John D. W. Morecroft

Executive knowledge, models and learning

Abstract Over the last decade modelling and simulation have come of age, extending their influence beyond the mind and desktop of the analyst into the boardroom and the mental models of managers. In the past, business computer models were thought of as technical tools for tightly structured problems of prediction, optimization, or financial planning. But increasingly models are seen to have a different and more subtle role as instruments to support strategic thinking, group discussion and learning in management teams. In this respect they are quite similar to qualitative problem structuring approaches used by strategy advisers and process consultants. In the paper, models are described in terms of three attributes that support different cognitive and group processes in management teams. Models can be viewed as maps that capture and activate knowledge. They can also be viewed as frameworks that filter and organize knowledge. Finally, they can be viewed as microworlds for experimentation, cooperation and learning. The paper explains how the modelling process fits into conventional management team meetings, and then contrasts the value chain methodology and system dynamics in order to illustrate the variety of group and cognitive support provided by different maps and frameworks. The final section provides a brief review of the companion articles in this special issue of the European Journal of Operational Research, ‘Modelling for learning’.

Strategy support models

A major challenge in strategy development is to deduce the consequences of the interacting programmes underlying strategy. The paper argues that behavioural simulation models can help meet this challenge by acting out the consequences of strategy proposals in their full organizational setting. However, the real key to effective strategy support is not simply having a model, but using it in a structured dialogue with executives. To illustrate the idea, the paper presents a system dynamics simulation model used to aid executives of an advanced office equipment firm in setting their marketing strategy. The paper describes the process by which the model was created and brought to the attention of executives. Several examples are provided of the dialectical use of the model, showing how differences in management intuition and model-generated opinion led to improved insight into the consequences of strategy.

Complex behaviour in a production-distribution model

Abstract The purpose of this paper is to show how the cascaded structure of a production–distribution chain can produce a wide variety of dynamic behaviours. Despite the apparent simplicity of the chain, the bounded rationality of human decision making interferes with the information feedbacks, nonlinearities and time delays of the system to produce exceedingly complex behaviour. When simulated with realistic parameter values, the model can exhibit stationary periodic, quasiperiodic as well as chaotic and hyperchaotic motions. Lyapunov exponents are used to characterize the different types of behaviour. Repeated simulation reveals how the profile of operating cost is related to the modes of behaviour and to the conditions that generate chaos. Detailed maps of parameter space graphically show the influence of inventory control policies upon dynamics and costs. The analyses illustrate why it is so difficult for decision makers to “navigate” in low-cost policy parameter regions. Suggestions are made for decision heuristics that avoid high-cost, unstable solutions.

Performance and learning in a simulation of oil industry dynamics

Abstract Experimental studies on decision making in dynamically complex simulated systems have shown that poor performance arises from decision makers’ failure to correctly interpret feedback information due to the confounding effects of stock accumulation, time delays between decisions and actions, and non-linearities between system elements. This experimental simulation study examines ways to improve performance through online information feedback that clarifies for subjects the task structure of their decisions including cause and effect. In order to test our ideas we devised an assignment for business school students using a microworld simulator representing the global oil industry. Subjects completed a set of six upstream investment tasks and their resulting financial performance was measured and recorded. The repeated measures factorial design included three different treatment groups, who received various task structure feedback during the first three trials only. A fourth control group received no task structure feedback at all. The results show that mean subject performance was significantly greater for the treatment groups during the first two trials, consistent with our view that task structure feedback is helpful. However, in later trials the performance of all groups, including the control group, eventually reached a similar plateau, some 30% below a behavioural benchmark. From these results conclusions are drawn about individual and team learning in complex dynamic systems.

Visualising and Rehearsing Strategy

This article describes the use of business modelling and simulation for visualising and rehearsing strategy. A small-scale model of customer growth and competitor retaliation (based on easyJet, the three-year old UK start-up airline) demonstrates the approach and its emphasis on interactive team-led model building. Accompanying the article is a downloadable mini-simulator (available at www.lbs.ac.uk/sysdyn – go to that address and select “what is modelling”). Readers can use the mini-simulator to replay all the simulations shown in the paper and to experiment with new ones. The article also describes a modelling project at BBC World Service, conducted as an interactive learning process with an experienced management team. This includes examples of maps created by the team as well as a screen shot from the gaming simulator (or “microworld”).

Competitive dynamics and gaming simulation: lessons from a fishing industry simulator

Experiments with a gaming simulator of the fishing industry show that a wide range of firm and industry performance can arise from players’ differing perceptions of the competitive environment. When transferred into the arena of applied strategy development, the results suggest that modellers should give more attention to modelling alternative conceptualizations of strategic intent in the minds of rival business leaders and the firms they create. This new interpretive emphasis should complement the traditional modelling of cross-functional coordination that has been the hallmark of much published work in strategic modelling and simulation. When leaders and firms in the same industry adopt quite different views of the overall system of resources in the industry, it is important to model the heterogeneity of rival firms in order to understand the dynamic performance of the firm and the industry. We propose a modelling approach that captures heterogeneity among the strategic resources that rival firms seek to build and in the operating goals and coordinating processes they use to build them.

Resource-based strategies and problem structuring: using resource maps to manage resource systems

The resource-based view of strategy seeks to explain why some firms consistently outperform rivals in the same industry by acquiring a unique set of strategic assets (or resources). However, differences between dominant managerial mental models in management teams lead to disagreement at the moment of implementing distinct resource-building strategies. This managerial and cognitive view of strategic decision making and competition lends itself to investigation through problem structuring methods. We suggest that resource maps, as a problem structuring method, can be used to interpret managerial mental models for strategic decision making in terms of resource-building processes. Through resource maps, we represent the system of asset stocks believed to be most important for driving business performance. We illustrate the framework by comparing and contrasting maps of the system of resources (asset stocks) that best characterize two leading firms in the UK commercial radio broadcasting industry.

Managing product lines that share a common capacity base

Abstract This paper examines the difficulties of maintaining competitive delivery times on product lines that share a common capacity base. The analysis is derived from a case study of a manufacturing firm producing finished product and service parts at a single plant. A system dynamics simulation model is used to represent production and ordering policies of the firm and its distribution network. Simulation analysis shows that these policies cause demand volatility for the finished product to be converted into supply volatility of service parts, leading to long parts delivery times and loss of service parts market share. To improve the performance of the service parts business, the production of finished product and parts should be decoupled, so the supply of the two product lines becomes independent. The results are discussed for the general multiproduct-line case. A brief report of implementation results is included.

Devil's staircase and chaos from macroeconomic mode interaction

Abstract To examine how a self-oscillatory dynamic system responds to an external perturbation we have investigated the interaction between an endogenously generated cycle and an external periodic forcing. As a result of resonance interactions between cycle and forcing as well as between the harmonics each generate in the nonlinear system, the model produces a devils staircase of frequency-locked oscillations. For higher forcing amplitudes, deterministic chaos can develop either through intermittency or through period doubling.

Computer-Based Case Studies in Management Education and Research

There is growing interest in combining system dynamics models with conventional case studies in order to create learning environments for management education. Such computer-based case studies promise improvement in strategic thinking skills and better integration of modeling in the policy and strategy area. Moreover, these models-with-cases are tangible products with which to conduct research in computer-based learning. This paper surveys the opportunities for using computer-based case studies in management education and for conducting novel research on management learning.