The basic purpose of logic models is to articulate the “if-then” of why and how your program affects participants or communities. Technically, it is a visual depiction of a program’s activities and results. The models can be presented in many formats, and are similar to Theories of Change (which we also facilitate).
You may need a logic model because a program funder requires it, and this is a good reason to complete one. However, we believe logic models should be more than a piece of paper that sits forgotten in a grant application. Our service aims to help you better understand and communicate your program theory and outcomes.
Logic models help you and your program staff understand the what and why of what you do each day, tell funders why your program should be funded, and measure your program outcomes.
Via Evaluation clients who have taken part in our logic model process have expressed how valuable it was to fully understanding their program and the ways it may affect positive change. They have used the logic model to communicate with program sites and key decision makers about why a program works or what needs to change if it doesn’t. They have also used logic models to reduce the burden of data collection by focusing data collection efforts on elements in the logic model, rather than collecting anything and everything.
Clients have called our approach “energizing,” “clear,” and “useful”. Other comments include:
Love the visual & the real understanding of what we do. You are very easy to understand and work with.
The visual display really helps to look at where we have been, where we are, and where we (hopefully) are headed as an organization.
Via Evaluation staff has extensive training and experience creating and using logic models for many types of programs. If you choose to work with Via Evaluation to create a logic model, you will receive:
If appropriate, Via Evaluation also will conduct site visits or interviews with program staff of existing programs before doing the logic model. Completing these activities have helped reduce the gap between perceived theory and “reality on the ground,” resulting in discovery of unanticipated program outcomes and more realistic logic models that staff understand and use.