Logic model

A logic model is a tool used to organize information and goals for programs and projects. Logic models are common in social science fields, but are also used in many different fields including health care, education, and business. People or groups can create their own logic models, helping them organize and prioritize the data they need. Logic models are flexible and can be updated as the data needed for the model changes. This data can include inputs, outputs, outcomes, assumptions, and external factors. Logic models are usually represented as graphic organizers with the organizer including a section for each factor included the model. The graphic organizer shows the relationships among the different factors in the model. Logic models can be used during various stages of a program or project.

Background

People use logic models to design, implement, and evaluate programs and projects. Projects are temporary activities that people or groups undertake to meet certain goals. Programs are made of a bundle of various related projects that can be managed as a whole. Logic models can help people and groups in all the different stages of a project. The same program or project might use a logic model during various points of its lifecycle. Furthermore, logic models are flexible documents that can be created and updated over time as facts and factors change.

Logic models can be used in various fields, especially in the social sciences, to collect and understand data. One of the most common uses for the models is as a tool for project evaluation, gauging whether certain projects, plans, or initiatives are working the way they should be. Logic models also organize data and help people understand patterns in the data. For example, a person might use a logic model to observe infection rates and trends in a particular hospital. The logic model will help analyze patterns in the data, which can later be used to find ways to reduce infection rates. Urban planners can also use logic models to study traffic flows in cities. They can use that data to make changes to roadways and other elements to decrease traffic congestion.

Logic models are also important because they help motivate teams of people to find solutions to group problems. The logic model acts as a guide to help the team understand the project’s goals and resources. Sharing the logic model with employees or members of a group can help teams understand the steps needed to reach certain goals and to make programs successful.

Logic models became common in American workplaces during the 1990s and 2000s. In the modern workplace, they are commonly used by a myriad of businesses and organizations, including government entities such as the Centers for Disease Control and Prevention (CDC). Following the onset of the COVID-19 pandemic in 2020, a number of agencies utilized logic modeling to track and treat the disease.

Overview

A logic model should be standalone document that does not require extensive explanation. All people involved in the program should be able to read the document and understand the information presented with little or no explanation. The logic model presents the highest-level information about the project. Logic models are popular because they are simple tools, allowing for easy understanding of the model by a wider spectrum of people. As a result, those who create such models should try to keep them as simple as possible.

Some individuals and teams find the logical model useful because it helps them understand the data that needs to be collected. Others find the logical model useful because it can help them organize large amount of data that they have already collected. Logic models are useful in another way because they allow input from various individuals and groups. Data from many different levels of a company or organization could be used to create a logical model. The models’ flexibility is also a vital element in its success. Ideally, individuals or groups will create a logic model close to the beginning of a project or initiative. However, they can be created at any time to evaluate the effectiveness of a project or program. When developing a logic model, a person or group should consider the problem they wish to solve or the issue they are trying to change. It is valuable to have more than one person complete a logical model, as multiple perspectives could help improve the information in the model. Furthermore, more people brainstorming can help provide more valuable inputs.

Logic models are typically constructed of several elements, including inputs, outputs, assumptions, external factors, and outcomes.

• Inputs: These are people, products, and other investments that are put into a system, program, or solution. Inputs can include any software or equipment people purchase, or people who are employed to help solve the problem. Inputs can be broken into different groups, such as equipment, teams, and more.
• Outputs: These typically include statistics and measurable results. For example, a logic model could include statistics on the number of people who found jobs through a program meant to decrease local unemployment.
• Assumptions: These are pieces of data people collect and enter into a logical model. The assumptions include existing data about a particular topic.
• External factors: These are elements that may be relevant to the project, but are outside of the control of the project team. For example, the number of people who have a genetic disorder might be an external factor in a health-care program.
• Outcomes: These are the goals of the individual, group, or organization. People creating logic models must attempt to develop the outcomes that they want. In the planning phase, people insert their desired outcomes into the logic model. As the project progresses, the outcomes should remain the same, but they should also be based on the actual results of the program or project. If the program was successful the actual outcomes will match the desired outcomes. Outcomes can include short-, medium-, and long-term goals. The goals should be related to ensure the model is focused on one area. Some people confuse outputs and outcomes, but they are two distinct elements related to the program.

Bibliography

Chun, Hae-Ryoung et al. “Generic Logic Model for Coronavirus Disease-2019 Responses Based on the South Korean Experience.” Risk Management and Healthcare Policy, vol. 14, 2021, pp. 4765-4774, doi:10.2147/RMHP.S336425. Accessed 22 Aug. 2024.

“Developing a Logic Model or Theory of Change.” Community Tool Box, 2018. ctb.ku.edu/en/table-of-contents/overview/models-for-community-health-and-development/logic-model-development/main. Accessed 18 Jun. 2019.

Finley, M. Wayne. “Uniform Grant Guidance: Using Logic Models to Enhance Program Performance.” Hancock College, 25 June 2015, www.hancockcollege.edu/institutional‗grants/documents/LogicModels%20Thompson.pdf. Accessed 18 Jun. 2019.

“How to Develop a Program Logic Model.” Corporation for National and Community Service, www.nationalservice.gov/sites/default/files/upload/OpAC%20Logic%20Model%20draft%20in%20progress.pdf. Accessed 18 Jun. 2019.

Knowlton, Lisa Wyatt, and Cynthia C. Phillips. “Introducing Logic Models.” The Logic Model Guidebook: Better Strategies for Great Results. Sage Publications, 2012, pp. 2-15.

“Logic Model Development Guide.” W.K. Kellogg Foundation, January 2004, www.bttop.org/sites/default/files/public/W.K.%20Kellogg%20LogicModel.pdf. Accessed 18 Jun. 2019.

“Logic Models.” Center for Disease Control and Prevention, 18 Dec. 2018, www.cdc.gov/eval/logicmodels/index.htm. Accessed 18 Jun. 2019.

“Logic Models.” Eastern Washington University, 2016, sites.ewu.edu/ogrd/pre-award/proposal-development/writing-resources/logic-models/. Accessed 18 Jun. 2019.

“Logic Models.” University of Wisconsin-Madison, 2019, fyi.extension.wisc.edu/programdevelopment/logic-models/. Accessed 18 Jun. 2019.