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Visualising program logic: Two new graphic conventions

This article1 introduces two new kinds of graphic representation which have been developed by the evaluation and policy teams in two Commonwealth agencies, Environment Australia and Agriculture, Fisheries and Forestry Australia (AFFA), to assist in understanding the logic of complex programs. The traditional type of program logic diagram was intended to serve two purposes at once. One was to provide a basis for detailed analysis of the program, the sequence of actions and consequences, and the inputs and results required at each stage. The other was to allow a reader who was unfamiliar with the program and its context to seize in a single page the most important gist of what the program did and how it was expected to work. Most people who have used the standard technique have quickly found that the normal conventions serve both purposes adequately only when the program is a relatively simple one – ideally, one with a single intervention strategy and a single output. As soon as the program develops multiple strands, or has an outcomes hierarchy extending beyond a couple of levels, the traditional boxes-and-arrows diagram falls down on both counts. On the one hand, any account of the program simple enough to be captured in a single logic tree on a single page misses much of the content and strategic detail, in particular those aspects that make the program strategy unique. On the other hand, the number of boxes and the thatch of arrows that connect them rapidly become so confusing (often even to someone who knows the program) that the whole purpose of diagrammatic representation is defeated. Matters become several orders of magnitude worse when one comes to deal with environmental and Natural Resource Management programs of the kind which are becoming increasingly common in Australia and elsewhere. Such programs use multiple strategies to address complex problems of management and rehabilitation, involving a multiplicity of causative factors – biophysical, economic, social and political – and have a variety of objectives, not all of them strictly compatible. The difficulty is all the greater because in many such cases, however well the program works, it is unrealistic to expect to identify any clear sustained impact on the variables affecting resource condition (i.e. the true high-level objectives of the program) until anywhere between 10 and 40 years after the cessation of program funding. In such cases, it becomes all the more important to model the complex interactions as rigorously as the science and the evidence permit, simply to enable program managers and funders to establish with some confidence within the funded life of the program whether or not it is on track to achieving its real objectives. To be sufficiently informative, such models must necessarily be detailed and intricate. Conversely, the complexity of these programs is such that even those who work in quite strategic positions within them often have great difficulty in identifying where they fit into the overall scheme, or exactly where their work leads, without some form of road map. Imagine how much worse the challenge must be for a new minister coming into the portfolio for the first time, for a community-based group trying to adapt to the new program structure, or for a parliamentary committee attempting to come to grips with it in order to assess its effectiveness. At this level of complexity, it is no longer feasible to combine both purposes in the same kind of model. The kind of model needed for detailed planning could only be described in Doug Fraser