Research history

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Every program can be described as a chain: resources pay for **activities**, activities produce **outputs**, and outputs may or may not lead to **outcomes**. The W.K. Kellogg Foundation’s *Logic Model Development Guide* defines the links this way:

- **Outputs** are the direct products of a program’s activities, usually counted by size and scope: classes taught, meetings held, materials distributed, people served.
- **Outcomes** are specific changes in participants’ behavior, knowledge, skills, status and level of functioning. The guide expects short-term outcomes within one to three years and longer-term outcomes within four to six.
- **Impact** is the fundamental change, intended or not, in organizations, communities or systems, which the guide places seven to ten years out, often after the grant has ended.

## An example

Imagine a bed-net program distributing 10,000 nets. That is an output. Families sleeping under the nets is an early outcome. Fewer children dying of malaria is the outcome that matters. In the trials pooled by a 2018 Cochrane review, insecticide-treated nets cut child deaths from all causes by about 17 percent compared with no nets. A program that only counts nets handed out cannot say whether it achieved anything like that.

## Why outputs win

Outputs are cheap to count and can be counted in-house. Monitoring outcomes may need follow-up and time. Attributing changes to a program also needs a credible comparison, which does not always require randomization. The risk is that a count such as “10,000 meals served” is read as evidence of a later change without that change being checked. That is the [Measurement Gap](/diagnosis/measurement-gap/). The [Overhead Myth](/diagnosis/overhead-myth/) makes it worse, because measuring outcomes takes staff and systems that donors often see as overhead.

## Outcomes can be negative

The Kellogg definition of impact includes unintended change. Some programs produce outcomes opposite to the ones intended, which only a comparison shows. See [Scared Straight](/record/case-studies/scared-straight/).

## Outcomes and depth

Some work at the structure and source levels of the [depth scale](/record/encyclopedia/source-depth/) has outcomes far from its activities or takes a long time to show them. Depth does not determine timing by itself. A campaign to change a law has outputs within months and outcomes over years. That is part of why source-level work is so hard to judge. See [theory of change](/record/encyclopedia/theory-of-change/) and the [Impact Measurement Toolkit](/tools/impact-measurement-toolkit/).

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    "body": "\nEvery program can be described as a chain: resources pay for **activities**, activities produce **outputs**, and outputs may or may not lead to **outcomes**. The W.K. Kellogg Foundation’s *Logic Model Development Guide* defines the links this way:\n\n- **Outputs** are the direct products of a program’s activities, usually counted by size and scope: classes taught, meetings held, materials distributed, people served.\n- **Outcomes** are specific changes in participants’ behavior, knowledge, skills, status and level of functioning. The guide expects short-term outcomes within one to three years and longer-term outcomes within four to six.\n- **Impact** is the fundamental change, intended or not, in organizations, communities or systems, which the guide places seven to ten years out, often after the grant has ended.\n\n## An example\n\nImagine a bed-net program distributing 10,000 nets. That is an output. Families sleeping under the nets is an early outcome. Fewer children dying of malaria is the outcome that matters. In the trials pooled by a 2018 Cochrane review, insecticide-treated nets cut child deaths from all causes by about 17 percent compared with no nets. A program that only counts nets handed out cannot say whether it achieved anything like that.\n\n## Why outputs win\n\nOutputs are cheap to count and can be counted in-house. Monitoring outcomes may need follow-up and time. Attributing changes to a program also needs a credible comparison, which does not always require randomization. The risk is that a count such as “10,000 meals served” is read as evidence of a later change without that change being checked. That is the [Measurement Gap](/diagnosis/measurement-gap/). The [Overhead Myth](/diagnosis/overhead-myth/) makes it worse, because measuring outcomes takes staff and systems that donors often see as overhead.\n\n## Outcomes can be negative\n\nThe Kellogg definition of impact includes unintended change. Some programs produce outcomes opposite to the ones intended, which only a comparison shows. See [Scared Straight](/record/case-studies/scared-straight/).\n\n## Outcomes and depth\n\nSome work at the structure and source levels of the [depth scale](/record/encyclopedia/source-depth/) has outcomes far from its activities or takes a long time to show them. Depth does not determine timing by itself. A campaign to change a law has outputs within months and outcomes over years. That is part of why source-level work is so hard to judge. See [theory of change](/record/encyclopedia/theory-of-change/) and the [Impact Measurement Toolkit](/tools/impact-measurement-toolkit/).\n",
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          "publisher": "W.K. Kellogg Foundation",
          "title": "Logic Model Development Guide",
          "url": "https://www.naccho.org/uploads/downloadable-resources/Programs/Public-Health-Infrastructure/KelloggLogicModelGuide_161122_162808.pdf",
          "year": 2004
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          "publisher": "Joseph Pryce, Marty Richardson and Christian Lengeler, Cochrane Database of Systematic Reviews",
          "title": "Insecticide-treated nets for preventing malaria (Cochrane systematic review)",
          "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6418392/",
          "year": 2018
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      "summary": "Outputs are what a program does or delivers. Outcomes are what changes for people as a result. Counting outputs alone does not establish outcomes.",
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