Master Data Management – Beyond Customer Information Integration

by Rick Clements

When asked about Master Data Management (MDM) I often focus my answer on the most common form of MDM – customer data integration – which connects customer information from different parts of the company. This means that business decision makers have a more complete view of who the customer is including: understanding preferences, customizing and providing better service while reducing business costs.

But, there is a large variety of MDM use cases that are quite different and I thought I would explore three of the most interesting here: product information management, reference data management and threat and fraud analytics.

Product Information Management – Just like customer data, strategic product information is scattered across the organization in systems, with individuals, and in documents. Therefore, delivering this essential data to any important stakeholder is difficult, time consuming and unreliable.  For organizations to quickly bring new offers to market, they need to centralize the creation and maintenance of master information about products. This process is called product information management (PIM) and allows employees, contractors, vendors and other supply chain participants to enter and collaboratively update relevant information throughout the development process. For example, product managers might enter product descriptions and bills of materials, while marketing managers update advertising images and engineers input components and packaging data into a single repository of information. The result is a single, consistent and accurate view of product information that enables accurate decision making.

Reference Data Management – Reference data is found in every enterprise application – from back-end systems through front-end commerce applications to the data warehouse. Reference data – country codes, state codes and gender identification, for example – are typically static and help categorize other data within code tables. Code tables are typically defined and managed on an application by application basis which means that the values and the codes for a specific reference data set differ within each application. Managing reference data as part of an MDM implementation:

  • Reduces burden on IT to support reference data integration and resolve failures due to reference data inconsistencies
  • Assists with regulatory compliance providing provenance, security, auditability of reference data
  • Helps to reconcile reference data from back end systems for loading to a data warehouse
  • Manages reference data transcoding (translation between codes) for application integration and data load/transfer
  • Helps to on-board and distribute reference data changes from external standards
  • Supports government directives and regulatory change – ICD-9 to ICD-10 changeover in Healthcare in the US, reconciliation of NACE Codes across countries in banking & finance in Europe

Threat and Fraud Analytics – One of the more interesting MDM use cases, often found within the intelligence community and law enforcement, is understanding data and providing trusted information across IT systems when people are trying to hide or mask their identity. Using this capability, MDM and entity analytics can be used to link analysis and possible threat alerts as well as develop master person index and analytics for law enforcement. Within social services and taxation it can provide a platform for benefit verification – when a person deserves but isn’t receiving or when a person is trying to take advantage of the benefits provided.  The same solution can be applied successfully in financial crimes and insurance fraud analytics. The common theme across all of these examples is looking for persons who may be actively attempting to hide with the data, creating relationships between them or looking for non-obvious relationships in the data, associating persons with their activities – and alerting when suspicious things are found.

So, as you can see, MDM solves quite a variety of business problems and is applicable in many interesting ways across a variety of industries.

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