outcomes they know they need to measure if the theory is going to hold. These are the outcomes that must be operationalized (that is, made measurable by one or more indicators.) At a minimum, every outcome for which initial interventions will be designed should have at least one indicator. Though indicators are valuable, it may be necessary to do more in-depth data collection and analyses to assess whether and how outcomes and assumptions have been realized. Monitoring and evaluation As the origins of Theory of Change lie in the field of monitoring and evaluation, developments over the years have ensured that Theory of Change continues to be an invaluable method to conduct evaluations of many different types of projects and organizations. Often posing theory-based evaluation questions helps to focus evaluation efforts on key concerns. As well, there may be a need to pick the right indicators from among the many available, and one can use “monitoring questions” to select the indicators that will be most helpful. The monitoring questions take the form of “What do we really need to know in order to manage grant-making directed to the achievement of this outcome? It is important to understand success beyond just knowing “what works”. Experience has shown that blindly copying or scaling an intervention hardly ever works. An important task for monitoring and evaluation is to gather enough knowledge and understanding so as to be able to predict – with some degree of confidence – how an initiative and set of activities might work in a different situation, or how it needs to be adjusted to get similar or better results. We also need to be able to combine evidence from a number of studies in order to build a stronger picture of what is taking place, how it is unfolding, and, most importantly, how context influences the initiative. Just as development of a Theory of Change is a participatory process, a ToC-based monitoring and evaluation system can be designed in a participatory way. For example, grant managers can be involved in choosing the outcomes of greatest interest to them in their decision-making. Similarly, people on the ground can have input into which indicators to use and how to operationalize them, choices of instruments and methods of data collection, and which existing sources of data may be used in tracking indicators. Comparison with other models Practitioners have developed logic models and