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CHAPTER II 1

LITERATURE REVIEW

1.1 Introduction Organizations are more complex today than in the past, in part due to their structure, other times due to the increasing number of constrains in resources or the increasing level of technology required to accomplish the augmented tasks and interactions among different entities in the organization. Because of this complexity, organizations are required to deal with an increasing amount of information generated and processed by them, and the required time to perform decision-making processes is extremely limited.

The need to understand and control the behavior of critical variables for the organization is an increasing demand from managers and engineers in the attempt to improve the decision-making process. This need to understand and control can be applied to governmental entities as well.

The government requires

understanding on how economy is behaving to take better and more informed decisions. While business organizations have applied applied several techniques techniques to follow up the critical variables, the Federal Government usually applies to economic indexes, decision rules much more complex than a statistical control chart, as an example of this, the following reference explains the way a recession is declared:  ―While  ―While a recessions is popularly defined as occurring when the real gross domestic product (i.e., the inflation-adjusted GDP) declines for two quarters in a row, the NBER actually considers a variety of monthly and quarterly data before making a determination, including the GDP in current and inflation-adjusted dollars, business sales, bank debits outside New York City, industrial production, unemployment rate, nonfarm employment and hours worked, and personal income.‖ (Frumkin, 1998, p. 5) Let consider economic variables or indexes, such as Gross Domestic Product (GDP), Government Gross Investment (GGI) or Gross National Product (GNP), as examples of a complex complex situations.

Complex econometric models have been

created in order to understand, and perhaps predict, the behavior for these variables. The understanding on how the Gross Domestic Product (GDP)  –or any other economic index for the USA   —  behaves will help to define better economic practices and policies. Unfortunately, there is no easy alternative to identify if GDP (among others) is following a natural behavior or not. It is even more difficult to establish if there is a solid reason for assigning a special situation when the GDP is not behaving as usual.

To better manage complex systems  –as GDP —  it is imperative to understand their components, their behavior and create a simpler scheme for decision-making.

A systemic view of the organization can help with the

understanding of components and behavioral interactions of the system, while statistical techniques, such as statistical control charts, can exist with the for decision-making endeavors. Process behavior charts, or control charts, are effective only when the manager can use the knowledge gained from the charts (Wheeler, Advance Topics in Statistical Process Control, 2004).

For simpler processes, process behavior charts are a perfect tool to identify points that are out of the natural behavior of the system. When the process is more complex, there are other considerations to tackle such as the amount of data available within a reasonable time period is limited, and considering that the assumed growth in the critical variables is not constant.

This has led to the belief that in the GDP case, as in any other economic or business index, there are three important elements to consider. First, the critical variable can be considered as an indicator of a Living System (LS) due to its nature. Secondly, the need for managers and engineers to have a tool that helps to make the decision-making process easier. Thirdly, the presence of statistical techniques used to identify situations to handle behavior that has an atypical pattern for critical variables within the process.

This chapter presents information divided in three segments. The first one look at the systems approach, more precisely Living Systems Theory (LST), to understand their main characteristics and elements and how these are relevant to the understanding of the process and the critical variable under study. The second one is about the statistical techniques, specifically process behavior charts, that exist to evaluate the behavior of critical variables and their comparison. The third one concerns the modification required in current process behavior charts to overcome the limitations presented in segment two and to propose an alternative to evaluate the economic or business indexes such as GDP.

1.2 Primary Theories in Systems Approach and Historical Background

 According to Bertalanffy (1969), a system is a set of elements that are interconnected. This concept can be applied to practically any entity, whether it is a machine or a living organism. Through time, the concept of a system has changed. Table 2.1, provides a historical development of the original concept of  ―system‖ initiated by Bertalanffy.

The focus of system‘s definition has changed through time but conc ur in a system as a set of interrelated, interconnected, interacting elements that are organized in such way that can achieve a specific purpose. More aspects on the notion of system are: a) A perspective (also called weltanschauung). b) A concept of unity or wholeness. c) A clear and definable boundary, among others.

1.2.1

General Systems Theory

Once the system concept has been clearly defined, it is time to explain another important concept: the systems approach. This is a way of thinking to create an integrated view of a total system(Churchman, 1979). Based on the systemic approach the General Systems Theory (GTS) investigates the common principles that is inherent in all complex changes in the real world (Chambers, Piggott, & Coleman, 2001), in all complex entities and the models used to describe them (Canto, 2007).

The GST concept was initiated by Bertalanffy, who started an effort to counteract the oversight of disciplinary specialization by incorporating a holistic worldview(Mulej, et al., 2004). Miller (1965) in his Living Systems, defines GST by saying:

General Systems Theory is a set of related definitions and propositions, which deal with reality as an integrated hierarchy of organizations of matter and energy. General Systems Behavior Theory is concerned with a special subset of all systems, the living ones (p. 193).

Table 1.1 Evolution of system‘s definition  Author

Bertalanffy Rapoport  Ashby Mesarovic

Forrester Churchman Bertalanffy

Concept

 ―Set of elements standing in interrelation‖ p.28  ―Entity which can maintain some organization in the face of change from within or without‖  p.  ―A set of variables selected by an observer‖ p.  ―A set of implicitly defined formal objects; a set of elementary transformations; a set of rules for forming the sequences of transformations, and a set of statements indicating initial forms of the formal object for use in generating new forms of the objects‖ p. 7  ―Grouping of parts that operate together for a common purpose‖ p.1-1  ―Systems are made up of sets of components that work together for the overall objective of the whole‖ p.11  ―A whole made up of interrelated and interdependent parts, interacting to maintain that whole‖ p.38

Time

1950 1953 1960 1964

1968 1968 1969

Table 1.1 Evolution of system‘s definition  Author

Concept

Ryan

 ―Set of objects or elements in interaction to achieve a specific goal or mission‖  Reference made by Jackson (1990) p. Weiss  ―A system is anything unitary enough to deserve a name‖ Referenced by Skyttner (1996) p.16 Bertalanffy  ―Set of elements standing in interrelation among themselves and with the environment‖ p. 417 Katz &  ―is composed of interrelated parts or elements. This is true Rosenzweig for all systems –mechanical, biological, and social.‖ p. 450 Maturana  ―Any definable set of components‖   and Varela Churchman  ―A structure that has organized components‖  Referenced by Skyttner (1996) p.16  Ackoff  ―is a set of two or more elements that satisfies the following three conditions: a) the behavior of each element has an effect on the behavior of the whole, b) the behavior of the elements and their effects on the whole are interdependent, and c) however subgroups of the elements are formed, all have an effect on the behavior of the whole but none has an independent effect on it‖  p. Boulding  ―A system is anything that is not chaos‖ Referenced by Skyttner (1996) p.16  Anderson  ―A group of interacting, interrelated or interdependent and components that form a complex and unified whole‖ p.2 Johnson Kossiakoff  ―A set of interrelated components working together as an & Sweet integrated whole to achieve some common objective‖ p.10

Time

N/A 1971 1972 1972 1979 1979 1981

1985 1997

2003

The main concern of GST is to provide a structure of knowledge that can be applied to several scientific fields (Wang T. , 2004) so the development in one area of knowledge can be applied to another completely different area.

Bertalanffy

coined the term isomorphism to refer to the common attributes that different sciences have allowed for the creation of bridges among specialized knowledge and then transforming them into a  ―science of similarities‖ (Mulej, et al., 2004, p. 49).

In 1968, Anatol Rapoport, presents a definition for the proprietary task of GST saying:

In short, the task of General Systems Theory is to find the most general conceptual framework in which a scientific theory or a technological problem can be placed without losing the essential features of the theory or the problem (p. 457).  According to Mulej, et al. (2004), Bertalanffy‘s concept of GST is based on the following ideas: a)  A concept relates to other concepts. b)  A concept melds of components of the unified entity. c)  A concept condenses components. d)  ― A concept is in a state of symbol in relation to other concepts‖  (Pelko, 2000), (Mulej, et al., 2004, p. 49).

In order to create knowledge applicable to all sciences, GST discusses and elaborates on two types of systems: close/nonliving systems and open/living systems (Wang T. , 2004). Miller (1965) proposed the concept of nonliving and living systems, while Bertalanffy (1969) proposed the concept of closed and open systems in the middle of the 1950‘s. In both approaches, the open/living systems tend to have a higher hierarchy as well as higher complexity.

1.2.2

Principles, assumptions and concepts concerning systems

 According to Bertalanffy (1972), the holistic notion of a system problem was first stated by Aristotle (384-322 B.C.) when he said ―the whole is more than the sum of its parts‖. Then Hegel (1770-1831) reformulated this statement into four statements rephrased by Skyttner (1996) saying that: a) The whole is more than the sum of the parts. b) The whole defines the nature of the parts. c) The parts cannot be understood by studying the whole. d) The parts are dynamically interrelated or interdependent.

These statements coincide with the definition of a system that was presented in the introduction for this section (2.2). Derived from those statements some hallmarks of the systems‘ concepts are presented in Table 2.2.

From these definitions, it is important to emphasize four concepts that are related to complex systems, which are open system, living system, regulation and equifinality.

First, the concept of open system refers to the continuous interchange of matter, energy and information among system components and with the environment in which the system resides. Open systems tend to have a steady state creating stability in the system.

Table 1.2 Hallmarks of Systems Theory Concept Definition  According to Miller, any complex system requires specialized units to perform specialized functions. ―Differentiation is the increased Differentispecialization that occurs as systems grow in complexity (Katz & ation and Kahn, 1978; Bertalanffy, 1956)‖ and ―Integration is the countering Integration process of coordination and centralization of the differing parts (Ford, 1987; Bertalanffy, 1969)‖ (Vancouver, 1996). Referred to as the second law of thermodynamics, entropy can by Entropy defined as the ―amount of disorder or randomness present in an y and system‖ (Skyttner, 1996) and Negentropy, in association with the Negentro- previous definition, as negative entropy, which means the import of py energy, information or matter in order to create order or stability (Miller, 1965). In closed systems, the final state depends on the initial conditions in the system. In open systems, the final state may be reached in spite Equifinality of the alteration of the initial conditions or changes in the process (Bertalanffy, General Systems Theory, 1969).  Any system is formed by sub-systems creating a structure or hierarchy in such way that the individual members (sub-systems) are, again, Hierarchy systems by themselves on the next lower level. This hierarchy helps to sustain order and requires import energy to achieve it (Bertalanffy, General Systems Theory, 1969).

Table 1.2 Hallmarks of Systems Theory Concept Definition Presented in its primary form by Aristotle, this concept represents the view of a system as a complete and unified unit, and the integrative Holism approach of systems to understand how the sum of parts is different from the whole. Presented by Bertalanffy in his definition of system, this concept means the connection that exists among the elements of a system. Interrelatio These connections make possible the interchange of matter, nship information and energy that is required by a system to survive (Miller, 1965). The concept of connections in this segment includes interrelationships, interconnections and interdependency. Defined by Bertalanffy, this concept refers to the common attributes Isomorph- or structural similarities in which different sciences can create a bridge ism among specialized knowledge and transform it into general system principles (Bertalanffy, 1969).

Table 2.2 Hallmarks of Systems Theory. Continued  ―Living systems are open systems, maintaining themselves in exchange of materials with the environment, and in continuous Living and building up and breaking down of their components‖ (Bertalanffy, The Non Living Theory of Open Systems in Physics and Biology, 1950). A non living Systems system is a system which does not have the characteristics of a living system (Miller, 1965).  According to Bertalanffy (1950) ―a system is closed if no material Open and enters or leaves it; it is open if there is import and export and, Closed therefore, change of the components‖. In open systems entropy level Systems may increase, decrease or remain in steady state while in closed systems entropy generally increases. This attribute implies the existence of feedback required for effective control. In closed systems this attribute represents a steady state of static equilibrium while in open systems represents a steady state of Regulation dynamic equilibrium. A system must be regulated in order to achieve the goals defined for/by the system. The tendency of a system to sustain steady states is also called homeostasis. Presented by Churchman, this concept implies the goal-seeking requirement that Ryan mentions in his definition of a system. Teleology Interactions and interconnections must result in some goal to achieve or some ―final‖ state to be reached.

The second concept is living systems, which refers to a subset of open systems that possess specific characteristics about critical subsystems (see Table 2.4). These characteristics make it possible to understand the organizations work and how their behavior is related to systems approach.

Third, the concept of regulation refers to the feedback and self-regulation property of living/open systems. Regulation marks the presence of ―equilibrium or steady state‖   (from section 1.1 p. 2). Equilibrium in a closed system is defined by maximum entropy and minimum free energy (Bertalanffy L. , General Systems Theory, 1969). Steady state is the ability of a system to sustain its operation even when there is a constant interchange of matter-energy and information. Bertalanffy (1969) explains, in  ―General Systems Theory‖ , that the concept for steady state in open systems is ―where the system remains constant as a whole an in its (macroscopic) phases, though there is a continuous flow of component materials.‖  (p. 125)

Equilibrium or steady state is an important concept in systems theory being the self-regulative characteristic that allows a system to grow and develop. Equilibrium can be achieved as static equilibrium, in the case of closed systems, or as dynamic equilibrium when open systems are involved.

Static equilibrium is

present in a system when even some disturbances are involved; the resultant behavior remains the same once the disturbance disappears. Dynamic equilibrium is the ―changing yet finely-balanced condition which requires continuous adjustments in order to maintain its present or stable state‖  (Business Dictionary, 2007). Dynamic equilibrium means maintaining a certain order of processes when some disturbances are present in the environment of the system (Bertalanffy L. , General Systems Theory, 1969). Another definition of dynamic equilibrium is the property of the system that allows sustaining its present state under some disturbances within the system. When the disturbance in the system is big it may

be possible to attain a different state than the initial state. This new state will become the steady state in open systems with dynamic equilibrium allowing a system to recover the trend, positive, neutral or negative, after a disturbance occurs.

 Another term related to regulation is homeostasis, which is the ―disposition of living beings (and inanimate and approximately designed systems) to keep on functioning at an optimum level, despite changes in the environment within certain limits.

Homeostasis employs feedback mechanisms to maintain the dynamic

equilibrium of a self-regulating system.‖   (Business Dictionary, 2007). Along with homeostasis, autopoiesis, is the  ―theory that living systems are 'self producing' mechanisms which maintain their particular form despite material inflow and outflow, through self-regulation and self-reference. Proposed by Chilean scientists Maturana & Varela in late 1960s or early 1970s, autopoiesis combines the  concepts of  homeostasis and systems thinking‖  (Business Dictionary, 2007).

The fourth concept, equifinality, is the ability of the system to reach a final state independently of the initial conditions and determined only by the system parameters (Bertalanffy L. , General Systems Theory, 1969).

Bertalanffy confers a close relationship between equilibrium and equifinality by saying ―It has been emphasized that every system attaining an equilibrium shows, in a certain way, ‗finalistic‘ behavior‖,  (Bertalanffy, General Systems Theory, p.131). The finalistic behavior refers to equifinality as the goal and may be reached even if different conditions and ‗pathways‘ are taken.

Homans and Curtis (1970) presented their own definition to Pareto‘s dynamic equilibrium:

This state is such... that if a modification were artificially introduced in it unlike that which it in reality undergoes, immediately a reaction would be produced which would tend to bring it back to the real state… Under 'artificial changes‘,  the old equilibrium is regained, but under more violent changes a new equilibrium may be reached. (p. 271) The interrelation of these four concepts (open systems, living systems, regulation and equifinality) can be more appreciated in the Figure 2.1.

 Another element that could be appropriate to mention as part of regulation is feedback. According to Bertalanffy, the essential criteria for feedback control systems are the following three: a) Regulation is upon pre-established arrangements ‗structures‘ in a broad sense. b) Typical feedback system is linear and unidirectional. c) Typical feedback or homeostatic phenomena are ‗open‘ with respect to incoming information but ‗closed‘ with respect to energy and matter.

Figure 1.1 Interrelations among systems concepts

1.2.3

Living Systems Theory

Living Systems, according to Miller (1965), are made of matter and energy organized by information. He defined a living system as a ―special subset of the set of all possible concrete systems, composed of the plants and the animals‖   (p. 203). Recall that a concrete system is a ―nonrandom accumulation of matter energy, in a region in physical space-time, which is non-randomly organized into coacting, interrelated subsystems or components.‖ (Miller J. , 1965, p. 202).

Living Systems Theory is one of the best developed theories of GST. His precursor, James G. Miller, developed a general theory, which oriented to deal with structural and behavioral properties of systems. In his theory, Miller presents 20 basic functions or subsystems, besides the hierarchical structure of systems based

on its complexity (amount of interchange of matter-energy). The hierarchical structure and a brief definition of the main function for that subsystem, is presented in Table 2.4.

 As shown, in Table 2.4 structure, Miller proposes that each level contains the previous one. Along with the hierarchy, Miller proposed as a central thesis of LST that living systems are open, composed by matter/energy, information, and every system includes subsystems with processes that are essential for life. Those living systems that carry out all the critical processes at their own level are called totipotential systems(Suan, 2007).

Table 1.3 Hierarchy of Living Systems. Adapted from (Miller & Miller, 1990, p. 3) Level Description Cell Organ Organism Group Organization Community

Society Supranational

A cell is the basic form of a system, which represents the molecules union.  An organ is the ―upwardly dispersed to organism‖ (Miller & Miller, 1990). An organism is the conjunction of several organs that are working together to conform a unitary entity. A group is a collection of organisms able to create new entities.  An organization is a ―chartering group‖ (Miller & Miller, 1990).  A community is ―a group of interdependent organisms inhabiting the same region and interacting with each other‖ (WordReference, 2008). A society is ―an extended social group having a distinctive cultural and economic organization‖ (WordReference, 2008). A supranational system is a conglomerate of societies with a mix of cultural and economic organization but with a common objective.

The critical processes that Miller describes in LST, are represented by the twenty basic functions or critical subsystems that a living system has to have (having those functions by itself or throughout symbiotic relationships with other systems). The twenty basic functions are presented in Table 2.5.

The most relevant concept for this research is the characteristics of a living system rather than its definition. According to Miller (1965, 1978), there are eight distinctive characteristics that every living system has:

a) b) c) d) e) f)

They are open systems. They maintain a steady state of negentropy. They tend to be more complex than they should be. They contain genetic material, usually known as DNA. They are composed of protoplasm (in most part). They contain an essential function called decider, which controls the entire system. g) They contain other critical functions or subsystems. If not, they have a symbiotic relationship with other living or nonliving systems, which carry out these functions in order to have them completely. h) These subsystems are integrated (to form a whole) to conform a selfregulating, evolving unitary system.

Table 1.4 Functions/Critical-subsystems of a Living System. Adapted from Miller(1978), Merker(1985) and Suan(2007) Function 1. 2. 3. 4. 5. 6. 7.

Reproducer Boundary

Ingestor Distributor Converter Producer Matterenergy storage 8. Extruder 9. Motor 10. Supporter

Process Process matter-energy and information Reproduces another similar system Holds together and protects components of the system Process matter-energy Brings matter-energy across boundary from environment Carries various inputs and outputs around the system Changes inputs to system into more useful forms Forms stable associations of energy and matter Retains various kinds of matter and energy over time Transports matter and energy out of the system Moves system to its parts in relation to the environment Maintains spatial relationships among system components

Table 1.4 Functions/Critical-subsystems of a Living System. Adapted from Miller(1978), Merker(1985) and Suan(2007) Function 11. Input transducer 12. Internal transducer 13. Channel and net 14. Timer 15. Decoder 16.  Associator 17. Memory 18. Decider 19. Encoder 20. Output transducer

Process Process information Brings information markers into systems Receives and transforms information markers from within system Physical routs for transmission of information markers Measures the passage of time  Alters information into an internally usable form Forms lasting associations among items of information Stores information within the system Coordinates, control and guides the system  Alters information from internal private code to a public code Puts out information markers from system to environment

The relevance of Living System Theory in complex systems, such as business organizations, is important because the structure defined by Miller, supports the understanding of the behavior for this type of systems.

The transformation processes, commonly used in complex systems, are governed by the laws of thermodynamics, stability and feedback /control theory, natural variation and uncertainty (Chambers, Piggott, & Coleman, 2001). Thus, any organization can be described as a complex system if it follows these three characteristics. Of course, business organizations have feedback cycles that help it to create stability in their processes; the behavior of business organizations show natural (common) variation as described by Deming (1992); and concerning the laws of thermodynamics, it is clear that having physical elements that integrate the organization, business organizations are no doubt ruled by them.

Once the business organization is recognized as a complex system, the next step in the process is to look at it as a living system. Miller (1965) presents a living system as a special subset of a concrete system that possesses all of the

following characteristics: open system, persistent negentropy, it also contains genetic material, composed of protoplasma, self-controlable, it contains other critical subsystems or possesses symbiotic relationships that allows self-regulating, developing and reproducing unitary systems with purposes and goals (Miller J. , 1965).

 Any business organization can be described, in systems‘ terms, as a living system. Three of the most relevant distinctions for living systems are non-zero slope growth, dynamic equilibrium and non-normal behavior. These aspects are not usual assumptions in statistical techniques that are stated based on independence, normality, and in most cases, zero slope assumptions.

1.2.4

Technorganic systems

Technorganic

systems

are

formed

by

both

human

and

machines

representing the close interaction and interdependence of living systems and technological systems.

Furthermore, business organizations are considered

technorganic systems.

 Any business organization can be described as the combination of at least one of the following systems: technological, human activity (structure), social, and human(Bertalanffy J. &., 2008). Organizations are systems composed of subsystems (in other cases also called systems considering the System of Systems Theory) with very specific functions. Recall that living systems (section 2.2.3) concept states that the system has specialized subsystems or functions(Miller J. , 1965). In the business organization case, these functions are performed by the technological, human activity, human and social systems.

Technological systems are composed of technical entities such as equipment, machinery, information systems and telecommunication networks. These kinds of systems have as their main functions to support the organization in their activities through hardware and /or software and to create the infrastructure in which those activities are going to be performed.

Human activity systems (HAS) are formed by all activities required by the system to fulfill the goals (Banathy, 2004)(Bertalanffy J. &., 2008) . It‘s main function is to create the structure of what is required for the organization.

Social systems are ―the conjunction of living components, their interactions, interconnections and relations among them, as well as the interactions with the environment and with the system‘s structure characterized by a specific organization‖ (Bertalanffy J. &., 2008)

 As the final component of a technorganic system, humans are the people in charge of executing the activities (established in HAS) and making decisions about the infrastructure (technological system) and the structure (HAS) taken as the frame of the culture of the organization (social system).

Figure 2.2 presents the connections among Technological, Human Activity and Human Systems. In this figure, as is any system, feedback is represented by dotted lines. It also shows how the culture becomes the context in which the decisions are made, and the activities and technology are selected and performed.

The concept of technorganic systems is to describe and understand that humans support the creation and improvement of technological implements in order to facilitate the execution of activities within the system. It is also important to consider that technological implements facilitate the augmentation of social networks and the way the organization culture is understood.

Figure 1.2 Conceptualization of business organization as technorganic system [Adaptation of exhibit 2 from (Bertalanffy J. &., 2008)]

The relevance of technorganic systems, in this research, is to understand how a performance measurement indicator could be integrated in a control system to give statistical follow up to continuous processes for trended systems.

1.2.5

Trended Systems

In section 2.2.3 it was shown that living systems have inherent growth (increasing behavior) or decline (decreasing behavior). Business organizations as any living system generally present a natural growth through time.

Organizations are meant to have certain growth, which can be designed, given by the environment situations or defined by a benchmark with similar systems. If it is the designed growth case, the organization defines some metrics and strategies that allow the company to achieve the designed goal. In this case it is important to have a tool that follows the trend and helps on deciding if this goal is been achieved.

On other occasions, when a plethora of factors is involved, the environment gives the growth trend and historical data that should be used to define the trend used to evaluate if there is an anomalous behavior.

This is the case in most

economy indexes, such as GDP (Gross Domestic Product) or GNP (Gross National Product).

Finally, the growth trend could be defined by a benchmark with similar systems, in this case competitors market share or the knowledge gained from past analysis are some of the ways to set the trend and with it, evaluate if the behavior is not the usual.

When the behavior is anomalous or not usual, it is time to define corrective actions. Actual statistical tools are based on assumptions of normality, non-trend (non-zero slope) and non-correlated relationship. These assumptions are rarely fulfilled in the practical environment. Thus, an alternative should be organized in order to be able to make decisions based on statistical tools.