Shewhart cycle
This page describes the organizational forces that limit change.  It explains how to overcome them when necessary. 

Power& tradition holding back progress
This page uses an example to illustrate how:
  • A business can gain focus from targeting key customers,
  • Business planning activities performed by the whole organization can build awareness, empowerment and coherence. 
  • A program approach can ensure strategic alignment. 
Be responsive to market dynamics
This page uses the example of HP's printer organization freeing itself from its organizational constraints to sell a printer targeted at the IBM pc user. 
The constraints are described. 
The techniques to overcome them are implied. 
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The plan, do, check, act cycle and iterative development

Summary
Walter Shewhart's iterative development process is found in many complex adaptive systems (
This page introduces the complex adaptive system (CAS) theory frame.  The theory is positioned relative to the natural sciences.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents. 
John Holland's framework for representing complexity is outlined.  Links to other key aspects of CAS theory discussed at the site are presented. 
CAS
).  The mechanism is reviewed and its value in coping with random events is explained. 
Introduction
The plans in an adaptive system are the
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
schematic genes and memes
.  They are associated with the current state of the environment
Rather than oppose the direct thrust of some environmental flow agents can improve their effectiveness with indirect responses.  This page explains how agents are architected to do this and discusses some examples of how it can be done. 
indirectly
via
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
modeling
.  The models generate predictions of the results of enacting the schema.  Doing - i.e. performing - a salient schema from alternatives modeled and then checking the results of the action compared to the models predictions, say by
The page describes the SWOT process.  That includes:
  • The classification of each event into strength weakness opportunity and threat.  
  • The clustering process for grouping the classified events into goals.  
  • How the clusters can support planning and execution. 
Operational SWOT matrices and clusters from the Adaptive Web Framework (AWF) are included as examples. 
SWOT analysis
, allows for adjustments to be made.  When the action did not result in a beneficial situation the model that represented the selected schema can be re-weighted to reduce the predicted benefit in future equivalent situations. 
The iterative process depends on the germ-line, a master copy of the schematic structures is maintained for reproduction of offspring.  There will also be somatic copies which are modified by the operational agents so that they can represent their current state.   plan being consistent.  This is achieved by the
This page reviews the implications of reproduction initially generating a single child cell.  The mechanism and resulting strategic options are discussed. 
single cell bottleneck
.  A similar effect can be provided by having only one instance of each source string and deploying a copy of the source whenever a transient replica is required.  This process is used by RSS is Rob's Strategy Studio

Just as significantly the checking occurs after the actions have interacted with the system in its current environment and as its
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agents
respond to the new
Agents use sensors to detect events in their environment.  This page reviews how these events become signals associated with beneficial responses in a complex adaptive system (CAS).  CAS signals emerge from the Darwinian information model.  Signals can indicate decision summaries and level of uncertainty. 
signals
.  Additional focused models can be included in the checking process. 
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
Exception agents
can participate in this process as is seen in the role of the stress management enzyme, a protein with a structure which allows it to operate as a chemical catalyst and a control switch. 
p53 is a tumor suppressor which improves the specificity of transcription's DNA binding and promotes the transcriptional activity of E2F.  P53's activity is controlled by phosphorylation by cyclin Cdk complexes allowing indirect control of the cell cycle.  Among the many genes controlled by p53 are cyclin genes, genes for an inhibitor of cyclin-dependent kinases (Cdk), and the bax gene, which promotes apoptosis.  p53 can thus promote cell proliferation.  It can drive cells into apoptosis.  But it can also stop cell proliferation by arresting the cell cycle.  Normally there is a dynamic balance between proliferation of cells and their death.  In cancer proliferation may become unregulated due to oncogenic mutations or over expression of key regulatory signalling G proteins such as Ras.  Mutations of the p53 suppressor gene are the most frequent suppressor gene mutations in human cancers.  Elephants like humans, have a relatively low buildup of cancer with age.  Elephant's cells have twenty copies of p53 gene pairs which ensure cells with damaged DNA go into apoptosis blocking cancer onset. 
in the cell cycle, a key control mechanism in eukaryotic cells ensures that the cell can replicate when required.  The process is complicated but is logically equivalent to a Shewhart cycle with four phases: (1) general operation using the DNA as the plan, (2) generation of copies of genetic material, (3) checking that the copies were robust, (4) separation of the cell into two.  The details of the cell-cycle are described by Helmreich.  In AWF the eukaryotic cell-cycle has been abstracted in a codelet based implementation. 
process. 

By cycling round this series of steps the match of particular situations and schema/models weightings can be expected to align to the benefit of the system's efficiency and effectiveness.  For human agents they gain situation specific expertise. 

The
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agents
in an adaptive system must generate the
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
models
of the
This page reviews the potential to benefit from strategy in a complex adaptive system (CAS).  The challenges described by Dorner require a careful search of the proximate environment. 
environment
which includes themselves and other agents.  These models can be used to generate predictions of the outcomes of events and actions performed by the agents.  However, since the models don't start off with a good representation of the environment they must be checked for predictive accuracy and refined.  A Shewhart cycle encourages this process. 

In a situation where a new market is being entered, there is a need to effectively perceive, and represent, the details for shared use by an
This page reviews the strategy of architecting an end-to-end solution in a complex adaptive system (CAS).  The mechanism and its costs and benefits are discussed. 
end-to-end operation
;

Iterative planning cycles can alert planners of our associative mind's general bias to
This page discusses the methods of avoiding traps.  Genetic selection and learning to avoid traps are reviewed. 
attribute causal effects to random events
.  An artifact of small sample size is naturally, but invalidly, associated with a cause.  Deming's paddle sampling red bead experiment and Kahneman's 'law of small numbers' highlight the problem.  Over many iterations the random effects will be averaged out. 

Since the effective understanding of signals from the market and value chain will only develop over time iterative planning mixed with execution, as recommended by Deming enables the gradual refinement of plan, operation,
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
structurally enhanced state
, and offer. 
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integrating quality appropriate for each market
 
This page looks at schematic structures and their uses.  It discusses a number of examples:
  • Schematic ideas are recombined in creativity. 
  • Similarly designers take ideas and rules about materials and components and combine them. 
  • Schematic Recipes help to standardize operations. 
  • Modular components are combined into strategies for use in business plans and business models. 

As a working example it presents part of the contents and schematic details from the Adaptive Web Framework (AWF)'s operational plan. 

Finally it includes a section presenting our formal representation of schematic goals. 
Each goal has a series of associated complex adaptive system (CAS) strategy strings. 
These goals plus strings are detailed for various chess and business examples. 
Strategy
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This page uses an example to illustrate how:
  • A business can gain focus from targeting key customers,
  • Business planning activities performed by the whole organization can build awareness, empowerment and coherence. 
  • A program approach can ensure strategic alignment. 
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