The building of decision rules is the core of business organization in the 4^th industrial revolution. It provides the basic information to build adaptive automation in business processes and to design business cobots to work as collaborative systems.

These rules implicitly provide the knowledge of the triadic structure of business functions and processes to build the necessary binary actions and business objects that allows managing their adaptability. 

Introduction to Decision Making and its Rules

There is nothing in the universe, which is part of a system, that does not work with a purpose, an active function, and an energy conservation function, integrated by complementation and supplementation laws, that define its concept.

Any decision process that deals with systems is therefore based on this triadic structure that requires developing binary actions to influence it. Businesses are adaptive environments that require using binary actions to make them work. Univocal actions only work when businesses do not need to be adaptive.

The following description provides the structure of the unicist functional designer to build decision rules to manage adaptive business processes.

It allows building Cobots (collaborative business robots) to sustain automated processes or work as decision support systems. 

An example will clarify why decision rules are needed to enable the development of binary actions.

An Example

The purpose of an electric motor is to convert electrical energy into the mechanical energy. DC motors and AC motors are based on the same essential principles that define their triadic structure.

Their active function is based on transforming electrical energy into magnetic energy. The energy conservation function transforms the magnetic energy into mechanical energy.

The binary actions of the process are, on the one hand, the transformation of electrical energy into magnetic energy and, on the other hand, the transformation of the magnetic force into mechanical energy. These processes happen within the rotor and the stator of an electric motor.

Decision Rule Building in Business Environments

The research on decision rule building was carried out for more than 10 years, developing decision rules based on the use of the unicist ontology of decision making. Decision rules are implicit in the use of the ontogenetic maps that describe and define the functionality of things.

This work describes how to approach the ontogenetic map of a business function to find the necessary decision rules to build an inference engine -based on the unicist logic- to be able to build Unicist AI or a collaborative business robot (Cobot).

The purpose of a decision rule is to sustain a decision-making process. It is integrated by proactive decisions to influence the environment and reactive decisions to have instantaneous defensive responses when they are needed. These rules must make actions feasible. This requires that the decision rules must fit into the parameters of acceptability established by the environment.

This requires that the decision rules must fit into the parameters of acceptability established by the environment.

This means that the rules can only be found by using collective intelligence, which includes the parameters of the wide and restricted context of the decisions that are made. A rational approach suffices only when the environment has no influence and can be dominated.

After the acceptability of the decision process has been confirmed, the functionality of the decisions needs to be defined. The functionality is defined by the ontogenetic map of the business function that is involved. It is what makes the rule-finding necessary and provides the structural information to develop the process.

The Ontogenetic Map of Decision Rule Building

The final purpose that drives the building of decision rules is the achievement of objectives that have been established. These objectives need to fit into the parameters of necessity, possibility, and acceptability. Decision rules are functional when they are needed, their achievement has been confirmed as possible and they are acceptable in the wide and restricted contexts. 

While the justification of decisions explains what they are for, the justification of decision rule building deals with the decisions that need to be made and not with the rules themselves.

This requires managing the functionality of the process where the decisions take place. It is not possible to define decision rules without being involved in the whole process.

When this is the case, the decision rules must ensure the functionality of the processes by dealing with the foundations of the actions involved.

The foundations of the decisions are based on the triadic functionality of the processes and the necessary binary actions to make them work.

The Maximal Strategy to Manage Proactive Decisions

Proactive decisions are focused on growth, expansion, or the development of structural solutions. This requires developing conscious decisions, discriminating what is possible to be achieved from what is not possible.

This process is based on the use of an experience-based intuition, which is included in the conscious concept deciders have in their minds that provide the initial hypothetical solution to be assessed.

When this has been achieved, it becomes necessary to validate the intuitive solution using logical rationality, which needs to be based on the use of the unicist logic that manages the triadic structure of processes and allows making a conscious approach to the building of the rules that drive towards binary actions.

This unicist logical rationality is the catalyst of the minimum strategy because it opens the boundaries for solutions, and at the same time accelerates decision making processes by providing a safe environment.

The Minimum Strategy to Manage Reactive Decisions

Reactive decisions allow building univocal actions in controlled environments. They also enable the development of automatic decisions driven by instincts to survive in extreme situations. These types of decisions are natural in survival threatening environments.

They are sustained by the genetic intuitive intelligence of people to develop actions in those fields where their genetic intelligence is more powerful. The entropy inhibitor, that ensures the functionality of these reactive decisions is the empirical rationality of people. In plain language, their experience. This experience works as a filter to build a bridge between the instinctive decisions and the use of the genetic intelligence of deciders.

Types of Decision Rules

Four basic types of decision rules have been found plus a dysfunctional type which is frequently used.  

Dysfunctional Rules:

The dysfunctional rules are analogical rules, which will be described in the first place to be able to recognize them.

Analogical rules are those that are established based on analogical benchmarks that disregard the context of the functionality of things and are therefore not predictable in their results.

They are naturally used by those who have a tunnel vision of the business processes. When dysfunctional rules are used and things do not work, the context is usually blamed for this.

Functional Rules:

1. Operational decision rules
2. Analytical decision rules
3. Systemic decision rules
4. Adaptive decision rules

Operational Decision Rules

The operational decision rules define the operation of processes and are valid when the processes are not adaptive. They are based on the accuracy of the actions that need to be done and are functional to establish operational steps that need to be fulfilled to achieve an objective.

They are based on empirical decisions and the management of univocal actions that can generate predefined results.

Analytical Decision Rules

Analytical decision rules are based on the division of problems into their parts to make them manageable. They are functional in non-adaptive complicated environments. They are based on a theory-practice and top-down approach to generate decisions. They allow managing the knowledge that is necessary to make decisions.

Analytical decision rules are functional to avoid operational mistakes in complicated operational environments.

Systemic Decision Rules

They manage decisions based on the integration of the elements of a system considering them in terms of univocal cause-effect relationships, although assuming that their functionality is interdependent. They are based on a conscious experience-based approach to decision making.

Systemic decision rules are functional to make decisions in fields where the external influence of the environment is low.

Adaptive Decision Rules

Adaptive decision rules are based on the use of the ontogenetic maps of business functions and the use of the unicist logic to define the functionality of processes and the possibility of achieving results. They are based on managing a strong influence of the external environments by managing the rules to integrate the text, the restricted context, and the wide context as a unified field. 

They are based on a bottom-up – top-down approach to define the rules that must guide decisions. They use a conceptual and fundamentals-based approach to decision making.

Conclusion

The building of decision rules provides the basic information to build adaptive automation in business processes and to design business cobots to work as collaborative systems. The functionalist approach to rule building is based on using the rules that are implicit in the ontogenetic maps of the processes involved. The action of these rules is triggered by indicators and/or predictors to manage the operational consequences of the functionality of processes.