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Foundational axiom of Variety Dynamics
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Hierarchy and control
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Sub-system distribution and control
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Control by variety overload
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Transaction costs
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Dynamic behaviour
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Variety generation creates control
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Catalogues
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Variety definition
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Feedback loops for control
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Distribution of benefits
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Stability
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Shortfall and transfer of control
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Time is control
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Nyquist number
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Meta-functions of control
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Solution space
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Control of rogue systems and states
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Service design
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Control of feedback loops
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Control without feedback loops
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No system boundary or feedback loops
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Feedback and control variety
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Variety and information
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Variety as thermodynamic
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Power groups
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Variety as physical system
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Open systems
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Conservation of energy
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Reversibility
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Counterfactual variety
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Powerflow between HQ and departments
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Power acquisition via variety costs
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Transaction costs and scale
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Variety and exponential transaction costs
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Calculation of optimum variety
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Power laws and variety
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Opacity past 2 feedback loops
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Mimising damage of local power
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Security controls
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Organisational stability
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Reverse agency
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Relative transaction costs
Variety Dynamics is a powerful tool to help design the early stage interventions to control epidemics and reduce their scope, scale, costs and adverse consequences on populations and countries.
The early stages of epidemics are characterised by lack of information, positive feedback loops and the resulting need to act as early as possible.
Practically, positive feedback loops in epidemics occur in many ways. At heart is that the more people are infected, the more people become infected.
Typically, government epidemic decision making has been based on the output of Discrete Event Simulation software (DES). This models the epidemic in terms of changes to the state at discrete event points in the epidemic (e.g. infection, visiting doctor, pathological testing, hospital triage, bed in ICU, treatment, review, recovery, death...). DES has been preferentially used due to familiarity - hospitals use it in normal life for planning.
Discrete Event Simulation software (DES) has two serious limitations.
- DES does not identify the positive feedback loops needed to be addressed and how urgently they need to be addressed. It is essentially a linear model.
- DES takes time, a long time to gather the information to make its model. In fact, ideally, the epidemic has to reach a stable state before a DES model has the information to make the simulation model. Together, these mean that government's responses to epidemics are to late to be effective at early control.
Systems Dynamics (SD) modelling improves on DES because it identifies problematic feedback loops at the outset, via its preparatory stage of creating a causal loop diagram. Also, besides producing decision guidance mucSD modelling requires much less information than DES. SD can provide some of the same data as DES for health purposes, e.g. . flows of patients through the system. However, SD although faster than DES still does not explicitly provide strategies to manage the epidemic.
Variety Dynamics analysis provides a means to identify strategies, operations and tactics likely to be effective in the early stages of an epidemic, and also, if necessary at later stages. Epidemics dynamically change the distribution of variety. If nothing is done in response, or if the response is delayed, then power and control of the society/state flows towards the epidemic and its cause, and away from the government, people and existing institutions.
Variety dynamics can be used to quickly map the distribution and dynamics of distribution of new variety caused by the epidemic. This then offers those intervening with a ready understanding of the scale and diversity of variety changes needed to address the epidemic. Variety Dynamics works symbiotically with System Dynamics modelling. However, DES modelling, by its nature, is too slow in its response to be useful.
Variety Dynamics is concerned with the dynamic distribution of variety in any situation.
Variety is the number of possible options available to different elements in a situation.
Theory of Variety Dynamics research currently has eleven strands:
- The development and use of Variety Dynamics axioms to manage power and control in a wide variety of contested or complex situations
- Modifying the dynamics of distribution of variety to influence ownership and direction of power and control
- Using the Two-feedback loop limitation axiom to manage human agent behaviours and identify failure areas in decision-making
- The roles of time dynamics in variety dynamics
- Identifying the differing roles of transaction costs in modifying variety distributions to change locus and ownership of power
- Identifying where Variety Dynamics is more effective than conventional force and related approaches to change the locus of power and its ownership
- Identifying the benefits of Variety Dynamics analysis over conventional causal analyses
- Mapping the benefits of the reduced information needs of Variety Dynamics guidance on decision-making compared to conventional causal analyses
- Exploring the benefits and potential of the intrinsic covert nature of Variety Dynamics interventions
- Practical application of Variety Dynamics in improved guidance for addressing hyper-complex wicked problem situations that do not conform to the standard system analysis assumptions
- Development of the new mathematical field of Variety Dynamics, the dynamic V distribution, its dynamics and its mathematical relationship to power and control.
Variety Dynamics offers a new insight into Military History. It is particularly relevant to New Military History that includes sociological, economic, environmental, historical, technological and cultural factors.
Variety Dynamics offers deep insights about the progression of events in the realms of aggressors and defenders.
In Military terms, Variety Dynamics offers a new overarching analysis of military doctrines, and, in its own right, offers a new military doctrine and a new basis for understanding strategy, operations and tactical decision-making.
Advantageously, Variety Dynamics provides a tool to analyse situations that are information-sparse or fully covert. On the larger scale, Variety Dynamics is capable if undertaking analyses and identifying reasons for outcomes without the same need for comprehensive information required of typical Military History analyses that depend on causal understanding of events
In short, Variety Dynamics offers:
- A new from of Military History analysis
- A new approach that includes addressing covert situations or those with substantially missing information
- A new overarching approach for comparing and contrasting existing military doctrines and their application and effectiveness
- A new form of military strategy
- A new field of Military History
Below are articles, conference papers, theses and sundries relating to Variety Dynamics. These are typically as pre-prints. The final published versions are available from the publishers described in the references.
2025
Love, T. and Cooper, T. (2025) Variety Dynamics for Taking Control of Complex Heterogenous Systems in Information Warfare, Journal of Information Warfare, 24 (2), pp. 60-78
2024
2023
2022
2021
Love, T. (2010). An introduction to Variety Dynamics. ANZSYS Conversations. July 2021
2019
Love, T. (2019) Eight Keys to Effective Natural Surveillance. LinkedIn Pulse
2018
2015
2011
2010
2009
Love, T. (2009). Complicated and Complex Crime Prevention and the 2 Feedback Loop Law. In T. Cooper, P. Cozens, K. Dorst, P. Henry & T. Love (Eds.), Proceedings of iDOC'09 'What's Up Doc' International Design Out Crime Conference. Perth: Design Out Crime Research Centre. Proceedings online at http://www.designoutcrime.org/ocs2/index.php/iDOC/2009/schedConf/presentations
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999 and before