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Planning with Logic Models

Planning with Logic Models

Do you sometimes find that your plans sit on the shelf collecting dust or the goals that you identified are seldom realized? Some plans are challenging to implement because they fail to identify SMART outcomes, measurements of success, or the long-term change that the each initiative was meant to accomplish.

One tool for creating effective plans, which is often used in the nonprofit sector, is the logic model. Logic models provide a structure for strategically identifying the resources needed for a new initiative or program and linking these resources to the intended results. To better understand the logic behind our plans, each initiative is broken down into inputs, activities, outputs, outcomes, and impacts.


Inputs are the resources needed to support and sustain a program or initiative. Using the example of a new affordable housing incentive program, an input would be staff time spent developing the program.


Simply put, the activities describe what the program does. For the affordable housing incentive program, one activity may be to offer bonus density in exchange for the development of affordable housing units.


When talking about the success or failure of a program or initiative, we tend to focus on outputs, which are the direct results of program activities. For example, the creation of 10 new affordable housing units in a year could be the output (result) of the affordable housing incentive program. Outputs address the immediate results produced by the program.


Outcomes, on the other hand, are the changes anticipated to occur as a result of the program’s outputs. An outcome for the affordable housing incentive program could be that the number of low-income households that are cost-burdened decreases 10% by 2025. A common method of vetting outcomes is to makes sure they are Specific, Measurable, Achievable, Relevant, and Time-bound, or SMART.


Finally, impacts are the long-term, community-wide change that we hope to see as a result of the program. Impacts are typically broader aspirations or goals. An impact of our affordable housing incentive program might be: Housing in our city will be accessible to people at all income levels.

Putting It All Together

Below is an explanation of how to read a logic model using our affordable housing incentive program example. As the “if...then” statements demonstrate, the elements listed should be logically connected to each other. 


Open a larger version of the logic model

Creating a logic model can help to identify flaws in your strategy or plan that don’t align well with the intended results. For example, if the affordable housing incentive program creates 10 affordable units per year, is it realistic to say the number of low-income renters that are cost-burdened will decrease 10% by 2025? Unless we are dealing with a small community, 10 units per year is probably not enough to make that great a change, so we may need to go back and adjust the inputs and activities to increase the number of units or decrease the outcome to something more reasonable. For example, we could increase the density bonus (our activity) to entice more developers to participate in the program (our input), leading to a greater number of affordable units being built (our output).

When you are creating a new plan or program, it is often helpful to work backwards, starting with the desired impacts. For example, when creating a new policy or initiative to address homelessness, a good long-term impact could be, “everyone has access to stable housing.” With that desired impact in mind, you can better identify the outcomes that would indicate progress and the specific outputs the plan should produce, such as the number of housing units needed. Once you have intended results for each level outlined you can create strategic programs and align resources to accomplish those results.

Measuring Success

With your strategy laid out in a logic model, it is easier to set up a system for evaluating your progress. During the process of creating outcomes statements, you may have already identified good measures of success, such as “the number of cost-burdened renters”. For impacts that cannot be measured directly, such as, “housing in our city is accessible to people of all income levels,” you may need to get creative or turn to academic research to find good indicators or proxies for housing accessibility.

Redmond Performance Measures

Redmond is using a version of the logic model assessment to measure performance on their Comprehensive Plan and Budget Priorities.  Plan priorities are broken into six areas: 

  • Vibrant Economy
  • Clean and Green
  • Diverse and Connected Community
  • Infrastructure
  • Responsible Government
  • Safety

For each priority area, Redmond has identified key outcomes and impacts and is publishing the results online to demonstrate whether the city is on track and where more work is needed (see the Vibrant Economy Performance Measures example below).


In this example, the desired impact is “a diverse and vibrant range of businesses and services in Redmond.” Two outcomes have been identified as:

  • A yearly increase in the number of businesses that have been in operation for seven years or more; and
  • A high level of satisfaction with employers, restaurants, retail shops, and services in Redmond, with 90% of residents indicating that they are either “satisfied” or “somewhat satisfied”.

Redmond’s performance measures provide a good snapshot of their progress on key outcomes from the city’s Comprehensive Plan and Budget Priorities. The range of inputs and activities dedicated to accomplishing these outcomes are outlined in Redmond’s 2017-18 Budget Priorities. These include marketing the city as a destination for tourism and implementing entrepreneurial programs like innovation districts to spur business growth.


If your agency is not already using logic models, they can take some time to become accustomed to. However, the time and effort dedicated to fleshing out your strategy can help to make your planning efforts more effective. Logic models are a useful tool for creating new initiatives or for evaluating existing programs to ensure that they align with clear, desired results, that resources are allocated effectively, and that a framework is in place for measuring progress towards each desired impact.

Additional Resources

MRSC is a private nonprofit organization serving local governments in Washington State. Eligible government agencies in Washington State may use our free, one-on-one Ask MRSC service to get answers to legal, policy, or financial questions.

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About Ben Johnson

Ben served as the MRSC Public Policy Intern from September 2017 to 2018 and assisted with updating topic webpages and responding to policy inquiries.

He is currently pursuing a Master of Urban Planning degree at the University of Washington. Prior to returning to school, Ben worked for five years facilitating neighborhood level planning and outcome evaluation for Habitat for Humanity of Kent County in Michigan. His outcome evaluation and resident engagement efforts helped to make community input and resident leadership central to Habitat Kent’s approach to working in neighborhoods.