Chapter 8: 
Dynamic Scenarios
: Systems Thinking Meets Scenario Planning

by Anika Ellison Savage (formerly Audrey Schriefer) and Ed Ward

Scenarios depict various imaginary worlds, environments in which an organization’s strategy will play out against its rivals. In the real world of competition, however, Newton’s Third Law applies: every competitive action will set off a reaction. And every reaction changes the environment. The real world is an ever-evolving system, not a static set of conditions that can be charted on a matrix. So the competitive arena and the broader social and political environment facing business organizations should be studied in terms of its complexity and dynamism.

Complexity takes into account the multiplicity of variables that must be considered and the variety of relationships that can exist among them. Dynamism accounts for the types and rates of change that can occur . This chapter shows how the systems thinking approach can be applied to deal with the dynamic complexity that has intensified in recent years. We call the methodology for preparing and using this special type of futures analysis “Dynamic Scenarios”.

Later in this chapter, using an example from the automobile industry, we will explain in detail the set of steps involved in developing these Dynamic Scenarios and show how they can be instrumental in the development and, most importantly, in the evaluation of strategic alternatives.

Systems Thinking: The Engine of Dynamic Scenarios

The notion of dynamic scenarios advocated in this chapter stems from the application of systems thinking to the development and use of scenarios. One fundamental principle, reflected in the work of leading systems theorists such as Jay Forrester, Peter Senge, C. West Churchman and Russel Ackoff, is that complexity and dynamism can best be understood in the context of a “system”. Ackoff defines a system as “a set of two or more interrelated elements of any kind: for example, concepts (as in the number system), objects (as in a telephone system or human body), or people (as in a social system)”. It is therefore “a whole that can be divided into parts”.

A characteristic of any system is that the behavior of each element has an effect on the behavior of the system as a whole. For example, the actions of an individual doctor can affect many elements in the work system within a hospital. The actions of an individual manager can affect many of the sub-units within the operational system of a corporation. The actions of customers can affect many of the other elements in the system that constitutes an “industry”: suppliers of raw materials and components, various manufacturers or solution providers, distribution channels, retailers, the industry association, lobbying groups, and legislative bodies, among others. In short, any system in more than the sum of its parts.

Another fundamental principle of systems thinking is that one must view the world simultaneously from three levels: events; patterns of behaviors; and structure. Let us explain each one by putting it in the context of a simple but common business system: the logistics and sales system that connects a manufacturing firm to its many customers. In this system, we’ll focus on observing the effect of delivery delays on product sales.

The Systems Thinking Perspective: Structure Produces Behavior

An example of an event is each sale to each customer. These events are recorded in a report, showing the number of products sold in the prior month. The report includes a chart which plots prior monthly sales over a rolling twelve month historical horizon. This graphs the “pattern of behavior” of the monthly sales rate. The pattern demonstrates a healthy sales increase up until six months earlier, when the sales rate flattened out and then turned down slightly. Another chart illustrates the average delivery time to the firm’s customers. The pattern of behavior of delivery time over the past twelve months shows that up until eight months ago, delivery times were equal to the industry average, but then began to increase steadily. Taken together, the patterns of behavior of these two variables, monthly sales and average delivery time, suggest an increasing average delivery time causes a decrease in sales. This relationship is a manifestation of the cause-effect-cause “structure” of the industry system in which this firm competes. The implications of this simple logistics-sales illustration can be inferred: any organization can affect greater change in its environment when it understands a system at the structural level, as opposed to the event or pattern level. For example, the organization analyzing the logistics and sales system, armed with its new understanding of the delivery-sales structure, can make a number of decisions that will shorten the average delivery time, and as a consequence, increase sales.

On the other hand, if the organization tried to fix its delivery and sales problems without understanding the structure of the system, its efforts to affect individual events, such as sales to individual customers might result only in making some of the underlying problems even worse. For example, new sales might add to the average delivery time if the firm did not invest in additional logistics capacity such as new delivery trucks.

It is important to note that in this example the “structure” is not readily apparent. Instead, it had to be discovered through analysis and then it must be compared to the mental models and experience of the organization’s managers. By identifying the structure of a system, the analysts create a theory of how things work. That is, they model how , in a particular situation the organization’s logistics and sales interact and influence each other. Creating such theories of “how things work” or how a system operates draws upon and reshapes the “mental models” of managers and other experienced members of the firm.

The goal of applying systems theory to scenarios therefore is to provide decision makers with a methodology to allow them to identify and better understand the complex relationships that are at the heart of any “system” and the dynamic nature of how these relationships change.

This chapter will demonstrate how organizations can apply Dynamic Scenarios to dramatically improve the quality and value of the scenarios they develop. Seven specific steps characterize the application of the Dynamic Scenario methodology. The table briefly describes each step before it is illustrated in the automobile industry example which follows. Each time the team members move through this process, they learn more, and share with each other a deeper understanding of the systemic structure and dynamics of the industry, and how a firm can create and achieve its desired effect.

Dynamic Scenarios and the Five Disciplines of the Learning Organization


Discipline Definition

How the Discipline links to Dynamic Scenarios

Personal Mastery

Personal mastery is the discipline of continually clarifying and deepening our personal vision, and expanding our capability to crate the results that we desire

The challenge of confronting uncertainty about the future is stressful for many people. Scenario planning provides a way for them to rehearse and master the future in a simulated environment.

Mental Models

Mental models are deeply ingrained assumptions, generalizations, or even pictures or images that shape our understanding of the world and influence our actions and decisions.

The firm’s shared mental models of industry and firm structures are made explicit and documented in “Dynamic Scenario Generators” and in system dynamics computer simulation models.

Shared Vision

Shared Vision builds a sense of commitment rather than compliance by developing shared “pictures of the future” that we seek to create.

The Shared Vision of an organization emerges from its most desirable future scenario. Scenario planning, especially Dynamic Scenarios is a way to credibly develop attractive plausible futures.

Team Learning

Team learning is the group process of aligning vision and developing capability greater than the sum of the individual members’ contributions.

Dynamic Scenarios provide an occasion for the organization to conduct open dialogues about how the firm can create its own future and align their members in the purposeful pursuit of it.

Systems Thinking

Systems thinking is a discipline for understanding wholes, a framework for seeing interrelationships and patterns of change which shape our environment, rather than unrelated events.

Systems thinking provides the tool and techniques for creating and communicating scenarios. Dynamic Scenarios is the methodology which integrates systems thinking with scenario planning.


For the full text of the Chapter and an illustrative example from the automotive industry, see Learning from the Future: competitive foresight scenarios, edited by Fiam Fahey & Robert M. Randall, John Wiley & Sons, Inc. 1998, Chapter 8:  Dynamic Scenarios: Systems Thinking Meets Scenario Planning, by Anika Ellison Savage (formerly Audrey Ellison Schriefer) and Ed Ward, page 140.

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