Data quality is central to our work and allows us to confidently make data-driven improvements to our programming and stand behind our reported results. We conduct data quality assessments based on five categories: validity, reliability, timeliness, precision, and integrity. Using industry best practices, innovative MEL methodologies, and the latest technology for data collection, management, and analysis, we mobilize large quantities of data for effective management and evidence-based decision making in our development projects. This focus on quality data enables us to track and deliver results for our stakeholders and beneficiaries.