Master Data Management challenges

MDM CHALLENGEExperience shows there is a clear and integral relationship between data quality, process execution and reporting integrity. Unified and accurate data allows for better business process integration, timely decision making, and streamlined process execution. It is imperative to achieve information consistency across the business and IT landscape.

Aside from the “Excel spreadsheet wars” where decisions are made or not based on whose report you trust; the foundational master data which is consumed by ERP and other enterprise applications must have integrity in order to support business continuity and provide reporting integrity.

Master data is best described as: “the information required to create and maintain an enterprise-wide system of record for you business entities, in order to capture business transactions and measure results for these entities.” However, without cleansed data with a high level of quality going into a master data management repository, organizations run the risk of a central repository where all their bad data is centrally stored. Hence, master data must be cleansed. “Get it clean” before it can be managed and “keep it clean” within the master data management system.

TRANSACTION RISKSConsistent customer master data has a direct correlation to business intelligence effectiveness. Without data integrity and business rules enforcement at the point of creation, data tends to be scattered, out of date, inaccurate and irrelevant; which makes it unusable for decision making.

The reality is that without properly attributed data, your ability to extract information and execute decision making are often comprised. To make it clear, your ability to meet business goals and metrics are often jeopardized due to the integrity of your data.

The challenge, of course, is that master data is often stored in multiple, disconnected systems/databases, and there can even be data management issues with companies implementing a new ERP, especially with multiple locations on different instances. As illustrated here, poor master data quality exposes companies to an array of business risks.


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