4 Measuring Flexibility Measuring a parametric model’s flexibility is a somewhat challenging proposition. There is no agreed upon definition of flexibility, nor is there any existing way to measure it. Furthermore, as I outlined in the introduction (chap. 1), flexibility is often intwined with the circumstances of a project, making it hard to clearly observe what is happening. Flexibility remains largely enigmatic. In this chapter I outline a framework for observing the flexibility of parametric models. I begin by proposing a research method that relies upon triangulation between case studies to mitigate some of the circumstantial challenges of observing flexibility. In the second half of the chapter I draw upon concepts encapsulated in the Testing [2.4] section of the SWEBOK.1999. Borrowing from software engineering, I outline a suite of quantitative and qualitative research instruments for measuring various types of flexibility in a parametric model. In aggregate, the research method and research instruments will serve as a foundation for observing flexibility in the case studies presented during chapters 5, 6, & 7.
4.1 Research Method The flexibility of a parametric model can be hard to observe. To date, the best observations have come from architects working on projects where the model became inflexible and failed. While architects can be reluctant to talk about their failures, the few who have done so (discussed in chapter 2.3) prove useful in identifying the challenges associated with parametric modelling. However, in coming to understand why parametric models are failing, these reports tend to offer little insight beyond documenting general symptoms – a major change breaks the model, the model is hard to share, there is a need to anticipate changes whilst parametric modelling (see chap. 2.3). Most of these observations come in the course of other research; the authors had not set out to study model flexibility and while they were able to identify the symptoms of inflexibility, they generally 70