As the demand for Customer Data Integration (CDI) solutions is ramping up, the large application vendors (like Siebel, SAP and Oracle) are trying hard to position themselves as the preferred solution provider in this space. Unfortunately, their attempts have been quite unsuccessful because of some inherent limitations of their approach. As these application vendors anchor their CDI solutions on their own applications (in particular CRM applications), they lack the flexibility to become an enterprise-wide platform that delivers unified customer views across diverse set of application systems and data repositories to multiple users. Moreover, their rigid framework limits the ability of an enterprise to adapt these solutions to the changes in data sources and IT environment that are routine in most large organizations. Consequently, it is not surprising that according to a recent survey by industry analyst firm The CDI Institute, more than 75% of IT professionals stated that they were actively considering purchases ‘outside the family’ to facilitate connectivity between customer-facing applications and processes to better handle CDI initiatives.

CDI is rapidly becoming a strategic initiative for enterprises who want to successfully target, acquire, develop and retain customers. However, in order to benefit from CDI, an enterprise needs to create a unified and comprehensive customer view from all disparate data sources—including CRM, financial, product, and external data services. Once integrated, these unified customer views provide the entire organization with the ability to drive meaningful business action within and across operational systems. While building and managing a unified customer view—across disparate data source, applications and channels—has often proved to be a complex and costly exercise, a neutral, metadata driven, rules-based approach to building a open customer hub can make the process much easier.

Neutral, Template-driven Data Model

The most critical feature of a CDI solution is its ability to let organizations develop an enterprise-wide customer data model suitable to provide a system of record for all master customer data. In order to be effective across an organization, a CDI platform must support a broad range of data structures contained in multiple customer data sources.

Application vendors take the approach of building an enterprise data model, often borrowed from one of their enterprise applications, in their CDI solutions. This approach requires an enterprise to adopt this pre-determined model with minor modifications. There are two key problems with this approach. First, it is extremely difficult to change or extend the data model that comes with these CDI solutions. This makes it very challenging to consolidate data from other applications and data sources that are outside the scope of the application vendor. In a large enterprise, where it is common to have customer data spread across 20-30 data sources, applications from a single vendor typically control at the most 10-20% of these sources. The rest of the data sources, including most of the external data sources, have to be mapped and transformed to feed data into the vendor’s customer data hub. Therefore, standardizing on the application vendor data model means more, not less, work. Second, since the application vendor data models were developed originally to support proprietary applications, these models are too complex and contain too many extraneous attributes than are not required for the CDI solution. This not only duplicates a lot of unnecessary data in the customer hub and impairs the performance of the system, but also makes data mappings, data imports, and addition of new data sources unnecessarily complex.