In my examination of the top criteria applied by IT organizations during customer data integreation (CDI) and master data management (MDM) solution evaluations, I consistently see 10 major areas of focus:
- Customer data model,
- Business services,
- Identity management,
- Data management,
- Developer productivity, and
- Vendor integrity.
Much discussion has already been given to criteria one through seven. Given my recent experiences with evaluation teams, I would like to provide more detail on number eight - analytics - in this month's column.
The basic premise is that CDI and MDM solutions go a long way toward integrating front- and back-office systems, i.e., linking sales/marketing/service enterprise customer relationship management (CRM) functionality with the financials, especially with the enterprise resource planning (ERP) back office. Despite being marketed by the various CRM and ERP vendors as ready for such integration off the shelf, most businesses are underwhelmed by CRM and ERP packaged capabilities to do so.
Additionally, there is the contemporary requirement to link the operational aspects of the business with the analytical. This is where both CRM and ERP have evolved to bundle a series of data marts or an enterprise data warehouse to bridge the two worlds.
However, no longer are batch-oriented data marts or data warehouses sufficient to provide the fundamental analytics necessary to drive customer profitability and value assessments to enable just-in-time, segmented and differentiated customer service.
If one of the primary justifications for CDI and MDM investments is to provide cross-sell capabilities across heretofore siloed product lines, we will need the analytics component of our systems to, for example, suggest the "next best offer" to increase share of wallet for our customers.
Furthermore, much of the information captured in real time at the point of contact with the customer (B2C, B2B or B2B2C) needs to feed the analytics/business intelligence (BI) engines such that the various customer-scoring algorithms can further determine likelihood of attrition and so forth. Again, this is a simple but poignant example of integrating analytical with operational systems. Often such in-line analytics are characterized as closed-loop marketing.
Another example of the necessity for BI systems to link up or embed themselves in the operational aspect of CDI-MDM solutions is related to the fine-tuning of the algorithms for customer identification management. BI tools such as data profiling help manage the degree of trust associated with given customer master data sources - for example, completeness, uniqueness, accuracy and data lineage. For certain CDI-MDM vendors this is a critical advantage, as they allow the data steward consoles to capture heuristics and otherwise fine-tune the probabilistic and deterministic algorithms used for identification management.
Compliance management is another key driver in the adoption and justification of CDI-MDM solutions. Regulatory compliance and the associated reporting are often key business justifications for the deployment of a master data solution. To do so, it makes economic sense to leverage existing data marts as certain vendors do with their prepackaged anti-money laundering, Basel II and Patriot Act compliance and reporting systems.
The continuing convergence of BI capabilities with CDI-MDM solutions provides a number of benefits to both initiatives:
- IT can better deliver core capabilities to manage master data in a manner complementary to existing major enterprise data warehouse investments (note that master data already resides in such data warehouses);
- Both BI and CDI-MDM can cooperate to mutually drive down the high costs of manual data administration, i.e., eliminate duplication of master data processes for customer data; and
- Data governance is mutually simplified and coordinated through convergent architectural and stewardship processes to reduce total cost of ownership for both BI and CDI-MDM.
See you at CDI-MDM Summit 2006 in New York City this October 15-17 and in Amsterdam November 6-8. There will be numerous case studies that highlight the ongoing integration between BI and CDI-MDM.
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