The quest of meaning coincides with the search for answering the four essential questions raised by Immanuel Kant (1724-1804) in course of the European enlightenment:
On the previous pages of this page sequence, we addressed already aspects of the first three questions briefly, or sometimes with a certain level of depth. For a comprehensive coverage of our current subject, let us summarise and integrate the main findings at first. We start with a discussion of the first question and the specific human intellectual capabilities. The next two questions are associated with the intelligibility of reality in general.
The main focus of the content below lies in the ethical implications of the fourth question. It is not the attention here to raise universal ethical principles. Preferably, the ethics of systems engineering must be discussed in the particular application specific context. The way humans identify their needs, how needs turn into motivation, and how motivation leads to action are as well common enablers as common constraints for ethical behaviours. Thus, we will concentrate on the cognitive capabilities controlling human action.
As this is the last page of this website’s initial page sequence, some overall conclusions are drawn finally. Based on the systems engineering context as considered by the initial page sequence, the further content of the website is dedicated to the corresponding Theory of Systemgestaltung and provides records of the author’s lifetime contributions for advancing systems engineering theory founded deeply in applying systems engineering in innovative and challenging systems engineering projects successfully throughout his professional life.
Humans share the principle organic architecture of their nervous system at least with all other vertebrates. As evolution follows the mutual principles form follows function and function follows form, the similarities of organic structures support similarities of resulting functions. What is proven for simpler organic functions in many instances most likely applies to complex brain functions as well. It is further reasonable that with increasing brain complexity new complex functions emerge. On this basis, it is possible to investigate the evolution of nervous systems regarding their functional impact although we are far from understanding complex brains in detail.
Brains operate basically by perceiving concrete scenarios, analysing its meaning and concluding appropriate actions, or in other words: Brains perform systems thinking. By their actions, individuals shape their living environments, many times accidentally, but sometimes also intentionally, e.g. they perform systems engineering. This includes the production of tools enabling otherwise impossible goal achievements. New inventions spread by imitation, occasionally including continuous improvement of tools and operation techniques by other individuals.
Humans surpass other species due to the capability of using argumentative language. It is the current view of leading anthropologists including Michael Tomasello that argumentative language may be the sole but is at least the main feature constituting today’s human dominance in the biosphere. Argumentative language allows time-logical explanations for understanding scenarios in the sense David Hume (1711-1776) has defined causality. In addition to imitation, the dissemination of inventions is supported by argumentative language for motivation and explanation. Overall, argumentative language improves social interactions and enables a high variability of social behaviours and social relationships beyond other genetic dispositions determining hierarchical dominance.
Argumentative language allows the generation of theories about phenomena beyond the capabilities of human senses. These theories provide forward and backward translations assisting in inventing and applying new technologies. Kant’s question two – What can I know? – and three – What may I hope? – together cover two concerns: First, is the whole real world intelligible by human invented theories? Second, is there a single universal theory integrating all other theories and capturing all phenomena of the real world at once?
There is significant evidence that both claims are deniable with some evidence provided already by previous considerations of this page sequence. It is worth to illustrate the reasoning in condensed form. First, we will turn to two examples from physics. We will continue with summarising the limitations of strict logical formal languages. Finally, we extend our considerations to natural languages with their nearly unbounded semantical complexity.
Is time continuous or quantised? This question is undecidable. All measurements of physical phenomena rely themselves on physical phenomena with quantum leaps as the lowest resolution known. According to basic physical theory, quantum leaps taking place in infinitesimal time would require unlimited power what would support a claim for continuous time, respectively the possibility of higher time resolutions than measurable. On the other hand, we do not even know, if the concept of time could be reasonable without a physical world at all. Paradoxes like this point us to the limits of acquirable knowledge and let raise doubts regarding the universality of theories and pure reductionistic world views.
The detection of quants revived Gottfried Wilhelm Leibniz’ (1646-1716) hypothesis of monades in the sense that all worldly phenomena are caused by quants, their states, and their state changes. Logically, this hypothesis is easily validated: If quants are the unique smallest building blocks of reality, then the whole physical and imaginable world is made of quants. Just one unmentioned contextual detail is debatable: the role of the human observer.
We have little reason to doubt the existence of a unique and universal reality. All alternatives result in flavours of solipsism assuming reality as a mere construct of an individual intellect or a kind of super-intellect. Solipsism does not lead to any epistemological progress. For the human observer, the universality claim is dependent on the most advanced human cognitive capabilities, e.g. the availability of argumentative language. Is argumentative language fully suited to provide unambiguous translations between theories in all directions without information losses, and what would be the character of unambiguous translations? The latter question may be simply answered claiming unambiguous translations must be reasonable. In our discussion, we set reasonability equal to the causality criteria according to David Hume’s definition.
As an example for translations between theories, we take again Ludwig Boltzmann’s (1844-1906) theorem linking classical mechanics and statistical mechanics, e.g. how the energy state of individual molecules in a gas volume are related to pressure and temperature of the whole gas volume. For the translation from classical mechanics to statistical mechanics, the translation works under two conditions: either we assume that all molecules share the same energy state, or we identify the energy state of all molecules. The first condition is unrealistic as the occurrence probability of the condition lies in the magnitude of a once-in-a-universe event. Practically, we cannot conclude the features of the whole from the energy state of a single molecule. With respect to the second condition, the identification of the energy state of every molecule is unfeasible. Due to physical interferences, measurements of the energy state of every molecule would result in massive, incalculable distortions of the temperature and pressure of the complete gas volume. Nevertheless, in theory an unambiguous translation works without information loss. This does not hold for the opposite direction. Only statistical statements on the energy state of a particular molecule may be derived without considering the actual trajectory and past collisions with other molecules of the particular molecule. In general, the example illustrates the limitations of reductionistic world views. The emergent properties of the whole – in our example temperature and pressure – may be determined from the parts if the existence of those features is known upfront. Potentially, further emergent features of the whole may come as a surprise. In the opposite direction, the features of the parts cannot be deduced from the whole without information losses. These findings set limits to claims for the unique and universal intelligibility of reality.
Now the reader may be a bit puzzled about associating a physical law expressed in mathematical formula with argumentative language. The reason and the validity of this move may become clear below. We go even a step further by interpreting arithmetic as a strict logical formal language for investigating the limits of logic and causality. In their Principia Mathematica, Alfred North Whitehead (1861-1947) and Bertrand Russell (1872-1970) define arithmetic based on pure logical axioms. The first surprise is provided by the existence of prime numbers. No mathematical formula determining the sequence for the occurrence of prime numbers exists. Their occurrence is arbitrary. We must conclude that even strictest logical rules may lead to disorder. Kurt Gödel used prime numbers to express basic arithmetic symbols, e.g. definitions and operators. Then, the prime factorisation of other numbers may be used to express arithmetic theorems in arithmetic itself. For some hypothetical theorems, their validity may be proven within arithmetic, for others that they are invalid. In addition, hypothetical theorems are proposed arithmetic can neither prove that they are true or false. Kurt Gödel’s undecidable theorems may be generalised as follows: In any strict logical formal language issues and questions may be raised that cannot be solved within the scope of the particular language.
For natural languages, Juri Lotman (1922-1993) has coined the term semiosphere. In analogy to the term biosphere as the world of biology, the semiosphere denotes the world of language. He uses the term recursively like we use the term system. A semiosphere may contain other semiospheres like the family of Indo-European languages, dialects, discipline specific languages and so forth. Principally, research on the semiosphere has concluded the same results as the scientific theorists Thomas Kuhn (1922-1996) and Imre Lakatos (1922-1974) have concluded on the sociology of science. Thomas Kuhn talks about scientific paradigms and Imre Lakatos about research programmes. Briefly summarised, all talk about the life cycles of languages. Languages are initially formed to serve particular purposes, evolve extending their grammar – e.g syntax and semantics –, and reach out for generalisation. They become fuzzy and challenged at the periphery. Their owners and supporters start fighting against the periphery for defending the paradigm. Paradigm changes happen usually when someone close to the centre of the semiosphere adopts the concerns of the periphery. This narrative allows manifold interpretations and applications. For our subject, we can learn how we overcome the limitations of strict logical formal languages: We just invent new language! Without going into details here, this happens always when we engineer innovative complex systems.
Our actions depend on our perceptions. Behaviourism assumed behaviour is to be explained by the perceptions of the external world exclusively. Consequently, all living creatures including humans would operate as some sort of deterministic automata. Henry Maslow (1908-1970) opposed such radicalism emphasising human individuality: Humans act according to their needs. He also claimed a pyramid of needs. A particular need drives human action when needs on lower levels become satisfied.
In the context of the human capability for using argumentative language and the corresponding richness and variability of social behaviours, his findings support a view that body state needs have precedence over social needs – a statement compatible with the evolutionary fact that argumentative language resides cognitively on top of all other cognitive capabilities inherited from the brain architecture of other vertebrates in the course of evolution. Consequently, precarious living conditions leaving basic body state needs unsatisfied limit the unfolding of material growth and societal progress.
Our species emerged from earlier hominids more than 200 000 years ago. We do not know to what extent our evolutionary ancestors had developed argumentative language already. Our species possessed argumentative language and the corresponding social capabilities up from the beginning. There is no reason that cognitive dispositions have changed since then. What has changed over time was the climate on Earth. Around 200 000 years ago the world became significantly colder hampering the opportunities for extending human settlements. Since then, two major interglacial periods are identifiable, the first one about 130 000 years ago. The second began less than 20 000 years ago. Sea levels rose approximately linearly by 120 meters within less than 10 000 years.
As commonly known, humans emerged in Africa. Coincidently, Africa consists mainly of lot of the oldest land masses. So-called cratons have not altered much by the geological forces vulcanism and subduction. Dominant is the third geological force shaping the Earth’ surface: erosion. Rich deposits of minerals and metal ores are located deep under the surface. This is one potential reason why humans in Africa had not developed metallurgy earlier. The fertility of human habitats allowed a reasonable living and thanks to the social capabilities of humans they not only survived but were able to increase human population and to settle into regions with harsher living conditions. This all changed with the end of the ice age. Former habitats became arid land. People migrated into remaining niches, for example to the Nile valley and coastal regions in the northwest of Africa when we talk about former human populations of the Sahara region, or migrated to latitudes further north where living conditions were improving due to climatic change. There they found soil fertilised by abrasions from glacier movements providing agricultural conditions much better as known from their earlier habitats, and metal ores close to the surface. The better fertility of the soil enabled permanent settlements. Humans entered an accelerated path of growth, and invented civilisation. The invention and sustenance of irrigation systems led to societal structures with an unprecedented level of workshare, specialisation, and standardisation far beyond the former social practices.
Please, don’t read the story of the last paragraph as a strong causal explanation of human prehistory and history. There are myriads of other traits and interdependencies in addition. All attempts to reduce the complexity of human prehistory and history in one paragraph cannot satisfy scientific standards at all. The paragraph just collects some evidence for three hypotheses: First, the neolithic revolution was no revolution in the sense we use this term in other historic instances. Agriculture developed most likely over time periods exceeding the duration of historic times by far. Second, human cognitive and social capabilities have not changed with the emergence of civilisations. Considering the comparably short duration of historic times, we may talk about progress in the sense of a cultural evolution but not about progress in the sense of a biological evolution. Third, our cognitive and social capabilities may be not fully adopted to cope with the complexity of the societal architectures we create. Advanced societies may develop societal architectures hardly to be transformed in cases of massive internal and external threats. Specialisation inherits a risk for reductionistic views and may have contra productive impacts when more holistic views are required to identify strategies and solutions to cope with those threats. Sound processes, methods, and tools for multidisciplinary cooperation are an important prerequisite for successful societal transformations.
For this section’s subject – motivation and action –, the considerations above provide some hints on a reasonable scope of our investigations. We start with what human needs are and how needs drive action. Then we turn to the relations between individual needs and the behaviour of social groups analysing major social motivation systems. We continue with discussing the characteristics of social motivation systems in a societal context. We close with a survey on the dynamics of motivation cycles within individuals and social groups.
Humans have many needs at once. Some are concerned with maintaining existential living conditions for survival or a more comfortable state of well-being, others with desires and hopes regarding an anticipated future state of well-being. The grade of need satisfaction may be partitioned in four categories: unsatisfied, precariously satisfied, comfortably satisfied, and over-satisfied.
Needs are unsatisfied when there is a desire for a change from the present state to something better. They have the potential to become action-driving when other high-priority needs are satisfied and opportunities for their fulfilment arise. Precariously satisfied needs are satisfied but remain action-driving due to fears to fall back into an unsatisfied state again. The priority to invest further in precariously satisfied needs may even exceed the priority allocated to unsatisfied needs. When needs are comfortably satisfied, the investment for need satisfaction falls to a maintenance level, or below in case that satisfaction of the need is felt as something given by default. Over-satisfied needs may become a major concern when they remain action-driving without reducing the priority to a maintenance level. Then, continuing high investments in their satisfaction do not improve the well-being further. Over-satisfied needs come along with greedy and addictive behaviours.
Greed and addiction are a threat to every social community. This sheds a new light on the history of civilisations. The anthropologist David Graeber (1961-2020) and the archaeologist David Wengrow provide comprehensive evidence that human communities of the past constituted themselves by choice. Of course, prehistory was not free of fraud, robbery, and violence but patriarchal government executing authoritarian power may have been the exception among a huge variety of other social leadership arrangements. For executing power projections against the will of people successfully, rich resources are required to force and to sustain authority. More likely, it was widely a free choice of people to cooperate and to found civilisations due to expectations to satisfy individual and commonly shared needs.
Let us now consider the following statement: The agriculture production in Egypt achieved a surplus and then the Egyptians built pyramids. Due to the general characteristics of argumentative language and narratives, we are tempted to interpret the sentence in a way that economic profit from agriculture was achieved for the purpose of building pyramids. More convincingly, the increase of agricultural production by irrigation systems had the sole purpose to feed a growing population. When societal leaders recognised that agricultural overproduction led to greed and addiction, they feared the detrimental impact on societal stability and invented new transcendental needs to consume the surplus. The solution to move gigantic amounts of soil, clay, or stone to construct monuments seems to have been a standard solution in early civilisations around the world.
It is a common pattern that human cultures do not develop following a great plan but more on a trial-and-error basis. Whenever new unknown threats are identified new societal needs and solutions must be developed for survival. If a civilisation is not able anymore to adopt to challenges, it is doomed to collapse. In other words, civilisations need multidisciplinary systems engineering. Without setting and agreeing on feasible societal goals and breaking them down consecutively in feasible objectives for all parts of society, all institutions of a society may try their best defining objectives on their own. Then, resulting actions are likely biased by defending the institution’s survival. Rampant bureaucracy may lead to collateral damages. The capability to alter societal architectures appropriately is hampered or may be lost totally.
Before civilisations have emerged, humans lived in tiny bands. Internally, these bands cooperated for ensuring survival and well-being of its members. Like with other mammals living in family associations, a network of trust balanced the needs of individuals with the needs of the whole social group dynamically. New group members were born, and old ones died. In order to avoid inbreeding depressions, people from other bands joined the community while others left for following other bands. Due to argumentative language and corresponding advanced social capabilities, it is reasonable to assume that social arrangements varied far more between human bands than observable in today’s family associations of apes. Probably, humans migrating between bands had a choice to select which band to join considering the character of social arrangements within a band. This is the way of living evolution has us designed for.
Humans have a long tradition to balance the needs of individual members with the needs of the group as a whole. From the perspective of an individual, role and status within the group is dependent on how the individual balances personal needs with group needs for sustaining personal well-being. In motivation research, it is talked about two corresponding motivation systems: self-efficacy and belongingness.
For individuals, belongingness is vital for survival and well-being. For the most time, prehistoric tiny bands lived and operated autonomously from other groups. A suitable level of group coherence was needed to ensure survival and well-being of the group and its individual members. The need for belongingness produces various behavioural patterns in dependence of the living conditions as perceived by individual group members and as construed by the group as a whole.
In precarious group-internal or external living conditions, individual group members tend to demonstrate their belongingness to the group in an explicit manner. Criteria characterising good and valuable members of the group become a major part of the discourse. The boundaries defining group membership are tightened. Dissenting opinions and actions are unwelcomed, if not penalised. Even when living conditions are improving again, the derived standards for group coherence are carved into the common memory of the group deeply.
A social group in stable living conditions has the chance to prosper when it generates a limited operational surplus to bolster future temporary shortages and to invest in continuous operational improvements. Then, the group’s coherence among its members remains high. Individual members invest not only their physical but also their cognitive resources to increase the sustainability of the group’s existence and well-being. The group supports investments in alternative and innovative solutions widening the group’s range of actual and potential operations.
When a group’s operations generate a large surplus continuously, the group may enter a path of growth. Overall, group coherence is weakened as individuals have more personal freedom to invest in their own interests. This widens specialisation paths from just a matter of status and talent to a matter of knowledge and personal experience in addition. As a long-term consequence, workshare may become institutionalised. At the end of the Ice Age, humans entered such a path of growth all over the world seeding the emergence of civilisations.
We like to work on challenging tasks. When we are aware that we are on a road to success, we likely intensify our engagement. The psychologist Mihaly Csikszentmihalyi has coined the term flow for a state we drop thinking on other issues and needs in an oblivious way as the maximum achievable level of satisfaction regarding the need for self-efficacy. In contrast, we feel uneasy swiftly about working on unchallenging tasks. They may be anticipated as tedious and boring.
In itself, self-efficacy has one critical aspect. Faced with overwhelming threats, we may feel no hope to cope with them successfully. Likely, we start to hesitate and to follow avoidance strategies. If avoidance is impossible, humans tend to reconceptualise the situation. The original threat is substituted by a problem to be worked on for which we assume solubility. Responsibility for coping with the original threat is transferred to others with or without excluding own contributions.
In social psychology, the research on group dynamics focuses on how groups balance the needs for self-efficacy and belongingness. Group dynamics assumes all behaviours within the group are instrumental to satisfy needs on this bipolar axis. This utilitarian approach is well suited for comparative behavioural studies comparing behaviours of family associations of apes with human groups. In this view, argumentative language is employed as explanation for the advanced social capabilities of humans. Another important dimension of argumentative language remains left out: Humans are in the quest of meaning.
The need for living in a meaningful world is the third essential social motivation system next to self-efficacy and belongingness. Unfortunately, in motivation psychology little research is spent on the need for living in a meaningful world today. Some research on human terror management comes close to it but does not investigate wider implications so far. Better traces can be found in communication psychology. Ruth Cohn (1912-2010) proposed a psychological communication model denominated as Theme-Centred Interaction. With respect to her own fate – emigrating as young Jewish psychologist from Berlin in 1933, she concentrated her further research on why culturally advanced communities may turn into barbarian behaviours. Her answer is: The whole societal discourse is limited to a choice between individualism and community affiliation. All other subjects are mapped just to this bipolarity. The actual content and implications of the actual subjects are not considered further anymore.
Let us start our considerations on the need for living in a meaningful world with Socrates’ paradoxical truth: I know that I know nothing. All our thinking starts with inductive thinking when we spend our attention on unexpected phenomena. Then, we start raising why-questions. With every answer found, a bunch of further why-questions arise. As we all know from endless sessions surfing the Internet, we likely end up with why-questions for which we have lost the connection to the initial why-question. When we have generated theories from inductive thinking, we also may employ deductive thinking. However, all deductive thinking is bounded by the limits of intelligibility discussed above. In the end, we need to start with inductive thinking again.
Alternatively, we could follow Ludwig Wittgenstein’s (1889-1951) last clause of the Tractatus Logico-Philosophicus published in 1922: “Whereof one cannot speak, thereof one must be silent.” But this is definitely not what humans tend to do. On the contrary, humans are keen to search for answers by inventing new language. Imagine our prehistoric ancestors sitting around a fireplace under starry skies during long nights. Inevitably, they start to tell stories to discuss their experiences. Later, they continue to invent transcendental ideas about cosmology and other unexplainable phenomena including killing and death. These origins of religious thoughts contributed to the coherence within the band. Common views and shared beliefs increased performance and success of goal-oriented common actions.
What this all has to do with systems engineering? Let us expand the situation acting as process responsible for a large-scale high-integrity technical system in crisis mentioned at the end of our discussion on High-Integrity Technical Systems. Applying the process implementation principles stated there, the disoriented team in charge became a well-performing group being able to tackle issues successfully that were assumed to be unsolvable without major budget increases and massive programme milestone delays. Everything was fine, but one dissonance remained: Team members felt widely uneasy with the process solution and the reasoning behind. This contrasted sharply with the behavioural changes within the team. All tensions, conflicts, and unhappiness typical for a blame culture were superseded by supportive behaviours to discuss issues with far less emotion by just taking reality seriously, and to work on successful solutions accepting mutually the potential contributions and limitations of individual disciplines. In general, the well-being of the team and most of its members was enhanced significantly.
Obviously, there were forces effective beyond the reasoning to justify the process changes by flow-oriented product data generation. The idea was that these forces must have a direct impact on the well-being of the team and its members with the implemented process changes playing just an instrumental role.
The innovative development task attracted engineers and scientists from various disciplines. Different professional affiliations and team members from several national origins increased diversity. For good reasons, it may be assumed that team members were convinced to work on a meaningful task. However, throughout development the team was faced with unforeseen challenges ignored by a milestone driven higher level management. Creative ideas to cope with the identified issues were denied by management. Convinced about their solutions, individual team members started heroic, partially successful actions for recovery, but felt misunderstood and blocked. In consequence, their commitment to the team faded. Overall, team members had lost the faith in the project’s success over time.
From the viewpoint of social motivation systems, the analysis of the scenario is reasonable simple. The level of satisfaction regarding meaningfulness among team members was high, but the needs regarding self-efficacy and belongingness remained widely unsatisfied. The process changes resulted in an enhanced traceability of the contributions of individual team members to the product. For team members, meaningfulness and self-efficacy became visibly connected. The team as a whole accepted that not individual heroism but only their cooperation would save project success increasing the feeling of belongingness.
For self-regulation, everyone is striving for a balance regarding the three social motivation systems. The weighting in between is dependent on general personal preferences, the concrete subject, and the actual situational context. Just concentrating on a single social motivation system leads to pathological behaviours. Reducing one-self’s needs to a matter of belongingness is far from living a happy and self-determined life. Selfishness ignores essential human social dependencies and is usually rejected by others. Religious or ideological fanatism has a high potential to violate humanity considering – on a large scale – for example Mao’s Great Leap with millions of casualties. In combination with appealing to the belongingness of all others despite all actual diversity, religious or ideological fanatism may lead to civilisational catastrophes like National Socialism reminding World War II and the annihilation of Jews and other minorities. Apart from such extremes, human groups with members personally known to each other manage their internal affairs quite well balancing the survival and well-being of the group and its personal members.
Our evolutionary heritage to cooperate in tiny bands comes under scrutiny under civilisational settings characterised by population growth, workshare, and specialisation. The universal responsibility of the particular tiny band for the survival and well-being of its members is split to various differentiated societal organisations. Family associations not too different from what is observable from family associations of primates are in charge of bringing up children and providing basic social security. Most other economic aspects are assigned to various types of guilds concerned with maintaining and advancing knowledge and skills in specialised areas. Overarching governmental layers are needed for overall planning and bookkeeping. For understanding the civilisational importance of systems engineering, a few principal tendencies in the evolution of guilds and governmental layers provide supportive evidence.
The governmental layer evolved most likely smoothly from the need of planning common actions among societal groups. Over time specific societal skills and knowledge emerged. Bookkeeping of provided services led to the invention of currencies and script. The advantages of sharing common views and following common rules caused the emergence of institutionalised religions. All these inventions shifted power to people practicing and acquiring governmental skills and knowledge. However, at this stage governments executed more soft power. The invention of metallurgy to manufacture metal tools became a game changer. Metal production is a labour and resource consuming affair. Metals maintain their value over long time periods compared with the durability of agricultural goods. Possession and control of metal enabled aggressive power projections for capturing governmental leadership.
Initially, guilds emerged around particular products and services. Increasing demand provided opportunities to increase employment. Accumulating experience and continuous improvement drove specialisation further resulting in staggered supply chains for the particular product or service eventually. Progresses in standardisation allowed the transition to economic networks of sometimes cooperating and sometimes competing enterprises.
In growing economic networks, organisational units are more and more reduced to their functional contributions to products and services. In other words, purpose considerations located on the meaningful world axis prevail. Regarding inter-organisational relations, self-efficacy and belongingness are relevant only for those involved in inter-organisational communication. Other members of the organisational unit are widely isolated from organisational units representing customers of their product and services, or suppliers. They strive for satisfaction with respect to their needs on self-efficacy and belongingness within the organisational unit primarily. The resulting intra-organisational divide may lead to internal tensions, especially when the second fraction outnumbers the first. Then, actual customer demands may be more and more replaced by internal views as the second fraction moves towards a balance among the three social motivation systems with allocating higher priorities to group internal considerations. This may be tolerable in stable, highly standardised markets since the particular economic sector may have evolved over long time periods. In case of innovations or other disruptions, missing capabilities to give actual demands adequate priority may hamper successful transitions to changing economic scenarios. For this reason, organisational units are best advised to acquire and maintain always a comprehensive understanding of the scenarios their products and services contribute to e.g. follow a sound systems engineering approach.
Typically, mature civilisations exist in a field of tensions between economic complexity and central governmental power. Central governments set societal goals while enterprises are concerned with enhancing their products and services demanding a stable economic and political environment. The flexibility of social arrangements is especially challenged in two cases.
First, human genius leads to innovative technologies challenging societal architectures. Concerted economic and governmental actions are required for civilisational stability and societal enhancements. Joseph Schumpeter (1883-1990) coined the phrase creative destruction for such scenarios of technological and economic innovation. Second, when societies approach economic resource limits civilisational rearrangements are required. Principally, solution strategies may contain solution elements of three kinds: exploring more resources of the same kind, searching for alternative resources reducing the demand of the original resource to a sustainable level, and adjusting societal goals accordingly.
When the Club of Rome published their study on the Limits of Growth in 1972, they focussed on the limitation of natural resources. The mid-term reaction was to intensify the search for geological deposits of the same natural resources. In parallel, humans learnt about environmental pollution with counterproductive consequences for human living conditions. Today’s climate crises caused by the dominance of human actions on the Earth is widely reduced to an issue of an increasing concentration of carbon dioxide in the atmosphere. In consequence carbon-mission-free technologies are promoted with great emphasis. For two reasons, this sound not only a bit strange:
In history, approaches to counteract resource constraints by exploring further resources have been preferred usually. They are ambivalent in case of getting close to global resource limits. In our times, it means trying to counteract the adverse impacts of the human dominance on Earth by extending human dominance even further. They may contribute to augment some adverse impacts in the peaks but are not suited as solution for the root cause. The adverse impacts of the human dominance on Earth to sustain human friendly living conditions demand a significant reduction of the human dominance on Earth to a level that biospheric and geological processes are able to support civilisational activities and to compensate civilisational impacts quantitatively. Without a serious debate about high level societal goals advances in this direction will be pointless.
The reluctance to avoid alterations of societal goals is understandable due to fears of uncertainty. In mature civilisations, there is no single individual or organisational body able to master the organisational and functional complexity in all detail. Goals set by pressure or requiring to waive the current living comfort will face a lot of opposition.
Motivation psychology provides some hints how societal goal setting may work. A distinction between self-defined and foreign goals is linked to the terms intrinsic and extrinsic motivation. Self-defined goals lead to intrinsic motivation. Achieving commitment to foreign goals is dependent on extrinsic motivation. Fortunately, personal goals are not invariant. People adopt goals, if they expect better or new kinds of satisfaction. Thus, foreign goals may be accepted and after time indistinguishable from self-defined goals regarding resulting motivational levels. Consequently, the issue whether a mature civilisation copes successfully with essential threats, or collapses, is dependent on the art how to define goals and how to achieve goal acceptance.
Defining and agreeing societal goals is usually a cumbersome and sometimes painful undertaking, especially when societal architectures must be altered. To drive societal goals just from utopian visions is not recommendable. Before defining societal goals, the current status and the problems to be solved need to be understood accurately and comprehensively. At best, all stakeholders and contributors should be involved in the analysis. For this reason, open societies perform principally better compared to organisations with authoritarian leadership. A reasonable starting point for every scenario analysis are the following four questions to be answered by stakeholders and contributors:
Analyses of this kind mark the entry to sound systems engineering approaches. A comprehensive understanding of scenarios allows the derivation of societal goals. In a next step, solution alternatives to achieve these societal goals may be derived accompanied by risk registers for identifying risks and controlling risks. It may take several iterations to mature solution alternatives to a level before a sound selection of the preferred solution alternative may be achievable. Afterwards the development of solution elements may be commenced followed by implementing the solution in the real world.
In individual psychology, Heinz Heckhausen (1926-1988) and Peter Gollwitzer developed the Rubicon model of action phases to describe the dynamics of motivation cycles. In the first stage, a need to be satisfied is selected in analogy to crossing the Rubicon as a point of no return. The second stage is concerned with seeking opportunities to satisfy the need. The third stage comprises the actions to satisfy the need. In the final stage, the outcomes are evaluated.
Let us now jump to the field of statistical process control. Walter E. Shewhart (1892-1967) and William E. Demings (1900-1993) generated a model for continuous improvement. It is defined as a closed-loop model with four phases for planning, doing, checking, and action widely known as PDCA cycle. When we cut the continuous improvement cycle not before P but before A, it becomes an APDC cycle fully congruent with the Rubicon model of action phases.
The main difference between the two models lies in the fact that the Rubicon model of action phases is comprehended as a logical sequence while the PDCA cycle is defined as a closed-loop model. The closed-loop model is in so far more realistic as it may be easily interpreted in a way to cope with the continuous switching of individuals between an action driven attitude and an evaluation driven attitude. The Rubicon model of action phases is in itself a bit too schematic to postpone all evaluation after all actions to satisfy the need are performed. In contrast, the PDCA cycle takes better into account that self-reflective humans tend to switch between action driven attitude and evaluation driven attitude all the time when deemed to do so. They also adopt their goals and actions continuously on the basis of their evaluations.
The equivalence of both models is a good example how latent issues may raise the attention of various scientific disciplines independently from each other, nearly concurrently in this case. Fortunately, the resulting models map easily complementing each other without discrepancies. Nevertheless, there is one essential difference. In motivation psychology, the aim was to explain psychological phenomena. In statistical process control, the psychological insight is a byproduct of minimising deviations in production by adequate process provisions. The Rubicon model of action phases is the response to why-questions while the PDCA cycle comes as a procedure in response to how-questions. In consequence, the PDCA cycle seems to root less in scientific reasoning. It may be just subsumed as personal view of experienced practitioners. The reasoning within this paragraph justifies the approach on this website further to consequently substantiate the responses to how-questions by responses to corresponding why-questions.
The dynamics of motivation cycles challenge systems engineering terminology with respect to the central term requirement as we may conclude:
Marketing terminology recognises these relations in adequate detail. Quality management terminology subsumes all aspects under a rather general requirement definition that cannot be implemented in systems engineering operationally. Instead, systems engineering terminology comes with a requirement definition constricting on the agreement aspect. In case of development-on-demand projects, this choice is plausible. When other market driven business models apply, it creates difficulties.
A further difference between the Rubicon model of action phases and the PDCA cycle is concerned with different basic assumptions. The Rubicon model of action phases is clearly directed to motivation cycles within individuals. The background of the PDCA cycle is continuous improvement performed by social groups in production environments. For claiming full equivalence, it is important to investigate how motivation cycles within individuals can be translated to social group dynamics.
Bruce W. Tuckman (1938-2016) published in 1965 a meta study on social psychological experiments titled “Development Sequence in Small Groups”. According to his findings, the setup of experiments in social psychology follows common characteristics: An ad-hoc group of people – in most cases students – gets a task to be solved more or less creatively. In such scenarios, the experiments show common behavioural patterns. Initially, the participants introduce themselves to each other and check out the atmosphere within the group. Bruce Tuckman denoted this phase as forming. On this basis, participants present their views and ideas. Lively and controverse discussions follow usually so that he called this the storming phase. In the storming phase, a group may break apart, if controversies cannot be moderated. If this challenge is passed successfully, the group will come to terms agreeing on an approach for solving the given task. Consequently, this phase is called norming. Afterwards – in the performing phase – the group is working on the solution coordinating the activities and contributions of group members.
Comparing Bruce Tuckman’s model of group dynamics with the Rubicon model of action phases, it is obvious that forming, storming, and norming are group specific activities mappable to the first stage of the Rubicon model of action phases. All other stages after crossing the Rubicon are subsumed as performing in group dynamics.
If new issues arise in the performing phase, group members will act individually reflecting their position and treatment within the group. They may stay engaged or may even intensify their engagement, if they feel committed to the solution approach and the group. In all other cases, engagement will fade to more passive behaviours down to inactivity. Some group members may clearly express their discontent, leave the group, or show even obstructive behaviours.
Clashes in the performing phase can be most likely traced back to causes induced much earlier. Incorrect implementation of earlier phases has adverse impacts on the group’s success solving the given task. As longer as issues remain undetected as higher the adverse consequences will become in tendency. There is a causal cascade starting with not generating acceptable levels of mutual trust in the forming phase. This hampers the storming phase by deficiencies in exploiting knowledge and experience of all group members. If group members feel unheard in the storming phase, their commitment to group decisions in the norming phase will be half-heartedly, or even dissenting. All accumulated frustration will break through when a crisis cumulates in the performing phase.
In systems engineering, knowledge of the described group dynamics pathologies is of outmost importance. With increasing levels of innovation, it is foreseeable that matters will not run as initially assumed and agreed. The forming of multidisciplinary teams is a major issue. Each discipline comes with its own body of knowledge expressed in discipline specific language. Those representing their discipline need the open-mindedness to accept that various narrations may be told about the same validated observations and facts. It is supportive, if they are trained and experienced in systems engineering principles already. With these prerequisites, storming may start in a good mood, but majority votes may be not decisive in case of open issues understood only by a minority of disciplines or even just a single discipline. Discussions should therefore be exhaustive. In the norming phase, approval from all disciplines is mandatory to achieve a commitment level sustainable during the performing phase without loosing the commitment of any discipline.
There is one further topic left. Individuals may switch between action driven and evaluation driven attitudes arbitrarily whenever felt necessary. In groups, action driven attitudes are dominant during the performing phase. When somebody is engaged in driving group actions forward, the arbitrary switching into evaluation driven attitudes by others is predominantly anticipated as annoying disturbance. This situation is not addressed by Bruce Tuckman’s group dynamics model.
An essential difference exists between the setup of social-psychological experiments and real systems engineering projects. In social-psychological experiments, the task is given upfront to the whole group at once. In reality, it is a creative act of an individual to pay attention to a specific issue unnoticed before by everybody. Provisions are required for encouraging problem reporting and for taking reported issues seriously by the group. There are good reasons to define problem reporting as a formal process with written records to counteract attempts to suppress them. In addition, a rule needs to be enforced that individuals reporting issues are not penalised but welcomed and appreciated independently from the final relevance of the report. Assessing the relevance of a problem report is a task for the whole group. It would be stupid to demand this from the individual raising the problem report starting with the fact that this person may not even possess all the necessary knowledge by herself or himself. It demands a group decision to rate the relevance and to agree on solution strategies as necessary.
The problem reporting and evaluation process described above instantiates a separate group dynamics cycle with storming and norming phases. If this difference between the group dynamics model and reality is not observed, groups may drive themselves in a deadlock when some group members feel still a need for a better understanding of the issue while others want to discuss solution alternatives already. Storming will be most effective and efficient when both aspects are considered separately.
Congratulations for approaching this concluding section after reading the five pages of this website’s initial page sequence. Each page is written to be understandable in isolation from the other pages and provides hopefully beneficial information for someone interested in systems engineering. Nevertheless, the page sequence follows a deliberate line of thoughts from clarifying basic systems engineering terms and concepts first.
Novices to and practitioners of systems engineering may profit directly from the concise recommendations for how to engineer high-integrity technical systems. However, experience has shown that readers may feel uneasy that applying just these four principles consequently for implementing systems engineering will make a difference and may even turn systems engineering projects in crises into successes. After reading systems engineering textbooks and standards you may have got reservations that the complexity of the subject and the intricacies of how systems engineering is presented cannot be reduced to just four practical implementation principles. I fully understand these concerns because I challenge the practicability of systems engineering textbooks and standards due to their illusionary assumptions that are even many times introduced silently instead of being stated explicitly. Compulsorily, omissions, incompleteness, weaknesses, and inconsistencies hamper the practical applicability of the provided instructions and recommendations.
Multidisciplinary systems engineering is an advanced civilisational activity essential for improving and sustaining mature societies and enterprises especially when existing societal or technical system architectures are threatened and demand alterations. Human cognitive and social capabilities need to be exploited up to their limits for leading systems engineering projects to success. For this reason, successful systems engineering as a primarily human endeavour requires a reasonable understanding of epistemological boundaries in addition to knowledge of solution specific technologies. Consequently, the further two pages concentrated on human cognitive and epistemological capabilities.
And now the caveat: The four principles are fairly straight and sound simple but implementing them is a rather complex and challenging undertaking. The good news is that this website provides further information on the Theory of Systemgestaltung. The Theory of Systemgestaltung is a flow-oriented implementation of systems engineering carefully designed not to jeopardise the four principles. Exploiting the narrative of Norbert Wiener’s general feedback theory, systems engineering is presented as a set of four basic systems engineering narrations. Each narration obeys causal principles allowing a direct time-logical implementation without getting tangled in circular dependencies. Together, they provide a comprehensive description of the intricacies of systems engineering enabling the successful evolution of High-Integrity Technical Systems. Please, turn to the Knowledge Category for further valuable information on the Art of Systemgestaltung that introduces the Theory of Systemgestaltung in general without becoming confused by or lost in detailed process requirements, data structures and fine-grained implementation hints.