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Introduction

A model for assessing the maturity of a public sector agency's implementation of master data management (MDM).

Highlights

  • Maturity stages roughly correspond to the level of data consolidation and managerial coordination. This means smaller agencies with fewer service lines will find it easier to achieve higher stages of maturity.
  • The road to MDM maturity is often one of recovery from a crisis. Disasters can help agencies to identify which data needs to be mastered first.
  • Data quality and data validation are essential first steps: You cannot create a golden record until you’re sure the data you put into it is reliable.

Features and Benefits

  • Defines the stages of maturity in public sector MDM and identifies their key characteristics.
  • Highlights the challenges involved in moving from one stage to another and assesses how different types of agencies will move through the stages.

Key questions answered

  • How does an agency get started with MDM, and why?
  • How can the usual pitfalls be avoided?
  • What are the essential steps for implementing MDM?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Stage 0: Data chaos

  • Zero data governance is an accident waiting to happen

Stage 1: The data hangover

  • The first step to recovery is admitting you have a problem

Stage 2: Service-oriented master data management

  • MDM is driven by project needs before agency needs

Stage 3: Agency-wide master data management

  • In MDM utopia, there is one record to rule them all

Stage 4: Multi-agency master data management

  • Inter-agency MDM is project-led

Appendix

  • Methodology
  • Further reading
  • Author

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