Wednesday, July 6, 2016

Establish a Resilient Enterprise through Homeostatic Controller Algorithm



The purpose of this case study is to provide general guidelines on how to establish and maintain Resilience in Enterprises, which have multiple locations outside national territories, by encapsulating Homeostatic Controller Algorithm into “Standardization Information Platform”.   A Resilient Enterprise can respond unpredictable environmental adversity, maximize product usability, and create sustainable value for customers.

Nature is used Homeostatic Algorithm within Biological Systems in order to regulate value discrepancy from standard setting operations. Enterprises (Non-Biological Systems) with wide boundaries require Standardization Platform Setting (preprogrammed algorithms). Standardization ensures proper value allocation, enforces configuration settings, and sustains consistent quality control in operations. Standardized Non-Biological Systems (enterprises with multiple locations) can also use Homeostatic Algorithm in terms of detecting and regulating value discrepancy from standard setting operations.

There is a good functional analogy beyond Homeostatic Algorithm in Biological Systems and Non-Biological Systems. Functional mechanisms beyond Homeostatic Algorithm in both systems are focused on regulating value discrepancy from standard setting operations.

Lack of Standardization Platform in enterprises can lead to a state of cognitive inconsistency within product and customer modules. Inconsistent quality control in operations can cause product usability issues and customer dissatisfaction. Homeostatic Controller Algorithm (Homeostatic Concept) can be encapsulated into “Standardization Information Platform” in terms of keeping diagnostic consistency and measurement accuracy in system operations.  Eventually, it responds unpredictable environmental adversity and provides resilience into Enterprises.  

Implicit observation pattern tracks integration and collaboration between external environment and boundaries of enterprise architecture. “Standardization Information Platform” is strategic coordination framework, which needs to create and implement within system boundaries. Following criteria will be ensured by encapsulating Homeostatic Controller Algorithm within “Standardization Information Platform”:

1- The best settings for industrial safety standards.

2- Monitor changes in external environments.

3- Assess product conformity.

4- Deliver product interoperability.

5- Improve business benefits with good customer relationship.  

Failure analysis framework (Homeostatic Algorithm) in integration approach model can generate error codes and modification issues in principles of “Standardization Information Platform”.  

For example: customers may experience product usability issues due to coordination constraints, chaotic optimization. Consequently, customers may confront operational complexity when they contact Global Support Portals.

Resilient into Enterprises must be designed and aligned by both Multiple Social Contexts and Homeostatic Controller Algorithm. Successful alignment can fulfill general criteria and guidance for integration platforms. It would support trade-off between distributed data structures from external environments and “Standardization Information Platform”. Homeostatic Concept is inspired by Self-regulating control System within Biological Systems. Homeostatic Controller Algorithm can play a substantial role in executing successful performances within Non-Biological Systems. Homeostatic Concept can address process instability and improve self-adjusting mechanisms. Self-regulating system may identify Open-loop in system performances and then instance of process stability generates realistic Closed-loop with the best possible feed-forward processing.

In the context of customer structure, standardization implies to how customer departments perform customer services through portal software. Conceptual Domain beyond Customer Engagement must deploy according to Protocols in “Standardization Information Platform”. (Figure 1)

In the context of Product structure, standardization implies to how product feature design and develop in order to handle compatibility and Social Changes. (Figure 1)

Enterprises with wide boundaries are vulnerable to modification through external environment. Therefore, “Standardization Information Platform” defines as an intelligent database, which is implemented by Systems Owners, in order to coordinate performance needs and add a value chain model. (Figure 1)

Homeostatic Controller Algorithm is encapsulated in “Standardization Information Platform” because it stabilizes internal components and keeps system platform steady. It is based on feedback loops and software applications monitor system operations (Inputs/ Outputs signals) and promote feedforward control system cross system boundaries. Homeostatic Controller Algorithm responds to unpredictable external changes. (Figure 1)

Lack of integration between Social Structures and “Standardization Information Platform” might hamper security algorithms and organizational interoperability cross system boundaries. External force would generate Invisible Entity into Social Context (Nation C). Instance parameters of Invisible Entity in Nation C can propagate Invisible Malicious Codes through five consecutive cycles and it infiltrates into enterprise subsystems. (Figure 1)

Invisible Malicious Codes might be integrated with different departments cross enterprises. Integration modifies Default Values and Properties of basic operations. For example: IT-department, Economy department, and Sell department can capture complex Intervention Process Model.  Complexity would instantiate abstract guidelines through entire submodules.  (Figure 1)

Integrated Product with Vague Differential Equations (complexity) would modify functional structure (Product Modules) and eventually, modification generates a significant complexity in synchronized manufacturing process. Therefore, Product functionalities and innovations would not fulfill minimum customer requirements and basic product quality expectations. (Figure 1)

Vague Differential Equations are imposed upon Product Module; consequently, two phases of product development might be minimized by complexity (Case Study Phase and User Testing Phase). Project costs and time to market are involved in complexity so that usability assessment would sometimes reduce during iterative life cycle model.

Customer integration with Vague Differential Equations (complexity) would also modify activities in Support Portal Platform. Call Center Agents may not respond customers’ request through organizational guidelines because Invisible Malicious Codes modify Customer Service Modules. Modification in support portals would hinder substantially conceptual framework in ERP, CRM and SCM applications. (Figure1)

Invisible Malicious Codes can be integrated by Supplier Structure and it generates Vague Differential Equations (complexity) into delivery resources and raw materials asset inventory. Service availability level may reduce when Subsupplier Structure would be modified by Invisible Malicious Codes. (Figure 1)

Case study:

Economic sanction against Nation C and lack of Homeostatic Controller Algorithm in Enterprises

Other Nations (External Forces) would impose range of trade sanctions and special Economic Measures against Nation C. Economic Sanctions modify instance parameters in Social Structure of Nation C. Functional Modifications (Invisible Malicious Codes) in Social Context can aggregate within “Standardization Information Platform”.  Aggregation Framework (the first cycle of invisibility) can set an array of complex parameters in Organizational Structure (the second cycle of invisibility). The second cycle can modify instance parameters in Organizational Structure (the third cycle of invisibility). Eventually, it can also become self-perpetuating evolutionary algorithms within subsystems (product usability and customer performances). (Figure 1) 
Raw material Storage Sites, Subsupplier Industry, and Logistic Services are located in Nation C.
                                                                              



Advantage of Homeostatic Concept in Resilient Enterprises (Non-Biological Systems):  
The homeostatic controller Algorithm targets a standard value key (default value) and system operational rules. Homeostatic regulations (All homeostatic control mechanisms) are pre-programmed in Biological Systems and Non-Biological Systems in order to correct value discrepancy and switch back system configuration to the default state.

The homeostatic control system regulates functions and events in Non-Biological Systems (Dynamic Systems) according to process modelling paradigm underlies “Standardization Information Platform” in the following passage: (Figure 2)



1- Open- loop Event: switching disturbance characteristics.

2- Analysis of Disturbance: identify and provide state of complexity.

3- Incident Notification: 1- stores diagnostic data 2-call Standard Controller 3-automate structured analysis.

4- Standard Controller: control default values.

5- Seek Feedback on Standard-Setting

6- Artificial Intelligence: Providing feedback consistently.

7- Closed-loop: meet default values (open-loop stability).

8- Rollback option: 1-Stop feedback 2- Reset to Standard Activity Mode 3- transmit data to initiate start point within Feed-forward Controller.

9- Open-loop Power Control: Transmit Factors and Path of disturbance propagation to “Analysis of Disturbance”.

10- Feed-forward Controller: Rollback Option transfers function map-ping and signal processing to “Standard Controller”. Signal processing extends to “Feed-forward Controller” in order to develop effective relationships with vulnerable parameters.

11- Feed-forward Setting: stop Feed-forward Mode.

12- Database normalization can illustrate product Information for customers through web service tutorial.

Optimal design of Homeostatic Controller Algorithm must be encapsulated into ”Standardization Information Platform” in order to improve  and ensure  Harmonic Balance  in  Resilient Enterprises.
                                                                              



Observation:

“Standardization Information Platform” is stored in database and it can be visible for general public users through web-based application framework. Users can sign in and download information from website aggregator software after registration. Information in database can be created a transparent form and it would be available to the public through web service tutorial. (without registration).

Observation:

Similar operations from synergistic interdependent components within Biological Systems can synergistic interdependent components within Non-Biological Systems integrate through collaborative models.

Observation:

A large enterprise with multiple locations can gain functional interdependence and mutual connectivity. All operations in this type of enterprise architecture framework (Infrastructure Interdependence Model) rely on mutual goal setting and entire subsystems have common responsibility for system outputs. Biological Systems can be considered as Infrastructure Interdependence Model because all components in Biological System have a mutual goal and responsibility to function with one another and respond to common goals.

Sunday, April 10, 2016

The Paradox of Compromise and complex evolutionary Maps in Decision Making



This case study is primarily focused on process development of compromise mapping beyond Decision Making Mechanism.  Experimental methods in Cognitive Science have also been used during observational studies in order to capture sequential Map Matching Algorithms in Brain Process and circumstances surrounding compromises.  The numbers of Analogical Attributes with within “Compromise Map Profile” can imply to potential compromise paths between two types of Human Characters.  Comprehensive Knowledge of underlying Analogical Attributes within “Compromise Map Profile” can raise awareness about influences of complex genetic codes and instance parameters of Social Context on Human Behaviors. Knowledge inspiration can increase public understanding about Complex Decision Making, Emotional purge tragedy, and Behavioral Disorders. Untimely, this study determines and illustrates the source of good and bad Compromises, which is based on properties and characteristic attributes, within “Compromise Map Profile”.

Synthetic profiles have been used in terms of comparing Sequential Map Matching Algorithms in three structural stages model. Observational experience on Compromise Mapping illustrates how aggregated attributes develop from The First Map to “Final Compromise Map Profile”.

Conceptual Metaphorical Mapping provides imagining aggregated attributes through three phases of process interactions between two Human Characters. Besides, it makes transparency on process development of compromise mapping.

For example, two people encountered with chaotic situation in Social Context and they need to make decision by compromising strategy in order to prevent chaos.  A wide variety of compromisers’ profiles reduced in this paper due to time constraints. Two case studies have been carefully chosen among many other case study scenarios. These two case studies are involved with multiple instances of Brain Mechanisms, Decision Making Patterns, and paradox of Compromises.

According to the following two case studies highlight, good and bad Compromises can identify and compare through encapsulated attributes within “Final Compromise Map Profile”.

1- The first case study:

Men and Women were selected with similar genetic factors, similar environmental Influences, and common Superego Adjuster. Consider the following scenario analysis and possible events:  

Problem:

A stressful or dangerous situation can occur in Social Context; consequently, Survival Instincts would be activated in Brain of designated default profiles (Man and Woman). Two people encountered with chaotic situation in Social Context and they need to make decision by compromising in order to prevent chaos. Genetic Instinct and Gender Instinct modify Survival Instincts through Secondary Instinct.

1.1 Definition:

The output of “Instinct Component” produces and perpetuates Evolutionary Algorithms within The First Map, which contains Genetic, Gender, and General Instinct Codes. (Figure 1)

1.2 Analysis:

Similar Genetic Instinct Codes and similar environmental factors generate analogical attributes within“(1) Compromise Map Profile”. However, different types of Gender Instincts in Brain of two compromisers would probably show low analogical model among Gender Instincts. (Figure 1)
                                                                          



1.3 Learning outcome 1:

“(1) Compromise Map Profile” would probably encapsulate Analogical Attributes for Genetic Codes and Analogical Attributes for General Instinct Codes. But Non-analogical Attributes for Gender Codes would not be encapsulated. (Figure 2)

1.2.1 Definition for The First Map:

The Evolutionary Algorithms within The First Map interact with instance parameters of Superego and Ego environment.

1.2.2 Analysis:

Two compromisers interact with common Superego Adjuster (Instance of Social Context). Therefore, there is tremendous potential for having common principles and values with similar algorithms within Superego/Ego environment. Similar algorithms in Superego/Ego environment produce and perpetuate Superego/Ego Code within The Second Map (Iceberg Map). Besides, similar Genetic Codes and General Instinct Codes transfer from The First Map to The Second Map. (Figure 2)

1.2.3 Learning outcome 2:

“(2) Compromise Map Profile” would probably encapsulate analogical attributes among Superego/Ego Codes, analogical attribute for similar Genetic Codes, and analogical attribute for similar General Instinct Codes. Gender Instincts may be absent or subtle. (Figure 2)

1.3.1 Definition for The Second Map:

Evolutionary Algorithms within The Second Map (Iceberg Map) interact with Evolutionary Algorithms within the Logical Part of Brain. Interaction is caused by chemical modification, which generates and perpetuates new Evolutionary Algorithms, within The Third Map. (Figure 2)

1.3.2 Analysis:

Superego/Ego Code is modified by algorithmic mechanism in Logical Part of Brain and the new algorithmic mechanism controls The Third Map (Decision Making Pattern). (Figure 2)

1.3.3Learning outcome 3:

 “Final Compromise Map Profile” would probably encapsulate sufficient condition for analogical attributes for Decision Making Model. It contains analogical attributes for Superego/Ego, analogical attributes for similar Genetic Codes, analogical attributes for similar General Instinct Codes. Gender Instincts may be absent or subtle. Therefore, two compromisers have almost similar principles and values for Decision Making Model. Logical inferences are based on “a Good Compromise Model”.

2- The second case study:

Men and Men were selected with Genetic Diversity, Environmental Influences (Competitive environment), and individual Superego Adjuster (Lack of Superego Adjuster). Consider the following scenario analysis and possible events: 

Problem:

A stressful or dangerous situation can occur in Competitive Social Contexts; consequently, Survival Instinct and Competitive Instinct would be activated in Brain of designated default profiles (Man and Man). Social Context encapsulates complex domain and Competitive characters.

2.1 Definition for The First Map:

The output of “Instinct Component” produces and perpetuates Evolutionary Algorithms within The First Map, which contains Gender Instinct Code and General Instinct Codes. 
                                                                             



2.2 Analysis:

Similar Gender Instincts Codes and similar environmental factors with complex competitive modes would process analogical Gender Instinct and analogical General Instinct within “(1) Compromise Map Profile”. However, Diverse Genetic Instinct would not generate and encapsulate analogical attributes within “(1) Compromise Map Profile”. (Figure 3)

2.3 Learning outcome:

“(1) Compromise Map Profile” would probably encapsulate Gender Attribute and General Instinct Attributes (Competitive Attribute, Survival Attribute). But Genetic Instincts is eliminated in this Brain Process Mapping. (Figure 3)

2.2.1 Definition for The Second Map:

The Evolutionary Algorithms within The First Map interact with instance parameters of Superego and Ego environment. Interaction can create process for The Second Map in Brain.

2.2.2 Analysis:

Two compromisers interact with individual Superego Adjuster (Instance of Social Context). Therefore, there is little/no chance of having common principles and similar algorithms within Superego/Ego environment. Lack of Superego Adjuster within Social Context can fortify and enhance Ego functioning; in contrast, Superego would have weak cognitive functioning. Harmonic Balance and regular mediation between Superego and Ego can be deteriorated by Ego functioning and environmental factors.

Diverse paths of algorithms in Superego/Ego environment produce and perpetuate discrepant codes within The Second Map (Iceberg Map).  (Figure 3)

2.2.3 Learning outcome:

 “(2) Compromise Map Profile” would probably not encapsulate analogical attributes from the Superego/Ego Framework due to diverse paths of algorithms in Superego/Ego environment. (Competitive Mode in Superego/Ego can generally activate instance parameters of Hypocrisy). A good deal of Hypocrisy processes Inconsistent and Non-analogical algorithms within “(2) Compromise Map Profile”. Therefore, “(2) Compromise Map Profile” can be only encapsulated and instantiated Analogical Gender Attributes, Analogical Survival Attribute, and Analogical Competitive Attribute. (Figure 3)

2.3.1 Definition for The Third Map:

Evolutionary Algorithms within The Second Map (Iceberg Map) interact with the Logical Part of Brain. Interaction is caused by chemical modification, which generates and perpetuates new Evolutionary Algorithms (Strategic Map), within The Third Map. (Figure 3)

2.3.2 Analysis:

Dissimilar Superego/Ego Framework can modify algorithmic mechanism within the Logical Part of Brain, which controls The Third Map (Decision Making Pattern). The logical Part of Brain process wide variety of Strategic codes within The Third Map. Strategic variety beyond diverse algorithmic mechanism in Logical Part of Brain generates Non-analogical Attributes within “Final Compromise Map Profile”. (Figure 3)

2.3.3 Learning outcome 2:

“Final Compromise Map Profile” would probably not encapsulate Non-analogical Attribute of Superego/Ego Framework. Inconsistent Strategic Codes remain in The Third Map. However, analogical Gender Codes, analogical Survival Codes, and analogical parameters beyond Competitive Codes can encapsulate within “Final Compromise Map Profile”.

Therefore, two compromisers have different principles and values but they pretend to compromise due to own interest or advantage (Political Strategies). Decision Making Pattern and logical inferences is based on “a Bad Compromise Model”.
                                                                              



3. Conclusion:

The good and bad Compromises can identify and compare through encapsulated attributes within “Final Compromise Map Profile”. The Good Compromise Mapping Profile requires that “Final Compromise Map Profile” encapsulates multiple analogical attributes, which instantiate through Instincts, Superego/Ego, and Logical Part of Brain. The Good “Compromise Mapping Profile” provides good potential compromise paths between two types of Human Characters. (Figure 4)

The first case study shows that “Final Compromise Map Profile” encapsulated sufficient attributes and met the minimum requirements for Good Compromise Mapping.

The second case study shows that “Final Compromise Map Profile” encapsulated insufficient attributes and the minimum (mandatory) requirements were not fulfilled.  Similar Survival, Gender, and Competitive Instincts would not ensure Good Compromise Mapping Profile. Similar Survival Instincts promote and suggest temporary regulations in order to achieve Compromise Mapping Profile. Politicians used to engage with this type of Compromise Mapping Profile; therefore, they are not confident with their own unreliable Compromises. Common Competitive Instincts between two compromisers generate Super-sized Hypocrisy in the Brain. Hypocrisy Mode can lead to obstruct Superego strength and modify Harmonic Balance between Superego and Ego. Therefore, “Final Compromise Map Profile” would no longer remain in power. (Figure 4)
                                                                                



Observation:

“(1) Compromise Map Profile” and “(2) Compromise Map Profile” are used in this study as imagining Maps in terms of improving transparency for development of aggregated attributes within “Final Compromise Map Profile”

Observation:

Superego Adjuster can modify Algorithmic Structure within Superego/Ego in the long term. Superego/Ego can modify Algorithmic Structure within Logical Part of Brain in the long term.

Observation:

Algorithmic parameters in Social Context develop according to Global Variables.

Observation:

Algorithmic parameters in structure of Global Variables articulate and create according to economic perceptions and political preferences within Competitive World.

Observation:

Political preferences in Competitive World are articulated and created by Big Corporations and Elites.

Observation:

System developers modify algorithmic parameters in Social Context. Those algorithmic Parameters fortify Ego strength, mistrust among people, and empowering Hypocrisy.

Observation:

Complex parameters in Social Context solve with Complex solutions because of low cost performances and measurable short term outcome. Systems Owners are not concern about possible side-effects of Complex Solutions. Systems Owners believe that they approach and define optimal solutions due to Optimal Economic Growth in short term. These types of solutions create multiple sides-effects in long term.

Observation:

Certain old cultures (within Superego Adjuster) modified Gender Instincts for men and modification ensured reliability for Compromising, Regardless to number of encapsulated Attributes in “Compromise Map Profile”.

Observation:

Systems Owners approach sometimes Hypocrisy Mode in order to reduce costs, build a competitive advantage, and maximize Harmonic Balance in Social Context in short term. However, they would not target possible side-effects of Hypocrisy over implementation due to low level implementation knowledge.  

Observation: 
According to observational study, one of the important reasons that human race was created on earth is to develop and improve Harmonic Balance between Superego and Ego in Brain during evolutionary path of life. 
Observation:
Harmonic Balance between Ego and Superego determines Harmonic Balance in Decision Making and Social Behavior. Certain Genetic Instincts and instance parameters in Social Context can modify property of Ego/Superego in Brain. Besides, they can promote and disturb Mode of Ego/Superego.
Individuals do not have control over Genetic Instincts and instance parameters in Social Context; therefore, they cannot modify Harmonic Balance in Ego /Superego without interference from external entities.
Observation:
Characteristics of Human Nature and Social Life are sometimes modified by so called common sense beliefs because Human beings cannot completely predict and evaluate possible side-effects of common sense beliefs in Social Context.


Observation:
Human Being is preprogrammed genetically. Making Decisions and Social Cognition Processes are functioned according to certain Identification Codes (Instincts). Systems Owners and Modern Humans can modify Identification Codes due to Global Competition, Economic Performances, and many other Complex Strategies. Consequently, Human Being would not act naturally in Social Context and on the evolutionary path of life.