Case Study - Customer Relationship Management
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.
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.
· 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
· 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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