Systems Engineering: Problem Solving (Just the Quotes)

"Even these humble objects reveal that our reality is not a mere collocation of elemental facts, but consists of units in which no part exists by itself, where each part points beyond itself and implies a larger whole. Facts and significance cease to be two concepts belonging to different realms, since a fact is always a fact in an intrinsically coherent whole. We could solve no problem of organization by solving it for each point separately, one after the other; the solution had to come for the whole. Thus we see how the problem of significance is closely bound up with the problem of the relation between the whole and its parts. It has been said: The whole is more than the sum of its parts. It is more correct to say that the whole is something else than the sum of its parts, because summing is a meaningless procedure, whereas the whole-part relationship is meaningful." (Kurt Koffka, "Principles of Gestalt Psychology", 1935)

"By some definitions 'systems engineering' is suggested to be a new discovery. Actually it is a common engineering approach which has taken on a new and important meaning because of the greater complexity and scope of problems to be solved in industry, business, and the military. Newly discovered scientific phenomena, new machines and equipment, greater speed of communications, increased production capacity, the demand for control over ever-extending areas under constantly changing conditions, and the resultant complex interactions, all have created a tremendously accelerating need for improved systems engineering. Systems engineering can be complex, but is simply defined as 'logical engineering within physical, economic and technical limits' - bridging the gap from fundamental laws to a practical operating system." (Instrumentation Technology, 1957)

"Systems engineering embraces every scientific and technical concept known, including economics, management, operations, maintenance, etc. It is the job of integrating an entire problem or problem to arrive at one overall answer, and the breaking down of this answer into defined units which are selected to function compatibly to achieve the specified objectives. [...] Instrument and control engineering is but one aspect of systems engineering - a vitally important and highly publicized aspect, because the ability to create automatic controls within overall systems has made it possible to achieve objectives never before attainable, While automatic controls are vital to systems which are to be controlled, every aspect of a system is essential. Systems engineering is unbiased, it demands only what is logically required. Control engineers have been the leaders in pulling together a systems approach in the various technologies." (Instrumentation Technology, 1957)

"Systems engineering is the name given to engineering activity which considers the overall behavior of a system, or more generally which considers all factors bearing on a problem, and the systems approach to control engineering problems is correspondingly that approach which examines the total dynamic behavior of an integrated system. It is concerned more with quality of performance than with sizes, capacities, or efficiencies, although in the most general sense systems engineering is concerned with overall, comprehensive appraisal." (Ernest F Johnson, "Automatic process control", 1958)

"[System dynamics] is an approach that should help in important top-management problems [...] The solutions to small problems yield small rewards. Very often the most important problems are but little more difficult to handle than the unimportant. Many [people] predetermine mediocre results by setting initial goals too low. The attitude must be one of enterprise design. The expectation should be for major improvement [...] The attitude that the goal is to explain behavior; which is fairly common in academic circles, is not sufficient. The goal should be to find management policies and organizational structures that lead to greater success." (Jay W Forrester, "Industrial Dynamics", 1961)

"Systems engineering is most effectively conceived of as a process that starts with the detection of a problem and continues through problem definition, planning and designing of a system, manufacturing or other implementing section, its use, and finally on to its obsolescence. Further, Systems engineering is not a matter of tools alone; It is a careful coordination of process, tools and people." (Arthur D. Hall, "Systems Engineering from an Engineering Viewpoint" In: Systems Science and Cybernetics. Vol.1 Issue.1, 1965)

"System theory is basically concerned with problems of relationships, of structure, and of interdependence rather than with the constant attributes of objects. In general approach it resembles field theory except that its dynamics deal with temporal as well as spatial patterns. Older formulations of system constructs dealt with the closed systems of the physical sciences, in which relatively self-contained structures could be treated successfully as if they were independent of external forces. But living systems, whether biological organisms or social organizations, are acutely dependent on their external environment and so must be conceived of as open systems." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"Only if mathematical rigor is adhered to, can systems problems be dealt with effectively, and so it is that the systems engineer must, at least, develop an appreciation for mathematical rigor if not also considerable mathematical competence." (A Wayne Wymore, "A Mathematical Theory of Systems Engineering", 1967)

"Solving a problem simply means representing it so as to make the solution transparent." (Herbert A Simon, "The Sciences of the Artificial", 1968)

"The systems approach to problems focuses on systems taken as a whole, not on their parts taken separately. Such an approach is concerned with total - system performance even when a change in only one or a few of its parts is contemplated because there are some properties of systems that can only be treated adequately from a holistic point of view. These properties derive from the relationship between parts of systems: how the parts interact and fit together." (Russell L Ackoff, "Towards a System of Systems Concepts", 1971)

"It remains an unhappy fact that there is no best method for finding the solution to general nonlinear optimization problems. About the best general procedure yet devised is one that relies upon imbedding the original problem within a family of problems, and then developing relations linking one member of the family to another. If this can be done adroitly so that one family member is easily solvable, then these relations can be used to step forward from the solution of the easy problem to that of the original problem. This is the key idea underlying dynamic programming, the most flexible and powerful of all optimization methods." (John L Casti, "Five Golden Rules", 1995)

"In sharp contrast (with the traditional social planning) the systems design approach seeks to understand a problem situation as a system of interconnected, interdependent, and interacting issues and to create a design as a system of interconnected, interdependent, interacting, and internally consistent solution ideas." (Béla H Bánáthy, "Designing Social Systems in a Changing World", 1996)

"It [system dynamics] focuses on building system dynamics models with teams in order to enhance team learning, to foster consensus and to create commitment with a resulting decision […] System dynamics can be helpful to elicit and integrate mental models into a more holistic view of the problem and to explore the dynamics of this holistic view […] It must be understood that the ultimate goal of the intervention is not to build a system dynamics model. The system dynamics model is a means to achieve other ends […] putting people in a position to learn about a messy problem … create a shared social reality […] a shared understanding of the problem and potential solutions … to foster consensus within the team [..]" (Jac A M Vennix, "Group Model Building: Facilitating Team Learning Using System Dynamics", 1996)

"It is, however, fair to say that very few applications of swarm intelligence have been developed. One of the main reasons for this relative lack of success resides in the fact that swarm-intelligent systems are hard to 'program', because the paths to problem solving are not predefined but emergent in these systems and result from interactions among individuals and between individuals and their environment as much as from the behaviors of the individuals themselves. Therefore, using a swarm-intelligent system to solve a problem requires a thorough knowledge not only of what individual behaviors must be implemented but also of what interactions are needed to produce such or such global behavior." (Eric Bonabeau et al, "Swarm Intelligence: From Natural to Artificial Systems", 1999)

"True systems thinking, on the other hand, studies each problem as it relates to the organization’s objectives and interaction with its entire environment, looking at it as a whole within its universe. Taking your organization from a partial systems to a true systems state requires effective strategic management and backward thinking." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"Systems thinking means the ability to see the synergy of the whole rather than just the separate elements of a system and to learn to reinforce or change whole system patterns. Many people have been trained to solve problems by breaking a complex system, such as an organization, into discrete parts and working to make each part perform as well as possible. However, the success of each piece does not add up to the success of the whole. to the success of the whole. In fact, sometimes changing one part to make it better actually makes the whole system function less effectively." (Richard L Daft, "The Leadership Experience", 2002)

"Self-organization can be seen as a spontaneous coordination of the interactions between the components of the system, so as to maximize their synergy. This requires the propagation and processing of information, as different components perceive different aspects of the situation, while their shared goal requires this information to be integrated. The resulting process is characterized by distributed cognition: different components participate in different ways to the overall gathering and processing of information, thus collectively solving the problems posed by any perceived deviation between the present situation and the desired situation." (Carlos Gershenson & Francis Heylighen, "How can we think the complex?", 2004)

"System Thinking is a common concept for understanding how causal relationships and feedbacks work in an everyday problem. Understanding a cause and an effect enables us to analyse, sort out and explain how changes come about both temporarily and spatially in common problems. This is referred to as mental modelling, i.e. to explicitly map the understanding of the problem and making it transparent and visible for others through Causal Loop Diagrams (CLD)." (Hördur V. Haraldsson, "Introduction to System Thinking and Causal Loop Diagrams", 2004)

"In engineering, a self-organizing system would be one in which elements are designed to dynamically and autonomously solve a problem or perform a function at the system level. In other words, the engineer will not build a system to perform a function explicitly, but elements will be engineered in such a way that their behaviour and interactions will lead to the system function. Thus, the elements need to divide, but also to integrate, the problem." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"Swarm intelligence can be effective when applied to highly complicated problems with many nonlinear factors, although it is often less effective than the genetic algorithm approach [...]. Swarm intelligence is related to swarm optimization […]. As with swarm intelligence, there is some evidence that at least some of the time swarm optimization can produce solutions that are more robust than genetic algorithms. Robustness here is defined as a solution’s resistance to performance degradation when the underlying variables are changed. (Michael J North & Charles M Macal, Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation, 2007) 

"A systems approach is one that focuses on the system as a whole, specifically linking value judgments (what is desired) and design decisions (what is feasible). A true systems approach means that the design process includes the 'problem' as well as the solution. The architect seeks a joint problem–solution pair and understands that the problem statement is not fixed when the architectural process starts. At the most fundamental level, systems are collections of different things that together produce results unachievable by the elements alone."  (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)

"Taking a systems approach means paying close attention to results, the reasons we build a system. Architecture must be grounded in the client’s/user’s/customer’s purpose. Architecture is not just about the structure of components. One of the essential distinguishing features of architectural design versus other sorts of engineering design is the degree to which architectural design embraces results from the perspective of the client/user/customer. The architect does not assume some particular problem formulation, as 'requirements'  is fixed. The architect engages in joint exploration, ideally directly with the client/user/customer, of what system attributes will yield results worth paying for."  (Mark W Maier, "The Art Systems of Architecting" 3rd Ed., 2009)

"DevOps is about team play and a collaborative problem-solving approach. If a service goes down, everyone must know what procedures to follow to diagnose the problem and get the system up and running again. Additionally, all of the roles and skills necessary to perform these tasks must be available and able to work together well. Training and effective collaboration are critical here." (Michael Hüttermann et al, "DevOps for Developers", 2013)

Systems Engineering: Issues (Just the Quotes)

"[Disorganized complexity] is a problem in which the number of variables is very large, and one in which each of the many variables has a behavior which is individually erratic, or perhaps totally unknown. However, in spite of this helter-skelter, or unknown, behavior of all the individual variables, the system as a whole possesses certain orderly and analyzable average properties. [...] [Organized complexity is] not problems of disorganized complexity, to which statistical methods hold the key. They are all problems which involve dealing simultaneously with a sizable number of factors which are interrelated into an organic whole. They are all, in the language here proposed, problems of organized complexity." (Warren Weaver, "Science and Complexity", American Scientist Vol. 36, 1948)

"The fundamental problem today is that of organized complexity. Concepts like those of organization, wholeness, directiveness, teleology, and differentiation are alien to conventional physics. However, they pop up everywhere in the biological, behavioral and social sciences, and are, in fact, indispensable for dealing with living organisms or social groups. Thus a basic problem posed to modern science is a general theory of organization. General system theory is, in principle, capable of giving exact definitions for such concepts and, in suitable cases, of putting them to quantitative analysis." (Ludwig von Bertalanffy, "General System Theory", 1968)

"Technology can relieve the symptoms of a problem without affecting the underlying causes. Faith in technology as the ultimate solution to all problems can thus divert our attention from the most fundamental problem - the problem of growth in a finite system." (Donella A Meadows, "The Limits to Growth", 1972)

"When a mess, which is a system of problems, is taken apart, it loses its essential properties and so does each of its parts. The behavior of a mess depends more on how the treatment of its parts interact than how they act independently of each other. A partial solution to a whole system of problems is better than whole solutions of each of its parts taken separately." (Russell L Ackoff, "The future of operational research is past", The Journal of the Operational Research Society Vol. 30 (2), 1979)

"The world is a complex, interconnected, finite, ecological–social–psychological–economic system. We treat it as if it were not, as if it were divisible, separable, simple, and infinite. Our persistent, intractable global problems arise directly from this mismatch." (Donella Meadows,"Whole Earth Models and Systems", 1982)

"The real leverage in most management situations lies in understanding dynamic complexity, not detail complexity. […] Unfortunately, most 'systems analyses' focus on detail complexity not dynamic complexity. Simulations with thousands of variables and complex arrays of details can actually distract us from seeing patterns and major interrelationships. In fact, sadly, for most people 'systems thinking' means 'fighting complexity with complexity', devising increasingly 'complex' (we should really say 'detailed') solutions to increasingly 'complex' problems. In fact, this is the antithesis of real systems thinking." (Peter M Senge, "The Fifth Discipline: The Art and Practice of the Learning Organization", 1990)

"Systemic problems trace back in the end to worldviews. But worldviews themselves are in flux and flow. Our most creative opportunity of all may be to reshape those worldviews themselves. New ideas can change everything." (Anthony Weston, "How to Re-Imagine the World", 2007)

"All forms of complex causation, and especially nonlinear transformations, admittedly stack the deck against prediction. Linear describes an outcome produced by one or more variables where the effect is additive. Any other interaction is nonlinear. This would include outcomes that involve step functions or phase transitions. The hard sciences routinely describe nonlinear phenomena. Making predictions about them becomes increasingly problematic when multiple variables are involved that have complex interactions. Some simple nonlinear systems can quickly become unpredictable when small variations in their inputs are introduced." (Richard N Lebow, "Forbidden Fruit: Counterfactuals and International Relations", 2010)

"The problem of complexity is at the heart of mankind's inability to predict future events with any accuracy. Complexity science has demonstrated that the more factors found within a complex system, the more chances of unpredictable behavior. And without predictability, any meaningful control is nearly impossible. Obviously, this means that you cannot control what you cannot predict. The ability ever to predict long-term events is a pipedream. Mankind has little to do with changing climate; complexity does." (Lawrence K Samuels, "The Real Science Behind Changing Climate", 2014)

"Because the perfect system cannot be designed, there will always be weak spots that human ingenuity and resourcefulness can exploit." (Paul Gibbons, "The Science of Successful Organizational Change",  2015)

Systems Engineering: Success (Just the Quotes)

"[System dynamics] is an approach that should help in important top-management problems [...] The solutions to small problems yield small rewards. Very often the most important problems are but little more difficult to handle than the unimportant. Many [people] predetermine mediocre results by setting initial goals too low. The attitude must be one of enterprise design. The expectation should be for major improvement [...] The attitude that the goal is to explain behavior; which is fairly common in academic circles, is not sufficient. The goal should be to find management policies and organizational structures that lead to greater success." (Jay W Forrester, "Industrial Dynamics", 1961)

"System theory is basically concerned with problems of relationships, of structure, and of interdependence rather than with the constant attributes of objects. In general approach it resembles field theory except that its dynamics deal with temporal as well as spatial patterns. Older formulations of system constructs dealt with the closed systems of the physical sciences, in which relatively self-contained structures could be treated successfully as if they were independent of external forces. But living systems, whether biological organisms or social organizations, are acutely dependent on their external environment and so must be conceived of as open systems." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"No matter how difficult or unprecedented the problem, a breakthrough to the best possible solution can come only from a combination of rational analysis, based on the real nature of things, and imaginative reintegration of all the different items into a new pattern, using nonlinear brainpower. This is always the most effective approach to devising strategies for dealing successfully with challenges and opportunities, in the market arena as on the battlefield." (Kenichi Ohmae, "The Mind Of The Strategist", 1982)

"It is, however, fair to say that very few applications of swarm intelligence have been developed. One of the main reasons for this relative lack of success resides in the fact that swarm-intelligent systems are hard to 'program', because the paths to problem solving are not predefined but emergent in these systems and result from interactions among individuals and between individuals and their environment as much as from the behaviors of the individuals themselves. Therefore, using a swarm-intelligent system to solve a problem requires a thorough knowledge not only of what individual behaviors must be implemented but also of what interactions are needed to produce such or such global behavior." (Eric Bonabeau et al, "Swarm Intelligence: From Natural to Artificial Systems", 1999)

"Systems thinking means the ability to see the synergy of the whole rather than just the separate elements of a system and to learn to reinforce or change whole system patterns. Many people have been trained to solve problems by breaking a complex system, such as an organization, into discrete parts and working to make each part perform as well as possible. However, the success of each piece does not add up to the success of the whole. to the success of the whole. In fact, sometimes changing one part to make it better actually makes the whole system function less effectively." (Richard L Daft, "The Leadership Experience", 2002)

"[…] in cybernetics, control is seen not as a function of one agent over something else, but as residing within circular causal networks, maintaining stabilities in a system. Circularities have no beginning, no end and no asymmetries. The control metaphor of communication, by contrast, punctuates this circularity unevenly. It privileges the conceptions and actions of a designated controller by distinguishing between messages sent in order to cause desired effects and feedback that informs the controller of successes or failures." (Klaus Krippendorff, "On Communicating: Otherness, Meaning, and Information", 2009)

"If an emerging system is born complex, there is neither leeway to abandon it when it fails, nor the means to join another, successful one. Such a system would be caught in an immovable grip, congested at the top, and prevented, by a set of confusing but locked–in precepts, from changing." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

Performance Management: Mentoring (Definitions)

 "A technique used to help less skilled or experienced people learn from more experienced people. The mentor is the experienced person and the protégé is the person who is guided. A product manager will benefit throughout his or her career by establishing relationships with others deemed to have a comprehensive set of skills and experiences." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"The process of transferring the lessons of greater experience in a workforce competency to improve the capability of other individuals or workgroups." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

"The offering of experience, emotional support, and guidance by an experienced person to a less experienced person." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"An opportunity for a more experienced person to impart knowledge and expertise to a less experienced person." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"The helping of an employee in formulating her future plans beyond the present role by someone higher in the organization." (Fred MacKenzie, "7 Paths to Managerial Leadership", 2016)

"Provides access to knowledge and experience within a supportive professional relationship. A mentor is usually at a more advanced career stage than the person being mentored." (Christina Lovelock & Debra Paul, "Delivering Business Analysis: The BA Service handbook", 2019)

Systems Engineering: Failure (Just the Quotes)

 "A complex system can fail in an infinite number of ways." (John Gall, "General Systemantics: How systems work, and especially how they fail", 1975)

"A complex system that works is invariably found to have evolved from a simple system that worked. The inverse proposition also appears to be true: A complex system designed from scratch never works and cannot be made to work. You have to start over, beginning with a working simple system." (John Gall, "General Systemantics: How systems work, and especially how they fail", 1975)

"A system represents someone's solution to a problem. The system doesn't solve the problem." (John Gall, "General Systemantics: How systems work, and especially how they fail", 1975)

"Systems Are Seductive. They promise to do a hard job faster, better, and more easily than you could do it by yourself. But if you set up a system, you are likely to find your time and effort now being consumed in the care and feeding of the system itself. New problems are created by its very presence. Once set up, it won't go away, it grows and encroaches. It begins to do strange and wonderful things. Breaks down in ways you never thought possible. It kicks back, gets in the way, and opposes its own proper function. Your own perspective becomes distorted by being in the system. You become anxious and push on it to make it work. Eventually you come to believe that the misbegotten product it so grudgingly delivers is what you really wanted all the time. At that point encroachment has become complete. You have become absorbed. You are now a systems person." (John Gall, "General Systemantics: How systems work, and especially how they fail", 1975)

"The failure of individual subsystems to be sufficiently adaptive to changing environments results in the subsystems forming a collective association that, as a unit, is better able to function in new circumstances. Formation of such an association is a structural change; the behavioral role of the new conglomerate is a junctional change; both types of change are characteristic of the formation of hierarchies." (John L Casti, "On System Complexity: Identification, Measurement, and Management" [in "Complexity, Language, and Life: Mathematical Approaches"] 1986)

"The system always kicks back. - Systems get in the way - or, in slightly more elegant language: Systems tend to oppose their own proper functions. Systems tend to malfunction conspicuously just after their greatest triumph." (John Gall, "Systemantics: The underground text of systems lore", 1986)

"Physical systems are subject to the force of entropy, which increases until eventually the entire system fails. The tendency toward maximum entropy is a movement to disorder, complete lack of resource transformation, and death." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

"Most systems displaying a high degree of tolerance against failures are a common feature: Their functionality is guaranteed by a highly interconnected complex network. A cell's robustness is hidden in its intricate regulatory and metabolic network; society's resilience is rooted in the interwoven social web; the economy's stability is maintained by a delicate network of financial and regulator organizations; an ecosystem's survivability is encoded in a carefully crafted web of species interactions. It seems that nature strives to achieve robustness through interconnectivity. Such universal choice of a network architecture is perhaps more than mere coincidences." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)

"A fundamental reason for the difficulties with modern engineering projects is their inherent complexity. The systems that these projects are working with or building have many interdependent parts, so that changes in one part often have effects on other parts of the system. These indirect effects are frequently unanticipated, as are collective behaviors that arise from the mutual interactions of multiple components. Both indirect and collective effects readily cause intolerable failures of the system. Moreover, when the task of the system is intrinsically complex, anticipating the many possible demands that can be placed upon the system, and designing a system that can respond in all of the necessary ways, is not feasible. This problem appears in the form of inadequate specifications, but the fundamental issue is whether it is even possible to generate adequate specifications for a complex system." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"It is no longer sufficient for engineers merely to design boxes such as computers with the expectation that they would become components of larger, more complex systems. That is wasteful because frequently the box component is a bad fit in the system and has to be redesigned or worse, can lead to system failure. We must learn how to design large-scale, complex systems from the top down so that the specification for each component is derivable from the requirements for the overall system. We must also take a much larger view of systems. We must design the man-machine interfaces and even the system-society interfaces. Systems engineers must be trained for the design of large-scale, complex, man-machine-social systems." (A Wayne Wymore, "Systems Movement: Autobiographical Retrospectives", 2004)

"[…] in cybernetics, control is seen not as a function of one agent over something else, but as residing within circular causal networks, maintaining stabilities in a system. Circularities have no beginning, no end and no asymmetries. The control metaphor of communication, by contrast, punctuates this circularity unevenly. It privileges the conceptions and actions of a designated controller by distinguishing between messages sent in order to cause desired effects and feedback that informs the controller of successes or failures." (Klaus Krippendorff, "On Communicating: Otherness, Meaning, and Information", 2009)

"Experts in the 'Problem' area proceed to elaborate its complexity. They design complex Systems to attack it. This approach guarantees failure, at least for all but the most pedestrian tasks. The problem is a Problem precisely because it is incorrectly conceptualized in the first place, and a large System for studying and attacking the Problem merely locks in the erroneous conceptualization into the minds of everyone concerned. What is required is not a large System, but a different approach. Trying to design a System in the hope that the System will somehow solve the Problem, rather than simply solving the Problem in the first place, is to present oneself with two problems in place of one." (John Gall, "The Systems Bible: The Beginner's Guide to Systems Large and Small"[Systematics 3rd Ed.], 2011)

"Pragmatically, it is generally easier to aim at changing one or a few things at a time and then work out the unexpected effects, than to go to the opposite extreme. Attempting to correct everything in one grand design is appropriately designated as Grandiosity. […] A little Grandiosity goes a long way. […] The diagnosis of Grandiosity is quite elegantly and strictly made on a purely quantitative basis: How many features of the present System, and at what level, are to be corrected at once? If more than three, the plan is grandiose and will fail." (John Gall, "The Systems Bible: The Beginner's Guide to Systems Large and Small"[Systematics 3rd Ed.], 2011)

"Complex systems seem to have this property, with large periods of apparent stasis marked by sudden and catastrophic failures. These processes may not literally be random, but they are so irreducibly complex (right down to the last grain of sand) that it just won’t be possible to predict them beyond a certain level. […] And yet complex processes produce order and beauty when you zoom out and look at them from enough distance." (Nate Silver, "The Signal and the Noise: Why So Many Predictions Fail-but Some Don't", 2012)

"If an emerging system is born complex, there is neither leeway to abandon it when it fails, nor the means to join another, successful one. Such a system would be caught in an immovable grip, congested at the top, and prevented, by a set of confusing but locked–in precepts, from changing." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"Stability is often defined as a resilient system that keeps processing transactions, even if transient impulses (rapid shocks to the system), persistent stresses (force applied to the system over an extended period), or component failures disrupt normal processing." (Michael Hüttermann et al, "DevOps for Developers", 2013)

"Although cascading failures may appear random and unpredictable, they follow reproducible laws that can be quantified and even predicted using the tools of network science. First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between the network structure and dynamics affects the robustness of the whole system." (Albert-László Barabási, "Network Science", 2016)

Systems Engineering: Tools (Just the Quote)

"Systems engineering is most effectively conceived of as a process that starts with the detection of a problem and continues through problem definition, planning and designing of a system, manufacturing or other implementing section, its use, and finally on to its obsolescence. Further, Systems engineering is not a matter of tools alone; It is a careful coordination of process, tools and people." (Arthur D. Hall, "Systems Engineering from an Engineering Viewpoint" In: Systems Science and Cybernetics. Vol.1 Issue.1, 1965)

"[…] cybernetics studies the flow of information round a system, and the way in which this information is used by the system as a means of controlling itself: it does this for animate and inanimate systems indifferently. For cybernetics is an interdisciplinary science, owing as much to biology as to physics, as much to the study of the brain as to the study of computers, and owing also a great deal to the formal languages of science for providing tools with which the behaviour of all these systems can be objectively described." (A Stafford Beer, 1966)

"System theory is a tool which engineers use to help them design the 'best' system to do the job that must be done. A dominant characteristic of system theory is the interest in the analysis and design (synthesis) of systems from an input-output point of view. System theory uses mathematical manipulation of a mathematical model to help design the actual system." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Fitting lines to relationships between variables is the major tool of data analysis. Fitted lines often effectively summarize the data and, by doing so, help communicate the analytic results to others. Estimating a fitted line is also the first step in squeezing further information from the data." (Edward R Tufte, "Data Analysis for Politics and Policy", 1974)

"Fuzzy systems are excellent tools for representing heuristic, commonsense rules. Fuzzy inference methods apply these rules to data and infer a solution. Neural networks are very efficient at learning heuristics from data. They are 'good problem solvers' when past data are available. Both fuzzy systems and neural networks are universal approximators in a sense, that is, for a given continuous objective function there will be a fuzzy system and a neural network which approximate it to any degree of accuracy." (Nikola K Kasabov, "Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering", 1996)

"Linear programming and its generalization, mathematical programming, can be viewed as part of a great revolutionary development that has given mankind the ability to state general goals and lay out a path of detailed decisions to be taken in order to 'best' achieve these goals when faced with practical situations of great complexity. The tools for accomplishing this are the models that formulate real-world problems in detailed mathematical terms, the algorithms that solve the models, and the software that execute the algorithms on computers based on the mathematical theory." (George B Dantzig & Mukund N Thapa, "Linear Programming" Vol I, 1997)

"Delay time, the time between causes and their impacts, can highly influence systems. Yet the concept of delayed effect is often missed in our impatient society, and when it is recognized, it’s almost always underestimated. Such oversight and devaluation can lead to poor decision making as well as poor problem solving, for decisions often have consequences that don’t show up until years later. Fortunately, mind mapping, fishbone diagrams, and creativity/brainstorming tools can be quite useful here." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

"As systems became more varied and more complex, we find that no single methodology suffices to deal with them. This is particularly true of what may be called information intelligent systems - systems which form the core of modern technology. To conceive, design, analyze and use such systems we frequently have to employ the totality of tools that are available. Among such tools are the techniques centered on fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing and related methodologies. It is this conclusion that formed the genesis of the concept of soft computing." (Lotfi A Zadeh, "The Birth and Evolution of Fuzzy Logic: A personal perspective", 1999)

"[…] swarm intelligence is becoming a valuable tool for optimizing the operations of various businesses. Whether similar gains will be made in helping companies better organize themselves and develop more effective strategies remains to be seen. At the very least, though, the field provides a fresh new framework for solving such problems, and it questions the wisdom of certain assumptions regarding the need for employee supervision through command-and-control management. In the future, some companies could build their entire businesses from the ground up using the principles of swarm intelligence, integrating the approach throughout their operations, organization, and strategy. The result: the ultimate self-organizing enterprise that could adapt quickly - and instinctively - to fast-changing markets." (Eric Bonabeau & Christopher Meyer, "Swarm Intelligence: A Whole New Way to Think About Business", Harvard Business Review, 2001)

"A model is a representation in that it (or its properties) is chosen to stand for some other entity (or its properties), known as the target system. A model is a tool in that it is used in the service of particular goals or purposes; typically these purposes involve answering some limited range of questions about the target system." (Wendy S Parker, "Confirmation and Adequacy-for-Purpose in Climate Modelling", Proceedings of the Aristotelian Society, Supplementary Volumes, Vol. 83, 2009)

"System dynamics is an approach to understanding the behaviour of over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system. It also helps the decision maker untangle the complexity of the connections between various policy variables by providing a new language and set of tools to describe. Then it does this by modeling the cause and effect relationships among these variables." (Raed M Al-Qirem & Saad G Yaseen, "Modelling a Small Firm in Jordan Using System Dynamics", 2010)

"Complexity scientists concluded that there are just too many factors - both concordant and contrarian - to understand. And with so many potential gaps in information, almost nobody can see the whole picture. Complex systems have severe limits, not only to predictability but also to measurability. Some complexity theorists argue that modelling, while useful for thinking and for studying the complexities of the world, is a particularly poor tool for predicting what will happen." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"A key discovery of network science is that the architecture of networks emerging in various domains of science, nature, and technology are similar to each other, a consequence of being governed by the same organizing principles. Consequently we can use a common set of mathematical tools to explore these systems."  (Albert-László Barabási, "Network Science", 2016)

"Although cascading failures may appear random and unpredictable, they follow reproducible laws that can be quantified and even predicted using the tools of network science. First, to avoid damaging cascades, we must understand the structure of the network on which the cascade propagates. Second, we must be able to model the dynamical processes taking place on these networks, like the flow of electricity. Finally, we need to uncover how the interplay between the network structure and dynamics affects the robustness of the whole system." (Albert-László Barabási, "Network Science", 2016)

Systems Engineering: Information Processing (Just the Quotes)

"The term 'systems engineering' is a term with an air of romance and of mystery. The romance and the mystery come from its use in the field of guided missiles, rockets, artificial satellites, and space flight. Much of the work being done in these areas is classified and hence much of it is not known to the general public or to this writer. […] From a business point of view, systems engineering is the creation of a deliberate combination of human services, material services, and machine service to accomplish an information processing job. But this is also very nearly a definition of business system analysis. The difference, from a business point of view, therefore, between business system analysis and systems engineering is only one of degree. In general, systems engineering is more total and more goal-oriented in its approach [...]." ("Computers and People" Vol. 5, 1956)

"Cybernetics is the science of the process of transmission, processing and storage of information." (Sergei Sobolew, Woprosy Psychology, 1958)

"The notion of a fuzzy set provides a convenient point of departure for the construction of a conceptual framework which parallels in many respects the framework used in the case of ordinary sets, but is more general than the latter and, potentially, may prove to have a much wider scope of applicability, particularly in the fields of pattern classification and information processing. Essentially, such a framework provides a natural way of dealing with problems in which the source of imprecision is the absence of sharply denned criteria of class membership rather than the presence of random variables." (Lotfi A Zadeh, "Fuzzy Sets", 1965)

"The great difference between the graphic representation of yesterday, which was poorly dissociated from the figurative image, and the graphics of tomorrow, is the disappearance of the congential fixity of the image. […] When one can superimpose, juxtapose, transpose, and permute graphic images in ways that lead to groupings and classings, the graphic image passes from the dead image, the 'illustration,' to the living image, the widely accessible research instrument it is now becoming. The graphic is no longer only the 'representation' of a final simplification, it is a point of departure for the discovery of these simplifications and the means for their justification. The graphic has become, by its manageability, an instrument for information processing." (Jacques Bertin, "Semiology of graphics" ["Semiologie Graphique"], 1967)

"The greater the uncertainty, the greater the amount of decision making and information processing. It is hypothesized that organizations have limited capacities to process information and adopt different organizing modes to deal with task uncertainty. Therefore, variations in organizing modes are actually variations in the capacity of organizations to process information and make decisions about events which cannot be anticipated in advance." (John K Galbraith, "Organization Design", 1977)

"The effective communication of information in visual form, whether it be text, tables, graphs, charts or diagrams, requires an understanding of those factors which determine the 'legibility', 'readability' and 'comprehensibility', of the information being presented. By legibility we mean: can the data be clearly seen and easily read? By readability we mean: is the information set out in a logical way so that its structure is clear and it can be easily scanned? By comprehensibility we mean: does the data make sense to the audience for whom it is intended? Is the presentation appropriate for their previous knowledge, their present information needs and their information processing capacities?" (Linda Reynolds & Doig Simmonds, "Presentation of Data in Science" 4th Ed, 1984)

"Cybernetics is concerned with scientific investigation of systemic processes of a highly varied nature, including such phenomena as regulation, information processing, information storage, adaptation, self-organization, self-reproduction, and strategic behavior. Within the general cybernetic approach, the following theoretical fields have developed: systems theory (system), communication theory, game theory, and decision theory." (Fritz B Simon et al, "Language of Family Therapy: A Systemic Vocabulary and Source Book", 1985)

"Fuzziness, then, is a concomitant of complexity. This implies that as the complexity of a task, or of a system for performing that task, exceeds a certain threshold, the system must necessarily become fuzzy in nature. Thus, with the rapid increase in the complexity of the information processing tasks which the computers are called upon to perform, we are reaching a point where computers will have to be designed for processing of information in fuzzy form. In fact, it is the capability to manipulate fuzzy concepts that distinguishes human intelligence from the machine intelligence of current generation computers. Without such capability we cannot build machines that can summarize written text, translate well from one natural language to another, or perform many other tasks that humans can do with ease because of their ability to manipulate fuzzy concepts." (Lotfi A Zadeh, "The Birth and Evolution of Fuzzy Logic", 1989)

"The cybernetics phase of cognitive science produced an amazing array of concrete results, in addition to its long-term (often underground) influence: the use of mathematical logic to understand the operation of the nervous system; the invention of information processing machines (as digital computers), thus laying the basis for artificial intelligence; the establishment of the metadiscipline of system theory, which has had an imprint in many branches of science, such as engineering (systems analysis, control theory), biology (regulatory physiology, ecology), social sciences (family therapy, structural anthropology, management, urban studies), and economics (game theory); information theory as a statistical theory of signal and communication channels; the first examples of self-organizing systems. This list is impressive: we tend to consider many of these notions and tools an integrative part of our life […]" (Francisco Varela, "The Embodied Mind", 1991)

"Reliable information processing requires the existence of a good code or language, i.e., a set of rules that generate information at a given hierarchical level, and then compress it for use at a higher cognitive level. To accomplish this, a language should strike an optimum balance between variety (stochasticity) and the ability to detect and correct errors (memory)."(John L Casti, "Reality Rules: Picturing the world in mathematics", 1992)

"An artificial neural network is an information-processing system that has certain performance characteristics in common with biological neural networks. Artificial neural networks have been developed as generalizations of mathematical models of human cognition or neural biology, based on the assumptions that: (1) Information processing occurs at many simple elements called neurons. (2) Signals are passed between neurons over connection links. (3) Each connection link has an associated weight, which, in a typical neural net, multiplies the signal transmitted. (4) Each neuron applies an activation function (usually nonlinear) to its net input (sum of weighted input signals) to determine its output signal." (Laurene Fausett, "Fundamentals of Neural Networks", 1994)

"In spite of the insurmountable computational limits, we continue to pursue the many problems that possess the characteristics of organized complexity. These problems are too important for our well being to give up on them. The main challenge in pursuing these problems narrows down fundamentally to one question: how to deal with systems and associated problems whose complexities are beyond our information processing limits? That is, how can we deal with these problems if no computational power alone is sufficient?"  (George Klir, "Fuzzy sets and fuzzy logic", 1995)

"The robustness of the misperceptions of feedback and the poor performance they cause are due to two basic and related deficiencies in our mental model. First, our cognitive maps of the causal structure of systems are vastly simplified compared to the complexity of the systems themselves. Second, we are unable to infer correctly the dynamics of all but the simplest causal maps. Both are direct consequences of bounded rationality, that is, the many limitations of attention, memory, recall, information processing capability, and time that constrain human decision making." (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

"It is not only a metaphor to transform the Internet to a superbrain with self-organizing features of learning and adapting. Information retrieval is already realized by neural networks adapting to the information preferences of a human user with synaptic plasticity. In sociobiology, we can 1 earn from populations of ants and termites how to organize traffic and information processing by swarm intelligence. From a technical point of view, we need intelligent programs distributed in the nets. There are already more or less intelligent virtual organisms {'agents'), learning, self-organizing and adapting to our individual preferences of information, to select our e-mails, to prepare economic transactions or to defend the attacks of hostile computer viruses, like the immune system of our body." (Klaus Mainzer, "Complexity Management in the Age of Globalization", 2006)

"An artificial neural network, often just called a 'neural network' (NN), is an interconnected group of artificial neurons that uses a mathematical model or computational model for information processing based on a connectionist approach to computation. Knowledge is acquired by the network from its environment through a learning process, and interneuron connection strengths (synaptic weighs) are used to store the acquired knowledge." (Larbi Esmahi et al, "Adaptive Neuro-Fuzzy Systems", 2009)

"Many AI systems employ heuristic decision making, which uses a strategy to find the most likely correct decision to avoid the high cost (time) of processing lots of information. We can think of those heuristics as shortcuts or rules of thumb that we would use to make fast decisions." (Jesús Barrasa et al, "Knowledge Graphs: Data in Context for Responsive Businesses", 2021)

Systems Engineering: Ecology (Just the Quotes)

"The general study of the equilibria and dynamics of populations seems to have no name; but as it has probably reached its highest development in the biological study known as 'ecology,' this name may well be given to it." (Kenneth E Boulding, "A Reconstruction of Economics", 1950)

"Can any of us fix anything? No. None of us can do that. We're specialized. Each one of us has his own line, his own work. I understand my work, you understand yours. The tendency in evolution is toward greater and greater specialization. Man's society is an ecology that forces adaptation to it. Continued complexity makes it impossible for us to know anything outside our own personal field - I can't follow the work of the man sitting at the next desk over from me. Too much knowledge has piled up in each field. And there are too many fields." (Philip K. Dick, "The Variable Man", 1952)

"The thing the ecologically illiterate don't realize about an ecosystem is that it's a system. A system! A system maintains a certain fluid stability that can be destroyed by a misstep in just one niche. A system has order, a flowing from point to point. If something dams the flow, order collapses. The untrained miss the collapse until too late. That's why the highest function of ecology is the understanding of consequences." (Frank Herbert, "Dune", 1965)

"Evolution cannot be understood except in the frame of ecosystems." (Ramón Margalef, "Perspectives in Ecological Theory", 1968)

"For some years now the activity of the artist in our society has been trending more toward the function of the ecologist: one who deals with environmental relationships. Ecology is defined as the totality or pattern of relations between organisms and their environment. Thus the act of creation for the new artist is not so much the invention of new objects as the revelation of previously unrecognized relationships between existing phenomena, both physical and metaphysical. So we find that ecology is art in the most fundamental and pragmatic sense, expanding our apprehension of reality." (Gene Youngblood, "Expanded Cinema", 1970) 

"Ecology is the scientific study of the interactions that determine the distribution and abundance of organisms." (Charles J Krebs, "Ecology", 1972)

"It is the intertwined and interacting mechanisms of evolution and ecology, each of which is at the same time a product and a process, that are responsible for life as we see it, and as it has been." (James W. Valentine, "Evolutionary Paleoecology of the Marine Biosphere", 1973)

"This paper introduces a concept of organizational ecology. This refers to the organizational field created by a number of organizations, whose interrelations compose a system at the level of the field as a whole. The overall field becomes the object of inquiry, not the single organization as related to its organization-set. The emergence of organizational ecology from earlier organization theory is traced and illustrated from empirical studies. Its relevance to the task of institution-building, in a world in which the environment has become exceedingly complex and more interdependent, is argued." (Eric Trist , "A concept of organizational eecolog", Australian journal of management 2 (2), 1977)

"We argue that in order to deal with the various inertial pressures the adaptation perspective must be supplemented with a selection orientation. We consider first two broad issues that are preliminary to ecological modelling. The first concerns appropriate units of analysis. Typical analyses of the relation of organizations to environments take the point of view of a single organization facing an environment." (Michael T Hannan, "The Population Ecology of Organizations", 1977)

"The world is a complex, interconnected, finite, ecological–social–psychological–economic system. We treat it as if it were not, as if it were divisible, separable, simple, and infinite. Our persistent, intractable global problems arise directly from this mismatch." (Donella Meadows,"Whole Earth Models and Systems", 1982)

"Ultimately, uncontrolled escalation destroys a system. However, change in the direction of learning, adaptation, and evolution arises from the control of control, rather than unchecked change per se. In general, for the survival and co-evolution of any ecology of systems, feedback processes must be embodied by a recursive hierarchy of control circuits." (Bradford P Keeney, "Aesthetics of Change", 1983)

"To halt the decline of an ecosystem, it is necessary to think like an ecosystem." (Douglas P Wheeler, EPA Journal, 1990)

"Ecological Economics studies the ecology of humans and the economy of nature, the web of interconnections uniting the economic subsystem to the global ecosystem of which it is a part." (Robert Costanza, "Ecological Economics: the science and management of sustainability", 1992)

"The new paradigm may be called a holistic world view, seeing the world as an integrated whole rather than a dissociated collection of parts. It may also be called an ecological view, if the term 'ecological' is used in a much broader and deeper sense than usual. Deep ecological awareness recognizes the fundamental interdependence of all phenomena and the fact that, as individuals and societies we are all embedded in (and ultimately dependent on) the cyclical process of nature." (Fritjof Capra & Gunter A. Pauli," Steering business toward sustainability", 1995)

"Economics emphasizes competition, expansion, and domination; ecology emphasizes cooperation, conservation, and partnership. (Fritjof Capra, "The Web of Life", 1996)

"A major clash between economics and ecology derives from the fact that nature is cyclical, whereas our industrial systems are linear. Our businesses take resources, transform them into products plus waste, and sell the products to consumers, who discard more waste […]" (Fritjof Capra, "The Web of Life", 1996)

"These, then, are some of the basic principles of ecology - interdependence, recycling, partnership, flexibility, diversity, and, as a consequence of all those, sustainability... the survival of humanity will depend on our ecological literacy, on our ability to understand these principles of ecology and live accordingly."(Fritjof Capra, "The Web of Life", 1996)

"Understanding ecological interdependence means understanding relationships. It requires the shifts of perception that are characteristic of systems thinking - from the parts to the whole, from objects to relationships, from contents to patterns. [...] Nourishing the community means nourishing those relationships. (Fritjof Capra, "The Web of Life", 1996)

"Organizations need to undergo fundamental changes, both in order to adapt to the new business environment and to become ecologically sustainable." (Fritjof Capra, "The Hidden Connections", 2002)

"Limiting factors in population dynamics play the role in ecology that friction does in physics. They stop exponential growth, not unlike the way in which friction stops uniform motion. Whether or not ecology is more like physics in a viscous liquid, when the growth-rate-based traditional view is sufficient, is an open question. We argue that this limit is an oversimplification, that populations do exhibit inertial properties that are noticeable. Note that the inclusion of inertia is a generalization—it does not exclude the regular rate-based, first-order theories. They may still be widely applicable under a strong immediate density dependence, acting like friction in physics." (Lev Ginzburg & Mark Colyvan, "Ecological Orbits: How Planets Move and Populations Grow", 2004)

"It is science that brings us an understanding of the true complexity of natural systems. The insights from the science of ecology are teaching us how to work with the checks and balances of nature, and encouraging a new, rational, limited-input, environmentally sound means of vineyard management that offers a third way between the ideologically driven approach of Biodynamics and conventional chemical-based agricultural systems." (Jamie Goode," The Science of Wine: From Vine to Glass", 2005)

"An ecology provides the special formations needed by organizations. Ecologies are: loose, free, dynamic, adaptable, messy, and chaotic. Innovation does not arise through hierarchies. As a function of creativity, innovation requires trust, openness, and a spirit of experimentation - where random ideas and thoughts can collide for re-creation." (George Siemens, "Knowing Knowledge", 2006)

"Knowledge flow can be likened to a river that meanders through the ecology of an organization. In certain areas, the river pools and in other areas it ebbs. The health of the learning ecology of the organization depends on effective nurturing of flow." (George Siemens, "Knowing Knowledge", 2006)

"Nodes and connectors comprise the structure of a network. In contrast, an ecology is a living organism. It influences the formation of the network itself." (George Siemens, "Knowing Knowledge", 2006)

"When we focus on designing ecologies in which people can forage for knowledge, we are less concerned about communicating the minutiae of changing knowledge. Instead, we are creating the conduit through which knowledge will flow." (George Siemens, "Knowing Knowledge", 2006)

"Any new dominant communications medium leads to a new information ecology in society that inevitably changes the way ideas, feelings, wealth, power and influence are distributed and the way collective decisions are made." (Al Gore, "The Assault on Reason", 2007)

"In ecology, we are often interested in exploring the behavior of whole systems of species or ecosystem composed of individual components which interact through biological processes. We are interested not simply in the dynamics of each species or component in isolation, but the dynamics of each species or component in the context of all the others and how those coupled dynamics account for properties of the system as a whole, such as its persistence. This is what people seem to mean when they say that ecology is ‘holistic’, an otherwise rather vague term." (John Pastor, "Mathematical Ecology of Populations and Ecosystems", 2008)

"This new model of development would be based clearly on the goal of sustainable human well-being. It would use measures of progress that clearly acknowledge this goal. It would acknowledge the importance of ecological sustainability, social fairness, and real economic efficiency. Ecological sustainability implies recognizing that natural and social capital are not infinitely substitutable for built and human capital, and that real biophysical limits exist to the expansion of the market economy." (Robert Costanza, "Toward a New Sustainable Economy", 2008)

"Ecology is] the science of relations between organisms and their environment." (Ernst Haeckel)

More quotes on "Ecology" at the-web-of-knowledge.blogspot.com.

Performance Management: Resilience (Definitions)

"The capacity of individuals and the holding environment to contain disequilibrium over time." (Alexander Grashow et al, "The Practice of Adaptive Leadership", 2009)

"Ability to recover easily or to adapt to change and adversity." (Maria de Ludres Cró, "Resilience and Psychomotricity in Preschool Education", 2013)

"The ability to withstand stressful and adverse circumstances in one’s life as if one has some internal protective mechanism." (Constantine Ngara, "Educating Highly Able Students from an African Perspective", 2017)

"A capability to anticipate, prepare for, respond to, and recover from significant multi-hazard threats with minimum damage to social well-being, the economy, and the environment." (Carolyn N Stevenson, "Addressing the Sustainable Development Goals Through Environmental Education", 2019)

"It is the attitude of adapting quickly to different situations in order to achieve the goal in the best way." (Marco A C Paschoalotto et al, "The Role of the Entrepreneur in the Promotion of the Digital Economy", 2019)

"the act of resolving conflicts, turning disruptive changes into new directions, learning from this process, and becoming more successful and satisfied in the process." (Amina Omrane, "Which Are the Appropriate Skills Needed for the Entrepreneurial Success of Startups in the Era of Digitalization?", 2020)

"The ability of human or natural systems to cope with adverse events and be able to effect a quick recovery." (Maria F Casado-Claro, "Fostering Resilience by Empowering Entrepreneurs and Small Businesses in Local Communities in Post-Disaster Scenarios", 2021)

"The word resilience refers to the ability to overcome critical moments and adapt after experiencing some unusual and unexpected situation. It also indicates return to normal." (José G Vargas-Hernández, "Urban Socio-Ecosystems Green Resilience", 2021)

Performance Management: Organizational Learning (Definitions)

[single-loop learning:] "This is adaptive learning which involves detecting and rectifying errors or exceptions within the scope of the organisation’s existing practices, policies and norms of behaviour." (Bernard Burnes, "Managing change : a strategic approach to organisational dynamics" 5th Ed., 2009)

[double-loop learning: "This process involves challenging the appropriateness of an organisation’s basic norms, values, policies and operating procedures." (Bernard Burnes, "Managing change : a strategic approach to organisational dynamics" 5th Ed., 2009)

[triple-loop learning:] "This involves questioning the rationale for the organisation and, in the light of this, radically transforming it." (Bernard Burnes, "Managing change : a strategic approach to organisational dynamics" 5th Ed., 2009)

"This term describes the process of collective, as opposed to individual, learning in an organisation. Its aim is to improve the performance of the organisation by involving everyone in collecting, studying, learning from and acting on information." (Bernard Burnes, "Managing change : a strategic approach to organisational dynamics" 5th Ed., 2009)

"A set of concepts, methods and tools popularized in Peter Senge’s book The Fifth Discipline that enable both individual and collective learning in the context of an organization or social network." (Aldo Romano & Giustina Secundo (Eds.), "Dynamic Learning Networks: Models and Cases in Action", 2009)

[enterprise learning:] "Any system that delivers instruction that is critical to the entire organization and must be disseminated to a large number of people dispersed over a wide geographic area." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed, 2012)

"A discipline concerned with the way individuals, groups, and organizations develop knowledge." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide)", 2017)

"A theory proposing that an organization adjusts to changes in the environment through the learning of its employees." (Thomas L Wheelen & J David Hunger., "Strategic management and business policy: toward global sustainability" 13th Ed., 2012)

Performance Management: Emotional Intelligence (Definitions)

"A gauge of an individual’s ability to control his or her emotions and evaluate and manage the emotions of others. Individuals with high levels of emotional intelligence do an outstanding job at leading teams, managing others, and working with customers." (Gina Abudi & Brandon Toropov, "The Complete Idiot's Guide to Best Practices for Small Business", 2011)

"The capability to identify, assess, and manage the personal emotions of oneself and other people, as well as the collective emotions of groups of people." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"The ability to perceive, control, and evaluate emotions in oneself and in others. US psychologist Daniel Goleman noted that high EQ is common in business leaders and facilitates other leadership traits. |" (DK, "The Business Book", 2014)

"Describes an ability, capacity, or skill to perceive, assess, and manage the emotions of oneself, of others, and of groups." (Project Management Institute, "Project Manager Competency Development Framework 3rd Ed.", 2017)

"The ability to identify, assess, and manage the personal emotions of oneself and other people, as well as the collective emotions of groups of people." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide )", 2017)

"Emotional intelligence is the measurement of an individual’s abilities to recognise and manage their own emotions and the emotions of other people, both individually and in groups." (Christina Lovelock & Debra Paul, "Delivering Business Analysis: The BA Service handbook", 2019)

"The ability to identify, assess, monitor, and control emotions of self to guide thinking and impact effective actions of others." (Joan C Dessinger, "Fundamentals of Performance Improvement 3rd Ed", 2012)

"The ability to identify, assess, and manage your own emotions and the emotions of others; useful in reducing tension and increasing cooperation." (Cate McCoy & James L Haner, "CAPM Certified Associate in Project Management Practice Exams", 2018)

"The ability, capacity, and skill to identify, assess, and manage the emotions of one's self, of others, and of groups." (IQBBA)

Performance Management: Feedback (Definitions)

"The return of information about the status of a process. Example: annual performance reviews return information to an employee about the quality of his or her work." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Casual Loops", 1997)

[360° feedback:] "A performance appraisal system that elicits input from an employee's boss, peers, and subordinates." (Dale Furtwengler, "Ten Minute Guide to Performance Appraisals", 2000)

"Information concerning the correctness of one's performance on a learning task or question. May also include explanations to guide learners to a correct response." (Ruth C Clark, "Building Expertise: Cognitive Methods for Training and Performance Improvement", 2008)

[explanatory feedback:] "Instructional responses to student answers to practice exercises that tell the learners whether they are correct or incorrect and also provide the rationale or a hint guiding the learners to a correct answer." ( Ruth C Clark, "Building Expertise: Cognitive Methods for Training and Performance Improvement", 2008)

[instructional feedback:] "Responses given by a trainer or program that may correct and/or offer explanations to learner responses to practice assignments." (Ruth C Clark, "Building Expertise: Cognitive Methods for Training and Performance Improvement", 2008)

[360° feedback] "A multi-source assessment that taps the collective wisdom of those who work with an individual, including supervisors, peers, direct reports, and internal and external customers." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"Information provided by others designed to help people adjust their behavior, continue successful performance, or establish goals." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"A process in which the effect or output of an action is 'returned' (fed back) to modify the next action." (Project Management Institute, "Navigating Complexity: A Practice Guide", 2014)

[peer feedback:] "A comment given by other learners on the learner’s response to an engagement activity. Peer feedback should be guided either by training or by a template. Peer feedback has been shown to promote learning of the individual giving the feedback." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2016)

[normative feedback:] "An evaluation (often a grade) that compares the learner’s outcome with the outcomes of others. A common example is 'grading on the curve'. Because it directs attention to learners’ egos, normative feedback should be avoided." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2016)

"Information concerning the correctness of one’s performance on a learning task or question. Effective feedback includes an explanation for correct and incorrect responses and should direct attention to the task or task process rather than the ego." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2016)

"A reaction or response to a particular process or activity." (Project Management Institute, "Project Manager Competency Development Framework" 3rd Ed., 2017)

[360° feedback:] "The type of feedback in which project team members, project sponsors, and other stakeholders are surveyed anonymously in regard to the project manager's performance. This can be used to assess baseline competence in order to complete a competence gap analysis and create a development or training plan." (PMI, "Project Manager Competency Development Framework" 3rd Ed., 2017)

"Praising an employee when something good was accomplished (positive) and telling an employee when results are not up to expectations (constructive)." (Fred MacKenzie, "7 Paths to Managerial Leadership", 2016)

Performance Management: Pareto Principle (Definitions)

"A rule that posits that 80 percent of business activity comes from about 20 percent of the customers or clients. Named for Vilfredo Pareto, an Italian economist." (Robert McCrie, "Security Operations Management 2nd Ed.", 2006)

"The general observation that a small amount of effort can derive a great amount of rewards. Also known as the 80/20 rule because it often is stated as 80 percent of the results come from 20 percent of the effort." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"Also known as the 80/20 rule, Pareto’s principle holds that a small number of causes may account for the vast majority of observed instances. For example, a small number of rich people account for the majority of wealth. Likewise, a small number of diseases account for the vast majority of human illnesses. A small number of children account for the majority of the behavioral problems encountered in a classroom. A small number of states or provinces contain the majority of the population of a country. A small number of books, compared with the total number of published books, account for the majority of book sales. Sets of data that follow Pareto’s principle are often said to follow a Zipf distribution, or a power law distribution. These types of distributions are not tractable by standard statistical descriptors. For example, simple measurements, such as average and standard deviation, have virtually no practical meaning when applied to Zipf distributions. Furthermore, the Gaussian distribution does not apply, and none of the statistical inferences built upon an assumption of a Gaussian distribution will hold on data sets that observe Pareto’s principle." (Jules H Berman, "Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information", 2013)

"In the Dynamic Systems Development Method, the assumption that 80-percent of an application’s features will take 20-percent of the project’s total time to implement. (The 80/20-rule often applies to other situations, too. For example, 80-percent of the bugs are usually contained in 20-percent of the code.)" (Rod Stephens, "Beginning Software Engineering", 2015)

"Better known as the 80/20 rule, this observation is that 20% of things will make 80% of difference, i.e. 20% of customers account for 80% of profits (and vice versa)." (Duncan Angwin & Stephen Cummings, "The Strategy Pathfinder" 3rd Ed., 2017)

"Doctrine which shows that approx. 20% of causes create 80% of problems. Also known as 80/20 rule." (Albert Lester, "Project Management, Planning and Control" 7th Ed., 2017)

"Sometimes called the Pareto distribution, the notion that to be strategic organisations should focus on the 20% of the business/customers/suppliers/stakeholders that make 80% of the difference to the business. The potential weakness of using this logic is that it may not adequately reflect dynamic situations." (Duncan Angwin & Stephen Cummings, "The Strategy Pathfinder" 3rd Ed., 2017)

"A general rule of thumb that suggests that 80 percent of the cost comes from 20 percent of the cost factors, or that 80 percent of the value is generated by 20 percent of the people. Also called the 80/20 rule. Used to guide system designers to focus on the aspects that matter most to outcome." (O Sami Saydjari, "Engineering Trustworthy Systems: Get Cybersecurity Design Right the First Time", 2018)

Performance Management: Brainstorming (Definitions)

"A group of people working together to generate ideas." (Timothy J  Kloppenborg et al, "Project Leadership", 2003)

"A creative technique used to come up with ideas or concepts. In Product Management, brainstorming can be used for product ideation or general problem solving." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"A general data gathering and creativity technique that can be used to identify risks, ideas, or solutions to issues by using a group of team members or subject matter experts." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"A group technique for discovering creative solutions to a problem." (Rod Stephens, "Beginning Software Engineering", 2015)

"A problem-solving meeting with specific rules intended to generate a wide range of ideas." (Pamela Schure & Brian Lawley, "Product Management For Dummies", 2017)

"A general data gathering and creativity technique that can be used to identify risks, ideas, or solutions to issues by using a group of team members or subject-matter experts." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies", 2011)

"An idea generation process in which individuals or groups are instructed to generate ideas without criticizing or censoring themselves or one another." (Rachel Heinen et al, "Tools for the Process: Technology to Support Creativity and Innovation", 2015)

"A technique that helps a team to generate ideas" (ITIL)

Performance Management: Practice (Definitions)

"Structured opportunities for the learner to engage with the content by responding to a question or taking an action to solve a problem. Also called interaction." ( Ruth C Clark, "Building Expertise: Cognitive Methods for Training and Performance Improvement", 2008)

"a set of work tasks performed to realize a specific development intent." (Bruce P Douglass, "Real-Time Agility: The Harmony/ESW Method for Real-Time and Embedded Systems Development", 2009)

"Description of an activity essential to, in part or in whole, accomplish a goal of the process area. A practice is a subprocess of a process area that contributes to achieving a process area goal." (Sally A Miller et al, "People CMM: A Framework for Human Capital Management" 2nd Ed., 2009)

"A repeatedly performed, customary way of doing something." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"A specific type of professional or management activity that contributes to the execution of a process and that may employ one or more techniques and tools. " (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies", 2011)

"Structured opportunities for the learner to engage with the content by responding to a question or taking an action to solve a problem. Effective practice exercises prompt psychological engagement that leads to achievement of learning goals." (Ruth C Clark & Richard E Mayer, "e-Learning and the Science of Instruction", 2016)

"A specific type of professional or management activity that contributes to the execution of a process and that may employ one or more techniques and tools." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide )", 2017)

 "a way of working or a way in which work must be done" (ITIL)