Seven ways to reduce IT costs for master data management systems

In the midst of the current economic crisis, IT managers are caught in a dilemma: while spending is shrinking, companies do not want to lower the level of service that it provides to their users.

So, how do you maintain and even improve the service level while ensuring the efficient operation of the enterprise? It decision-makers are starting to seek help in this area: investment can accelerate cost reduction while simplifying business processes. Master Data Management (master MANAGEMENT,MDM) software and services are designed specifically for this purpose. Master Data management is designed to help organizations coordinate multiple systems and multisectoral master data assets-files, Internet and LAN sites, e-mail, spreadsheets, video and audio, and 24x7 maintenance services.

An MDM platform comprehensively demonstrates the persistence of enterprise data assets and aggregate allocation data, accelerating processes, projects, and products through different channels.

But a major factor in MDM applications is front-end cost. The cost of deploying MDM may be more than $1 million trillion, which is somewhat unacceptable for companies that are not fortune 1000 companies.

However, market competition has changed the situation. So far, the MDM market has been dominated by IBM, SAP and Oracle. The best-selling MDM software and services suite includes IBM WebSphere customer Center, Oracle-siebel customer Data Hub, Universal Customer Master, and SAP NetWeaver Mdm.

Other companies are also starting to move into the field, broadening the market for MDM products. Teradata, which was separated from NCR in 2007, also launched an MDM product, as well as companies such as Dataflux, I2, Initiate Systems, Kalido, Purisma and Siperian.

This article provides 7 ways to reduce IT costs with master data management, and the author is Senior product Marketing director Ravi Shankar, the master data management platform provider Siperian.

Approach one: reduce integration costs

An inevitable way to reduce it costs is to cut end-to-end integration of applications. Business processes such as OTC (accounts receivable) reduce applications in heterogeneous environments-including order management and accounts receivable-for complex end-to-end integration between stand-alone applications.

Add up the number of business processes that are processed by all business applications and you get a highly complex information network.

This end-to-end integration is very costly both for configuration and maintenance, but MDM simplifies this process by centralizing common information (master data), which is available at any stage of the business process.

Two ways: eliminating duplication of third-party data costs

Streamlining data from third-party data providers can save a lot of cost. For many organizations, the integration of third-party data such as Dunn & Bradstreet, Acxiom, IMS, or Reuters is an important requirement in their business operations.

However, the different departments within the same enterprise often obtain data based on their own needs, and they are unaware that other departments within the enterprise have obtained the same data from the same source.

Using MDM, you can integrate Third-party data directly into the MDM system and then allocate it to all branch applications. This reduces the cost of duplicate data to the cost of a single piece of data.

Approach three: Reduce the cost of cleaning up data

Clearing data centrally in an MDM system can also save a lot of costs. Most businesses buy data quality tools to clean up data in applications for business goals such as direct marketing.

This can lead to two problems. First, the cost of multiple applications can add up to a serious impact on the IT budget. Second, because cleanup is an application that works independently, it has not been extended to duplicate deletion between multiple applications.

By integrating the data generated by these stand-alone applications into a central MDM system, enterprise users can purge all redundant data within the enterprise under one system. This method can not only solve the conflict between the original application, but also create or save any data change events.

Therefore, by centralizing the data, enterprise users can save the licensing and support costs of purchasing data quality tools.