Author(s): Randall Gibson, Managing Principal – Diamond Head Associates Inc.
Appeared In : Innovations Newsletter, Vol 2, Diamond Head Associates
Effective decision making and learning in a world of growing dynamic complexity requires new skills and tools to understand the structure of complex systems and their behavior. The field of systems thinking, and the development of systems dynamics modeling was created to address this need, and has today become an important part of business analytics and management decision making.
What is System Dynamics?
System dynamics is an approach to understanding and modeling the behavior of complex systems over time. It deals with internal feedback loops and time delays that affect the behavior of the entire system. The basis of the method is the recognition that the structure of any system — the many circular, interlocking, sometimes time-delayed relationships among its components — is often just as important in determining its behavior as the individual components themselves. What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems display baffling nonlinearity.
System dynamics is also a computer simulation modeling technique for framing, understanding, and discussing complex systems and problems. Originally developed in the 1950s to help corporate managers improve their understanding of industrial processes, system dynamics is currently being used throughout the public and private sector for policy analysis and design.
The goal of system dynamics modeling is to improve our understanding of the ways in which an organization’s performance is related to its internal structure and operating policies, including those of customers, competitors, and suppliers and then to use that understanding to design high leverage policies for success. It allows us to construct simulations of our mental models – “virtual worlds” – where space and time can be compressed and slowed so we can experience the long-term side effects of decisions, speed learning, develop our understanding of complex systems, and design structures and strategies for greater success (Sterman, Business Dynamics. Mcgraw-Hill, 2000).
Systems dynamics models have been used to represent everything from very tangible bottom-line variables like inventory, profit, and cash, to very qualitative variables like trust, customer loyalty, and morale. It is this ability to represent, model, and analyze the interaction and impact of the qualitative variables in systems, business, and the economy that has set systems dynamics apart from all other analytical decision support techniques. Yet, very few people are familiar with it, much less understand the basics of what it is and where it can be applied.
In system dynamics models, “maps” of a system or process (similar to a flow-chart) are created using graphical icons: nouns (called stocks, depicted by rectangles) represent things and states of being; verbs (called flows and depicted by arrows) represent actions or activities over a period of time – which create the dynamics in the models. By defining the nouns and verbs for a problem, and building up a system map to represent the system elements, relationships, and activities, we create a dynamic model which can be used to understand the behavior of the system and how it will respond to future changes. The modeler constructs the flows to change flow rates throughout the simulation. The system dynamics model interprets these flow rates in conjunction with the stocks to create differential equations which are used to execute the system dynamics model.
Note that the systems we can represent can be either physical (e.g., a lumber mill consuming raw materials and producing finished wood products, or they can be non-physical (.e.g., market share, customer satisfaction, etc.). In the supply chain world, there is a myriad of non-physical problems or challenges that organizations need to track and analyze in order to understand and improve their operations and maximize financial performance. For example, what is the effect of customer loyalty on market share, and how does market share relate to product sales, which relates to inventory turns, which relates to bottom line financial performance?
Originally developed in the late 1950s, system dynamics modeling has been more widely applied since the advent of the personal computer (mid 1980s) and available simulation software. Over the past decade, many top companies, consulting firms, and governmental organizations have used system dynamics to address critical issues.
Certainly, there is an art to constructing system dynamics models, which requires significant training and experience. Specialized consulting firms, such as Diamond Head Associates, can provide expertise to explore how system dynamics modeling could be applied to your organization’s problems.
For further information and some simple examples, see:
For more detailed information on system dynamics modeling, an excellent reference is:
Sterman, John D. (2000). Business Dynamics: Systems thinking and modeling for a complex world. McGraw Hill. ISBN 0-07-231135-5.