Method: The design is based on a pattern the author observed repeatedly during a decade of building systems for actuaries and researchers: data is provided using traditional data warehousing, the calculations are implemented by IT in a manner that solidifies stable elements yet externalizes change-prone elements, system operation is exposed through self-service interfaces that allow users to configure and run the calculations against large data volumes, and the output is delivered by standard business intelligence tools and customized approaches.
Results: Systems with this design: optimize the users’ time by moving the majority of the lower-value work to IT, have solid auditability and legal compliance, and provide high computing power and storage capacity, but do require users to give up some amount of control and flexibility.
Conclusions: Organizations should use this design to give their most advanced knowledge workers high power, localized control, and optimal efficiency.
Keywords: Data warehousing, exploratory data analysis, actuarial systems, ratemaking, modeling, simulation.
