Nevertheless, I experienced a sense of excitement about the possibility of using computer models to visualise and simulate issues that were foremost in the minds of business and political leaders and important for our everyday lives. Certainly I was no novice to computer modelling, but up until then I had used computational power for optimisation and decision support. What I found appealing in this new area of system dynamics was the promise of a subject aimed at broad policy making backed up by the discipline of model building and the power of simulation.
Imagine you are contemplating the dilemma of fast-growing global population in a world of finite resources. Today, there are 7 billion of us on the planet. Back in 1850 there were just over one billion. By 2050 there could be as many as nine billion people. Is it really possible that mankind could outgrow the planet and overexploit its abundant natural resources to usher in a dark age of pollution, poverty and suffering? Why might this happen and when? How do you begin to answer such questions and how do you conceive a ‘global system’ in your mind? I was captivated by a representation in World Dynamics that limited itself to only two pages of symbols whose clearly defined purpose was to explore alternative future time paths for global industrial society. It was a bold sketch on a compact canvas.
For those who have read World Dynamics, Figure 1.1 will evoke memories of the model. However, for most readers who are new to system dynamics you will glimpse what I saw as a graduate student: strange symbols and familiar phrases which claim to set some sort of boundary on the set of factors that will shape the environmental and economic destiny of mankind. I have deliberately chosen to show a much-simplified diagram that leaves out many intermediate variables and the complex network of connections, because that is how I first perceived the model. There are only four stock accumulations (shown as rectangles with inflows and outflows), representing aspects of our world, that have grown steadily and relentlessly over many centuries: population, capital, pollution and natural resources (which have declined). This fact alone I found remarkable for its brevity yet common-sense appeal. To understand global limits to growth one surely has to think hard about the drivers of population (birth rate and death rate, shown as small circles with tiny taps superimposed on arrows); the engines of human economic activity (capital investment, capital discard and the usage rate of natural resources); and the consequences of human activity on the global environment (the processes of pollution generation and absorption).
Figure 1.1 Stock accumulations for global growth
Source: Adapted from Forrester (1971, pp. 20–21).
These factors must co-evolve over time. But what forces or influences make sure they evolve in a balanced way that can satisfy the aspirations and sustain the living standards of a healthy global population? My picture does not show the full web of coordinating forces. That is something you will learn to model and interpret later in the book. For now you just have to imagine there is such a web operating behind the scenes that determines how, for example, the birth rate depends on population, capital and pollution, or how capital investment depends on population and natural resources. But can a sustainable balance be achieved? Is there a coordinating web that will steer global growth within the constraints of finite natural resources, limited land area, and biological/physical laws (that govern the world's ecology), while at the same time meeting the needs of billions of global stakeholders (parents and families, investors in productive capital, exploiters of natural resources)?
It came as a shock all those years ago to realise there is no nation, no government and no responsible business community that has the power or the information to mastermind a global growth engine.8 A coordinating web is certainly there (reproduced in the Appendix as Figure 1.13), but it is a weak and imperfect invisible hand. In the long run, this invisible hand will achieve a ruthless balance of population, resources and human activity. But the time path to this ultimate balance may involve a catastrophic decline of living standards and population or spiralling pollution.
Figure 1.2 Limits to global growth – rough sketches of alternative futures
Figure 1.2 compares two (among many) alternative time paths that summarise the message as I recall it from my early encounter with system dynamics (Randers, 1980). Bear in mind these are rough hand-drawn sketches, not formal simulations. Nevertheless, the century-long timescale on these charts is representative of the time horizon in the original study and left a deep impression about the ambition of the field to understand the long term by simulating the interaction of human decisions-and-actions with enduring natural forces. On the left is a likely scenario. Global carrying capacity (defined as how much human activity the globe can sustain) starts high in the uncrowded world of the 1950s. Human activity starts low. As population and capital grow, human activity rises steadily and exponentially, approaching the finite (but unknown) global capacity around the turn of the millennium. There is no particularly strong signal to announce that this hidden capacity limit has been reached, nor any coalition of stakeholders with the power to restrict human activity once the limit is exceeded. So ‘the band plays on’ for another 20 years. Collectively, we live beyond the generous but limited means of our planet. This overexploitation of resources and the environment leads to a steady erosion of global carrying capacity and a consequent rapid decline in human activity. In human terms, this multi-decade period of decline is a dark age of low living standards, high pollution, food shortage, premature death and economic depression. It is a dramatic story arising from simple yet plausible assumptions about human behaviour and planetary limits.
The story has not really changed in the four decades since it was first simulated. But there was always another, much more optimistic story. This alternative and sustainable future is sketched on the right of Figure 1.2. I won't say here what differences in the coordinating web can lead to this new outcome. Instead, I invite you to think about the task of balancing the stock accumulations in Figure 1.1 in light of what you learn from the book. I also refer you to the comprehensive simulations of the Limits to Growth team (Meadows et al., 1972; 2002 and Cerasuolo, 2013) and to two of the original simulations from World Dynamics reproduced in the Appendix as Figure 1.14.
A New Approach to Modelling
World Dynamics and Limits to Growth anticipated a new and participative approach to modelling and simulation. People's ability to manage their complex world can be improved by visualising and simulating it. Plans and alternative futures become clearer by rehearsing them (O'Brien and Dyson, 2007). Only now is this approach coming to be widely appreciated in business, political and academic circles. During the 1970s, models were still viewed as instruments for accurate prediction whose validity rested primarily on short-term predictive power, conformance with established economic theory and goodness-of-fit to historical data. Modelling for learning, of the kind presented in this book and intended to complement people's mental models, was in its infancy.
The idea of rehearsing alternative futures is fundamental to contemporary strategic modelling and scenario development. The purpose of models and simulations is to prepare organisations and individuals for alternative futures by bringing these futures to life so they are imagined more vividly than would otherwise be possible. Moreover, as you will see throughout the book, strategic models not only help people to generate alternative futures for their firms and industries, but also to challenge, shape, change and enrich their interpretation of a complex world.
An important objective for modellers (and arguably for anyone in a leadership position who has to make sense of complex business