The thorough monitoring of progress on poverty and inclusion, and on the leave no one behind imperative, depends on reliable baseline data on the excluded groups and individuals and on the definition of indicators that can be used to track progress. To determine if and how the theory of change is realised, the monitoring system and the indicators must allow the close tracking of the progress of the defined group of people left behind.
There are currently no specific indicators to measure progress on leave no one behind, but this principle should rather be reflected in the indicators of all SDC programmes. The aspects below are key to consider in determining whether an indicator is relevant to measuring poverty and inclusion.
Disaggregated data: the disaggregation of data by sex, wealth, ethnicity or caste, religion, age and place of residence or other identity criteria such as disability enables the monitoring to identify who has benefited from development programmes and who has not. Context determines the criteria for disaggregation. Data collection is highly political and disaggregated data often are unavailable in contexts where they would be most relevant. This issue is of special importance for leaving no one behind, and the SDC should address it in its policy dialogue.
Qualitative data: indicators should also report on qualitative aspects of the results. Qualitative data collection methods such as focus groups, interviews or observations can capture transformative change and empowerment, help the SDC understand the motivations and opinion of the people, and provide insights. Beneficiary assessment is an excellent tool for integrating excluded people's knowledge and views into the planning and prioritising of interventions. In addition, gender and social inclusion analysis of a programme or portfolio and its projects will help the SDC understand any changes in the circumstances of the excluded people. Indicators should also provide qualitative information at the systems level, for example reporting on the nature of policies and measures addressing discrimination and inclusion of certain groups. This can provide a qualitative element in the review of the theory of change.
> Using knowledge from the margins to meet the SDGs: the real data revolution
> The Invisibility of People in Development Projects