An MDM layer enables companies to realize internal efficiencies by reducing the cost and complexity of processes that use master data (through fewer code clashes, less data duplication, better control over business processes, and so on). It reduces manual translation and analysis to improve repeatability and speed to insight. An MDM layer improves the ability to share, consolidate, and analyze business information quickly, both globally and regionally. And it makes it possible to rapidly assemble new, composite applications (software that combines the elements of a business activity in a coordinated application and user interface) out of accurate master information and reusable business processes.
Why is the whole concept of master data management gaining so much traction right now?
MDM is trendy now, but I would still consider the implementation of it very immature. There are many technology alternatives on the market to solve a wide variety of master data challenges, but end users are still struggling a great deal to effectively scope and define their MDM strategies.In the current economic environment, MDM is playing an important role in reducing compliance risk due to a lack of data transparency and trust, especially in the financial industries and others that have been hit hard. However, organizations are also looking for MDM to improve efficiencies and analytical insights so they can make better decisions, faster.
The business benefits of MDM:
MDM helps organizations handle four key issues:
1) Data redundancy: Without MDM, each system, application, and department within an organization collects its own version of key business entities. This leads to redundant master data and poor data quality.
2) Data inconsistency: Enterprises spend enormous resources trying to reconcile master data, often with limited success. Furthermore, this reconciliation process is repeated over and over because there is no mechanism to capture the data assets garnered from the first or succeeding reconciliations.
3) Business inefficiency: Redundant and inconsistent master data leads to inefficient supply chain management, inconsistent customer support, customer dissatisfaction, and wasted marketing efforts. Fractured master data in business processes causes ineffectiveness and inefficiency.
4) Supporting Business change: Organizations are constantly changing as new products and services are introduced and withdrawn, companies are acquired and sold, and new technologies appear and reach maturity. These disruptive events cause a constant stream of changes to master data, and without a way of managing these changes, the issues of data redundancy, data inconsistency, and business inefficiency are exacerbated.