Learn About Utilization Logic Models


In an age of shifting accountability requirements and increasing emphasis on producing results, a need has emerged among the NIDILRR grantee community for a new mechanism to guide planned project activities - especially those intended to produce dissemination and utilization outcomes. Many researchers struggle to find efficient and effective methods of communicating their project goals, activity strategies, and intended outcomes. Logic models can assist these goals by encouraging project staff to plan for results by envisioning a "big picture" view of a project's scope of work and potential significance to varied target systems.

Logic models are most useful when developed at the beginning of project activities. Such planning at the initiation of a project or within a proposal development context facilitates coordination of resources and can inspire consideration of project strategies and realistic expectations for outcomes resulting from the project's work. However, the benefits are not unique to new projects, and logic models are also useful for ongoing projects working to clarify how current project activities are unfolding to accomplish specific objectives and identify data sources and collection strategies that suggest progress toward expected outcomes.

What is a Logic Model?

A logic model is a highly visual method of demonstrating relationships between project resources, activities, outputs, and outcomes. Logic models are planning tools that indicate the resources a NIDILRR project will employ to conduct activities that are intended to produce specific, describable, and measurable changes or results in people, organizations, or the broader physical and social environment. It is important to understand the context in which the project will unfold and the basic assumptions related to the purpose of the project and the target systems the project is designed to impact.

Logic modeling evolved from the work of program evaluators in the 1970s and 80s. It is a long-term process that involves a team of people invested in the work and the results of the project. Specific terms are used in logic modeling that help to establish a common foundation for describing and understanding a project, and learning to use these terms is a part of the logic model process (McLaughlin & Jordan, 2004).

The elements of a basic logic model may include:

Purpose or Situation What is the goal of the scope of work of your project and which target systems will it benefit?

Focus: Identifies the problem or priority the project is responding to and the expected benefit to specific audiences.
Resources or Inputs What is available to make your project's scope of work operational?

Focus: Resources could include the human, financial, host organization, or community resources and support a project has available to apply to its work.
Activities With your project resources, what project activities do you plan to implement?

Focus: Project activities include the research, development, training, technical assistance, dissemination, utilization, and other activities specified in your NIDILRR grant proposal that was selected for funding.
Results or Outputs What products, services, or events do you anticipate delivering through accomplishment of your planned activities?

Focus: Outputs may include direct products from activities or direct services or events delivered through planned activities.
Participant Outcomes What benefits, changes, or results do you anticipate would derive from your activities and outputs?

Focus: Describe how participants' awareness, knowledge, behavior, skills, or level of functioning will be measurably changed by your activities and outputs.
Organizational or
Environmental Outcomes
What benefits, changes, or results do you anticipate would derive from your activities and outputs?

Focus: What changes or effects would you anticipate occurring in organizations, in the environment, or in social policies as a result of your activities and outputs?

Focus: Describe how organizational systems, communities, policy structures, or other broad physical/social constructs will be affected by your project activities and outputs.

The elements of a logic model are displayed in individual cells that are read from left to right. The cells depict a set of "if-then" relationships, for example, if resources were available, then a certain set of activities would be enabled for planning and implementation. Likewise, if planned activities were implemented, then certain outputs would be expected, and the outputs, if successfully achieved, would then be likely to produce expected outcomes.

Why a Logic Model?

Logic models can be useful tools to demonstrate integrated, systemic planning in relation to the achievement of goals and expected outcomes. Often, project proposals may not clearly specify the relationship shared among resources, planned activities/outputs, and the benefits expected from the project. In short, a logic model can help you answer the question: "So, how has your project work made a difference? (Or, how will it make a difference?")

The graphic features of the logic model serve to depict the relationships among components of the project. A logic model provides a common vocabulary to describe elements of project work and results in a way that encourages understanding over a variety of projects. Several NIDILRR grantees who have used the logic model described a steep learning curve at first, to understand and begin to use the logic model vocabulary. Once internalized, however, this vocabulary becomes second nature and helpful in describing project work.

NIDILRR grant time frames frequently do not allow for the comprehensive data collection that is required for researchers to conduct long-term impact analyses. However, logic models enable NIDILRR grantees to describe the data collection methodologies that will suggest progress in relation to specific shorter-term outcomes. In this way, the logic model format can also be very useful in communicating important features of the project and its goals to people who are external to the project such as funding agencies, the general public, and legislators.

Envision Outcomes Through Logic Models

A logic model can also be an effective tool in communicating the desired results or effects of a project's scope of work. It represents a vision of how staff and other stakeholders with input into the planning process intend to produce anticipated results via project resources and activities. Further, the process of logic model development is helpful in focusing activities and in clarifying how each is expected to contribute to stated outcomes.

Through linking project elements, activities, and resources in a graphic logic model format, NIDILRR grantees are better able to monitor the direction of project activities as well as focus on the most important project objectives. Logic models encourage practical project planning and enable grantees to envision what can reasonably be expected from implementation of planned activities and delivery of intended outputs.

Logic Models and Project Evaluation

Logic modeling is a tool to help organize the relationship between major project activities and anticipated outcomes. It can be effective for planning a project design, implementing a project's activities, and evaluating project success.

For NIDILRR grantees, it is important to be able to describe and report results of NIDILRR project activities to both funding agency representatives and members of target systems that the project may benefit. Logic models have the capacity to communicate this important information to a variety of audiences in an understandable way.

By describing outcomes particularly at short and mid-term intervals, the logic model provides an excellent method of identifying the key elements of project evaluation design. Data which document and suggest outcome-related changes or effects can be collected to profile "successes" of a project. All logic model outcome statements should be coupled with descriptions of data and data sources that will be used to suggest progress toward outcome goals. The scope and intensity of data to be collected will be dictated by the time, resources, and person-power available to the project.

Some strategies for documenting the occurrence of anticipated outcomes that are generally available to most NIDILRR grantees include focus groups, limited surveys within target systems, or consumer and/or expert self-reports. Accordingly, logic models can match project goals with data needs and indicate which data collection methods can help to make a case for how project work has been successful in contributing to changes and improvements within targeted systems.

It should be noted that while a logic model demonstrates the relationships shared by project elements such as expected results, changes, or effects derived through project activities, a logic model does not take the place of an evaluation design within a proposal or project context. Relevant evaluation questions, targeted data and data sources, and data collection strategies are all essential elements of a project's ongoing goals of continuous quality assurance and improvement.

Develop a Dynamic Logic Model for Your NIDILRR Project

If all those who will be working on a project contribute to constructing a logic model, this activity can facilitate the working group's understanding and establishment of values associated with doing the project's work. While logic models may be helpful in evaluation efforts, they are probably more important and effective in promoting perceptions of purpose and scope of expected outcomes.

It is also clear that logic models developed at the beginning of project activities are subject to change just as proposal activities may need modification over time. Logic models should be a dynamic tool that assists staff in planning, implementation, and assessment efforts. Clearly, project progress and learning can and should influence the project's logic model as part of an iterative process


McLaughlin, J. A. & Jordan, G. B. (2004). Using logic models, in Wholey, J., Hatry, H. P., & Newcomer, K. E. (Eds.): Handbook of Practical Program Evaluation (2nd Ed.), 7-32. San Francisco: Jossey-Bass. https://www.wiley.com/en-us/Handbook+of+Practical+Program+Evaluation%2C+2nd+Edition-p-9781118008157

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