Operational data are collected by a variety of organizations, including government ministries and humanitarian and development actors, to inform decisions about programming, responses and resource allocation associated with humanitarian action. Some, but not all, use professional and scientific methods. Operational data are generally timelier than official statistics, but they may not be subject to the same rigor and validation. While operational data may not necessarily meet the highest quality standards, they may be the only type of data available on certain migrant groups such as internally displaced persons (IDP) especially in the context of conflicts or disasters where national statistical systems are not fully functional (EGRISS, 2020). Operational data are not always released publicly, for example, in situations of human rights violations where sharing operational data with government authorities might cause harm to vulnerable individuals.
What are examples of operational data sources?
Population movement tracking systems are the main source of data on IDPs and forced displacement more generally in contexts where the production of official statistics is limited, e.g., during armed conflict and sudden or slow-onset disasters (EGRISS, 2020). IOM’s Displacement Tracking Matrix (IOM, 2017), is a key example of a population tracking system. Surveys referred to as ‘needs assessments’ are data collection exercises conducted at a single point in time, providing humanitarian agencies with an understanding of the IDP population or wider situation. Registration/enrolment systems, such as the World Food Programme’s (WFP) SCOPE platform, are also used as a source of operational data in IDP contexts and are often integrated into aid delivery systems. In the early stages of displacement, operational data might be the only data available, but in some contexts the absence of a fully functioning statistical system may result in operational data being the only possible source for data on IDPs and forced displacement. “For operational data to be considered as a source for official statistics, quality in all processes and transparency in the production of the data are key, and an assessment of the quality of the data should be carried out by NSOs or other relevant statistical units within NSS” (EGRISS, 2020: 6).