Unicist Root Cause Management


A Logical Approach to the Root Causes of Problems

The unicist approach to root cause management in adaptive environments represents a simplification made possible by the development of unicist logic. This logic emulates the intelligence of nature, leading to the creation of the unicist ontology that defines the functionalist principles of entities, thereby granting access to the root causes of their problems.

The application of unicist logic has rendered businesses reasonable, understandable, predictable, and manageable. Moreover, it has facilitated the development of unicist artificial intelligence.

The strength of unicist logic resides in its simplicity. It only requires reasoning in terms of maximal strategies for growth and minimal strategies to ensure results, as well as the complementation and supplementation within relationships. This involves a shift from a dualistic to a functionalist approach.

It is founded on the discovery of the functionality of nature’s intelligence, which sustains the development of unicist logic. This logic enables the management of the functionality, dynamics, and evolution of adaptive systems with open boundaries, employing functionalist principles based on their unicist ontologies.

Thus, unicist logic is instrumental in managing the root causes of problems and in formulating binary actions that address maximal strategies for growth alongside minimal strategies to ensure results. It is the requisite approach for managing adaptability in the 4th Industrial Revolution.

The “Roots” of Unicist Root Cause Management

Introduction

The use of recurring palliatives in problem-solving, when the root causes of problems are unknown, demonstrated to be a fallacious shortcut, frequently used for conjunctural solution building, that produces paradoxical results.

Unicist root cause management introduced an approach for problem-solving, facing the management of root causes and avoiding the use of shortcuts used as palliatives, to develop structural solutions.

Unicist root cause management introduced an approach to develop structural solutions for problems in adaptive environments. It drives to research the fundamentals of efficacy and efficiency and find a solution that integrates the problems, their restricted context, and their wide context.

This approach showed that structural problem-solving is the most energy-saving action because it hinders the reappearance of problems. It requires apprehending the root causes of problems, working within the boundaries established by the limit-causes, and ending with a structural solution based on the functionality of the fundamentals of the problem and an operational solution that ensures results.

The Basics

The discovery of the intelligence that underlies nature and the structure of concepts that regulate the evolution of living beings and drive human actions opened the possibility of managing root causes.

The consequence of these discoveries is that the root causes of problems are defined by the dysfunctionality of the fundamentals that integrate the concepts that underlie the entity or action that cannot fulfill its purpose.

This approach became possible due to the development of the unicist ontology that defines the nature of things by emulating the structure of the triadic intelligence that underlies nature (purpose, active and entropic principle, energy conservation principle). Thus, the discovery of the root causes became possible due to the knowledge of the unicist ontology of the entities that are being managed.

It all begins by understanding their functionality and ends by measuring the standards to confirm the necessary threshold of the fundamentals to achieve results.

The Unicist Ontology of Problem Causality

The unicist approach to problem-solving was developed to deal with complex adaptive systems such as social, economic, and business processes.

On the one hand, the unicist management of causality in complex adaptive systems is based on the inexistence of both univocal cause-effect relationships and the exclusive disjunctions “OR” among their elements, which are substituted by bi-univocal relationships and the conjunction “AND” that integrates their elements.

On the other hand, these complex adaptive entities are not integrated by variables, which are based on univocal relationships, but by objects, which are autonomous adaptive systems that assume a role/function in these systems.

Complexity science was developed to explain, manage, and predict adaptive systems and environments. It allowed for managing the causality of adaptive systems, which have open boundaries to sustain their adaptability.

The Unicist Management of Causality

The unicist management of causality is based on the unicist ontology of the complex adaptive systems that describes their nature and defines the concepts that regulate their evolution.

A problem exists when a functionality, that has been defined as possible to be achieved, cannot be fulfilled.

The unicist approach to problem-solving defines three types of causes that are integrated in the concept of problem causality.

  • Triggering causes: that define the operational causes that generate a problem.
  • Necessary causes: that define the root causes of the problem.
  • The limit causes: that define the boundaries of what is possible to be achieved.

Different Levels of Solutions

The unicist approach to problem-solving defines four levels of solutions that can be achieved according to the level of knowledge of the problems.

It has to be considered that people who need to avoid risks cannot deal with problems’ causality and substitute the knowledge of problems with pre-concepts that allow them to avoid facing the risks of developing solutions.

The different levels of solutions that have been defined are:

  1. Repairs
  2. Palliatives
  3. Systemic Solutions
  4. Adaptive Solutions

Repair

The natural response of people when an urgent problem appears is to repair it, based on the negative consequences that need to be avoided. This is a short-term energy-saving action to face the solution of problems.

If the root-problem is not being addressed, the problem will reappear when the root cause acts again.

Palliatives

The natural response when people do not have the knowledge to solve specific problems is the use of palliatives to mitigate the consequences of such problems. This is a short-term energy-saving actions when there is a lack of knowledge to solve problems.

The problem will continue to exist mitigated by the palliatives that have been installed.

Systemic Solutions

The development of systemic solutions is the necessary approach when the problems deal with the efficiency of the processes. In this case, it solves the root causes of the problem, but if the lack of efficiency is produced by dysfunctional efficacy, it will reappear due to the entropy of the solution.

This is an energy consuming action that naturally drives towards finding the root causes that include both the problems with efficacy and efficiency.

Adaptive Solutions

This is the approach to developing structural solutions for problems. It drives to research the fundamentals of efficacy and efficiency and find a solution that integrates the problems, their restricted context, and their wide context.

It is the most energy-saving action because it hinders the reappearance of problems. It requires working within the boundaries established by the limit-causes and ends with a structural solution based on the functionality of the fundamentals of the problem and an operational solution that ensures operational results.

What Became Possible that was not Possible Before?

The unicist logic allowed access to the root causes of problems in adaptive environments. It gave access to manage the functionality of the concepts and fundamentals that define these root causes making possible what was not possible before:

  1. The definition of what is possible to be achieved in adaptive environments
    The unicist evolutionary approach requires defining first what is possible to achieve before defining what one wants to achieve. This avoids defining fallacious objectives.

  2. Research of the root causes of problems in adaptive environments
    The root causes of problems in adaptive processes are defined by the dysfunctionality of the concepts and fundamentals of the functions involved. This allows for optimizing and structuring adaptive processes.

  3. Management of the fundamentals of business functions
    Business functions are necessarily adaptive to satisfy the needs of the environment. The management of their fundamentals ensures their adaptiveness.

  4. Development of maximal and minimum strategy actions
    The unicist strategy emulates the intelligence of nature by developing maximal strategies to grow and minimum strategies to ensure results.

  5. Development of unicist binary actions to ensure results
    The need for maximal and minimum strategy actions requires developing sets of binary actions that influence the environment by fitting into preexisting concepts.

  6. The forecast of social, organizational, and individual behavior
    The knowledge of the structure of the concepts of business functions allows managing their functionality, dynamics, and evolution based on the laws of evolution provided by the unicist evolutionary approach.

  7. The design and development of social and business objects
    The management of adaptive environments requires installing objects that drive processes and ensure their functionality and evolution.

  8. Organization of adaptive systems
    The knowledge of the structure of the concepts of adaptive systems and environments allows defining and organizing the dynamics of their functionality.

  9. The design, building, and installation of business catalysts
    Biological catalysts are homologous to social and business catalysts. The unicist logic allowed the defining of the structure of the catalysts of biological processes and the development of business process catalysts.

  10. Future Scenario Buiding
    The management of the laws of evolution allowed the development of a future research model that is based on finding the unicist ontological structures of a scenario in the past, and using the data of the present in order to infer the future.
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