At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (e.g., the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision‐making, and supports preventative action.

Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision‐making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post‐2020 global biodiversity framework of the Convention on Biological Diversity.