Aligning KPIs with the Program Logic Model

July 5, 2016 by Stacey Barr

Some governments and other organisations not driven by profit use versions of program logic or outcomes models. But just because they use a logic or outcome model, doesn’t mean they automatically get great KPIs.

logicmodeldiagram

Program logic models visually map the cause–effect relationships that exist between the inputs, activities, outputs, and outcomes produced by their programs or projects, for specific stakeholders.

Program logic models also provide a framework for assessing the impact achieved by the organisation’s application of resources to its programs. These models are intended for organisations whose impact is social change, such as reducing health problems from smoking, reducing water consumption in times of drought, increasing use of sunscreen to minimise skin cancer incidence, or reducing homelessness.

The input-activity-output-outcome thinking that program logic frameworks encourage is very helpful in keeping performance measures focused on what matters, and I would suggest this thinking is useful beyond just social change organisations.

But most of the program logic literature focuses on how to build a program logic model, not on the nitty-gritty steps to find and implement appropriate performance measures to evidence the progress and impact at each stage in the cause-effect flow from inputs to outcomes.

Performance measurement methodologies, like PuMP, can help us design measures for anything, as long as we can articulate the results we want to measure, clearly and specifically. For the Program Logic Model, results are articulated at each stage in the cause-effect chain, from inputs to outcomes.

So once we’ve built our Program Logic Model, we can use a measurement methodology to create meaningful measures for it. Take this example of a Program Logic Model for reducing water consumption in a community:

ProgramLogicModel

So, a good measurement methodology can dovetail into any kind of outcomes model – be it for a program, a service, a project, a business process, a product, or a strategy – at the point where that model articulates the results that matter.

DISCUSSION:

Do you use some kind of outcomes or logic model in your organisation? How have you handled the measurement of it?

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  1. Thanks Stacey for giving a bit more information about how the PUMP Blueprint can help the many GOVERNMENt organizations come up with more meaningful measures. the challenge I often see with the logic model and performance measures that traditionally come from them is the organizations think they have to measure every step along the Logic model and they spend so much time and resources tracking tens and hundreds of measures. And often, they measure what is most easy to measure – outputs they can count. Though the organizations are likely having good conversations as they develop their logic models, the outcomes are still often filled with corporate jargon and weasel words. What I have found working with the teams who use the logic model (and also recognize their struggles with coming up with fewer and more meaningful measures) is this: PUMP’s measurability test helps them write much better outcomes (what pump calls results) in their logic models and then PUMP’s Measure design helps them come up with much more meaningful measures. PUMP is really seamless fit!! How you had similar experiences?

  2. Thanks Stacey for giving a bit more information about how the PUMP Blueprint can help the many GOVERNMENt organizations come up with more meaningful measures. the challenge I often see with the logic model and performance measures that traditionally come from them is the organizations think they have to measure every step along the Logic model and they spend so much time and resources tracking tens and hundreds of measures. And often, they measure what is most easy to measure – outputs they can count. Though the organizations are likely having good conversations as they develop their logic models, the outcomes are still often filled with corporate jargon and weasel words. What I have found working with the teams who use the logic model (and also recognize their struggles with coming up with fewer and more meaningful measures) is this: PUMP’s measurability test helps them write much better outcomes (what pump calls results) in their logic models and then PUMP’s Measure design helps them come up with much more meaningful measures. PUMP is really a seamless fit!! How you had similar experiences?

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