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  • Brittany Erikson

Quantifying and Increasing Impact - Start with Great Program Design


In the update to my last post, I included a list of topics this series will explore. These topics are process ordered and written as if the reader were considering starting a new program. In more mature organizations, many of these are happening constantly and concurrently.

  1. Start With Great Program Design

  2. Ensure Fidelity to the Researched Model

  3. Internal M&E Basics

  4. Guiding Principles for External M&E

  5. Using Data to Inform Practice and Improve Impact

Today, we'll start from the top with some basics about program design. Before beginning a new program or creating a new organization, there are a few things everyone should do.

Define the Population and Impact

First, they should clearly define the population they seek to serve and what impact really looks like for that population. As an aside, at RTNF, we hold specific values regarding how defining populations and impact should be done (see this blog post), but for the purpose of this post, we will simply say that a program director has to know who they are serving and what the desired impact on that population is. Some questions you might ask to define the population you seek to serve follow:

  • What are their demographics?

  • What are their hopes and passions?

  • What are their unique challenges? Or, what obstacles do they face?

  • What opportunities do they have/lack?

  • Do they have unique skills and abilities?

Once you know who you seek to serve, you can begin the work of defining what real impact for that population looks like. What life-improving or system-changing outcomes do you seek? How is success for that population defined? Some examples for inspiring outcomes we've seen are listed below:

  • Increased income

  • Increased food security

  • Improved health outcomes

  • Increased rates of gainful employment

  • Increased education level

  • Lives saved

  • Creation of more just/equitable institutions

  • Tons of CO2 abatement

Once you have defined the population you're serving and have a clear idea of the impact you seek, you can begin program research.

Base Program in Peer-Reviewed Research

What does program research look like? It can take many forms, from focus groups to visiting programs serving similar populations, but one thing it should always include is a literature review of peer-reviewed research and evidence-based policy databases. While learning from peers and clients is vital, such literature reviews are just as vital and often neglected or poorly executed.

Studying peer-reviewed research and evidence-based policy databases is critical because it helps you leap frog mistakes and problems other program directors have already encountered and is incredibly helpful in identifying the best interventions available (rather than just a "good" intervention). It is counter-productive to reinvent the wheel when there is often a plethora of information available about best practices offered by field-leading experts.

In our experience it is more rare than common that program directors will conceive of a truly new and promising program model wherein none of the program's constituent parts have been studied. However, when that does happen, it is more common than rare that said program director can then find enthusiastic faculty members in that field at a university to partner with to perform a new study of their program, and can sometimes even get the study funded by the researcher themselves (if the researcher sees the study as potentially field-building and publishable, they are more motivated to find a way to fund the study).

You may be catching on to a theme here. Programs should either be based in peer-reviewed research or should be generating peer-reviewed research so that program directors are not reinventing the wheel, but can instead identify the best wheel already on the market and begin innovation from that point.

Once you've identified the best program for your population, the next challenge is to ensure fidelity to that identified model. Our next post in this series will discuss some of the issues related to program fidelity.


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