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 on 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 decision making in our development projects. This focus on quality data enables us to make informed decisions that create maximum results for our stakeholders and beneficiaries.
Data Quality and Management.
Who Says Math Isn’t Cool? Applying Mathematical Optimization in Public Health Supply Chains
Across industries, companies work tirelessly to optimize their supply chains to get customers what they want, when they want it, and spend as little money as possible in the process. From agribusiness to e-commerce and information technology, companies strive for better data, stronger foresight, and breakthrough innovations that allow them to deliver high-quality goods faster…