Case Study - Customer Relationship Management

The Client

Our client was a large multi-billion Dollar financial services group headquartered in North America.

The Business Challenge

Our client wanted to automate their policy administration processes with the aim of reducing operational costs. This CRM strategy required the integration of different databases. There was a need for flexibility for future enhancements and upgrades to match both the changing business requirements of the client's dynamic insurance businesses, and the rapid technological and structural changes anticipated in the industry.

The Solution

Following PRINCE2, Six Sigma (6s) and CMM Level 5 methodology, mi2g gathered the requirements from our client to document the common thread and the specific differences. The next stage involved extensive design sessions, which produced the Detailed Design Specification. The operation was then phased to enable a collective experience across subsequent implementations. After that, the generic base system was developed, and further enhancements and customisations were carried out.

Coding and exceptional customisation was delivered using Siebel Visual Basic. Reports were developed using Actuate and WebFocus. The initial data load was provided through the EIM process from the Customer Information File (CIF), which pooled in and stored data from the different legacy systems. The daily transactions were sourced from different legacy systems and were updated through OCIF (Operational CIF). Real Time connection from Siebel to the legacy system was achieved through the Mitem product.

Business Value

· Centralised development has saved several US million dollars in development costs 85% of the OCIF strategy and process is re-usable
· Simple user access from a single, common dashboard
· Customer databases centralised to maintain customer profile, transaction and interaction information
· Sales lead details and associated sales activity recorded in a central sales mechanism
· Producers can view their annual year to date standing in relation to the sales measures
· Cross-selling of products to increase sales, from demographic profiling, purchase history and shared data.


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