Unlock the Value of Data with Master Data Management

Master data management (MDM) involves a set of processes and tools that manage one set of data across the enterprise, rather than maintaining multiple sets of it in each transactional system. MDM solutions attack the problem of data quality at its source, providing a systematic approach that improves data quality in the various data domains, and maintains it continuously. Recently, there has been increased attention on MDM due to the popularity of business intelligence applications. MDM unlocks the true value of business intelligence by providing a master version of data, which leads to a consistent view of business performance that can be accurately measured and analyzed.

MDM is a cross-functional, technically complex, process-oriented discipline affecting information about customers, products, suppliers, locations, and more. Since integrating master data is perceived as an IT issue, business stakeholders may be reluctant to engage in MDM initiatives. However, MDM requires acceptance and wide organizational support, and the message resonates best when MDM is placed into a business context.

The Business Impact of Bad Data
The business value of corporate systems is only as good as the information that can be leveraged to make decisions. Typically, the technology landscape of an enterprise consists of a complex set of disparate systems and technologies, including Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Supply Chain Management (SCM). This fragmented environment creates proliferating islands of information. The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year. Yet, most executives are oblivious to the data quality issues that are slowly eroding the value of their organizations.

Errors in master data across multiple sources cause the steady erosion of an organization’s credibility among customers and suppliers. They also cause an inability to leverage business intelligence investments and make sound decisions based on accurate information. For example, they could lead to a customer being shipped the wrong products, or being incorrectly billed. This will lead to customer returns and disputes, costing organizations from both a monetary and a reputation perspective.

Fragmented, inconsistent data also affects cross-sell and up-sell ability, delays time to market for new product or service launches, creates supply chain inefficiencies, and weakens market penetration. Enterprises often have to deal with long product release schedules, increased inventory, stock-outs, and increased costs in regulatory compliance. Overall, these issues can end up costing enterprises billions of dollars.

Why MDM? In our experience implementing MDM with customers, we have observed that the financial benefits can be derived from both a cost savings and a revenue enhancement perspective.

There are direct benefits of MDM — such as reduced data management and integration costs, and indirect benefits — such as added incremental value to existing initiatives, including increased cross-sell and up-sell opportunities, and improved customer retention. MDM is one of those technologies that deliver value to the organization by impacting both the top and bottom-line results of an organization. Having access to the most accurate information from various sources allows an organization to better target marketing messages to their customers, leading to increased revenue by up-selling and cross-selling products that are of interest to these customers. Furthermore, it helps organizations avoid customer defection, as often customers leave due to the dissatisfaction of not being understood. There are many other examples of how MDM helps organizations, including improved call center productivity, increased campaign responses, and reduced costs of implementing IT projects and building reports. However, managers must quantify this value for the organization to show the specific impact that will be delivered.