The Rock and the Bird – Static and Dynamic Processes
There is a parable in systems thinking that illustrates well the difference between static and dynamic processes. If you throw a rock into the air, you can predict with some accuracy where it will go. The harder you throw it the farther it will generally go. The higher you aim it, the higher its trajectory. And, if we eliminate the variability of the human thrower and use mechanical devices like a catapult we can predict even more accurately where the stone will go. A rock is a static object, one that cannot direct itself. On the other hand, if you throw a bird (gently, please!), there is virtually no way to predict which way the bird will go and where it will land. The bird can sense its surroundings and may head off in any direction. A bird is a living dynamic system that gathers and processes input and interacts with its environment.
This distinction between static and dynamic processes is important in systems theory and in evaluations that are done from a systems perspective. Since programs involve people and organizations they are inherently dynamic. It is difficult to predict where they will go and what will happen. As programs unfold the directions they take are influenced by the surroundings and by the interactions of the participants. In this sense, programs are more like birds than like rocks. On the other hand the idea of a “program” suggests that we are trying to do something systematic, that we are attempting to follow a pre-determined set of steps in order to achieve some predictable result. In this sense, programs are more static, they are more like the stone in the parable.
So, which is it? Are programs static or dynamic? Should our evaluations be constructed for one or for the other? The short answer is: both are important. Both the rock and the bird can be understood from a systems perspective. Both are parts in a larger whole. Both have relationships to the other parts. Over time programs are likely to evolve through different phases, some more static and others more dynamic. For instance, when a program is first being developed and piloted it is likely to be very dynamic and unpredictable. In fact, that dynamism is essential for learning and adaptation, for enhancing the focus and quality of the endeavor. Over time many programs will tend to become more static. They become routinized and develop standard operating procedures that can be implemented consistently. They can be transferred to new contexts and settings with some degree of predictability. This standardization is also essential. Over even a longer period of time the program may become too static or rigidified, or it may lead to insights that suggest even better variations that might be tried. In either case, we might be motivated to begin other cycles of dynamic-static program development and evolution.
Understanding the interplay of static and dynamic systems is essential for systems evaluation. We need to recognize that both have their place in evaluation and identify how our evaluation approaches need to evolve over time to encourage program evolution as well as provide feedback and learning about it.
