The benefits of master data management (MDM) can only be achieved if the strategy is broad-reaching and comprehensive. But, many organizations make the mistake of viewing MDM as a technical issue – a misbelief that can lead to project failure.
The premise is quite simple. In order for MDM to solve business problems, it must be tightly aligned with business activities.
The truth is, MDM encompasses both business processes and technologies. The technical solution will ultimately support the strategy – but the strategy itself must take into account the various people, policies, and procedures that play a role in data governance, access, sharing, and administration. In order for any MDM plan to work, it must take into call for the needed process adjustments and re-alignments.
The formalization and enforcement of data collection and management standards across the enterprise is what truly will enable the effective execution of MDM. For example, if the accounting department archives information in one way, yet sales and marketing handle the storage of historical data in a completely different manner, the results of an MDM program will be seriously hindered. In other words, consistent workflows must be implemented to promote the accuracy, timeliness, and integrity of corporate information.
In fact, in a recent post on BeyeNetwork, a popular blog that covers the business intelligence and information management industries, the following steps to reaching a stage of MDM readiness were defined as critical:
• Document business processes and how they map to application functionality
• Define and use common information concepts
• Assess the organization’s capabilities as they related to data quality and governance
The purpose of this exercise? Determine where procedures are lacking, and re-structure in a way that will most effectively support the new MDM strategy.
And, perhaps most importantly, which processes should be reviewed and assessed? Those that relate to information creation, updating, deletion, or archiving are the activities that have the greatest impact on data quality. Therefore, it is these procedures that must be effectively controlled in order for MDM to deliver desired returns.
Our next post will highlight data validation techniques. We’ll discuss the critical role they play in MDM, helping to ensure data consistency, accuracy, and integrity.
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