2Science

I’ll get you all you wish and more, it’s true.

The task is light, yet light is heavy, too.

It lies already there, but how to reach it?

Aye, there’s the art, but where’s the man to teach it?

from: Faust, Second Part of the Tragedy by Johann Wolfgang von Goethe 1832 [1]

Science is the art of understanding the nature of reality. Yet, science is restricted to the respective conditions of the present state of that art.

In consequence, science is not just a description of real perceptions, which is mainly a cause for some irritation for people without scientific instruction. But science requires education, literally meaning guidance beyond the appearances. However, science does not include an understanding beyond reality, such as astrological constellations, religious convictions, or other supernatural concepts. And this is sometimes a delusion for people with personal faith in esoteric or magic apparitions.

The classical philosophers Plato and Aristotle already discerned two sources of scientific truth: true by fact and true by reason [16]. Kant concluded in his Critique of Pure Reason, that just one of those truths can never be true by itself: Factual observations are insignificant without reasonable definitions of human concepts, and reasonable thoughts are irrelevant without factual substance [18]. A simple perception of facts is not enough to be called scientific knowledge but is just an experience, and sophisticated reasoning is insufficient to be scientifically reliable but is only a scientifically arguable hypothesis. Similar to an innovation, not only reasonable ideas of the human mind are required but a durable verification by physical facts is also necessary.

Science itself can be regarded as the greatest innovation of humanity in general. Just take a look at its innovation characteristics as given in the first chapter of this book: It was intentionally instituted and has both incremental as well as radical impacts on prosperity and wealth; it shows evolutionary improvements within the framework of the appropriate theories, as well as revolutionary disruptions by change of those theories from time to time, as Kuhn showed in his book The Structure of Scientific Revolutions [19]. Reciprocally, innovations are based on scientific progress that enables new technologies. Thus, science and innovation are truly closely correlated terms.

The main difference is that science is about knowledge and innovation is about business. Surely, one may argue that science also needs business, and at times even a great deal of it. And conversely, business also needs knowledge, and ignorance of scientific premises is often one of the main causes economies fail. But this argumentation holds true for other terms as well: for instance, knowledge is power, as stated by Francis Bacon [20]—and time is money, as attributed to Benjamin Franklin [21]. Consequently, the power to save time links all of these aspects together and insinuates that they are almost all the same thing. This is why it may be going too far to equate science and innovation. However, it may be helpful to investigate similarities in order to transfer useful knowledge about science for the purpose of innovation management.

The traditional way of science is from facts to figures, that is, from factual physics to reasonable metaphysics, which literally means the nature behind the physical appearances. Actually, in nature no one can ever experience something like a mechanical force, an electrical charge, a chemical reaction of molecules, a mathematical integration of data, a complex in its psychological or therapeutic meaning, or a virus infection on a cellular scale. Changes in reality are the only things we can observe. And a metaphorical or metaphysical understanding of nature behind reality helps us to explain these changes. The traditional benefit of the scientific approach is to act appropriately—if the figure fits to the facts, that is.

Obviously, the way of innovation is the opposite, that is, from reasoned imagination to factual realization. This might be why it took so long for humanity to establish a general acceptance of this novel direction, as previously described about the origins of innovation. Only by a sufficient scientific knowledge of approved understanding can one begin to use this understanding to change the very nature of things through the introduction of technology. With only limited understanding, the chance of error and failure is generally much too large.

The title of this book can be either understood as innovations in science or the scientific methods for innovations. However, if we discard for a moment the idea of economic interests in genuine scientific work, there are no real—that is, economic— innovations to be expected from science. Yet, science has allocated an enormous inventory of methods that can be readily applied to bring about innovation.

More than 2,500 years elapsed between the earliest scientific discoveries and the first innovations in the professional significance of this book. The scientific understanding in the age of the classics—literally meaning the first level—can be useful for an understanding of the processes of innovations.

The origins of science emerged from the prehistoric times of humanity, when no scientific theories were available, yet. Only phenomena—which literally means “appearances”—were regarded as rules of nature and handed down as myths—which literally means tales. This mythological interpretation of earthly phenomena was then attributed to the activities of supernatural gods.

For example, in Greek mythology the messenger for divine law and decisions is Hermes and consequently hermeneutics in science means the interpretation of axiomatic prescriptions. With regard to innovations this aspect of science is still useful for describing, claiming, and defending a novel idea and its related patent, in order to obtain and maintain exclusivity for the marketing of an invention.

However, in connection with the rise of philosophy—literally meaning love of wisdom—it became imaginable that normal appearances rely on impersonal rules and on some hidden laws of nature. Thus, the quest for a natural phenomenon became merely an understanding of the principle behind the appearance—and no longer the acceptance of divine capriciousness.

At the beginning of this novel insight stands the reported exclamation of Archimedes Heureka—literally meaning: I have found out—when he discerned the principle of buoyancy in his bathtub. Therefore, in science the term “heuristics” stands for a very practical understanding of observations. In regard to innovations this aspect of science applies to the rather incremental progress in exploring and extending the impact of the present technology to an obvious improvement.

Thus, an analysis of the classics already permits us to link some scientific aspects to innovations. And again the interaction of facts and reason becomes evident: hermeneutic reasoning alone is worthless without any realistic impact, and heuristic progress by itself is futile without any ideas which can be reliably defended. The combination of these two aspects of scientific truth is probably so familiar to us that we imply understanding by mere observation, and we imagine realization by pure explanation. Only through a deeper investigation, for example, at court or in other disputable cases, does the proceeding distinguish more correctly whether a statement is due to a certain fact or just due to a general reasoning on the issue.

During the Renaissance these two aspects of science were slowly revived. The principle of induction improved heuristic understanding by the concept of systematic research. In his programmatic work Instauratio Magna the Lord Chancellor of England Sir Francis Bacon demanded a comprehensive investigation program and named some twenty laboratories, which he called chambers or houses, to discern all the secrets of the world within a period of some decades. Meanwhile, it has become clear that this approach was a huge underestimation of the effort and time needed. Yet, the concept of institutions dedicated to the synthesis of more reliable scientific expertise has become generally accepted.

The principle of deduction also improved the hermeneutic interpretation by methodic analysis. The French scientist René Descartes described in his work Discours de la Méthode a procedure of how to analyze—literally meaning disassemble— an accepted belief until elementary notions are obtained, which can be verified by facts. Meanwhile it has become clear that it sometimes takes more than a lifetime to discern even simple theoretical concepts, and even an enormous number of analytical steps by computer algorithms is sometimes not enough for that purpose. However, the concept of obligatory methods for more convincing scientific argumentation has been generally accepted.

Induction and deduction are still the fundaments of any scientific examination. And there is a never-ending dispute among scientists about which of the two builds the primary source of science. An understanding induced just from facts corresponds to the ideology of materialism, apparently without any theoretical ideas behind it. In science; this approach is also called empiricism. On the other hand, an understanding deduced just from theories corresponds to the ideology of idealism, relying in the end on some sort of religious dogma. In science this is also called rationalism.

Many scientists tend to turn away from any idealistic aspects in science. It is told that Albert Einstein should once have been confronted with the claim of a student at Princeton that his theory of relativity was merely contrived and had nothing in common with any realistic perception—and the student insisted that he himself believed only in notions that can be sensually experienced: seen, heard, tasted, touched, or experienced by any other human sense. Einstein should have been replied by simply asking the student to come forward and please make exactly this belief sensually perceptible to the others present. The lesson of this anecdote is that idealistic belief cannot be avoided in science, or, as Schopenhauer [22] stated: “Physics is unable to stand on its own feet, but needs some metaphysics on which to support itself, whatever noble pretending to be towards the latter.”

So far, the similarity of science and innovation seems clear. An innovation is deduced from rational arguments and ideas, yet has to be induced by facts, while at the same time only experiencing perceptible things will never lead to an innovation without some idealistic notion. The main activities in science are the generation, distribution, and application of knowledge, all of which are equally part of innovations. The main difference is that a scientist tries to find out about already existing things, starting with induction, whereas an innovator tries to create new things, and therefore has to begin with deduction. And this causes some difficulty, which will be explained in the following.

According to the canonical classification of science—literally meaning the guideline classes—a factual truth is only really true if it corresponds exactly to a fact. For instance, a certain effect has to be proven and confirmed to be true, for example, the impact of a new medicine. But a reasonable truth is already true if it does not contradict the obvious facts. For example, the declaration of certain effectiveness is often plausibly true, for example, the perception of wellbeing during a therapeutic treatment. It is remarkable here that scientific reasoning contains considerably more freedom for creativity, whereas purely sticking to the facts seems a somewhat inept way to make any kind of innovation.

For example, the reorganization of complex manufacturing systems may be highly profitable, as described by the theory of lean thinking [23]. However, as the authors of that theory Womack and Jones pointed out, sometimes profit vanishes completely if there is attempt to verify by the fact how each action works and interacts within the system. A deductive proof using the essential elements, as conceived by Descartes, often costs more than it saves. Therefore, it is recommended that we remain on the level of rule-of-thumb explanations and monitor the integral changes. The scientific insistence of factual truth can obviously prohibit an innovation.

But also pure reasoning has a so-called ontological problem—literally meaning a problem of generalization. Whether someone who possesses $1,000 can be regarded as rich depends on where one lives and what aspirations one has, as Kant argued— of course he spoke of thalers, which was the currency of his time and place. A US citizen or a third-world resident will see their wealth quite differently, as will also a millionaire or an ascetic monk. These subjective views are countless, making a generalized view useless. It is always tempting for innovators to simply establish a different way of thinking rather than arriving at some facts. But it must also be considered that while a subjective opinion may be true it is not necessarily easy to arrive at an objective agreement. This appears to be crucial for any innovation.

Accordingly, reasoning is not a license to explain all kinds of effects caused by supernatural forces or energy flow in the way esoteric, magical, or occultist circles do. Force and energy are real phenomena that can be actually measured and physically calculated. If the real facts are not known, it does not really help to apply factual terms in order to make them appear believable. A statement of virtual facts that cannot be verified does not count as a scientific proof. Thus, scientism does not mean scientific, but it only means an inappropriate application of scientific means for esoteric, religious, mythical, magical, or occult purposes.

Consequently, objectivity has come to be a further requirement in modern sciences, in particular since the Age of Enlightenment. While medieval sciences were strongly subject to hermeneutic interpretation of the Bible and other traditional scriptures, nowadays factual objectivity is mandatory, and mere subjective convictions without provable consequences are inchoate.

The philosopher Schopenhauer described the process of objectivation as a procedure that begins with subjective ideas and the human will to make this idea become a reality. It is by focusing on objectives that individual ideas will agree with perceptions of other people and become scientifically sound. Obviously, the concept of objectivation describes a particular approach of an innovator (see Figure 2.1).

Factual truths are always subject to a law of conservation. This means that stated facts and properties from a scientific investigation must be kept to at all times— nothing comes from nothing, as Parmenides stated already about 500 BC. All real facts exist independently of man’s ideas and desires, and therefore remain somewhat constant. All apparent change of natural properties—for example, mass, volume, energy, or electric charge—is virtual or a zero-sum game, respectively. This is the basis for all equation formulas in science, where any change of appearances is described by a collection of given parameters, on one side, and an equality of resulting parameters, on the other. Also, every change of the premises is due to a shift in input parameters with regard to a similar shift in output parameters. In this way it becomes actually possible to establish an equation and conclude a measurable result for variations.

Inversely, the law of conservation for factual truths corresponds to an exclusion potential, which means that nothing can vanish into nothing. A scientific analysis— which literally means dissection—breaks down an observation into single testable statements, which remain true in any subsequent composition—that is, synthesis. This scientific procedure is found in all kinds of scientific approaches.

For example, mechanical bodies are broken up and reassembled to form new ones, and mechanical forces are decomposed and recomposed in an appropriate manner by vector analysis; the distribution of things in processes is separated and then mixed to form new compositions, and chemical bonding is dissolved and subsequently reacted to form new molecules in chemistry; nuclear operations consist of fission and fusion to split or merge new atoms, and mathematical calculus is built on differential and integral operations to calculate infinitesimal changes; economic accounting compares assets and liabilities to establish a balance, and entrepreneurial projects are split into working packages and framed within a structured plan. In anticipation of the management of innovations we can already disclose that an innovation project is analyzed in a similar way for success factors and phases and integrated by promoters and the appropriate culture.

In contrast, the truth of reason is apparently related to a law of entropy, which literally means changeability. This means that reasonable explanations can virtually increase unlimitedly. As long as there is no objection arising from facts, all thought is free, as guaranteed by the First Amendment of the Bill of Rights [24]. It is a perplexing peculiarity of science that the metaphors required to describe knowledge are incredibly variable. Since the metaphysical notions in the science of art are not in fact manifested by natural facts, they can be infinitely specified with new definitions. For mental concepts—for example, interpretations, theories, hypotheses, or fantasies— there is always room for further ideas. And every attempt to explain a new inspiration needs new expressions to describe it.

For instance, if you compare the amount of fictional and nonfictional literature in any given library, fiction will outnumber nonfiction by at least one order of magnitude. In this way in the end it becomes finally possible to create something genuinely new that exceeds the framework of mere redistribution.

And inversely again, this law of entropy corresponds to a certain dispersion potential, which means that there is a certain compulsion to attribute to an idea an endless series of new paraphrases or circumlocutions, until an official realization and a general public understanding are reached. A concept without factual representation vanishes into nothing when it is no longer taken up, interpreted, explained, and commented. And scientific theories can almost disappear if they are not discussed any more, for example, aether as the matter of light propagation or the phlogistron as the matter for heat expansion. In particular, some topics seem to lead a shadowy existence when only being discussed by a small group of experts, for example tachyons [25] moving against time or quantum entanglement [26] permitting teleportation. A notion that is unfashionable during a certain period may be suppressed for a long time until eventually rediscovered in the light of newly discovered facts.

For instance, Lamarck’s theory of adaptation from around 1800 was disrupted by Darwin’s theory of evolution in 1859 and then more recently reestablished by the new field of epigenetics, that is, genetic changes within a lifetime due to switchable protein sequences in the genetic code.

Another example is the development of cosmology: The theory of the circular rotation of planets around the sun, as conceived by Copernicus in 1543, was improved in 1609 by Kepler’s concept of elliptical orbits, and this explanation was in turn disrupted by Newton’s theory of mutual gravitational attraction in 1686, until finally understood as some sort of space warp according to Einstein’s general theory of relativity in 1915.

A very fascinating wandering theoretical path can be found when following the development of the concept of energy, starting with Joule’s law of energy conservation from 1843 and improved by Clausius’s concept of entropy, that is, heat dissipation, in the 1860s, until disrupted by the concept of Hawking radiation [27] in 1974: According to this newest explanation black holes collect dissipated energy and subsequently blast it away due to quantum effects. This mirrors the concept of factual truths by conservation and the related exclusion potential on an utmost level of theoretical abstraction.

This transformation of scientific abstraction from reason to fact and back again to reason—as often as required until things match—is also fundamentally valid for any innovation. Metaphysical convictions can produce endless ideas, and they are at the same time a prerequisite. Then physical proof is required to restrict the rapidly growing amount of fictional persuasions about the feasible options. In general, another surge in fantastic ideas is often required as a consequence in order to recommence when the verifications turn out more or less differently than expected. Here, the mutability of metaphors is a superb vehicle for the generation of any ideas at all and for the creation of innovations. It is the character of reasonable change to follow some sort of cycle, or, as Heraclitus concluded: Change is the only constant in progress.

Thus, science and innovation belong themselves to the class of rational truths. They are not real phenomena and therefore they are subject to the law of entropic increase with a given potential of dispersion. In that sense, an evolutionary improvement happens in the framework of a theory, whereas disruptions override the established theories. New technologies can even cause a big bang or economic boom and produce investment bubbles, which disappear into almost nothing when the bubble bursts and the situation is reset to the matters of fact.

Innovation requires a sort of convincing poetry; and—as has been already stated at the very beginning of this book—poets were given the prime right to interpret the divine rules of the world in different way. Thus, poets are a sort of basic innovators.

Most cases will probably only reproduce some tacit knowledge and affirm subjective biases. Several cases will establish a new merging with related topics and allow for the sharing of knowledge. Other cases will lead to new effects or solutions that were previously unknown. Only a few, rather seldom cases will detect a blank spot in the scientific or innovation agenda and may be the impetus and birth of a profound investigation. This seems to be the most promising benefit for innovation management.

The whole process of elenctic conviction is not at its end with the status of cognition by maieutic enlightenment (see Figure 2.2). The average human brain disposes of other processes to obtain oblivion by trauma—literally leakage, gap, or sink. Especially during sleep—and sometimes in consequence of excessive stress—the brain removes memories and cognitive achievements that seem to be obsolete, because they are of no practical use, or might be a threat to mental health and conscious thought. This cycle sometimes needs the help of therapy—literally a service or a cure—in order to be completed, when this suppression causes mental disturbances or blockages. Then an equally strenuous and guilt-ridden cycle of conviction and rebirth may be required— sometimes followed by another round of oblivion and therapy.

The respective states in this cycle can be circumscribed by distinguishing knowledge and consciousness. Initially, every objectivation in science and innovation has hidden problems to be solved, that is, things that are initially unconscious and unknown. By the process of elenctic conviction this unawareness becomes clear and leads to a shameful/guilt-ridden aporia and the admission of ignorance, that is, the state of something consciously unbeknown. But maieutic birth rewards these efforts with sudden enlightenment, that is, the state of something consciously known. However, traumatic oblivion suppresses this insight, that is, the state of unconscious knowledge. Then it requires some sort of therapy to restore the experienced state of ignorance, that is, the state of the unconscious unknown.

The order of Discourse is another adaptation of this analogy and was elaborated by Foucault around 1970 [34]. According to this approach, factual things obtain a novel signification by conscious attribution of notions, which have not been discovered before. And reciprocally, the attribution induces an alternated perception of those factual things—and by this a change is perceived in reality itself.

The innovative aspect of such a discourse can be demonstrated by the change of some verbal meanings in the recent years. For instance, the “Internet” has become a linguistic reality, although being basically a mere virtual matter. But Internet services, such as Google, Amazon, Facebook, or Wikipedia, have become an institutional reality, increasingly dominating the real economy, and social and political lives, although relying just on an exchange of information. Yet, processes such as browsing, twittering, or googling reveal a real new performance by the Internet, which have considerably changed modern business and the related lifestyle, although they consist just of a soulless, automated data processing. And by new features, opportunities, and threats, a novel discursive practice has evolved—for example, cybercrimes like hacking, phishing, or identity theft—with downright true impacts, although it is all just about exchange of abstract data.

Modern innovations within the frame of Internet business have become extensive in such a way that they represent the general abilities for the improvements and for the disruptions of our time. A typical innovation today consists mainly of a discourse: What kind of new business might be possible by means of cross-linked electronic data communications? Concerning this matter, a suitable and catchy name for a new project case seems to be a primary obligation in order to make it manifest—and noticeably a project team develops an own discursive practice during the evolution of a project.

A particular sort of such a discourse is negotiation. And the concept of Principled Negotiation by Harvard University in 1981 took on the challenge to increase reasonably the mutual interests of the negotiating parties by appropriate wording at first, before starting to distribute the facts [35]. The merit of a negotiation consists principally of the effort, to employ manifold reasonable truths by the law of entropy, as described before. This requires slow and strenuous thinking and shameful convictions of a previous ignorance. For negotiations, too, are subjected to a mutual lack of knowledge about the interests of the respective other parties. And novel results can be principally obtained by making the unbeknown obvious.

In a first step, the advice for principled negotiations is to separate the people from the problem, that is, to split the disperse quantity of reasonable interests on one side from the limited availability of factual resources on the other. In a second step, the advice is to focus on interests and not on positions, that is, to investigate the ample opportunities of reasonable interests and not on the restricted perspectives of factual statements. Then, in a third step, it is advised to create options that satisfy both parties, that is, to find out novel aspects, which can be satisfied in another manner, in another moment, by shared utilization or by other compensations. Finally, in a fourth step, it is advised to insist on objective criteria—or refer to a best alternative to the negotiated agreement, abbreviated as BATNA. Obviously, these advices follow the concept of the Line Analogy for an innovation, as mentioned before. And they even include the necessity of objectivation, to avoid errors and fraud by illusions.

Thus, for innovations, it is similarly advisable to distinguish between individual desires and technical problems and to focus first on these desires instead of the limitations of the existing technology. Only afterward does it seem appropriate to engineer technical possibilities, which combine both, fact and fiction. And finally, the obligation to an objective truth is to respect—or to content oneself with the state of the art. Apparently, principled negotiation is a feasible way to make an innovation, too. And a conclusion is that innovations require a sophisticated way to negotiate about reason (see Figure 2.4).

A fundamental error in scientific or innovation proceedings is the attempts to cut short or skip a step—or even change the sequence of the funnel. For example, when the feasibility of an idea is tested, although the idea itself is theoretically not even plausible, it represents a waste of budget, in general. And the preparation for a prototype launch is a lavish spending as well, when its feasibility has not yet been proven. In both cases the majority of resources is dispersed outside the innovation funnel and is lost forever for the purposes of targeting the objectives. What is more, it seems to be obviously quite dispensable to check afterwards the feasibility of a failed prototype, just to make sure, that the original idea had not been plausible. However, these avoidable errors happen time and again.

The scientific logic of induction is also named Epagogic—literally meaning achieving. Explorations, experiments, and detections of physical objects can be seized in the framework of a theory. The epagogic conclusion is from single to general understanding. For example, an innovative material will first be checked for its properties before being employed in a new construction. And the general introduction of an innovation will first be realized by a prototype before being generally implemented by a product launch. The diffusion of an innovation is obviously rather epagogic, in general.

The scientific logic of deduction is then also named Apodictic—literally meaning demonstrating. Convictions, opinions, beliefs, and ideas are subjects of metaphysical thinking and have to be objectivated. The conclusion here is from the general to a single perception. For example, an innovative product will first be tested in a prototype project before being launched in the market. And an innovative process will first be examined in a pilot scheme before being implemented in production. The projection of an innovation is therefore rather apodictic in general.

An anecdote attributed to Einstein may bring more clarity: A logical conclusion can be right, even if the result is obviously wrong, when it bears on an equally wrong assumption. For example, if 2 = 1, then Einstein is the Pope. Indeed, the Pope and Einstein are different people, however, if 2 = 1 that does not matter and therefore Einstein is the Pope. The logic was derived correctly, though obviously with a false result.

Now, when we accept a logical conclusion as an own scientific world, then the concluding techniques are of considerable importance. In general, the propositional calculus of logics is considered “closed”, that is, a system with just true or false and no half-truths. If that Law of Excluded Middle is employed, some features of conclusion can be stated:

The first one is the direct conclusion or Modus Ponens, that is, two arguments match in their truths. If one is true and consequently the other, too, then the untruthfulness of the other concludes the untruthfulness of the former. For example, an innovation requires an execution, so if there is no execution, there is neither an innovation. This seems to be the most comprehensible and trustable logical technique.

The second one is an indirect conclusion or Modus Tollens, that is, two arguments contradict each other. Either one is true and then the other is false, or the other is true and then the former false. For example, if an innovation project is required to achieve improved results, then more time and/ or money is required, and if time and/ or money are saved, fewer results have to be expected. This seems to be a challenging and obstructive logical technique; in order to overcome these limits you are tempted to resort to tricks and/or imply half-truths.

The third concluding technique is about a chain of arguments or Modus Barbara, that is, if one argument matches with another and that one with a further one, then the former does also match with that further. For example, if the execution of an innovation is applied and this application is economically sound, then the execution is also economically sound. This seems to be the most seductive technique, because in reality the required exclusivity of the excluded middle is not always given. For example, there may be innumerable reasonably grounded exceptions, of why that unknown status of the middle is different in the logical conclusion chain, since a complete chain is seldom provided in reality: The costs of an innovation project may increase, although the targeted application and business case would be achieved as genuinely budgeted; several supplementary compliances might have turned up or mistakes made or workers fell sick or tools were unavailable and so on and so forth. Again, as Socrates is said to have stated: How numerous are those things, which I do not have any need for.

In reality, a Tetralemma is basically required—literally meaning a fourth technique. As real systems are always open to contain further, hidden or yet unknown facts and/ or rational arguments, “maybe” or “otherwise” have to be practically accepted. Hence, a logical conclusion should not contain “either-or” but rather a “both-and” structure. Perhaps the metaphor of the triangle is just “magic,” because it illustrates this uncommon open way in real argumentation. Sometimes we tend to conclude logically where the particular rules of conclusions are not appropriate.

For example, the logic of a tetralemma can be explained by an old allegory: Which of the two men will logically bathe next if one is dirty and the other is clean? Probably the dirty one—however, he might not be inclined to bathe, therefore he is dirty. Then probably the clean one—however, he does not need to bathe, because he is already clean. Then probably neither of them—however, either of both should be next. Then probably both together—however, that would require an extraordinary coincidence; and it is doubtful that both are friends, if they differ in their appreciation of personal hygiene. Neither one, nor the other, neither none, nor both . . . evidently, a logical conclusion seems impossible in this case. A tetralemma results in the most surprising insight, that there are always open expectations to expect.

Coming back to the Theaetetus’s interrogation about epistemological verification, even Socrates revealed some dissatisfaction with that triple need of confirmations to assess a truth. Since verification is achieved just by a concerted action of the three aspects, which have to be verified each one by itself, respectively, it looks suspiciously like a senseless self-affirmation. And since the statement of a truth by just a single of those aspects does not hold true enough, the general assessment is always somewhat incomplete. For, there are always innumerable arguments that can also be untrue.

According to innovations, it would be similarly strange to explain a novelty just by stating a novel technology along with novel markets and a novel business concept. What indeed is novel or innovative is not explained but just those aspects that have been considered. Sometimes a commercial advertisement claims already for an innovation, when a well-known technology within an equally well-known product is offered the first time to well-known customers. In this case, just the combination of the specifications is somehow novel. And no one can call it fraudulent, since the application of reasonable words is free of charge. Therefore, some keywords—such as exclusive, modern or unique—are just catchwords to attract attention, not to describe innovations. One may easily obtain enough examples on each page in appropriate magazines or over the Internet.

Anyhow, Socrates is reported to have adjourned the questioning. And, to date only three aspects of truth are known. And nobody can say what truth is. Likewise, an innovation cannot be predicted scientifically, but it always bears a certain risk of failure. And nobody can assert to know what has to be understood by the term “innovation”.

As for science, however, this adjournment lasted until 1963, when Edmund Gettier III discerned some novel evidence for the statement that a verification of ignorance may be doubtful [37]. Even if something is justified and corresponds to a perception as well as is reasonable to believe, this may be due to mere coincidence, accident, fortune, or chance.

To explain this, a common setting of a detective story may be considered: If the true offender was actually not seen, yet later mistaken for someone, who has occasionally been around the crime scene, then the truth has ostensibly restored again— but notably not by a knowledge of the truth. And all verifications prove to be right, when place and time are checked, as well as a reasonable motive and seemingly justified testimonies. However, nobody had really known the truth.

In such cases the spectator will be probably contended with the fate and maybe muse about divine justice, although, the result was not obtained by scientific knowledge. Such a fictional story surely takes an interesting turn, but trust has been appalled. Nothing seems to be right, not even the assessment by perception, reason and logic. Still, nothing more certain is known to us (see Figure 2.6).

Innovations are achieved after various chances and many risks. And anybody who has ever participated in an innovation project can surely confirm that it is an on-and-off again and a ubiquitous coincidence whether you fail or you succeed. So, failure or success does not completely exclude each other. Just one of both, will rather not occur, and nothing at all, neither. Because it has always to be something new . . .

Lesson 9

Nothing is more certain for an innovation than a believable and justified perception!

2.4Categories

Plurality should never be applied without necessity.

Ontological Parsimony by William of Ockham 1287–1347

A common misunderstanding of science is that by comprehension things become simplified. Just inversely, through countless thoughts the human brain tries to understand reality, indeed [38]. Since science itself is not real but just a metaphor for reliable knowledge, its truths are just reasonably justified and become only verifiable due to an epistemological reasoning. Therefore, science itself underlies the law of entropy with considerable diffusion potential, as previously explained.

In order to work with scientific knowledge many aspects are to be considered, for example, the unconscious ignorance and its overcoming by an elenctic conviction, which leads to an experience of shameful aporia—then the achievement of conscious knowledge by obtaining a maieutic birth of a new apprehension—and then its oblivion by trauma. Furthermore, the proceedings of entelechy have to be considered by a funnel rising from appearances to impressions and later to understanding and comprehensibility. And additionally the complexity in epistemology regarding perception, belief, and justification is to be respected. Beyond that, all these aspects can be apparently described and explained by countless different words and their connections. Those who expect simplicity in science will surely be disappointed.

The economic advantage of any scientific approach is that thoughts are comparably fast and cheap. In our era of informatics it becomes more and more obvious that information spurs economy—and perhaps enables a novel global prosperity, too. The ways of thinking and of imitation are noble and easy, yet experience is arduous, as Confucius has put it in his analects. And this is the economic benefit of education and studies: brainwork beats physical strength—at least on the long run. [Trust me; I am a professor—literally meaning a salesman of scientific knowledge.]

Yet, all things are limited, however fast and cheap they may ever be. And information, too, is bound to some physical reality, since it depends on electrons, on molecules, or at least on photons for transport. Each consideration should come to an end, as well as all books, speeches, movies, or computer programs. Now, to link that to innovations means the following: Although the objectivation of reasonable truths is an uncertain and risky process, you have to make a start sometimes—or you will certainly never succeed. The implementation of an innovation requires an imperfect decision, eventually. Thus, the crucial question is how much thinking quota is reasonably justified with regard to the remaining imperfection.

This was the original motivation why Aristotle has introduced Categories into sciences—literally standing for a complete exhibition in a market. Everything imaginable required for purchase and for subsequent activities lies there exposed for the customer. So, let us go on a shopping tour and find out what can be helpful for the purpose of scientific innovations:

At first, we need a pair of truths. And such dualisms are on stock in various offerings. In Chinese Daoism it is described as yin and yang, standing for passive objects and active subjects, respectively.1 In Indian Yoga that dualism is described as prakrti and purusha, standing for physical substance and psychical spirit, respectively. In European rationalism Descartes baptized these aspects as res extensa and res cogitans, meaning extended and cognitive things. In the age of enlightenment Leibniz then applied the French wording verités de fait and verités de raison, meaning truths of fact and reason, respectively [39]. And in German idealism Kant applied the words of observations and thoughts among others to seize the concept of dualism. Modern existentialism by Sartre distinguishes existing from essential aspects; and materialism by Marx disclaims objective being and conscious being. The Split Brain Theory of Sperry was rewarded in 1981 with the Nobel Prize for medicine and the Prospect Theory of Kahneman in 2002 with the Nobel Prize for economics—both discerning that particular dualism in the human brain. And even the Nobel Prize for physics was awarded to Heisenberg in 1932 for the particle-wave duality, that is, located objects and moving targets in quantum mechanics. Obviously, there is a rich choice of categorical dual flavors available on the scientific market.

At next, we need triple confirmations for our expectations. Here, the marketplace seems copiously equipped. There are those three ways for wise actions as quoted from Confucius, namely, experience, imitation, and thinking. They can be related to the epistemological assessment by Socrates, namely, perception, belief, and justification. They are still in use within Popper’s Three World concept of physical, psychical, and logical understanding. And they are beneficial for stakeholder expectations by the magic triangle of costs, time, and results. The German philosopher Hegel created in 1807 an interlaced system of triangles within his Phenomenology of Spirit, departing from the aspects of nature, spirit, and logic. And there is a theological challenge in understanding the Christian doctrine of a Trinity of god as the native Son, the eternal Father and the Holy Spirit. Again, manifold and inspiring categorical triple offerings are found in the market.

Then, we need a quadruple set of confirmations. The earliest are commonly known as earth, water, air and fire by Empedocles of the 5th century BC, which obviously become more and more volatile and intangible in that order. This corresponds reasonably well with the explained entelechy from solid appearances to affluent impressions leading to ubiquitous understanding and finally to burning comprehensibility, equally losing substance in that order. This concept of Four Elements has been subsequently widely employed, for instance by Aristotle as the concept of Four Causes, that is, a material cause as some sort of earthy substance, a formal cause as some sort of fluent design, an efficient cause as some sort of volatile potency, and a final cause as some sort of inflaming purpose. Hippocrates extended this in his analysis of human Humorism by tempers of earthly melancholic, hydrous phlegmatic, aerial sanguine, and flamy choleric. In medieval times these attributes were equally assigned to spiritual beings like earthly gnomes, hydrous undines, aerial sylphs, and flamy salamanders. More scientific seems the Essay Concerning Human Understanding by Locke in 1690, where he explains the evolution of ideas in four stages, namely, from the simple perception of things to the acknowledgment of their substance then to their connecting relations and finally to their various modes. Accordingly, in 1913, the psychiatrist Jung introduced a renowned concept of Psychological Complexity by the mutual interference of simple perceptions, acknowledged memories, related thoughts, and modified emotions. The orders of Discourse by Foucault in 1970 and the Principled Negotiation by Harvard University in 1981 have been previously explained and may be completed by the Four-Sides-Model of communication by Schulz von Thun in 1981, which consist of factual information, informal self-revelation, corresponding relationship, and general appeal. Again, even modern physics contains quadruple settings, like the basic forces due to earthly gravity, electromechanical fluxes, strong relations, and weak modes of nuclear bonding. Once more, these quadruple categories in the scientific market seem to be quite saturated.

But, there are scientific categories with multiple characteristics. For instance the International System of Units contains since 1971 seven elementary metrics, that is, meter, kilogram, second, kelvin, ampere, candela, and mole in order to measure the extension, mass, time, temperature, charge, light, and substance, respectively. An octet of aspects is applied not only in the concept of I Ching in Daoism but also in the Noble Eightfold Path in Buddhism. And the number six has a particular meaning in mathematics as the smallest Perfect Number, which is equal to the sum of its divisors 6 = 1 + 2 + 3, as well as the regular Hexagon as the largest polygon to tile a plane without any gaps or intersections. There are even two different concepts of infinity in mathematics: Infinitely countable sets like integers, which are infinite but still theoretically countable one after the other, and uncountable infinities as explained by Cantor in 1874, which contain numbers without any countability, like the square root of two or the circle’s number pi. Hence, scientifically there are not only numerous alternatives for categorical settings but also settings with innumerable categories. Reluctant scientist may thereby see an insurmountable hindrance to succeed. But entrepreneurial innovators will thereby see an eternal chance to proceed.

In his script Organon Aristotle sets up ten categories, which he subsequently employed in different specifications, however. Kant in his Critique of Pure Reason adopts the idea of categories but specifies a setting of four classes of judgments, each with three categories. The resulting twelve categories for reason are: A universal, a particular, or just a single quantity of the judgments—then an affirmative, a negative, or even a limited quality of the judgments—further a general, a probable, or an exclusive relation of the judgments—and finally an ambiguous, a specific, or irrefutable modality of the judgments. And it is advisable to refer to these categories, for instance, to judge the chances of an innovation project.2

Scientifically, this opulence of categories may appear somehow random and maybe confusing. It becomes never assured, if any systematic approach contains all of the categories required. And it is equally uncertain, if some categories are already included and just result from a joint cooperation of some others. Unfortunately, the former discussion of epistemological truth showed that there is never a reliable clearness in any scientific system. What can be provided, altogether, is the essay to define a possibly complete system without interference. This is the purpose of categories.

Hence, a typical task for students in industrial engineering is the elaboration of a plausible setting of categories for the innovation of products, processes, sales, or organization. In general, they just list their observations, gathered experience, related considerations, and best assumptions and then try to categorize them. This proceeding seems absolutely appropriate, if you do not know better. But a skilled, taught, instructed, and experienced bachelor or master of engineering should know better. At least for graduation, the sophisticated art and reasoning of skilled mankind can be expected.

The first default is usually a disregard of the dualism in science, either by just limiting a study to facts or by rambling about long-winded assumptions. In particular the transfer of theoretical considerations to objective facts is a challenge for many [40].

The next usual omission is the quest for the unknown. Whether this is too shameful or too exhausting for the students is hard to say, however, many prefer to stay close to the demands and make just poor efforts for a deeper understanding. The Dunning- Kruger effect concerns the hindsight bias of obviously unskilled people to realize their inabilities [41]. In the related studies it turned out that it requires a certain skillfulness to estimate one’s own skills. Thus, the more unskilled you are, the more you ignore your lack of understanding. Therefore, the first task in education is always an instruction about perseverance in self-doubts and the insistence of scrutinizing one’s own confidence—without getting personal, for sure.

In order to achieve the merits of inspiring insights, each one has to learn how to pass the shameful state of ignorance. Most interestingly, some students frankly admit to be just good in ideation or, contrariwise, they prefer to stay at the obvious. So, the readiness for arduous mental work is an urgent as well as an indispensable target in education.

Then, if you like to follow rules, it becomes somewhat easier. However, it is the privilege of youth to take it easy and skip guidelines—if not prevented to do so. And it is a pity, how often very promising scientific approaches—with apparent deepened understanding and balanced considerations of facts and reason—finally do not perform well because the student urges prematurely for some destination and thereby skips some steps of sufficient comprehension, theoretical research, feasibility investigations, or even prototypic implementations. Such slips and oversights are nasty yet not as expensive during an academic formation as later in the reality of professional business.

Further on, the openness of an epistemological proof is very tempting for students to gamble instantaneously for best luck and stay on with mere creative thinking— instead of trying first the best scientific practice. As the overall harmonization of the three aspects is quite laborious and often frustrating, this seems somewhat comprehensible, though not reasonably gratified. Contrariwise, the best ratings should be reserved to those who can handle complexity and are able to manage disappointments. And the justification of perception and reason counts among the most difficult tasks in science. Again, a default during instruction is much less meaningful than the impact when one carelessly fails at the commercial launch of an innovation.

Finally, the general intention for academic studies can be seen in the discovery and the establishment of sound categories, for example, factors, features, characteristics, or attributes. Although it might not guarantee success, it guarantees a reduction of risks and of failures. And therefore this task is scientifically compulsory. If an innovation seems to be scientifically impossible, it does not mean that it is really and always impossible, but it just signifies that the logic of the business is incoherent with the physical execution and/ or its reasonable application.

Such categories for innovations are additionally helpful to become aware of different features and of expectations. In this way the progress can be tracked with more survey. Certainly, each enterprise may establish its own logics—and certainly at every moment some executive assistants are charged with such a mission. But the scientific categories have been selected by the experience of many centuries, at least, and therefore they should count as a fundament for further specifications. Sometimes the applied numbers for such specifications seem to include a particular significance or conjure even some hidden, miraculous, or secret power. Scientifically, numbers are rather a logical device for classification and not own categories by themselves.

A characteristic of most scientific approaches is Evidence, that is, there are obviously predominant relations between cause and effect, which stay true, even if further relations are added later on. If evidence is provided, the impact of further relations diminishes according to a Power Law. In consequence, further relations show a relatively poor impact due to a power of magnitude.

This Rule of Scale justifies the application of heuristic categories to seize a topic: If the main aspects are already included, the remainders are mostly negligible attributes. In particular, the Pareto Principle is a heuristic proof that in many cases just 20% of the possible causes are responsible for some 80% of the effects [42]. Thus, if there is some evidence for a scientific topic, it makes sense to start an investigation about its categories. If these categories cover evidently the topic in general, it may already count as being reasonable. However, there may be also no evidence, because the topic is not seized correctly, or, as the Scottish saying goes: Many a mickle makes a muckle. Then, another approach has to be made.

The term “KISS-Principle” for management stands for the corresponding advice to “keep it smart and simple” also known as “keep it simply stupid”. And that paraphrase seems an appropriate abbreviation for the meaning of categories—at least, in the first way revealed here. For example, in behavioral economics it is actually contestable whether a system of categories should be elaborated by trained and skilled experts or by untrained and naïve laymen. Some comprehensive surveys showed that the expectations of experts are more affected by exceptions and by extremes, which are unbeknown to the laymen, but perhaps of negligible significance, too [43]. Experts seem to be appropriate for a space mission, but for the preferred color of a fashionable shirt a certain amount of laymen would be almost sufficient. As the choice of categories is always somehow subjective, the categorical procedure itself does not simply comply with the demand of objectivation.

Thus so-called pragmatists prefer a spontaneously diced system of categories made up out of thin air. And they argue that any discussion about scientific approaches would be impractical and therefore wasted. They would rather develop for each enterprise and sometimes for each innovation project an own terminology to justify each decision and to decree in their proper way of management. The ensuing gaps and misses are then controlled by an equally pragmatic management, as well as hard work and additional tolerance to frustration. Even this may work—and hopefully successfully—because thoughts are free and science is always open to new ideas and inventions.

Yet, scientifically sound categories—as explained—are persuasively the best way to obtain equally sound and reliable results.

Lesson 10

Innovative ideas can be assessed by a plurality of categories!