Measuring quality, quantity, and results

By Pieta Blakely | May 2, 2022

One of the risks when developing an evaluation plan, is developing measures without being really clear about what kind of measure they are or how we’re going to use them to understand our program. In this post, I’m going to talk about process measures (AKA outputs) and outcome measures — how they are different from each other and how they are both useful in understanding a program.

When evaluating your programs, you may want to consider two kinds of measures: process measures and outcome measures. Process measures help you assess what you’re doing and how well you’re doing it, and they are evaluated while the program is in progress. Outcome measures evaluate the effect the program has/had on its target population (its impact), and they can be assessed during or after the program is complete. 

Using research and evaluations to complement your internal evaluation

By Pieta Blakely | January 3, 2018

  In previous posts, I’ve mentioned that the further outcomes are in time, the harder it is to collect that outcome data. For example, if your program provides tutoring services to middle schoolers that are intended to increase their college attendance rates, it will be very challenging — and take a long time — to…

3 keys to selecting measures for nonprofit performance management

By Pieta Blakely | December 18, 2017

Many nonprofits are looking at performance management as a way to improve their ability to provide services and to use data intentionally for strategic planning. Here, when I say performance management system, I mean the collection of process and outcome measures that your organization collects and its approach to using those measures in strategic decision-making.…

Including performance measures in a logic model for program evaluation

By Pieta Blakely | December 8, 2017

Now that you have developed a logic model (check out this post if you still need some help, or download my logic model guide), you might be wondering how to integrate your data collection plans with it. If your logic model is clear, using it to build an evaluation plan will be pretty straightforward.