Commitments match preconditions
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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. 
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The constraints are described. 
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Ensuring commitments match preconditions

Summary
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
can manage 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.   by limiting their commitments of resources until the environment contains
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
strongly correlated with the required scenario.  This page explains how agents can use
Walter Shewhart's iterative development process is found in many complex adaptive systems (CAS).  The mechanism is reviewed and its value in coping with random events is explained. 
Shewhart cycles
and
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 processes
to do this. 
Introduction
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.   can be managed if commitments are only made when preconditions are met;

The
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
of
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
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. 
self-assembled
into a successful
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
reaches sustainably into Stuart Kauffman's adjacent possible.  If no agent is able to provide a required operation within the
This page reviews the inhibiting effect of the value delivery system on the expression of new phenotypic effects within an agent. 
constraints of the network
, or the
First describes the dynamic nature of any complex adaptive system (CAS). 

It then introduces the broad effects of change which includes opportunities and risks/uncertainties. 

As a CAS grows opportunities become undermined so they must be acted on quickly. 

Uncertainties are also transformed and relayed by the dynamic network.  In particular the recombination of current and new ideas brought in from the network is discussed. 

targeted niche
, no commitment should be made.  If a desired potential agent's operations conflict with cross network synergies already present in agents cooperatively serving other niches integration will lead to
This page reviews Christensen's disruption of a complex adaptive system (CAS).  The mechanism is discussed with examples from biology and business. 
disruption


When time is of the essence, there can be great pressure to act, and little information to define the preconditions effectively.  A
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 process
, or equivalent accumulated applicable experience, is a good way to guarantee balanced judgment. 

In business the Just in time (
This presentation reviews just-in-time manufacturing with analysis based on complex adaptive system (CAS) theory. 
JIT
) strategy of 'small machines' limits each capital is the sum total nonhuman assets that can be owned and exchanged on some market according to Piketty.  Capital includes: real property, financial capital and professional capital.  It is not immutable instead depending on the state of the society within which it exists.  It can be owned by governments (public capital) and private individuals (private capital). 
investment, supporting
Walter Shewhart's iterative development process is found in many complex adaptive systems (CAS).  The mechanism is reviewed and its value in coping with random events is explained. 
Shewhart iterations
with experience leveraged for adjusting subsequent purchases, and by placing the machines in line reduces transportation, queues, wait times and complexity, M. Mitchell Waldrop describes a vision of complexity via:
  • Rich interactions that allow a system to undergo spontaneous self-organization
  • Systems that are adaptive
  • More predictability than chaotic systems by bringing order and chaos into
  • Balance at the edge of chaos 
of
Flows of different kinds are essential to the operation of complex adaptive systems (CAS). 
Example flows are outlined.  Constraints on flows support the emergence of the systems.  Examples of constraints are discussed. 
flows


In chess attack Alekhine and Capablanca were masters of matching commitments to preconditions. 
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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. 
Program Management
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