The question of management and coordination of CRM analytics is an excellent one because it hits the heart of how organizations can best ensure CRM success. CRM strategies that are woven into the organizational fabric of a company are most likely to succeed. Taking the view that CRM is a business strategy, first and foremost, requires new thinking about how traditional resources in the financial services industry will be deployed in pursuit of attracting and retaining profitable customers.
Historically, I've seen a clear concentration of analytical expertise in the credit-risk management area of financial services companies. While analytics' role in this line of business (LOB) is critical to the organization to ensure a reduction in risk exposure, customer-acquisition and retention efforts could have benefited greatly from analytics too. For example, the FICO, or Fair, Isaac & Company, score for a young, college graduate facing significant tuition-loan repayment might, at face-value, suggest that this applicant applying for low-margin products such as a low-interest credit card (as compared to a home-mortgage loan) represents a high-risk, low-value customer. As a result, they might be denied credit. However, using customer-acquisition oriented techniques to apply a lifetime value model to the same applicant's profile might identify them as a long-term high profit customer -- one contributing to the success of the company's acquisition strategy.
This new thinking begins to hint that concentrating analytical resources in the marketing department might be appropriate. While some companies are now concentrating analytical expertise in the marketing departments, this is often not the ideal location. Why? Even though the marketing department is generally responsible for customer contact management strategies, these contact strategies tend to be driven by a particular LOB within the marketing department. Lacking a customer-centric business strategy and with P&L responsibilities tied to the LOB, there's little incentive for a given LOB to promote additional products (cross-sell and upsell) outside of those for which that LOB has responsibility, even when the prospective customer's purchase affinity is positive towards products outside of the LOB.
Information technology (IT) is another popular area for concentration of modeling expertise. The most clear-cut advantages to this approach are (1) unlike risk management and marketing, IT is viewed as a shared corporate resource, and (2) their familiarity with the available data can overcome a significant barrier faced by the other departments. Since any modeling exercise weighs heavily on data acquisition, synthesis of the account-holder or household, and significant efforts at data hygiene -- IT is in a strong position to build reliable predictive models. So, while modeling expertise is essential, it can only be empowered by a deep understanding of the data. In order for CRM analytics to succeed in IT, the analytical group should report into the CTO or CIO's office. While IT departments don't drive business strategy, these officers in today's market-savvy organizations are intimately familiar with business strategy.
The optimal location for CRM analytics -- without constraints as to organizational preferences and given visionary leadership -- is either the corporate planning or business strategy department. In many cases this office is headed by the COO and this ensures that the CRM analytics team's efforts will be closely aligned with the organization's overall business strategy. From a practical point of view, it means speedier resolution of conflicts than if other departments managed and coordinated CRM analytics, a benefit that shouldn't be underrated, given the value of quick response in meeting evolving customer needs.
This was first published in January 2002