End-2-end architecture
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  • A program approach can ensure strategic alignment. 
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The constraints are described. 
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Imposing an end-to-end architecture

Summary
This page reviews the strategy of architecting an end-to-end solution in a complex adaptive system (
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 and its costs and benefits are discussed. 
Introduction
The complete definition of all resources,
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
,
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
(including their
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 plans
), and
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
models
operating within a
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. 
sub-network
of a complex adaptive system (
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
) presents the possibility of effectively architecting, and
This page discusses the strategy of modularity in a complex adaptive system (CAS).  The benefits, mechanism and its emergence are discussed. 
modularizing
the network. 

Typically it's a difficult and costly task, and if the system changes will require rework.  Agents may adapt and alternative plans and models may become significant.  However, when the sub-network is very valuable and will not be impacted by limiting its changes the results are significant.  They include:
Characterizing the sub-network will require
This page discusses the program strategy in a complex adaptive system (CAS).  Programs generate coherent end-to-end activity.  The mechanism is reviewed. 
organization as a program
and the use of
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
.  As the steps of each agent's processes are iteratively teased out and characterized, and models of the operations are improved, the association of written goals with effective defined strategies will remove the potential for error.  The agents who have checked and improved the plans and models will have gained an understanding of how to perform the strategies error free, and how to continue to add improvements. 

When the system changes rapidly and repeatedly and its agents must adapt, the imposition of an end-to-end architecture can be prohibitive.  Often it is not possible to constrain the system.  If the sub-network cannot be fully defined the benefits of the end-to-end characterisation and improvement activity may be limited.  With evolved systems our understanding of the schemata, flows etc. are often limited and appear chaotic when modeled.   Often we just don't have effective tools yet to fully characterize the operations of evolved agents. 

Fast changing systems, including computers, have not, generally, allowed end-to-end constraints to be imposed.  Apple with its focus on
This page describes the consequences of the asymmetries caused by genotypic traits creating a phenotypic signal in males and selection activity in the female - sexual selection.   
The impact of this asymmetry is to create a powerful alternative to natural selection with sexual selection's leverage of positive returns.  The mechanisms are described. 
sexual selection
is the notable exception adopting an end-to-end strategy with self-imposed
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. 
barriers
.  Without the constraints of
This page reviews the inhibiting effect of the value delivery system on the expression of new phenotypic effects within an agent. 
extended phenotypic alignment
it has successfully leveraged
To benefit from shifts in the environment agents must be flexible.  Being sensitive to environmental signals agents who adjust strategic priorities can constrain their competitors. 
flexibility
.  Most other approaches used separation of concerns, with specified interfaces between architected modules supported by extensive testing and rework. 

Systems such as car manufacture have provided enough benefit, and limited rates of change, to allow for end-to-end architecture and have gained significantly in the quality of the products and processes. 
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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. 
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