OBJECTIVES: Drug plan decision makers make choices of considerable financial impact in short periods of time. To reduce financial risks of new drug policies, they demand timely support from their analysts to: make transparent decisions in the midst of opposing objectives, monitor expenditures and revenues to meet budgets, minimize financial risk from poor policy choices, and communicate analyses in readily understandable ways. METHODS: Crude analytical methods such as simple trend projections are frequently used to assist policy makers in their day-to-day planning. However, crude techniques carry substantial financial risks if applied to complex policy changes. More sophisticated projections, if performed, prevent high-level decision makers from fully understanding all assumptions and limitations. We will present a case study of a change in a drug benefit plan decision-making process that evolved from a need to overcome the aforementioned limitations. The province of British Columbia implemented a complex drug policy change for its 550,000 elderly residents in May 2003. RESULTS: In the months prior to the policy, a decision-making process was created that made feasible the financial impact analysis of hundreds of policy scenarios. CONCLUSIONS: The capacity to analyze a large number of scenarios allowed decision-makers to minimize financial risks and tailor the new policy to available budgets.