Strategic Modelling and Business Dynamics. Morecroft John D.

strategies and communicate them) is to find a compact ‘shareable’ description of how a firm, industry or social system operates. Sooner or later, the creative and divergent thoughts that are present at a very early stage of enquiry (captured in the phrase ‘there's a lot going on out there’) must be turned to convergent thoughts that focus group attention on the essence of the situation at hand (by agreeing, through ruthless pruning, what's really important and what can be safely ignored). In business dynamics, this creative process of simplification (known as ‘conceptualisation’) takes shape as a picture of a firm or industry that the modeller agrees with the project team. There are of course guidelines to follow. You begin by identifying so called stock accumulations and feedback loops, the visual building blocks of system dynamics models and simulators. Striking the right balance of creativity and convergence is an essential art of modelling. The parsimonious structure of the World Dynamics model is evidence of creativity and disciplined convergence in model conceptualisation. The model's enduring appeal and power to communicate lies partly in its concise yet compelling representation of a massively complex reality.9

The Puzzling Dynamics of International Fisheries

      By now I hope your curiosity about modelling is stirred, but before probing the basic concepts and tools used by system dynamics modellers, I want to show you a model, a small model, designed to address an important contemporary issue facing society. I will explain its main assumptions, demonstrate some simulations and then give you the opportunity to run the simulator for yourself.

      The topic is fisheries. The problems of overexploitation facing international fisheries are well known, widely reported in the press and a subject of government policy in many nations. The performance of international fisheries is indeed puzzling. Fish naturally regenerate. They are a renewable resource, in apparently endless supply, providing valuable and healthy food for billions of consumers and a livelihood for hundreds of thousands of fishing communities worldwide. The fishing industry has been in existence since the dawn of civilisation and should last forever. Yet fish stocks around the world are volatile and some are even collapsing. Once rich fishing grounds such as Canada's Grand Banks now yield no catch at all. Stocks in other areas, such as the English Channel, the North Sea and the Baltic, are in terminal decline.

      The issue is powerfully expressed by environmental journalist Charles Clover (2004) in his acclaimed book The End of the Line. Here is an excerpt from Chapter 1:

      Fish were once seen as renewable resources, creatures that would replenish their stocks forever for our benefit. But around the world there is evidence that numerous types of fish, such as the northern cod, North Sea mackerel, the marbled rock cod of Antarctica and, to a great extent, the west Atlantic bluefin tuna, have been fished out, like the great whales before them, and are not recovering … The perception-changing moment for the oceans has arrived. It comes from the realisation that in a single human lifetime we have inflicted a crisis on the oceans greater than any yet caused by pollution. That crisis compares with the destruction of the mammoths, bison and whales, the rape of rainforests and the pursuit of bushmeat. It is caused by overfishing.

      (from The End of the Line by Charles Clover, published by Ebury. Reprinted by permission of The Random House Group Ltd and Charles Clover.)

Figure 1.3 Pacific sardine catch (top) and North Sea herring catch (bottom) from Fish Banks debriefing materials (Meadows et al., 2001)

      Source: Nichols (1999).

Figure 1.3 shows evidence of overfishing from two real fisheries. This kind of time series data is a useful focus for model building because it contains the dynamics of interest. The top chart shows the Pacific sardine catch in thousands of tonnes per year over the period 1916–1996. The annual catch grew remarkably between 1920 and 1940, starting at around 50 thousand tonnes per year and peaking at 700 thousand tonnes per year – a 14-fold increase. Over the next four years to 1944, the catch fell to 500 thousand tonnes per year, stabilised for a few years and then collapsed dramatically to almost zero in 1952. Since then it has never properly recovered. The bottom chart shows a similar story for the North Sea herring catch in the period 1950 to 1998. However, in this case, following a collapse between 1974 and 1979, the fishery did recover in the 1980s and early 1990s with an average annual catch around 600 thousand tonnes per year – similar to the catch in the 1950s and 1960s.

      Why does overfishing happen? We can be sure that no fishermen set out with the deliberate intention of depleting fisheries and wrecking their own livelihoods. Yet this outcome has been repeated in fishing communities around the world.10 A good explanation is to be found in a fisheries gaming simulator called Fish Banks, Ltd (Meadows et al., 2001; Meadows and Sterman, 2011). Since I am not an expert on fisheries, I will base my model on this popular simulator. Fish Banks has been used to teach principles of sustainable development to audiences that include politicians, business leaders and government policy advisers as well as fishing communities and high school students. Incidentally, it is no coincidence that the lead designer and author of Fish Banks, Dennis Meadows, was also a principal investigator in the Limits to Growth study. Fish Banks has proven to be a potent metaphor for sustainable development in many industries and enterprises, including the world itself viewed as a huge socio-economic enterprise.

Figure 1.4 shows the Fish Banks game board and its imaginary fishery. There is a region of ocean, close to land, containing a single species of fish. Fish regenerate as a function of the existing population. The local fishing community buys ships from the shipyard and takes them to sea to harvest fish. The total catch depends on the number of ships, the fish population and other factors, such as the weather. In the game, as in real life, the fish population is not known accurately, although it can be estimated. Also, in the game, as in real life, the process of fish regeneration is not fully understood by those in the system (players or fishermen). Regeneration is related to the (unknown) fish population, but the relationship is complex and may involve other external factors.

Figure 1.4 An imaginary fishery – the game board of the original FishBanks, Ltd

      Source: Meadows, et al., 2001

Model of a Natural Fishery

I have taken the situation and factors outlined above and used them to create a simple fisheries model (though the scaling I use is different from Fish Banks and there are no competing fishing companies). Figure 1.5 shows the fishpopulation and regeneration. For now there are no ships or fishermen – they appear later. So what you see is a natural fishery, free from human intervention.11 The fish population or fish stock, shown as a rectangle, accumulates the inflow of new fish per year (here the inflow is defined as births minus deaths). Initially, there are 200 fish in the sea and the maximum fishery size is assumed to be 4000 fish. Incidentally, the initial value and maximum size can be re-scaled to be more realistic without changing the resulting dynamics. For example, a fishery starting with a biomass of 20 thousand tonnes of a given species and an assumed maximum fishery size of 400 thousand tonnes would generate equivalent results.

Figure 1.5 Diagram of a natural fishery

      The flow of new fish per year is shown by an arrow. The size of the inflow varies according to conditions within the fishery, as explained below. This idea of a modulated flow is depicted by a tap or ‘flow regulator’ placed in the middle of the arrow. At the left end of the arrow is another special symbol, a pool or cloud, depicting the source from which the flow arises – in this case fish eggs.

A very important relationship is the effect of fish density on net regeneration, a causal link shown by a curved arrow. Since fish density itself depends on the number of fish in the fishery region, the result is a circular feedback process in which the size of the fish stock determines,

9

Modelling can be controversial. World Dynamics was and still is a thought-provoking model, a potent catalyst for political debate and an instrument for serious policy making. It was also a focus of learned criticism about the nature and use of modelling and simulation in the social sciences. Quotations from the press and academic literature at the time convey the impact, both positive and negative, of the model on opinion leaders: ‘This is likely to be one of the most important documents of our age …’, New York Times; ‘There are too many assumptions that are not founded, and there is too high a level of aggregation in the model’, Science; ‘This year will not see the publication of a more important book than Forrester's World Dynamics, or a book more certain to arouse dislike’, Fortune; ‘This is a piece of irresponsible nonsense, a publicity stunt … extremely simplistic, given the current state of knowledge in the social sciences’, economists from Yale. Notice the sharp division of opinion on the scope, size, adequacy and usefulness of the model. The serious press thinks the work is important for its readers and worthy of policymakers' attention. Academics question the model's apparent simplicity. Not surprisingly judgements vary about the complexity and accuracy required of models (or even ideas and theories) for them to offer useful guidance to business and society. Modellers need to strike a careful balance.