For Business Process Professionals

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	September 10, 2007 Data Governance: What Works And What Doesn't by Rob Karel with J. Paul Kirby, Boris Evelson	Average: 8  (9 ratings)

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Executive Summary

The demand for trusted information continues to spiral upward, driven not only by investments in customer relationship management (CRM), enterprise resource planning (ERP), supply chain management, business intelligence, and data warehousing, but also next-generation strategic initiatives in master data management (MDM) and information-as-a-service (IaaS). The cross-enterprise complexity of these emerging business requirements have led to an obvious yet often ignored fact: Technology is only part of the solution. Until you understand and embrace data governance, your information management initiatives won't deliver their promised value. Effective governance requires defining organizational roles and responsibilities, including ownership of the processes and policies by which information is captured, maintained, and consumed. Unfortunately, no single governance model works for everyone, so your first challenge will be to develop the unique governance model that will be successful for your unique organization.

TABLE OF CONTENTS

• An Evolving Need For Data Governance Has Emerged
• Case Studies Prove That There Are Multiple Roads To Success
• Let Others' Governance Programs Inspire — But Not Dictate — Your Own

RECOMMENDATIONS

• Design Your Governance Based On Company Culture

WHAT IT MEANS

• Data Governance Will Evolve Into Information Governance
• Related Research Documents

This is an excerpt

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