Global Business Intelligence Strategy Study


A large Financial Services company chose Reformis to carry out a Business Intelligence Strategy study, sponsored by their Sales and Marketing channel.

The study had the following objectives:

  • Obtain an holistic view of their clients
  • Better understand the nature of their products and those of their competitors
  • Identify current and future areas of growth in terms of AuM and revenue
  • Answer ad-hoc business questions relating to clients and products in terms of AuM and Revenue, in an accurate and timely fashion
  • Reduced risk of erroneous reporting
  • Gain improvements in operational efficiency – automated data collation and distribution, reduce manual effort and dependency on key-individuals
  • A scalable management information solution to the global enterprise is required

Reformis Solution

Reformis identified that to meet these business objectives, an enterprise data management and reporting solution was required which must include:

  • A consolidated view of all clients, and a common method of classification
  • A consolidated view of the Investment Manager’s and the Investment Manager’s Competitors’ products
  • Internal book of records for clients with whom there is an Investment Management Agreement in place
  • Transfer Agency and Central Securities Depository data for all clients investing in the Asset Manager’s pooled funds including “segregated” clients investing in pooled funds and therefore cross-referencing is required to avoid duplication
  • Billing system data to obtain revenue against actively managed clients or clients investing in externally-charged pooled funds
  • Product master for pooled fund management fees to enable calculation of revenue earned on internally-charged pooled funds
  • External information provider data which can give insight into competitor products and clients.

The Reformis solution had the following key elements:

Reporting database – A reporting database was created based on the standard ReformIS Dimensional model for Asset Management. This model utilises Kimble methodology and logically separates data into “Dimensions” (textual elements by which figures are ‘cut’, such as Client and Product), and “Facts” (measurable, additive data such as AuM and revenue). Furthermore, the model is extendable as more “facts” are required (e.g. performance, costs) without changing the overall design by re-using Dimensions. The methodology ensures that all reporting is historically accurate, regardless of run date.

Business Intelligence (BI) tool – Based on the Asset Manager’s existing technology, Business Objects was proposed as a suitable tool to enable users to access BI information and answer ad-hoc business questions. Our solution emphasised that by designing a robust reporting database, the front end-tool can be changed with ease, or an additional tool utilised to give more reporting functionality (e.g. OLAP or data mining tools).

Data Transformation functionality – The client’s preferred technology for a data management and ETL solution was Informatica.

Project proposal – A project budget and timeline for implementing the BI solution was delivered in the form of a fully costed business case based on an approach which delivered business benefit frequently in an incremental and iterative manner.

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