Strategic Modelling and Business Dynamics: A Feedback Systems Approach [Paperback]

John Morecroft's book is an excellent primer in system dynamics for aspiring practitioners. The backbone of his argument, developed in 10 chapters, focuses on developing intermediate skills in building models. The purpose of these models is to help us explain the dynamic behaviour of systems in the world of industry and business.

The first two chapters are introductory but vital reading for starters in the discipline. One learns about the rationale behind system dynamics and its basic underlying notions (causality, positive and negative feedback, the use of causal loop diagrams to visualise interdependences). Chapter 3 moves into dynamic simulation proper and discusses how changes in stocks and flows can be visualised and represented in algebraic form. Chapter 4 presents itself as an innocuous case study ("World of showers") but holds important lessons, both at a literal level (as a model to investigate temperature instability among interdependent shower takers) and at a metaphorical level (as a model for understanding competition for resources among interdependent business units). This chapter also introduces the big subject of goal seeking behaviour (driven by balancing loops) which is further elaborated in Chapter 5. In the latter, Morecroft zooms in on cyclical dynamics rooted in the presence of a powerful balancing loop with a delay. In addition, the discussion is a canvas for discussing generic strategies to move from problem articulation to a working simulation model in team-based, practical settings.

In Chapter 6 the perspective moves from goal seeking behaviour to the dynamics of growth (due to diffusion, as elegantly encapsulated in the Bass diffusion model) and this is further developed in the next chapter where Jay Forrester's Market Growth model is the basis for the exploration of the risks of imbalances (due to underinvestment) between production capacity, sales force and customer orders. Throughout the discussion is thorough but didactic and hands-on. Numerous diagrams facilitate the understanding. In addition there are numerous references in text and diagrams to a number of modelled case studies that can be consulted and worked through on a CD with a working version of iThink. Chapter 8 and 9 consolidate the learning by working through the simulation of macroscopic systems in business (oil markets) and in the public policy arena (urban dynamics, fisheries policy). The final chapter focuses mainly on practical strategies to validate models at different levels of rigour (tests of model structure, model behaviour and learning).

In these pages one senses a mind that has applied this methodology to a variety of real-world problems, and has a long experience in developing and working through these models with decision-makers (who are as a rule unitiated in the arcana of systems modelling). In addition to the main line of his argument, Morecroft highlights seemingly small and unspectacular things that in practical settings often take on significant importance. For example, as he writes on p. 54, in naming variables (for a causal loop diagram) the choice of words is vital: "each variable must be a noun. Avoid the use of verbs or directional adjectives." Indeed, practice shows what a cumulative difference this kind of "language hygiene" makes to the problem solving capacity of a team. In many other places Morecroft shows himself very sensitive to the demands of real-world problem solving.

This experience also explains his keen attention for the various ways in which system dynamics models can be used. Indeed, over the last decades the systems approach in general has bifurcated into what seem to be two rivaling schools: the hard systems and the soft systems approach. The former is interested in modelling real-world systems, whilst the latter relies on modelling as a pragmatic device to support problem-solving oriented conversations between different stakeholders (and different conceptions of what the problem is about). Morecroft tries to find a middle ground between these two approaches (it is no accident that he asked Peter Checkland, the father of Soft Systems Methodology, to provide the foreword to this book). Just as a soft systems approach, the development of formal simulation models can be organised as a social learning process to discover the feedback structure that lies behind the observed dynamics. Models then function as transitional objects, aiding understanding and improvement of our mental models of the world rather than bluntly replicating reality. To a certain extent, this intellectual move certainly helps to bridge the gap between a hard and soft systems approach. However, important conceptual differences remain. A system dynamics model represents a consensus view of the problem (Morecroft gives no reason to assume that this is not the case) whilst in a soft systems approach (at least as advocated by Checkland) there is a multiplicity of world views that is kept in suspension: one modestly works towards a pragmatic, temporary accomodation to enable action for improvement of the problematic situation.

There is no doubt that this book is a very valuable addition to the (still surprisingly limited) literature on a subject of great practical importance, particularly in times of significant macro-dynamic instability such as ours.