Issues in this web site are all concerned with the causal simulation modeling techniques that provide modern decision support for complex managed systems. The techniques, now known as system dynamics (SD), became publicly available in 1957.

SD models in terms of information, not data. It borrowed causal feedback loops from engineering. For technical purposes of this site five important implications of modeling in terms of information are:

• Simulation proceeds in terms of the same factors that generate future outcomes of the actual system. That enables real prediction, in contrast to mere forecasting as delivered by mathstats techniques (including econometrics).

• Past periods can be accurately replicated for accountability purposes. Feedback loops enable deep structural analysis that correctly attributes responsibilities for previous outcomes.

• Requisite detail and comprehensiveness can be built into the model. Freedom from the real limitations of modeling in data terms means that SD can also get on top of the huge institutional and dynamic complexity that characterises many managed systems.

• With a virtual system that is an accurate ‘copy’ of the actual, the latter can be managed or commanded as a system. This has large beneficial results for effectiveness and efficiency.

• By providing substantial predictive-calibre information about upcoming developments and outcomes the virtual system removes much operating risk from day-to-day management or command.

SD is in widespread use in many fields, particularly academically. Professionally and commercially, however, is a different story. Based on personal experience in several ‘advanced’ countries most potential users of SD have never heard of the techniques. Among those that have, significant reservations about their use are often encountered, deriving from three main sources:

• Negative views about the technical soundness of SD, disseminated by the traditional mathstats modeling community on ‘ideological’ grounds. This community includes, as a distinct block, academic and professional econometricians.

• Accounts (correct or otherwise) of poor-quality work (academic and professional) undertaken with SD.

• Inertia, conservatism and fear of what is new to the person (often the result of having no public data base of existing successful uses of the techniques).

SD is almost totally excluded from international public-sector administration, budgeting and planning etc. SD is entirely excluded from international economic and financial policy formulation, implementation and monitoring. Both huge areas are parts of SD’s natural technical constituency.

This site has two overall objectives. These comprise the ‘issues’ presented.

• Attribution of responsibility for the present situation of SD, after more than fifty years of international availability of the techniques.

• Relation of SD to the real causes of, and solutions to, economic and financial aspects of the Great Recession that began in 2007.

SD is represented internationally by the academically-controlled System Dynamics Society (SDS), based in Albany NY. The SDS has ‘chapters’ in various countries.