The United Nation's Agenda 2030 and Sustainable Development Goals (SDGs) pick up where the Millennium Development Goals (MDGs) left off. The SDGs set forth a formidable task for the global community and international sustainable development over the next 15 years. Learning from the successes and failures of the MDGs, government officials, development experts, and many other groups understood that localization is necessary to accomplish the SDGs but how and what to localize remain as questions to be answered. The UN Inter-Agency and Expert Group on Sustainable Development Goals (UN IAEG-SDGs) sought to answer these questions through development of metadata behind the 17 goals, 169 associated targets and corresponding indicators of the SDGs. Data management is key to understanding how and what to localize, but, to do it properly, the data and metadata needs to be properly disaggregated. This paper reviews the utilization of disaggregation analysis for localization and demonstrates the process of identifying opportunities for subnational interventions to achieve multiple targets and indicators through the formation of new integrated key performance indicators. A case study on SDG 6: Clean Water and Sanitation is used to elucidate these points. The examples presented here are only illustrative-future research and the development of an analytical framework for localization and disaggregation of the SDGs would be a valuable tool for national and local governments, implementing partners and other interested parties.
localization disaggregation sustainable development goals data monitoring and evaluation international development statistical analysis