Extended phenotypic alignment
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. 
Overcome reactionaries
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Evolutionary alignment of phenotypic strategies

Summary
This page reviews the inhibiting effect of the
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
value delivery system
on the expression of new phenotypic is the system that results from the controlled expression of the genes.  It is typically represented by a bacterial cell or the body of a multi-cell animal or plant.  The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell. 
effects within an
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. 
agent

Introduction
The process of alignment of
This page discusses the effect of the network on the agents participating in a complex adaptive system (CAS).  Small world and scale free networks are considered. 
network
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
within a
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. 
complex adaptive system
(CAS) is a general one.  Biological and economic systems show the effect. 

In the early twenty first century Globalization continues to leverage
This page discusses the effect of the network on the agents participating in a complex adaptive system (CAS).  Small world and scale free networks are considered. 
network effects
to powerful advantage.  The most developed countries in essence extend their nation state beyond the boundaries of their own workforce and trading partnerships to gain network, scale, and cost benefits. 

Biological Eco-systems demonstrate the process by synergistic alignment of both cellular components and separated phenotypes is the system that results from the controlled expression of the genes.  It is typically represented by a bacterial cell or the body of a multi-cell animal or plant.  The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell. 
, which Dawkin's analyzes in "the extended phenotype's Action at a Distance".  They illustrate the
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolutionary nature
of the forces that compete in the process. 
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
competing in adjacent environmental niches gain fitness from synergistic network effects.  Selection pressure then re-enforces the process of alignment. 

The biological Eco-systems demonstrate that alignment is quite natural, but that each alignment, by constraining the participating agents, potentially places the Eco-system components at increased uncertainty is when a factor is hard to measure because it is dependent on many interconnected agents and may be affected by infrastructure and evolved amplifiers.  This is different from Risk.   from major environmental shifts. 

This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS).  Key research is reviewed. 
Emergent
neuron circuits, a network of interconnected neurons which perform signalling, modeling and control functions.  In Cajal's basic neural circuits the signalling is unidirectional.  He identified three classes of neurons in the circuits:
  • Sensory, Interneurons, Motor; which are biochemically distinct and suffer different disease states. 
develop using extended alignment. 
The position and operations of different agents within a complex adaptive system (CAS) provide opportunities for strategic advantage.  Examples of CAS agents leveraging their relative positions are described. 
Banks of sensory neurons
issue waves of action potentials are the actively generated waves of voltage change across the neuron's membrane that flow down a neuron's axon.  Helmholtz noted that while they propagate far more slowly than electrical transmissions action potentials do not attenuate.  Lord Adrian showed the action potential to be an all-or-nothing signal.  Consequently Adrian extended the neuron doctrine from anatomy to function demonstrating:
  • Sensitivity is indicated by the frequency of transmission of action potentials. 
  • Anatomy indicates the meaning of the signal.  Hodgkin and Huxley's ionic hypothesis completed the characterization of the action potential. 
which provide
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
for the other neuron, specialized eukaryotic cells include channels which control flows of sodium and potassium ions across the massively extended cell membrane supporting an electro-chemical wave which is then converted into an outgoing chemical signal transmission from synapses which target nearby neuron or muscle cell receptors.  Neurons are supported by glial cells.  Neurons include a:
  • Receptive element - dendrites
  • Transmitting element - axon and synaptic terminals 
agents in the circuit to align by.  Poorly connected neurons without the stimulation of the waves of signals proceed to recycle resources via programmed cell death, programmed cell death is a signal initiated DNA controlled process which results in eukaryotic cells self-destructing.  

In
E. O. Wilson reviews the effect of man on the natural world to date and explains how the two systems can coexist most effectively. 
nature
the constraining effects of the gene pool on its members is limited by
Barriers are particular types of constraints on flows.  They can enforce separation of a network of agents allowing evolution to build diversity.  Examples of different types of barriers and their effects are described. 
separation
, where upon divergence may occur unconstrained and be maintained if the separated populations later recombine. 

Even without environmental shifts, agents will adapt to each other's effects.  One significant system transition is when a
This page reviews Christensen's disruption of a complex adaptive system (CAS).  The mechanism is discussed with examples from biology and business. 
disruptive sub-system
integrates and then destabilizes the resource pools of the eco-system.  The agents are dynamic entities, dependent on the presence of the resource pools, and so may collapse when these are removed. 

China has integrated into the US is the United States of America.   economic system, initially synergizing with the current network, but its lower cost collection of resource pools has induced the emergence of highly productive agents which remove profit pools from current agents (businesses) of the US system.  To maintain profits these threatened US agents will typically retreat to areas where higher profits remain and will become hollowed out is the shift of operations from one network provider to another lower cost connected network provider.  The first network provider leverages the cost benefits of the shift to increase its profitability but becomes disrupted.  The lower cost network provider gains revenue flows, expertise and increases its active agents.  Over time this disruptive shift will leave the higher cost network as a highly profitable shell, but the agents that performed the operations that migrated to the low cost network will be ejected from the network.  For a company that may imply the costs of layoffs.  For a state the ejected workers imply increased cost impacts and reduced revenue potential which the state are trading off for improved operating efficiency. 
.  Over time while they will appear highly cost effective businesses, their adaptability to environmental shifts will have been reduced. 
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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
| Design |
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. 
Program Management
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