We All Count develops tools, case studies, practices, and systems to improve equity in data science. This information is combined to create the Data Equity Framework, a living, feedback-responsive system for addressing data project equity which is continually updated, added to, and refined.
The Stanford Social Innovation Review's Generalizability Puzzle is a paper that recognizes that any practical policy question must be broken into parts. Some parts of the problem will be answered with local institutional knowledge and descriptive data, and some will be answered with evidence from impact evaluations in other contexts. The generalizability framework set out in this paper provides a practical approach for combining evidence of different kinds to assess whether a given policy will likely work in a new context. If researchers and policy makers continue to view results of impact evaluations as a black box and fail to focus on mechanisms, the movement toward evidence-based policy making will fall far short of its potential for improving people’s lives.
Performance Measurement and Management helps governments and nonprofit organizations track and improve their effectiveness and efficiency. Performance measurement is the process of regularly tracking progress on a series of program indicators. Performance management is the practice of using that data to inform decisions and make improvements. The Urban Institute has been a leader in performance measurement and management for four decades. Early on, we pioneered performance management techniques that government agencies still use to evaluate and improve public services, from garbage collection to human services to economic development. Our research also helps public agencies and private nonprofit organizations identify what questions to ask, what data to collect, and how to use that data to manage and improve their work.
This is a lovely book that simplifies all the academic program evaluation language so it can be readily used by nonprofits. This is a nice, easy book to read. A nice, easy primer in program evaluation, written for nonprofits. However, the book does assume that you know you need to do program evaluation - which most small- and medium-sized nonprofits do not really need to do. And, while she presents a section on reports, it's a little lean. This book is really great to read if you *want* to understand all the terms in program evaluation so you can do fancier impact measurement or talk with outside evaluators who are conducting a program evaluation with you.
This is an AMAZING book, well researched, easy to read, about why you should combine data and narratives, and some strategies for doing just that. WARNING: The book is written for data scientists and the author, the wonderful Brent Dykes, spends the first half of the book helping them understand why they should use data inside a story and with personal narratives - rather than just presenting a bunch of numbers! As a nonprofit leader, you might want to start at Chapter 4 (all the chapters are described in the link). I incorporate a lot of Brent's work ImpactStory™ Group Coaching.
