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Understanding MDM: Part 2
Informatica’s use of data integration to enable master data management (MDM)

by Lyndsay Wise, President, WiseAnalyticsMonday, August 25, 2008

Why MDM matters

Although master data management may seem very technical in nature and appears to have no bearing on business, master data management initiatives are actually one of the keys to ensuring customer satisfaction.  When customer information is not updated properly at a bank because a customer has both business and personal accounts, or when account numbers at a telco changes because a person moves to a new house within the same city, then receives notices about their account not being up to date, customers are bound to wonder whether or not they are valued.  After all, if an organization values their customers, their goal should be to make the customer experience a positive one, not one of frustration, where front-end employees do not have access to relevant customer data or where customers are responsible for their experience.  Instead of financial institutions, telcos, and other service organizations attaching people to account numbers and having disparate information across various systems, one main record should exist for each customer eliminating the need for the customer to have to manage account changes, disparate accounts separately, and be only connected through a series of account numbers.

Part 1 of this article identified Siperian’s partnership strategy to provide organizations with an end-to-end solution for master data management. Part 2 identifies business benefits of implementing MDM and how data integration activities such as those offered by Informatica can enhance the process of master data management.

How Informatica helps organizations with their customer experience management initiatives through data

To evaluate MDM and data integration solutions it becomes important to understand the overall process of how customer or product data stored in source systems across the organization comes to reside within a hub and act as a single source of reference for the organization. Within the overall MDM process, Informatica plays a complementary role by getting data into the hub from disparate systems across the organization, cleansing it, and then pushing the data back out to the appropriate applications and source systems.

Informatica partners with MDM vendors to provide an end-to-end MDM solution. The initial challenge of MDM involves identifying, capturing, and loading the appropriate data into the MDM hub(s) so that reference tables can be created.  To do this properly, a series of data quality and transformation activities have to occur. The diagram below shows the steps required to migrate data from the original source systems to an MDM hub.

Although seemingly simple, one of the barriers to many MDM solutions is capturing and accessing the right information stored in operational systems and turning that data into something that can be used within an MDM application.  Therefore, it is important to understand that to implement a successful MDM platform, additional data integration activities are required.

The general process of implementation

Informatica uses a three-step approach to enabling organization wide MDM. Using a systematic approach to MDM reduces the risks of capturing the wrong data initially and creating the need for iterative migration activities.  Avoiding these risks saves organizations money and increases the likelihood of project success.  Customers apply the three steps to help reduce the risks associated with an MDM project.

Step 1 involves the initial data loading.  This requires data profiling, cleansing, validation, and transformation (as shown in the diagram above).  These activities ensure that data entering the hub is valid and represents accurate data.  The ability to access different data sources, including complex structured and unstructured data can quicken the overall implementation process.  Identifying and accessing the proper data in legacy systems can take months. Integrating data integration within the process of MDM helps organizations focus on MDM as opposed to data capture.

Step 2 involves ongoing data quality initiatives to ensure the data constantly meets defined quality standards.  Additionally, batch and real-time data synchronization ensures that information is always kept up to date.  This allows data stewards and analysts to match records and validate at that is consistent and up to date, reflecting additions or changes made within operational and source systems.

Step 3 involves expanding the current use of MDM within the organization. Once an initiative is running smoothly and benefits are seen, organizations may want to expand MDM’s scope. For instance, organizations that implement CDI may want to expand towards consolidating and creating a single point of reference for suppliers or products to develop a more centralized view of information within the organization.

The chart below highlights these steps and identifies the information value and benefit of each.



Additional uses

In addition to the steps highlighted above, integrating data integration activities into the overall process also enables organizations to push data back out to sources systems.  By expanding data access, information can be stored in operational systems giving employees access to up to date information.  For employees that are the first line of contact to customers, this saves time and potential frustration, whether this involves only having to update customer information once or gives extra access to account and interaction history in one centralized location. Additionally, with the increased focus on data governance activities and integration, such as using Web Services or SOA to integrate disparate technologies, organizations need a better way to manage their data.  Using these processes enables organizations to collect metadata to manage how information interrelates as well as create an auditing process based on the information about the data that is collected. Basically, the audit function helps companies through the metadata management enabling data governance and delivering data as a service to help link MDM and SOA activities.

Tying it all together

It can be hard for businesses to understand the value of using technology to help drive success.  What MDM and the data integration processes surrounding it do are create a single access point to customer, product, supplier, etc. data to help organizations manage and enhance overall customer experience. This, in turn, can lead to increased customer retention rates, more effective marketing campaigns, and overall cost savings.  A popular example of how MDM does this is by creating a single customer reference record so that mail marketing campaigns do not send multiple mailings to one person. Although this may seem simple enough to accomplish without these initiatives, as data volumes grow and customer profiles become more complicated with multiple changes, additions, etc. a centralized method to manage customer information becomes essential.  In a world where people expect to be able to interact with a company the way they choose, to get impeccable service, and to come away satisfied, organizations that do not adopt some sort of data management process will fall behind of their competitors within the next few years.  To maintain competitive advantage, it becomes important to use data and technology to drive business agility.

About the Author

Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is a monthly columnist for DMReview and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at lwise@wiseanalytics.com. And please visit Lyndsay's blog at myblog.wiseanalytics.com.

(Copyright 2008 - Dashboard Insight - All rights reserved.)

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