Developing Logic Models for Grant Proposals

What Is a Logic Model?

A logic model is a visual representation of how your program works. It maps the relationship between the resources you invest, the activities you conduct, the immediate products of those activities, and the changes you expect to produce. Think of it as a roadmap that shows how your program gets from Point A (the problem) to Point B (the desired outcome).

Funders request logic models because they reveal whether your program design is coherent. A well-built logic model exposes gaps in reasoning — places where activities do not clearly lead to outcomes or where outcomes are assumed rather than supported. It also makes your proposal easier to evaluate, because reviewers can see at a glance how all the pieces fit together.

The Five Components

Most logic models follow a linear chain with five components, read from left to right.

Inputs

Inputs are the resources you bring to the program: funding, staff time, equipment, facilities, partnerships, and expertise. List everything you need to operate the program. If a critical input is missing — say, a trained evaluator or a community partner — reviewers will notice the gap.

Activities

Activities are what your program does with those inputs: training sessions, mentoring, outreach campaigns, service delivery, data collection, or research experiments. Activities should be specific and connected to your objectives. Avoid vague entries like "provide support." Instead, describe the particular activities you will conduct.

Outputs

Outputs are the direct, measurable products of your activities. If your activity is conducting workshops, the output is the number of workshops held and the number of participants trained. Outputs are things you can count and control. They answer the question, "Did we do what we said we would do?"

Outputs are necessary but not sufficient. A program can produce impressive outputs — hundreds of workshops, thousands of brochures — without producing any meaningful change. That is why the logic model continues beyond outputs.

Short-Term Outcomes

Short-term outcomes are the immediate changes that result from your activities, typically occurring during or shortly after the program. These are changes in knowledge, awareness, skills, attitudes, or motivation among your target population. For example, after a financial literacy workshop, participants demonstrate increased knowledge of budgeting concepts.

Long-Term Outcomes (Impact)

Long-term outcomes represent the sustained changes your program ultimately aims to achieve: changes in behavior, conditions, status, or systems. These might include reduced poverty rates, improved health outcomes, increased college graduation rates, or policy changes. Long-term outcomes may take years to materialize and are often influenced by factors beyond your program.

Building Your Logic Model

Start with the End

Begin by defining the long-term outcomes you want to achieve. Then work backward: what short-term changes must happen first? What activities will produce those changes? What inputs do you need? This backward design ensures that every element of your model connects logically to the desired result.

Test the Causal Chain

For each link in your model, ask: "If we do this activity, is it reasonable to expect this outcome?" If the connection requires a leap of faith, you may need to add intermediate steps, revise the activity, or adjust the expected outcome. Every link should be defensible.

Keep It Focused

A common mistake is trying to capture every nuance of your program in a single logic model. The result is an overly complex diagram that confuses rather than clarifies. Focus on the primary pathway from inputs to impact. If your program has multiple distinct components, consider creating a separate logic model for each one.

Identify Assumptions

Every logic model rests on assumptions — conditions that must be true for the causal chain to work. Common assumptions include that the target population will participate, that staff will have the necessary skills, and that external conditions will remain stable. List your key assumptions explicitly. Reviewers appreciate this honesty, and it strengthens your proposal by showing that you have thought critically about what could affect your results.

Presenting Your Logic Model

Visual Format

Most logic models are presented as a table or flow chart with columns for each component and arrows showing the direction of causation from left to right. Use clear labels, consistent formatting, and enough white space to keep the model readable. Avoid cramming too much text into small boxes.

Narrative Explanation

Always accompany your visual logic model with a brief narrative explanation that walks the reader through the model. Explain the rationale for the causal chain, highlight key assumptions, and connect the model to the evidence base supporting your approach. The visual and the narrative should reinforce each other.

Connecting to the Proposal

Your logic model should align perfectly with your project narrative, evaluation plan, and budget. If an activity appears in your logic model, it should be described in your narrative and funded in your budget. If an outcome appears in your logic model, it should be measured in your evaluation plan. Inconsistencies between the logic model and the rest of the proposal undermine your credibility.

Common Pitfalls

• Confusing outputs with outcomes — counting activities performed rather than changes produced
• Creating a logic model that does not match the project narrative
• Presenting an overly complex model that obscures the core program logic
• Omitting assumptions that underlie the causal chain
• Building the logic model after writing the proposal rather than using it as a planning tool

A logic model is not just a funder requirement — it is a thinking tool that helps you design better programs. Build it early in the proposal development process, use it to test your reasoning, and present it as evidence that your program is grounded in a clear theory of change.