5 Key Factors of Master Data Management

data management Master data management (MDM) is where an organization manages data via a single point of reference is a growing trend, and more and more companies are getting on board. In fact, GlobeNewsWire reports “the global master data management market is expected to grow from $9,440.4 million in 2015 to $26,799.6 million by 2020, at a compound annual growth rate of 23.2% during the forecast period from 2015 to 2020.” But for MDM initiation to be successful and for organizations to truly reap the rewards, it relies upon five key factors.

Management and Staff Support

Perhaps most important of all is having the complete support of everyone involved with the process. Because of the often exhaustive nature of MDM initiation, long-term commitment and changes it can bring about with in an organization, it’s crucial that everyone buys in and is willing to do whatever it takes to make the process a success. Otherwise, a lack of support can throw a serious wrench in things.

2) Quality Data

If master data is inaccurate, extraneous, contains duplicates or is generally of low quality, it basically defeats the purpose of implementing MDM. Not only can it be costly to an organization and reduce profitability, but it can put a damper on productivity as well. Consequently, it’s imperative that master data meets strict quality standards, which is why many companies utilize data profiling to assess the quality of data prior to data migration.

3) Efficient Data Integration

Besides upholding rigorous quality standards, the actual process of consolidating data and moving it to a master repository needs to be efficient. Whether it’s a single company creating a master repository between different departments or two companies combining data during a merger, the data integration process needs to be as streamlined as possible to minimize setbacks and prevent it from being overly time-consuming.

4) A Secure and Scalable Master Data Repository

MDM Cloud In an age where cybercrime is an omnipresent threat, security should be a major priority for everyone involved with MDM. An organization should uphold scrupulous security standards throughout initial integration and continue to uphold them moving forward. And because there’s a good chance that a data model will require modifications at some point in the future, it’s wise to have a repository that’s flexible enough to accommodate those modifications.

5) Continual Quality Control

For MDM to be successful in the long run, it’s important for an organization to take quality control seriously. Developing a data quality assurance program is usually the most effective way to go about it – and different departments throughout an organization need to be on the same page to maintain consistency. Doing so should ensure that data remains of the highest possible quality for years to come.

The bottom line is that MDM can do wonders for a company and is likely to be a growing trend over the next five years plus. But in order for MDM to be a success, it’s contingent upon these five main factors and a certain amount of persistence.