In today's market where analytics is becoming increasingly important, Master Data Management (MDM) increases the validity of data used to model customer behavior, cross-sell and up-sell. If your organization has multiple customer touch points or multiple service lines, then MDM will help ensure that you are able to assemble a complete picture of the relationship with customers. The definition of MDM: “In business, master data management (MDM) comprises the processes, governance, policies, standards and tools that consistently define and manage the critical data of an organization to provide a single point of reference.” (Wiki)
- Single source of information across the enterprise. MDM can eliminate data integrity issues (if any) across the organization. Access the data management maturity through asking: Do you have reports from different sources that don't match? Do you waste time running multiple apps or business processes that have substantially the same data domain but different data repositories? Do you have to combine this data somehow to get meaningful reports? Does one of the "ivory towers" have robust business processes that make their data better, more reliable or more accurate than the others? Use those examples and then demonstrate how it would work better in an MDM environment.
- The solid MDM can make more accurate and trustworthy analytics (dashboard, reports & others). Improvement of data quality, getting higher data quality is half way of successful analytics. Identification of data quality issues input points (where are the biggest problems and focus on real problems, not on subjective feelings). Follow the old wisdom: "Quality has to be designed in, not inspected out." For a successful MDM implementation, you need to work out the processes surrounding Master Data from day one, first what is already there and next how it's going to be processed after the implementation. MDM can make reduction of data errors, integrate data sets, enforce data management processes in order to execute more accurate and trustworthy analytics, which can better understand what the customer’s need and improve marketing campaign success rate; it can also improve sales/distribution effectiveness as the correct data is available to communicate and collaborate through MDM practices.
- MDM is a subset of data governance. From management and performance perspective, MDM can lower effort to correct identified bad data manually; from management and operation lenses, it can provide the right data for risk management, either for operational risk or reputation risk; from business value aspect, it is important to make MDM process driven, not data focused, and well align people, process, and technology to deliver business value through the effective data governance discipline.
- Cost optimization: MDM practice can also lower hardware cost and cost of its maintenance, by consolidation & removal of duplicate data sources across the enterprise. Data itself is one of the most invaluable raw assets in business nowadays; it would take other assets such as storage or software to manage it well. Hence, the effective MDM can achieve cost efficiency and business management optimization.
What’s the most influential MDM benefit: Looking for bottom line impacting, real life examples of weak master data constrain operational excellence; hunting for top line impacting, the strong MDM can improve analytics project success rate, it means to discover more opportunities for future business growth and increasing customer satisfaction.