Logic Model Workbook
The Innovation Network's Logic Model Workbook is a do-it-yourself guide to the concepts and use of a logic model. A logic model is a commonly-used tool to clarify and depict a program within an organization. You may have heard it described as a logical framework, theory of change, or program matrix—but the purpose is usually the same: to graphically depict your program, initiative, project or even the sum total of all of your organization’s work. It also serves as a foundation for program planning and evaluation. It describes the steps necessary for you to create logic models for your own programs. This process may take anywhere from an hour to several hours or even days, depending on the complexity of the program.
Hiring an Evaluation Consultant
This Usable Knowledge white paper breaks down tips to hiring an evaluation consultant, thoughts about what to look for in an evaluation consultant and how to select and hire one for your next evaluation project.
What Impact? A Framework for Measuring the Scale and Scope of Social Performance
Leaders of organizations in the social sector are under growing pressure to demonstrate their impacts on pressing societal problems such as global poverty. This Social Enterprise Initiative, Harvard Business School working paper reviews the debates around performance and impact, drawing on three literatures: strategic philanthropy, nonprofit management, and international development. We then develop a contingency framework for measuring results, suggesting that some organizations should measure long-term impacts, while others should focus on shorter-term outputs and outcomes. In closing, we discuss the implications of our analysis for future research on performance management.
How to Support Your Data Interpretations
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.
Ten Reasons Not to Measure Impact—and What to Do Instead
Ten Reasons Not to Measure Impact—and What to Do Instead, a Stanford Social Innovation Review article, simplified the task of improving data collection and analysis with a three-question test. The author emphasized that if your organization cannot answer yes to at least one of the following questions, then your organization probably should not be collecting data. 1) Can and will the (cost-effectively collected) data help manage the day-to-day operations or design decisions for your program? 2) Are the data useful for accountability, to verify that the organization is doing what it said it would do? 3) Will your organization commit to using the data and make investments in organizational structures necessary to do so?