A particular scenario has played out all too often in the past decade. A CEO develops a new vision for his enterprise and announces that becoming information-centric and customer-centric are at the heart of his vision. The executives, directors and managers tasked with delivering the new reality try to understand the vision and how to implement it. Sooner or later, they've heard from IT and data management about data quality, data governance and master data management as an assured path to a data-centric world and customer-centricity. The executives sign up for all these things and go back to the CEO for resources, telling him the path to his vision has been found.

As usual, the CEO asks for the business case and an explanation of return on investment. ROI is articulated using the IT industry logic that highlights positive effects of simplifying and centralizing integration, with data quality and data consistency improvements as the driving benefits. However, these benefits do not match the CEO's goals, which remain far from being achieved. The CEO wanted to understand, reorganize and manage all the touchpoints in the customer lifecycle. He wanted the enterprise to become truly customer-centric, rather than account-centric and merely focused on individual, isolated transactions with the customer. Instead, the CEO is left with an enterprise that has better control and quality of master data, but the operational and analytical processes and lifecycles remain nearly the same. Sadly, there is a widespread IT view that operational and data quality efficiencies are the totality of MDM. The CEO might want to transform the enterprise, but IT is typically unable to achieve this because it is incapable of finding and mitigating the root causes of inconsistency and brittleness.

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