6.7: Common pitfalls in creating and using Logic Models

People can be averse to the terms used–inputs-outputs-outcomes–and focus too much on the terminology. We find value in having a common language (and terms that have meaning across organizations and regions) even though it may take time for all to appreciate and understand the terminology.

Understanding and distinguishing inputs, outputs, outcomes, and impacts is fundamental to logic modeling. Logic models are often lists of items within columns or “bins.” To design, implement, and test a program’s theory of action, however, it is necessary to depict all the linkages and relationships including those with the external environment. Herein lies the opportunity for improving program practice and generating new knowledge about what works and what doesn’t under different circumstances.

Because the logic model has been and is being used extensively by evaluators, it has been erroneously called an “evaluation model.” It may be thought of only when evaluation is undertaken. We find it equally useful for program planning and management.

When logic models are mandated or are required without adequate preparation and participation, they can become paper work and just an “academic exercise.”

The common graphical depiction of logic models as boxes and arrows on a two-dimensional surface leads to complaints of linearity and irrelevance. This aspect can be an obstacle for some individuals and groups, so effort is needed to create representations that are meaningful and culturally relevant.

The level of detail that is depicted in a logic model needs to conform to what it is to be used for and by whom. A logic model that is dense with words and lines may be difficult to understand. We want to strive for simplicity but don’t want to oversimplify.

Often, we try to make a single logic model be “all things.” Being clear about the purpose and function of the logic model–who will use it and for what–will help improve its usefulness.

As we rush to find ways to better account for investments and improve programming, we have the tendency to think the latest “bandwagon” will be a panacea. Logic models are only a framework, a way of thinking, a process to help with planning, implementing, and evaluating.

When we focus too much on just the concrete paper product, we can lose sight of the value of the process–that creating and modifying logic models builds understanding, consensus, and knowledge and opens our eyes to new possibilities.

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