Some limitations of existing data are first identified and discussed. They include reliance on self-reports; the indirect relationship between available indicators and the underlying quantities of greatest interest; and an overemphasis on measures of drug use at the expense of other factors, such as externalities associated with drug-control efforts. Four encouraging trends are the ongoing expansion of traditional data systems, improving information about drug markets, greater integration across data sources, and better data from other countries. Although the relevant data are imperfect, they have been adequate to support initial efforts to quantify the effectiveness of a range of drug-control interventions. Which interventions are most effective depends on what one defines as the objective of drug control. Available evidence concerning one objective, i.e., reducing the quantity of drugs consumed, is reviewed and found to contain key insights but also to be lacking in important respects. There is a need for better information concerning interactions between various drugs and drug markets, interactions with other domains of social policy, how interventions' effectiveness varies over the course of a drug epidemic, and how epidemics emerge and how they can be controlled in their early stages. These limitations are best viewed as a challenge, not as an excuse for basing policy on less formal or ad hoc syntheses of the literature. Drug policy is not alone in demanding creativity in the adaptation and application of quantitative analysis to evaluate effectiveness. Other policy domains in which benefit-cost or cost-effectiveness analysis is now accepted went through a similar formative stage. 3 exhibits, 19 notes, and 163 references