Last month, my post Creative Placemaking Has an Outcomes Problem generated a lot of discussion about creative placemaking and grantmaking strategy, much of it really great. If you haven't had a chance, please check out these thoughtful and substantive responses by--just to name a few--Richard Layman, Niels Strandskov, Seth Beattie, Lance Olson, Andrew Taylor, Diane Ragsdale, Laura Zabel, and most recently, ArtPlace itself. I'm immensely grateful for the seriousness with which these and other readers have taken my critique, and their questions and suggestions for further reading have been tremendously illuminating.
Now that the talk has subsided a bit, it's a good opportunity to clarify and elaborate upon some of the subtler points that I was trying to make in that piece, which definitely left a bit of room for people to read in their own interpretations. So, just to be clear: despite the provocative title, I wasn't trying to slam the practice of creative placemaking itself, nor call it into question as a focus area for policy and philanthropy in general. As I wrote in response to one of the comments on the original post, I believe strongly in the power of the arts to have a role in revitalizing communities, and I view the desire to direct resources toward bringing such efforts to life as a very positive impulse on the part of funders and policymakers. Furthermore, although I agree with the point made by John Shibley and others that the arts may not be the best way to foment economic development, no one said that cities and regions can only use one strategy. Economic development is a complex beast, and intuition and common sense would hold that there are most likely some specific situations in which the arts can have a real, irreplaceable, and catalytic impact.
My critique is really about how we don't have much information about what those situations are - nor about how infusions of philanthropic capital can make a difference in those situations. What's more, I am not confident that the tools we're currently developing, as useful as they may be for other purposes, will get us there on their own. My contention is that logic models and their conceptual cousins, theories of change, can be useful tools in filling this gap - by forcing us to articulate our assumptions about the way the world works, and by providing a framework that we can use to test those assumptions. The problem is that most of the logic models that I see aren't worked out to the level of detail that I believe is necessary to gain really useful information about the dynamics of these complex processes. In my post, I provided a couple of examples of theories that, while surely far from perfect, at least attempt to recognize some of the numerous and interlocking assumptions embedded in grantmaking of the kind engaged in by today's funders supporting creative placemaking.
It's clear from some of the responses, however, that not everybody shares my optimism in the utility of logic models. Laura Zabel writes that she "hates" them for being too reductive. Diane Ragsdale, taking a cynical view, is worried that they may be misused by funders in order to make themselves seem smarter than they really are or blame grantees for failed strategies. ArtPlace's response suggests that logic models raise the bar for research too high, and that because proving a causal connection between these investments and the change they produce (or don't) is so difficult, we're better off not trying. While I can sympathize with each of these critiques, I also think that they give logic models a bad rap. I feel that logic models are a tool of tremendous power whose potential is only beginning to be unlocked. It's true that, just like philanthropy and policy, logic models can be done very badly. But that doesn't mean there's no gain for us in trying to do them well.
Before we get into all that, however, I'm guessing that some of you probably could use a refresher course on logic models and the terminology associated with them, which can be quite confusing. So let's start with a little background on what this is all about.
What the Hell Is a Logic Model, Anyway?
Simply put, a logic model is a method of describing and visualizing a strategy. Logic models have their conceptual origin in the "logical framework approach" originally developed for USAID in 1969 by Leon J. Rosenberg of Fry Consultants. Their use was largely concentrated in the international aid arena until 1996, when United Way of America published a manual on program outcome measurement and encouraged its hundreds of local agencies and thousands of grantees to adopt logic models as a matter of course. Since then, large private funders such as the Kellogg and Hewlett Foundations have integrated logic models into their program design and execution, and the concept is commonly taught in graduate programs in public policy, urban planning, and beyond.
Even though logic models have achieved greater adoption over the past several decades, there is little standardization in the content, format, and level of ambition seen in professionally produced logic models for institutions large and small. Worse, everyone seems to want to come up with their own terms to describe features of the logic model, and as a result, you'll notice a lot of variation in language as well. Below, I'll do my best to isolate the elements that most of these efforts have in common.
Nearly all logic models contain the following fundamental elements. In combination, they describe a linear, causal pathway between programs or policy interventions and an aspirational end-state.
- Activities are actions or strategies undertaken by the organization that is the subject of the logic model. These activities usually take place in the context of ongoing programs, although they can also be one-time projects, special initiatives, or policies such as legislation or regulation.
- Outputs refer to observable indications that the above activities are being implemented correctly and as designed.
- Outcomes are the desired short-, medium-, or long-term results of successful program or policy implementation.
- Impacts (or Goals) represent the highest purpose of the program, policy, or agency that is the subject of the logic model. Sometimes you'll find these lumped in with Outcomes.
Logic model for a bicycle helmet public information campaign, courtesy RUSH Project
Many realizations of logic models combine these essential elements with additional information that provides contextual background for this causal pathway. Several of these supplemental concepts are listed below in approximate order from most common to most obscure.
- Measures (or Indicators) for outputs, outcomes, and impacts are concrete, usually quantitative data points that shed light on the degree to which each result has been achieved.
- Inputs are resources available to the program or organization in accomplishing its goals.
- Assumptions are preconditions upon which the model rests. If one or more assumptions proves unsound, the integrity of the model may be threatened.
- Benchmarks extend the concept of measures to incorporate specific target goals (so, not just "# of petitions delivered to Congress" but "50,000 petitions delivered to Congress").
- Target Population refers to the audience(s) for the activities listed in the logic model.
- Influential Factors are variables or circumstances that exist in the broader environment and could affect the performance of the strategy as designed (e.g., an upcoming election cycle whose outcome might change the underlying landscape in which the program operates).
A frequently-employed alternative logic model approach strips out this latter set of contextual elements and instead aims to visualize the linear causal chain at a finer grain of detail. This version of a logic model is typically referred to as a theory of change (or, sometimes, a program theory). A well-executed theory of change diagram "unpacks" the processes and factors that lead to successful outcomes, exposing relationships between isolated variables that can then become the subject of research or evaluation.
Partial theory of change from Project SuperWomen case study (ActKnowledge/Aspen Institute Roundtable on Community Change)