order; what product did we promise to ship; and what is the correct shipping location?
Why MDM Vision May Fail
Without business enrollment in the MDM initiative, the project is often doomed from the start. Unlike other IT issues related to data management, master data and its management is not merely infrastructure. The business impact of master data is direct and its monetary benefits are measurable with ROI metrics. Given that the language of business is not the language of master data?the challenge lies in translating business issues and benefits into master data issues and MDM solutions.
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