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The writer Octavio Paz once said that “Wisdom lies neither in fixity nor in change, but in the dialectic between the two.” Customer Data Integration (CDI) has one foot in established systems – those that need newly-robust customer data on demand – and the other in a new paradigm of automated data management and purpose-built data integration. Marrying incumbent technologies, available skill sets, and business processes with a new paradigm of “integration on demand” means that launching a CDI effort is different, arguably more specialized, than other strategic IT programs. In this paper, we describe the critical success factors to consider when starting up CDI, involving larger master data management (MDM) principles, but delivering business value incrementally and quickly.
We’ll define CDI as the automation of the integration, reconciliation and management of customer reference data from enterprise systems and to enterprise systems. In other words, CDI solutions are purpose-built to package specialized data cleansing, rigorously-defined business rules, formalized policymaking (also known as governance), and on-going stewardship to create a single source of the truth about customer data as a service to the enterprise at-large. In this paper, we’ll describe the lifecycle of pre-facto CDI, which can be divided into three main phases:
The ability to deconstruct the early stages1 of a CDI effort into these three components has been a boon to companies who need integrated, well-managed and continually propagated customer data to a range of systems and users. Success in these areas virtually ensures a useful and sustainable CDI program.
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