This page describes the organizational forces that limit change.
It explains how to overcome
them when necessary.
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.
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.
The constraints are described.
The techniques to overcome them are implied.
Dark webs can help creativity and learning
Summary
Dark webs is a web site that is not open to the Internet. It is a set of deployed HTML files in a directory which refer to each other via file based references relative to the directory. can enhance individual creativity, local operational autonomy, enterprise strategic alignment and organizational learning. In this page we summarize the opportunity.Introduction
This page introduces the complex adaptive system (CAS) theory
frame. The theory provides an organizing framework that is
used by 'life.' It can be used to evaluate and rank models
that claim to describe our perceived reality. It catalogs
the laws and strategies which underpin the operation of systems
that are based on the interaction of emergent
agents. It highlights the
constraints that shape CAS and so predicts their form. A
proposal that does not conform is wrong.
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 systems (CAS) can
only be understood and controlled predictably with appropriate John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
The agents in complex adaptive
systems (CAS) must model their
environment to respond effectively to it. Evolution's
schematic operators and Samuel
modeling together support the indirect recording of past
successes and their strategic use by the current agent to learn
how to succeed in the proximate environment.
models and strategies that make
allowance for adaptive in evolutionary biology is a trait that increased the number of surviving offspring in an organism's ancestral lineage. Holland argues: complex adaptive systems (CAS) adapt due to the influence of schematic strings on agents. Evolution indicates fitness when an organism survives and reproduces. For his genetic algorithm, Holland separated the adaptive process into credit assignment and rule discovery. He assigned a strength to each of the rules (alternate hypothesis) used by his artificial agents, by credit assignment - each accepted message being paid for by the recipient, increasing the sender agent's rule's strength (implicit modeling) and reducing the recipient's. When an agent achieved an explicit goal they obtained a final reward. Rule discovery used the genetic algorithm to select strong rule schemas from a pair of agents to be included in the next generation, with crossing over and mutation applied, and the resulting schematic strategies used to replace weaker schemas. The crossing over genetic operator is unlikely to break up a short schematic sequence that provides a building block retained because of its 'fitness'; In Deacon's conception of evolution, an adaptation is the realization of a set of constraints on candidate mechanisms, and so long as these constraints are maintained, other features are arbitrary. modifications and responses. Otherwise the system appears chaotic provides an explanation for the apparently random period between water droplets falling from a tap. Typically the model of the system is poor and so the data captured about the system looks unpredictable - chaotic. With a better model the system's operation can be explained with standard physical principles. Hence chaos as defined here is different from complexity. and unmanageable as
Dietrich Dorner argues complex adaptive systems (CAS) are hard to understand and
manage. He provides examples of how this feature of these
systems can have disastrous consequences for their human
managers. Dorner suggests this is due to CAS properties
psychological impact on our otherwise successful mental
strategic toolkit. To prepare to more effectively manage
CAS, Dorner recommends use of:
described by Dorner.
- Effective iterative planning and
- Practice with complex scenario simulations; tools which he reviews.
A leader now aims to develop plans and strategies which ensure effective coordination to improve the common good of the in-group. Pinker notes the evolved pressure of social rivalry associating power with leadership. Saposky observes the disconnect between power hierarchies and wisdom in apes. John Adair developed a modern leadership methodology based on the three-circles model.
without a
This page looks at schematic structures
and their uses. It discusses a number of examples:
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.
written plan can make rapid changes of
direction. This seems to promote - 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.
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
but in a complex This page discusses the potential of the vast state space which
supports the emergence of complex
adaptive systems (CAS). Kauffman describes the mechanism
by which the system expands across the space.
environment it is
sure to lead to thrashing back and forth as the business and its
proximate environment rapidly adapt to each change. Adopting a rigorous planning methodology can allow top down
Terrence Deacon explores how constraints on dynamic flows can
induce emergent phenomena
which can do real work. He shows how these phenomena are
sustained. The mechanism enables
the development of Darwinian competition.
constraints to remove all flexibility
from the business.
- Creativity is a
complex process which can be undermined by top down
controls.
- 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 benefits from the
- Ability to prioritize based on the proximate
situation.
- Introduction of 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.indirection within the strategic action.
- The unbounded nature of complex environments requires a flexible representation.
- Without networked access to planning information islands
of understanding can become disconnected from each
other.
- Poor planning infrastructure is augmented by adding Carlo Rovelli resolves the paradox of time.time consuming meetings and status emails.
Rovelli initially explains that low level physics does not include time:
- A present that is common throughout the universe does not exist
- Events are only partially ordered. The present is localized
- The difference between past and future is not foundational. It occurs because of state that through our blurring appears particular to us
- Time passes at different speeds dependent on where we are and how fast we travel
- Time's rhythms are due to
the gravitational field
- Our quantized physics shows neither
space nor time, just processes transforming physical
variables.
- Fundamentally there is no time. The basic equations evolve together with events, not things
- Our familiar time emerges
- Our interaction with the world is partial, blurred,
quantum indeterminate
- The ignorance determines the existence of thermal time
and entropy that quantifies our uncertainty
- Directionality of time is real
but perspectival. The entropy of the world in
relation to us increases with our thermal time. The
growth of entropy distinguishes past from future: resulting in
traces and memories
- Each human is a
unified being because: we reflect the world, we
formed an image of a unified entity by
interacting with our kind, and because of the perspective
of memory
- The variable time: is one of the variables of the gravitational field. With our scale we don't register quantum fluctuations, making space-time appear determined. At our speed we don't perceive differences in time of different clocks, so we experience a single time: universal, uniform, ordered; which is helpful to our decisions
- A present that is common throughout the universe does not exist
The strategic and networked nature of systems is poorly supported by generic tools:
- Private and shared parts of the planning sources should be
handled differently.
- Flexible representation is needed that can associate
complex interdependencies with goals of the
plan.
- Broad visibility of the 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 is necessary to drive awareness and coherence.
- Creative Good ideas are successful because they build upon prior developments that have been successfully implemented. Johnson demonstrates that they are phenotypic expressions of memetic plans subject to the laws of complex adaptive systems (CAS).ideas and
Plans are interpreted and implemented by agents. This page discusses the properties of agents in a complex adaptive system (CAS).actions typically need protecting from the control systems until they grow strong enough to self-justify.
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.
- Goals should cascade throughout the businesses operational network as they are delegated.
- Different audiences should see appropriate subsets of the plans structure and details. Each goal owner should be able to decide where and when their strategies should be made visible to others.
Specialized tools are becoming available that can deploy HTML source into dark web is a web site that is not open to the Internet. It is a set of deployed HTML files in a directory which refer to each other via file based references relative to the directory. sites including the dark web generator that deploys this web site. Every page of www.robsstrategystudio.org is static, is built from a filtered subset of the core sources and is generated in this way.
HTML editors enable unstructured documents to be written describing highly complex environments and outlining goals and actions to carry the goals out. A system can be constructed when an editor is combined with tools to:
- Share the document sources among a team of writers.
- Filter the sources for presentation to different target
audiences.
- Deploy the filtered outputs into targeted dark webs for
each specific audience.
The resulting browser accessible plans can cover both business and execution allowing corporate strategy cascades to be represented as a recursive series of HTTP links between goals and the set of strategies that operationalize each goal.
Once the execution plans are specified as dark web pages it is possible to include them as the organization iterates round a
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 cycle helping support
organizational learning. The filtering process allows the pages of each dark web to include augmentation with:
- Checklist item details
- Glossary item details
- Execution status change cascades. For example the
delegator's dark web goal can be 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.signalled when the delegate's strategy status changes.
- Filtering (removal) of links to excluded areas of a
specific dark web plan instance.
 Politics, Economics & Evolutionary Psychology |
Business Physics |
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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:
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 |
- 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.
This page uses an example to illustrate how:
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- 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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