This document provides users with access to a data quality assessment checklist which can be used by operating units when creating data quality assessments.
The purpose of this document is to provide a foundational understanding of probability sampling to USAID staff to equip them as well-informed commissioners and consumers of surveys, evaluations, and other products (hereafter referred to as studies) that require probability sampling. We hope that it will serve as a resource for commissioners to make informed decisions about surveys and to use monitoring, evaluation, and learning (MEL) resources effectively. The main audience for this document includes monitoring, evaluation, and learning specialists, Contracting Officer’s Representative (CORs), and Agreement Officer’s Representative (AORs).
CLA and Developmental Evaluations
There is a growing recognition that political economy analysis (PEA) is an essential aspect of external donor assistance to complex health reform processes. USAID’s Vision for Health Systems Strengthening (2015–2019), for example, recognizes that “broad political economy issues often drive health systems organization,...
Six Simple Questions to Help Identify Your Monitoring and/or Evaluation Need
A learning agenda includes a (1) set of questions addressing the critical knowledge gaps impeding informed design and implementation decisions and (2) plans for learning activities to help answer those questions. A basic process for a learning agenda includes three key steps:Understanding the context Developing and...
This USAID Program Cycle Technical Note describes the 5Rs Framework and demonstrates how it can be applied to strengthen local systems and promote sustainability.
Monitoring and evaluation (M&E) is critical to all USAID programs for accountability reporting, measuring impact, and informing ongoing strategic management decisions. The principal lesson learned from the Office of Transition Initiatives’ (OTI) 15 years of experience operating in complex, dynamic, and...
As part of the Learning About Learning (L-squared) initiative, this one-pager describes lessons learned on the importance and role of feedback loops from the KDMD experience including a definition, value proposition, implementation process and recommendations, and a mini-case study.
This guidance provides information on conducting an After Action Review (AAR), including goals, assumptions/requirements, how tos, lessons learned/best practice, and resources.