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.
Adaptable execution
Summary
This page introduces some problems that make it hard for a business to execute effectively.It then presents a theory of execution.
It describes what the theory says must be done to execute effectively.
It reviews General Electric's use of adaptive planning to support effective execution.
Then it details the execution requirements.
Introduction
Each operation in a business is responsible for delivering value to its markets profitably. In a perfect world the product or service offered has reached its target customers because each function has achieved its required goals and commitments. Marketing has generated desire in the minds of customers. Sales have turned the desires into purchases. Product development has put the desired features into the product or service. Product management has identified the target market segments and identified how customer needs can be provided via developed features in a way that creates an advantage versus competitors. Management has correctly matched the required commitment of resources with the pre-conditions that implied the operation could deliver successfully.Sometimes this description is far from operational reality. In dynamic growth markets,
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.
segments can be hard to characterize and
operational methods may change significantly, so
identifying effective implementations of 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.
The drive to fulfill current customer requirements can result in
the innovator's dilemma.
While the customer interest can diminish typical requirements
databases continue to reflect the earlier desire.
Accurate modeling of the customer's roles and goals creates a more predictive indicator. Close relationships with sentinel customers for key target segments help build the models.
Processes should also support the migration of product and customers to the winning architecture in a positive return market.
valuable
features and relating Accurate modeling of the customer's roles and goals creates a more predictive indicator. Close relationships with sentinel customers for key target segments help build the models.
Processes should also support the migration of product and customers to the winning architecture in a positive return market.
Agents can manage uncertainty by limiting
their commitments of resources until the environment contains signals strongly correlated with the
required scenario. This page explains how agents can use Shewhart cycles and SWOT processes to do this.
commitments
to pre-conditions can be difficult. Hence product
development may start to develop a product or service release
without a clear understanding of the customer's priorities, or
even a clear vision of who the customer is or how to transform
the requirements into an effective offer.
Executives and venture capitalists is venture capital, venture companies invest in startups with intangable assetshave to decide on which subset of proposals to bet 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). needed to finance the proposals from their operations. Complex adaptive system (
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.
CAS) theory highlights the
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. John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
nature of the problems executives and their operations face and how they can cope with an iterative approach to development.
A CAS theory of execution
Execution occurs through 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
responding to goals
and other 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 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 with effective
actions. In a complex changing This web page reviews opportunities to find and capture new
niches, based on studying fitness landscapes using complex
adaptive system (CAS) theory.
CAS SuperOrganisms are
able to capture rich niches. A variety of CAS are
included: chess, prokaryotes,
nation states, businesses, economies; along
with change mechanisms: evolution
and artificial
intelligence; agency
effects and environmental impacts.
Genetic algorithms supported by fitness functions are compared to genetic operators.
Early evolution of life and its inbuilt constraints are discussed.
Strategic clustering, goals, flexibility and representation of state are considered.
environment
that is a significant challenge. As the situation alters
the goals may need to change too. The actions will be
effective when the agent's Genetic algorithms supported by fitness functions are compared to genetic operators.
Early evolution of life and its inbuilt constraints are discussed.
Strategic clustering, goals, flexibility and representation of state are considered.
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.
schematic
plan associates the required goal with appropriate
strategies, and these are the ones selected by the agent to
perform. The initial plan will probably start off with
gaps and flawed assumptions too. Execution is when the
problems become evident. The agents must be ready and able
to - 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.
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.
understand the implications of the
feedback and adjust the plan. 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.
CAS theory suggests what must be
done to execute effectively
Hence it is important to: John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
- Select agents who have the correct plans.
- Provide the agents with all appropriate
signals.
- Combine selected agents into an operational network.
- Ensure
that agents update their models with appropriate
feedback derived from the results of their actions.
GE an example of adaptive planning and effective execution
Each of these requirements is challenging. But they can be managed. Jack Welch famously transformed General Electric (GE)'s management processes into such an iterative 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.infrastructure.
The requirements derived from
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.
CAS
theory correspond to parts of GE's
extensive management processes. The top GE
executives are hub
agents driving the adaptive actions of the network.
John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
GE's main processes include the quarterly, two and a half day, Corporate Executive Council (CEC), the annual Session C leadership 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.
and organization reviews; S- 1 and S- 2 strategy and operation reviews; and the annual Boca meeting where operating managers meet to plan the coming year's initiatives and re-launch current initiatives. Through these processes the hub executives are able to promote alignment of goals, models and actions deep into GE's organization. GE's processes are one way to instantiate the CAS goals outlined above and discussed in more detail below.
GE's earnings misses during the global financial crisis pulled the covers back from Imelt/Welch's strategies. While the management processes contributed to the decades long success of GE, it is clear that financial engineering based on the presence of GE Capital was acting as an
This page reviews the strategy of setting up an arms race. At its
core this strategy depends on being able to alter, or take
advantage of an alteration in, the genome
or equivalent. The situation is illustrated with examples
from biology, high tech and politics.
evolutionary
amplifier that increased the pressure on GE's many
competitors. A clear illustration of how hard it is to
accurately model and attribute value to particular strategies
and actions. CAS execution requirements
Hiring agents who are recognized as being able to do the job
Recognizing which prospective team members have the required skills to do the job is challenging at the best of times. Hopefully some one close to the hiring manger already has first hand knowledge of the candidate and the demands of the role being recruited for. In 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.
CAS theory hiring is the
implementation of a John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
Plans change in complex adaptive systems (CAS) due to the action of genetic
operations such as mutation, splitting and recombination.
The nature of the operations is described.
genetic operator.
Most real systems demonstrate diversity in the phenotypes is the system that results from the controlled expression of the genes. It is typically represented by a prokaryotic 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. . A
particular expertise may be useful in the current situation but
other practices may be more useful at other Carlo Rovelli resolves the paradox of time.
Rovelli initially explains that low level physics does not include time:
times, and agents have evolved
strategies to support partners that will reciprocate. Once
the team is in place and becomes 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
This page reviews the inhibiting effect of the value delivery system on the
expression of new phenotypic
effects within an agent.
aligned
with the rest of the business network it can become very
difficult to alter the phenotypic attributes expressed. If
execution is failing badly it may be necessary to actively remove barriers to change.
Hub agents control execution
Hub agents 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 interact with large numbers of the other agents. Just
as E. O. Wilson & Bert Holldobler illustrate how bundled cooperative strategies can
take hold. Various social insects have developed
strategies which have allowed them to capture the most valuable
available niches. Like humans they invest in
specialization and cooperate to subdue larger, well equipped
competitors.
Queen ants utilize this This page reviews the catalytic
impact of infrastructure on the expression of phenotypic effects by an
agent. The infrastructure
reduces the cost the agent must pay to perform the selected
action. The catalysis is enhanced by positive returns.
infrastructure amplification to
distribute signals that E. O. Wilson & Bert Holldobler illustrate how bundled cooperative strategies can
take hold. Various social insects have developed
strategies which have allowed them to capture the most valuable
available niches. Like humans they invest in
specialization and cooperate to subdue larger, well equipped
competitors.
influence and
coordinate the behavior of rest of the nest, managers must
push desired
ideas to the other members of the group, building team
coherence. If done poorly the group members will reject
'the manipulation', or never align. Judging how well agents are modeling and learning from the situation
Judging success and failure of an action is often difficult. Which agent was responsible? Was the strategy selected the best one? When a success or failure becomes apparent it is likely to be the result of many intermediate actions. Arthur Samuel used a checkers game to research the selection of appropriate models, strategies and valuations of effects. He found that simple agents could use model based reasoning, including look ahead and predictive modeling of other agents, to learn effectively. However, he found that sampling limitations reduced the value of particular predictive events. It was 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.
much safer to learn by iteratively
adjusting weights by small increments, converging the
valuations of early strategies that had been part of the
execution towards later ones. Hence the trend in major
corporations towards skewing rewards to high performers for
immediate success seems inappropriate! GE's top executives Corporate Executive Council (CEC) meetings review broad aspects of their businesses and the external environment, looking for problems and opportunities, and sharing strengths. The
The page describes the SWOT
process. That includes:
SWOT technique
forces the effective categorization of environmental signals and
helps generate focused - 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.
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.
action plans.
GE's yearly S-1 strategy process allows the top executives to
check the alignment of their own and the business units' goals, valuations and
actions. The later S-2 process checks the effectiveness of
the operations actions relative to the expectations of the
goals. - 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.
Combining appropriate agents in an execution network
When the senior executives are agreed on an 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.execution plan they need to cascade the goals into a network of appropriate agents. GE's Boca meeting ensures the senior executives have an agreed plan to execute. GE's session C process allows the top executives to effectively initiate and then manage this cascade.
In an open progressive organization the feedback will be broadly shared. Changes will be absorbed by the execution teams where this is possible. Some problems will have such large impact as to move beyond the current mission.
In
This page describes the organizational forces that limit change.
It explains how to overcome
them when necessary.
other styles of organization change
may be resisted, or used to demand more resources or Carlo Rovelli resolves the paradox of time.
Rovelli initially explains that low level physics does not include time:
time. Any President of the US is the United States of America. faces particularly
challenging execution conflicts within their
administration. "Half of a president's suggestions which
theoretically carry the weight of orders can be safely forgotten
by the cabinet member. If the president asks about a
suggestion a second time he can be told its being
investigated. If he asks a third time, a wise cabinet
officer will give him at least part of what he
wants. But only occasionally except about the most
important matters do presidents ever get around to asking three
times" from Richard Neustadt's Presidential
Power. 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
True understanding of the nature of problems being worked on by a development program only occurs with the presence of feedback from the market and the channels to it. When the feedback arrives it must be prioritized and turned into adjustments to the day to day activities of the business. A
This page uses an example to illustrate how:
program approach can help drive the
adoption of iterative processes, alignment and sharing of
signals by agents in a large functional organization. - 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.
The presence of reactionary and hierarchic agents' intent on limiting change will be destructive to a development of the nascent execution network. Kim and Mauborgne's tipping point process can transform such organizations into progressive ones.
Network conflicts
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.
network of agents must extend all
the way out to the target customer. Typically the
customer will be reached via a sales channel. Since the
customer may be interested in a variety of products that the
sales channel can provide the sales agents can/should choose
which products to actively sell. If a product's business
managers fail to align the sales agents' goals with their
product, few sales or even customer interactions will
occur. The conflict is typical of a problem that agents
with multiple network partners and goals have. 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.
HP's HP9000 computer hardware business needed solutions to offer to its customers. Some of these solutions were produced by HP's software business but most were developed and sold by partners. The sales force was aligned with the hardware business and so was encouraged to sell partner solutions maximizing the opportunity to sell computer systems.
Any execution network's weakest links must be found and aligned as part of a successful execution activity. If the network adjustments undermine some other business within a corporation the corporate strategy must be examined. The conflict may require the removal of one of the businesses from the corporation to maximize overall value generation. HP's software businesses often struggled to get product through the computer hardware sales channel and were often candidates for sale.
.
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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:
Program Management |
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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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