Strategic Modelling and Business Dynamics. Morecroft John D.
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or process all the information needed to make ‘best’ (objectively rational) decisions. Whenever people take decisions that lead to action, they selectively filter information sources, disregarding or overlooking many signals while paying attention to only a few. Well-designed policies recognise this human trait, while functional ‘stovepipes’ are an unfortunate corollary that stem from poor design (or no design at all). In practice, bounded rationality leads to departmentalised organisations in which the left hand quite literally doesn't know (and shouldn't need to know) what the right hand is doing. Loose coordination among functions, departments or sectors is normal.
Bounded rationality helped me to identify, interpret and better understand information feedback loops in business and social systems. Puzzling dynamics nearly always arise from ‘hidden’ coordination problems and this idea is woven throughout the book, beginning with the simple fisheries model in Chapter 1, continuing in Chapter 4's world of showers and in Chapter 5's factory model, and culminating in Chapter 7's market growth model. The information/coordination theme continues in Chapter 8 (the oil industry), in part of Chapter 9 (a return to fisheries) and in Chapter 10 (product growth dynamics in fast-moving consumer goods).
I was not alone at MIT in working on bounded rationality and system dynamics. John Sterman too was studying the topic, and using it to make sense of long-term economic cycles generated by the National Economic Model. Through conversations, seminars and papers I gained a better appreciation of the information processing assumptions of system dynamics that distinguish the subject from traditional micro-economics on the one hand and optimisation methods in management science on the other.
Modelling for Learning
After more than 10 years at MIT, I returned to England in 1986 to join London Business School. John Stopford made possible this return and I joined him in the School's Strategy department. From this new academic base I entered a productive and enjoyable phase of ‘modelling for learning’. I was invited by Arie de Geus to collaborate with his Group Planning department in Royal Dutch/Shell, based at the headquarters of Shell International in London. There, over a period of six years, a series of modelling projects (some conducted by me, and others conducted by David Kreutzer and David Lane) unfolded within the framework of Arie's ‘planning as learning’ initiative. The idea was to take a fresh view of planning and decision making in organisations and see them as collective learning processes. A vital empirical finding, from educational psychologists' studies of child learning, was that learning and doing often go hand-in-hand; children learn as they play. Arie de Geus made the logical step from child's play to decision making by play. It was a big step. But it was insightful if you took the idea seriously, as he and others in Group Planning did. Modelling and simulation fit naturally with this new approach to planning since models are in essence representations of reality (toys) and simulators allow role-playing with a modelled (and much simplified) reality.
An important consequence of my collaboration with Arie and Shell was the launch, at London Business School, of a week-long residential executive education programme called Systems Thinking and Strategic Modelling (STSM). The programme used learning-by-doing to engage executives with the core principles of feedback systems thinking and system dynamics modelling. Chapter 2 (Introduction to Feedback Systems Thinking) and Chapter 3 (Modelling Dynamic Systems) are derived from STSM. Moreover, the programme brought together, for a period of 10 years, a faculty team at London Business School that helped to develop system dynamics in many important ways and materially contributed to the content of this book. The team members were Arie de Geus, Erik Larsen, Ann van Ackere and Kim Warren and then later Shayne Gary. I enjoyed working with this special group of people and know that together we accomplished a great deal. Thanks to you all.
The shower models in Chapter 4 were sparked by Erik Larsen who felt, in the spirit of modelling for learning, that we shouldn't simply lecture STSM participants about the tricky balancing loop in a shower ‘system’. Instead, we should build a simulator that would allow participants to see (or even experience) the resulting dynamics. So together we developed prototype simulators that became the basis for the World of Showers A and B models in Chapter 4. Alessandro Lomi and Ari Ginsberg later joined us to write a journal article based on these models, entitled ‘The dynamics of resource sharing – a metaphorical model’. Two MBA students at London Business School, Thomas Furst and Derrick D'Souza, helped me to develop an early version of the gaming interface, and my wife Linda Morecroft worked on the user guide and interface enhancements for World of Showers.
There is an anecdote to accompany the shower project. After Erik Larsen and I had formulated the model's equations, we needed to supply parameters. Erik suggested that the ‘desired temperature’ of the shower should be set at 25 °C. I asked him if that number was high enough. He said it didn't matter as the choice would make no difference to the resulting dynamics, which was what we wanted the model to demonstrate. He was right in principle, but in practice (as I discovered by taking a thermometer into my home shower) water at 25 °C feels distinctly cool. Erik was not easily moved by this piece of empirical evidence and so, as an amusing compromise, we decided to locate the model's imaginary shower taker in a hot and humid climate where a cool shower would be both desirable and plausible.
Perhaps the most memorable project from the modelling for learning era was a study of the structure and long-term dynamics of global oil markets. This study, conducted with the help of Kees van der Heijden, led to the Oil Producers' model described in Chapter 8. At the time, Kees was head of Group Planning's renowned scenario development team. He brought together 10 Shell managers who contributed to the model's conceptualisation. The project was a good opportunity to engage these managers with the model building process and to build a model that captured a collective view of their oil world as the basis for subsequent scenario development. The original Oil Producers' model was developed in the iThink modelling language. But several years later, prompted by a suggestion from Erik Larsen, the model's equations were transported into Visual Basic and a dramatic new interface was overlaid as the basis for experimental work on decision making in dynamically complex environments (the global oil industry is certainly dynamically complex). This work was carried out by Paul Langley as part of his doctoral thesis at London Business School (‘An experimental study of the impact of online cognitive feedback on performance and learning in an oil producer's microworld’, November 1995).
Systems Thinking and Strategic Modelling ran twice a year for 15 years and brought system dynamics to hundreds of managers and senior staff from organisations around the world.
The Dynamics of Strategy
Around 1995, I began working with Kim Warren on the dynamics of strategy. This development was motivated by our shared interest in strategy (we were both in the Strategy department at the time) and also by our familiarity with a widely cited paper in the academic management literature entitled ‘Asset stock accumulation and sustainability of competitive advantage’. The paper was written by INSEAD's Ingemar Dierickx and Karel Cool and appeared in Management Science in 1989. Their argument was that the sustainability of firms' competitive advantage could be better understood by thinking about the way firms accumulate the asset stocks or resources that underpin their business. A firm might achieve competitive advantage by building a distinctive set of asset stocks that rivals would find difficult to imitate. Sustainability of competitive advantage would stem in part from the time it takes to accumulate or reconfigure such assets or resources. We realised that here was a dynamic view of firm performance that could be further developed by formally linking system dynamics with the resource-based view of the firm (an important branch of contemporary strategy theory and practice).
Our way of carrying out this synthesis was to jointly design and launch an MBA elective course at London Business School, which we called the Dynamics of Strategy. Applied research projects followed, including PhD theses at London Business School by Edoardo Mollona, Shayne Gary, Abhijit Mandal and Martin Kunc.
Dynamic resource-based models of the firm were devised to study important strategy topics such as diversification and competitive advantage. The research partners for doctoral projects included François Delauzun from BBC World Service and Bill Howieson from Scottish Power. Another partnership was with the London Office of McKinsey & Co., during 1996–2000, when the Business Dynamics practice was in full swing. The company assembled a strong team of consultants with expertise