“Most BI and CRM projects fail due to the lack of data quality”
 Pascal Laik, VP, Oracle Master Data Management Products, Oracle Corporation, shares his perspective on why it is critical for BI or CRM projects to include a Master Data Management (MDM) component
How important is MDM to the CRM and BI strategy of an enterprise?
We believe MDM is a critical component of any successful CRM and BI project. Our experience shows that the most important reason why CRM projects fail is due to the lack of data quality. MDM originated when CRM customers asked vendors to provide MDM in addition to pure CRM features and functions i.e. with a layer of data management and data quality services that would enable superior data quality.
MDM technology provides a single view of a customer or product—which is what CRM and other enterprise application projects require to be successful. This can be done by executing some basic tasks such as consolidating data from multiple sources to build the single version of truth, cleansing the data centrally (standardization, reduplication and enrichment of the data) and sharing this data with consuming applications such as CRM systems, web applications, back office systems, etc. Similarly, a large cost of BI projects comes from constructing complex ETL (extract, transform, load) maps to move data from source systems to the data warehouse and maintain these rules. MDM can lighten this burden by constructing a single view of the master entity such as customer, supplier, product, sites etc. The population of these valuable cross reference tables that link a global ID with IDs of different systems together, can feed into the BI layer. This eases the job of doing analytics on a clean set of data. Thus, any modern system architecture supporting CRM or BI projects now includes an MDM component.
Based on your experience of dealing with Indian enterprises, how serious is the problem of data quality and how can MDM help?
Data quality is a major issue which prevents companies from fulfilling the ROI potential of their enterprise application initiatives. It slows down IT agility and represents a major obstacle to application solutions adoption. We believe that Indian enterprises have to address one more challenge vis-à-vis companies outside India. This challenge is with respect to the size of the datasets their applications have to manage and the scalability performance target their systems need to meet. The volume of data adds a level of complexity to the data quality challenge. As an example, the probability of having duplicate information in a database of 100 million records is higher than that in a database of 10 million records. In this context, MDM can help Indian organizations manage their data effectively and intelligently.
In which Indian sectors is there potential for adopting MDM solutions? And why?
Some sectors where MDM can help include telecommunications, the public sector, banking, retail and high-tech manufacturing (including automotive) and higher education. For example, the public sector can use MDM to get a single view of a citizen and the services he consumes. In the retail sector, MDM solutions can be used to build customer royalty and strategically source products.
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