For many (if not most) users, the indicators are the assessment: it is what they see at the end of the process, and what conditions how they respond.  How we choose and construct indicators is therefore crucial in determining the consequences of the assessment.    

Clearly the main need, in most cases, is to obtain some overall measure of impact.  Aggregated, synoptic indicators of the impacts are consequently essential outputs from most integrated assessments.  They can, however, be framed in very different ways (e.g. as the burden of disease or monetary cost), each of which may tell a somewhat different story and reflect different value systems.  They also do not tell the whole story, for by aggregating the impacts into a single measure they inevitably blur the detail, and because they focus on outcomes they only hint at the exposures and sources that have gone before.   For many assessments, therefore, a number of different indicators may be needed from different points in the causal chain and based on different perespectives, in order to tell users all they need to know, and to avoid unduly biasing the assessment.

Which to choose, and how to design them, are nevertheless difficult decisions.  They need to be based on a clear understanding of the issue that is being addressed, the interests of the stakeholders and the purpose of the assessment, in order to ensure that the indicators are useful for the task in hand.  The indicators also need to be individually interpretable (and, beneath that, scientifically valid), as well as collectively comprehensive and balanced, if they are to give reliable information.  

The figure below provides a framework for indicator selection and design, and lists key criteria that need to be considered in the process.  The links under See also, below, provide access to a more detailed set of guidelines for indicator selection, and a worked example. 

A framework for indicator selection and design