🕸Systems Engineering: Complex Systems (Definitions)

"Roughly, by a complex system I mean one made up of a large number of parts that interact in a nonsimple way." (Herbert Simon, "The Architecture of Complexity", Proceedings of the American Philosophical Society Vol. 106 (6), 1962)

"A complex system is one which possesses mathematical images which are not dynamical systems." (Robert Rosen, On complex systems, European Journal of Operational Research Vol. 30 (2), 1987)

"A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques can not easily handle the problem." (M Jamshidi, Autonomous Control on Complex Systems: Robotic Applications, Current Advances in Mechanical Design and Production VII, 2000)

"A highly coupled system where the outcomes of the system are the result of the interactions that occur between its different components." (David Lyell et al, "Health Systems Simulation", Encyclopedia of Healthcare Information Systems, 2008)

"Network-based systems characterized by feedback-driven flow of information, openness, self-organization, and emergence. (Ani Calinescu & Janet Efstathiou, "Measures of Network Structure", Encyclopedia of Networked and Virtual Organizations, 2008) 

"[a complex system is] a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution." (Melanie Mitchell, "Complexity: A Guided Tour", 2009)

"Systems made of several interconnected simple parts which altogether exhibit a high degree of complexity from each emerges a higher order behaviour." (Radu Mutihac, "Mathematical Modeling of Artificial Neural Networks", Encyclopedia of Artificial Intelligence, 2009)

"CS [complex system] is a system composed of many heterogeneous agents, which are nonlinearly interconnected, while the final emergence of the system is completely different than the individual element`s performance." (Shahrooz V Manesha & Massimo Tadi, "Sustainable urban morphology emergence via complex adaptive system analysis: sustainable design in existing contex", Procedia Engineering 21, 2011)

"A system that exhibits a mutual interdependency of components and for which a change in the input parameter(s) can result in a non-proportional large or small change of the system output." (Alexander Kolker, Management Science for Healthcare Applications, Encyclopedia of Business Analytics and Optimization, 2014) 

"A system whose intricacy impedes the forecasting of its behaviour." (Valentina M Ghinea, "Modelling and Simulation of the Need for Harmonizing the European Higher Education Systems", Handbook of Research on Trends in European Higher Education Convergence, 2014)

"A system which is usually composed of large number of possibly heterogeneous interacting agents, which are seen to exhibit emergent behavior." (Stephen E Glavin & Abhijit Sengupta, "Modelling of Consumer Goods Markets: An Agent-Based Computational Approach", Handbook of Research on Managing and Influencing Consumer Behavior, 2015)

"Complex systems are networks made of a number of components that interact with each other, typically in a nonlinear fashion. Complex systems may arise and evolve through self-organization, such that they are neither completely regular nor completely random, permitting the development of emergent behavior at macroscopic scales." (Hiroki Sayama, "Introduction to the Modeling and Analysis of Complex Systems", 2015)

"The occurrence of new phenomena generated unpredictably by the interaction of simple rules and individual mechanisms that are in constant flux and interaction. Emergence suggests something novel is perpetually emerging at a systems/global level as the world and environment constantly shifts and changes at a mechanistic/local level." (Kathy Sanford & Tim Hopper, "Digital Media in the Classroom: Emergent Perspectives for 21st Century Learners", Handbook of Research on Digital Media and Creative Technologies, 2015)

"A system characterized by the number of the elements that constitute it, and by the nature of the interactions between these elements." (Manuela Piscitelli, "Application of Complexity Theory in Representation of the City", Handbook of Research on Chaos and Complexity Theory in the Social Sciences, 2016)

"A complex system means a system whose perceived complicated behaviors can be attributed to one or more of the following characteristics: large number of element, large number of relationships among elements, non-linear and discontinuous relationship, and uncertain characteristics of elements." (Chunfang Zhou, "Fostering Creative Problem Solvers in Higher Education: A Response to Complexity of Societies", Handbook of Research on Creative Problem-Solving Skill Development in Higher Education, 2017)

"System made up of many interconnected elements on various levels; interactions on lower levels give rise to events on higher levels." (Naomi Thompson & Joshua Danish, "Designing BioSim: Playfully Encouraging Systems Thinking in Young Children", Handbook of Research on Serious Games for Educational Applications, 2017)

🕸Systems Engineering: Emergence (Definitions)

"Emergence is the phenomenon of properties, capabilities and behaviours evident in the whole system that are not exclusively ascribable to any of its parts." (Derek Hitchins, "Advanced Systems Thinking, Engineering and Management", 2003)

"The process of complex pattern formation from simpler rules; emergent properties are neither properties had by any parts of the system taken in isolation nor a resultant of a mere summation of properties of parts of the system." (Ani Calinescu & Janet Efstathiou, "Measures of Network Structure", Encyclopedia of Networked and Virtual Organizations, 2008) 

"A process where phenomena at a certain level arise from interactions at lower levels. The term is sometimes used to denote a property of a system not contained in any one of its parts." (Max Lungarella & Gabriel Gómez, "Developmental Robotics", Encyclopedia of Artificial Intelligence, 2009)

"Emergence is defined as the occurrence of new processes operating at a higher level of abstraction then is the level at which the local rules operate." (Jirí Kroc & Peter M A Sloot, "Complex Systems Modeling by Cellular Automata", Encyclopedia of Artificial Intelligence, 2009)

"Phenomenon through which complex systems and patterns emerge from multiple simple and local interactions. Emergence is central to the theory of complex systems." (Marielba Zacarias et al, "Modeling Human Resources in the Emergent Organization", Handbook of Research on E-Transformation and Human Resources Management Technologies, 2009)

"Refers to new unexpected behaviors and patterns that arise out of a multiplicity of relatively simple interactions. An emergent behavior can appear when a number of simple entities (agents) operate in an environment while forming more complex behaviors as a community."  (Andrew Kuznetsov, "Synthetic Biology as a Proof of Systems Biology", Handbook of Research on Systems Biology Applications in Medicine, 2009)

"The process of coherent patterns of behavior arising from the self-organizing aspects of complex systems." (Brian L Heath & Raymond R. Hill, "Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts", Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications, 2010)

"The notion of emergence is used in a variety of disciplines such as evolutionary biology, the philosophy of mind and sociology, as well as in computational and complexity theory. It is associated with non-reductive naturalism, which claims that a hierarchy of levels of reality exist. While the emergent level is constituted by the underlying level, it is nevertheless autonomous from the constituting level. As a naturalistic theory, it excludes non-natural explanations such as vitalistic forces or entelechy. As non-reductive naturalism, emergence theory claims that higher-level entities cannot be explained by lower-level entities." (Martin Neumann, "An Epistemological Gap in Simulation Technologies and the Science of Society", 2011)

"Emergence is a nontrivial relationship between the properties of a system at microscopic and macroscopic scales. Macroscopic properties are called emergent when it is hard to explain them simply from microscopic properties." (Hiroki Sayama, "Introduction to the Modeling and Analysis of Complex Systems", 2015)

"Process whereby global patterns arise through interactions between local and simple entities that themselves do not exhibit such patterns." (Carlos M Fernandes & Ivo D de Sousa, "Digital Swarms: Social Interaction and Emergent Phenomena in Personal Communications Networks, 2017)

"The insurgence, in a group or collective of individuals, of properties that are not shared by any single individual. It is the 'more' in the expression 'the whole is more than just the sum of its constituent parts'." (Alessio Erioli, "Anexact Paths: Computation, Continuity, and Tectonics in the Design Process", Handbook of Research on Form and Morphogenesis in Modern Architectural Contexts, 2018)

"Unexpected phenomena appearing (and often having a regularity or pattern) from a collection of apparently unrelated elements and where the elements themselves do not have the characteristics of the phenomena and that phenomena itself is not contained deductively within the elements." (Jeremy Horne, "Visualizing Big Data From a Philosophical Perspective", Handbook of Research on Big Data Storage and Visualization Techniques, 2018)

"A feature in a complex system that is generated through the dynamic interactions between the parts of a system at one level, and is realized at the next level of organization without intentionality or causality." (A Faye Bres, "Integral Post-Analysis of Design-Based Research of an Organizational Learning Process for Strategic Renewal of Environmental Management", Integral Theory and Transdisciplinary Action Research in Education, 2019)

"Feature of complex systems, meaning that the interactions between system’s components lead to unexpected behavioral properties, resulting from system’s self-organizational processes." (Francesca Costanza, "Managing Patients' Organizations to Improve Healthcare: Emerging Research and Opportunities", 2020)

"The capacity for a system to produce outputs which were unexpected by the original designers." (Kenneth Chen, "The Fallacies of MDA for Novice Designers: Overusing Mechanics and Underusing Aesthetics", Interactivity and the Future of the Human-Computer Interface, 2020)

🕸Systems Engineering: Self-Organization (Definitions)

"Self-organization can be defined as the spontaneous creation of a globally coherent pattern out of local interactions." (Francis Heylighen, "The Science Of Self-Organization And Adaptivity", 1970)

"Self-organization refers to the spontaneous formation of patterns and pattern change in open, nonequilibrium systems." (J A Scott Kelso, "Dynamic Patterns : The Self-organization of Brain and Behavior", 1995)

"[…] self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations." (Fritjof  Capra, "The web of life: a new scientific understanding of living  systems", 1996)

"A system described as self-organizing is one in which elements interact in order to achieve dynamically a global function or behavior." (Carlos Gershenson, "A general methodology for designing self-organizing systems", 2006)

"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." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"The components of a system make local decisions that have a coherent, organizing impact on the system as a whole. Therefore, the system displays organization without any external organizing principle being applied." (Ani Calinescu & Janet Efstathiou, "Measures of Network Structure", Encyclopedia of Networked and Virtual Organizations, 2008) 

"The process by which a system chooses way at a bifurcation point as a result of both individual variability and communication between individuals." (Tomas Backström & Marianne Döös, "Relatonics as a Key Concept for Networked Organizations", Encyclopedia of Networked and Virtual Organizations, 2008)

"A characteristic of complex and adaptive systems that display emergent behavior. A structure that self-organizes and gets its smarts from below; agents residing on a scale start producing behavior that lies one scale above them (e.g., ants create colonies, learners create learning communities)." (Daniel Burgos et al, Design Guidelines for Collaboration and Participation with Examples from the LN4LD, Handbook of Research on Learning Design and Learning Objects, 2009)

"It is a process in which the internal organization of a system, normally an open system, increases in complexity without being guided or managed by an outside source. Self-organizing systems typically exhibit emergent behavior." (Vineet R Khare & Frank Z Wang, "Bio-Inspired Grid Resource Management", Handbook of Research on Grid Technologies and Utility Computing, 2009)

"Self-organization is a process typically occurring within complex systems where a system is continuously fed by energy, which is transformed into a new system state or operational mode by a dissipation of energy and/or information." (Jirí Kroc & Peter M A Sloot, "Complex Systems Modeling by Cellular Automata", Encyclopedia of Artificial Intelligence, 2009)

"The ability of a system to arrange and organize itself spontaneously under appropriate circumstances in a purposeful (non-random) manner without any help of external agencies." (Ali Diab & Andreas Mitschele-Thiel, "Self-Organization Activities in LTE-Advanced Networks", Handbook of Research on Progressive Trends in Wireless Communications and Networking, 2014)

"Self-organization is a dynamical process by which a system spontaneously forms nontrivial macroscopic structures and/or behaviors over time." (Hiroki Sayama, "Introduction to the Modeling and Analysis of Complex Systems", 2015)

"Refers to how a system of agents organizes itself into a higher order and emerges from a set of simple rules in an interconnected network." (Wassim J Aloulou, "Understanding Entrepreneurship through Chaos and Complexity Perspectives", Handbook of Research on Chaos and Complexity Theory in the Social Sciences, 2016)

"The ability of a system to spontaneously arrange its components in a purposeful (non-random) manner, under appropriate conditions but without the help of an external agency." (Kijpokin Kasemsap, "Utilizing Complexity Theory and Complex Adaptive Systems in Global Business", Handbook of Research on Chaos and Complexity Theory in the Social Sciences, 2016)

"A process where a form of global order in a system (emergence of patterns at the global scale) arises by means and as a consequence of local interactions." (Alessio Erioli, "Anexact Paths: Computation, Continuity, and Tectonics in the Design Process", Handbook of Research on Form and Morphogenesis in Modern Architectural Contexts, 2018)

"This is a phenomenon, where elements self-organize under the influence of stimuli. In an organisation for self-organisation three elements are crucial: the purpose, values (principles) and the motivation of employees that is results from their responsibility." (Edyta Abramek, "Training Company Self-Organization", Handbook of Research on Autopoiesis and Self-Sustaining Processes for Organizational Success, 2021)

🕸Systems Engineering: System (Definitions)

"A system is an imaginary machine invented to connect together in the fancy those different movements and effects which are already in reality performed." (Adam Smith, "The Wealth of Nations", 1776)

"A system is a methodical arrangement of propositions and proofs; and without such arrangement, no distinct and certain knowlege of any subject can be obtained." (Johann G Burckhardt, 1797) 

"A system is a set of objects compromising all that stands to one another in a group of connected relations." (Charles S Peirce, "Cambridge Lectures on Reasoning and the Logic of Things: Detached Ideas on Vitally Important Topics", 1898)

"A system is a whole which is composed of various parts. But it is not the same thing as an aggregate or heap. In an aggregate or heap, no essential relation exists between the units of which it is composed. In a heap of grain, or pile of stones, one may take away part without the other part being at all affected thereby. But in a system, each part has a fixed and necessary relation to the whole and to all the other parts." (James E Creighton, "An Introductory Logic"‎, 1909)

"A system is any portion of the universe set aside for certain specified purposes. For our concern, a system is set aside from the universe in a manner that will enable this system to be built without having to consider the total universe. Therefore, the system is set aside from the universe by its inputs and outputs - its boundaries." (Kay Inaba et al, "A rational method for applying behavioral technology to man-machine system design", 1956)

"A System is a set of elements in interaction." (Ludwig von Bertalanffy, "General System Theory", 1968)

"A system is a set of two or more elements that satisfies the following three conditions. (1) The behavior of each element has an effect on the behavior of the whole. (2) The behavior of the elements and their effects on the whole are interdependent. the way each element behaves and the way it affects the whole depends on how at least one other element behaves. (3) However subgroups of the elements are formed, each has an effect on the behavior of the whole and none has an independent effect on it." (Russell L Ackoff, "Creating the Corporate Future", 1981) 

"A system is a network of interdependent components that work together to try to accomplish the aim of the system.” (William E Deming, "The New Economics for Industry, Government, Education”, 1993)

"In the most abstract sense, a system is a set of objects together with relationships among the objects. Such a definition implies that a system has properties, functions, and dynamics distinct from its constituent objects and relationships." (Tom R. Burns, "System Theories", 2006) 

"A complex entity that comprises a set of components, along with their properties, relationships and processes, which is described by an equivalent mathematical model." (Evangelos C Papakitsos et al, "The Challenges of Work-Based Learning via Systemic Modelling in the European Union", 2020)

"A group of elements or parts that are organized and interrelated in a pattern of structures that design a specific set of behaviors, often classified as its 'function' or 'purpose'." (Tatiana C Valencia & Stephanie J Valencia, "Cultivating Flow and Happiness in Children", 2020)

"Any notion or physical entity, comprising of mutually interlinked and interacting parts; a set of elements and relationships between them capable of realizing specified objectives; set of elements with specified structure and enabling logically ordered whole, arranged set of statements, views." (Jaroslaw Zelinski, "Synthesis of MOF, MDA, PIM, MVC, and BCE Notations and Patterns", 2020)

🕸Systems Engineering: Systems Theory (Definitions)

"Systems theory pursues the scientific exploration and understanding of systems that exist in the various realms of experience, in order to arrive at a general theory of systems: an organized expressing of sets of interrelated concepts and principles that apply to all systems." (Béla H Bánáthy, "Systems Design of Education", 1991)

"Systems theory is an interdisciplinary field of science concerned with the nature of complex systems, be they physical or natural or purely mathematical." (Thomas B Sheridan, The System Perspective on Human Factors in Aviation, 2010) 

"Systems theory is the interdisciplinary study of systems in general, with the goal of elucidating principles that can be applied to all types of systems at all nesting levels in all fields of research. The term does not yet have a well-established, precise meaning, but systems theory can reasonably be considered a specialization of systems thinking; alternatively as a goal output of systems science and systems engineering, with an emphasis on generality useful across a broad range of systems (versus the particular models of individual fields)." (Gabriela Walker & Elizabeth Pattison, "Using Bronfenbrenner's Ecological Framework to Design Support Systems for Education and Special Education: Learning About Thought Systems", 2016)

"The assumption that quality of a part of a system can only be understood in its relationship to the whole and investigating the parts in isolation cannot explain their combined effect on the whole system." (Margaret S Suubi, "Education for Sustainable Development (ESD) in Higher Education", 2019) 

"Framework of describing how smaller, multiple units and components work together to create a larger system that is designed to carry out a particular function or meet a certain goal." (RaMonda Horton, "Systems-Based Approaches to Speech-Language Pathology Service Delivery for School Age Children", 2020)

"Is an interdisciplinary study of systems that takes a holistic approach to analysis that focuses on the elements within a system, how they interrelate, how they work over time and within the context of larger systems (e.g., natural or man-made)." (Tatiana C Valencia & Stephanie J Valencia, "Cultivating Flow and Happiness in Children", 2020)

"Systems theory is an interdisciplinary theory about the nature of complex systems in nature, society, and science. It is a framework by which one can use to study, investigate and describe any group of objects that work in collaboration towards a common purpose/goal."

(Cheryl M Cordeiro et al, "Culture From a Value Systems Perspective", 2020)

"The domain of systems inquiry that explores the principles and the description models of the abstract organization of phenomena, in an interdisciplinary manner and independently of their nature (natural or social systems) or scale of existence." (Evangelos C Papakitsos et al, "The Challenges of Work-Based Learning via Systemic Modelling in the European Union", 2020)

"Theory that holds that systems in nature are holistic, interconnected and interdependent. If a change occurs in one part of a system, other parts of the system are affected as well." (Joe Monaco & Edward W Schneider, "Building Performance Systems That Last", 2020)

🚧Project Management: Project Planning (Just the Quotes)

"Planning starts usually with something like a general idea. For one reason or another it seems desirable to reach a certain objective, and how to reach it is frequently not too clear. The first step then is to examine the idea carefully in the light of the means available. Frequently more fact-finding about the situation is required. If this first period of planning is successful, two items emerge: namely, an 'over-all plan' of how to reach the objective and secondly, a decision in regard to the first step of action. Usually this planning has also somewhat modified the original idea. The next period is devoted to executing the first step of the original plan." (Kurt Lewin, "Action research and minority problems", 1946)

"Every company has beloved projects on which if prices had held up, if the contractors had finished on time (or finished at all), if the plans hadn't been altered, if the thing had actually worked, the planned return would have been earned. But since some or all of these calamities [things that don't go as expected] usually happen, any manager who neglects to allow for them is not planning - merely thinking wishfully. Desire for the project has, as usual, overtaken desire for profit." (Ernest Dale, "Planning and developing the company organization structure", 1952)

"Project management is the process by which it is assured that the objective is achieved and resources are not wasted. Planning is one of the two parts of project management. Control is the other. [...] Each project must first be planned in detail. Control is involved with comparing actual progress with the plan and taking corrective action when the two do not correspond. Without the plan, true control is not possible; the need for corrective action, its nature, extent, and urgency cannot he accurately determined." (Robert D Carlsen & James A Lewis, "The Systems Analysis Workbook: A complete guide to project implementation and control", 1973)

"Since software construction is inherently a systems effort - an exercise in complex interrelationships - communication effort is great, and it quickly dominates the decrease in individual task time brought about by partitioning [increasing the workers]. Adding more people then lengthens, not shortens, the schedule." (Frederick Brook, "The Mythical Man-Month", 1975)

"Because one has to be an optimist to begin an ambitious project, it is not surprising that underestimation of completion time is the norm." (Fernando J Corbató, "On Building Systems That Will Fail", 1991)

"If we decide to plan not to lose, we take a defensive posture in which we expend huge amounts of effort trying to prevent and track errors. This will lead us to a very heavyweight planning process in which we try to plan everything up front in a much detail as possible. Such a process will have many review steps, sign-offs, authorizations, and phase gates. Such a planning process is highly adept at making sure that blame can be assigned when something fails; but takes no direct steps towards making sure that the right system is delivered at a reasonable cost." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"One of the purposes of planning is we always want to work on the most valuable thing possible at any given time. We can’t pick features at random and expect them to be most valuable. We have to begin development by taking a quick look at everything that might be valuable, putting all our cards on the table. At the beginning of each iteration the business (remember the balance of power) will pick the most valuable features for the next iteration." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"Planning is not about predicting the future. When you make a plan for developing a piece of software, development is not going to go like that. Not ever. Your customers wouldn’t even be happy if it did, because by the time software gets there, the customers don’t want what was planned, they want something different." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"Projects sometimes fail long before they deliver anything. At some point they may be determined to be too expensive to continue. Or perhaps they took too long to develop and the business need evaporated. Or perhaps the requirements change so often that the developers can never finish one thing without having to stop and start all over on something new. Certainly these are planning failures." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"There are two ways to approach prevention of these planning failures. We can plan not to lose, or we can plan to win. The two are not identical. Planning not to lose is defensive; while planning to win is aggressive. [...] the problem that planning is supposed to solve is simply, to build the right system at the right cost. If we take a defensive posture by planning not to lose, we will be able to hold people accountable for any failures; but at an enormous cost. If we take an aggressive posture and plan to win, we will be unafraid to make errors, and will continuously correct them to meet our goals." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"We plan because: We need to ensure that we are always working on the most important thing we need to do. We need to coordinate with other people. When unexpected events occur we need to understand the consequences for the first two." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"When we plan to win we take direct steps to ensure that we are building the right system at the best possible cost. Every action we take goes towards that end. Instead of trying to plan everything up front, we plan just the next few steps; and then allow customer feedback to correct our trajectory. In this way, we get off the mark quickly, and then continuously correct our direction. Errors are unimportant because they will be corrected quickly." (Kent Beck & Martin Fowler, "Planning Extreme Programming", 2000)

"If you have no plan, you cannot have control, by definition, because it is your plan that tells where you are supposed to be in the first place. Further, if you don’t know where you are, you can’t have control. This comes from your information system. Most organizations have difficulties with both of these." (James P Lewis, "Project Planning, Scheduling, and Control" 3rd Ed., 2001)

"No project can succeed when the team members have no commitment to the plan, so the first rule of project planning is that the people who must do the work should help plan that part of the project. You will not only gain their commitment to the plan, but also most likely cover all of the important issues that you may individually have forgotten."(James P Lewis, "Project Planning, Scheduling, and Control" 3rd Ed., 2001)

"The big fallacy in our assumptions is that the world will stand still while we execute our project plan." (James P Lewis, "Project Planning, Scheduling, and Control" 3rd Ed., 2001)

"Project planning is the key to effective project management. Detailed and accurate planning of a project produces the managerial information that is the basis of project justification (costs, benefits, strategic impact, etc.) and the defining of the business drivers (scope, objectives) that form the context for the technical solution. In addition, project planning also produces the project schedules and resource allocations that are the framework for the other project management processes: tracking, reporting, and review." (Rob Thomsett, "Radical Project Management", 2002)

"If you've been in the software business for any time at all, you know that there are certain common problems that plague one project after another. Missed schedules and creeping requirements are not things that just happen to you once and then go away, never to appear again. Rather, they are part of the territory. We all know that. What's odd is that we don't plan our projects as if we knew it. Instead, we plan as if our past problems are locked in the past and will never rear their ugly heads again. Of course, you know that isn't a reasonable expectation." (Tom DeMarco & Timothy Lister, "Waltzing with Bears: Managing Risk on Software Projects", 2003)

"The pathology of setting a deadline to the earliest articulable date essentially guarantees that the schedule will be missed." (Tom DeMarco & Timothy Lister, "Waltzing with Bears: Managing Risk on Software Projects", 2003)

"Ending up somewhere entirely different from where you expected to go is the norm in this world. Software projects are prime illustrations of the law of unintended consequences, and their innovations and breakthroughs are more often side effects than planned outcomes." (Scott Rosenberg, "Dreaming in Code", 2007)

"[…] in software development, as in all things, plans get dodgier the farther into the future one looks. Any developer who has been around the block will admit that the cavalcade of methodologies over three decades of software history has left the field richer and given programmers useful new tools and ways of thinking about their work. But finding a developer or team that actually subscribes to a particular methodology isn’t easy." (Scott Rosenberg, "Dreaming in Code", 2007)

"The picture of digital progress that so many ardent boosters paint ignores the painful record of actual programmers’ epic struggles to bend brittle code into functional shape. That record is of one disaster after another, marking the field’s historical time line like craters. Anyone contemplating the start of a big software development project today has to contend with this unfathomably discouraging burden of experience. It mocks any newcomer with ambitious plans, as if to say, What makes you think you’re any different?" (Scott Rosenberg, "Dreaming in Code", 2007)

"Users may be annoyed by bugs, and software developers may be disappointed by their inability to perfect their work, and managers may be frustrated by the unreliability of their plans. But in the end, none of that matters as much as the simple fact that software does not work the way we think, and until it does, it is not worth trying to perfect." (Scott Rosenberg, "Dreaming in Code", 2007)

"And even if we make good plans based on the best information available at the time and people do exactly what we plan, the effects of our actions may not be the ones we wanted because the environment is nonlinear and hence is fundamentally unpredictable. As time passes the situation will change, chance events will occur, other agents such as customers or competitors will take actions of their own, and we will find that what we do is only one factor among several which create a new situation." (Stephen Bungay, "The Art of Action: How Leaders Close the Gaps between Plans, Actions, and Results", 2010)

"A project plan is a prediction. It predicts that a team of N people will complete X amount of work by Y date." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Development is a design process. Design processes are generally evaluated by the value they deliver rather than a conformance to plan. Therefore, it makes sense to move away from plan-driven projects and toward value-driven projects. […] The realization that the source code is part of the design, not the product, fundamentally rewires our understanding of software." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"The planning fallacy is the systematic tendency for project plans and budgets to undershoot. […] The reasons for the planning fallacy are partly psychological, partly cultural, and partly to do with our limited ability to think probabilistically." (Paul Gibbons, "The Science of Successful Organizational Change",  2015)

"An effort estimate is not complete without including its assumptions. Estimate assumptions include any and all underlying factors the estimate relies upon. Assumptions are especially important in more rigid estimation environments, but they are a good practice even where expectations are more flexible. Explicitly listing all assumptions helps to remove ambiguity and avoid misunderstandings during project delivery." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"Plans allow us to think through objectives beforehand in the hope of being prepared for delivery. Plans are useful when they preempt conflict, direct efforts in harmony, and align expectations. Plans are not useful when they waste valuable build time or provide a false sense of security, for example, by missing unknown unknowns." (Morgan Evans, "Engineering Manager's Handbook", 2023)

🚧Project Management: Risk (Just the Quotes)

"But the greater the primary risk, the safer and more careful your secondary assumptions must be. A project is only as sound as its weakest assumption, or its largest uncertainty." (Robert Heller, "The Naked Manager: Games Executives Play", 1972)

"Today, most project management practitioners focus on planning failure. If this aspect of the project can be compressed, or even eliminated, then the magnitude of the actual failure, should it occur, would be diminished. A good project management methodology helps to reduce planning failure. Today, we believe that planning failure, when it occurs, is due in large part to the project manager’s inability to perform effective risk management." (Harold Kerzner, "Strategic Planning for Project Management using a Project Management Maturity Model", 2001)

"Risks and benefits always go hand in hand. The reason that a project is full of risk is that it leads you into uncharted waters. It stretches your capability, which means that if you pull it off successfully, it's going to drive your competition batty. The ultimate coup is to stretch your own capability to a point beyond the competition's ability to respond. This is what gives you competitive advantage and helps you build a distinct brand in the market." (Tom DeMarco & Timothy Lister, "Waltzing with Bears: Managing Risk on Software Projects", 2003)

"The business of believing only what you have a right to believe is called risk management." (Tom DeMarco & Timothy Lister, "Waltzing with Bears: Managing Risk on Software Projects", 2003)

"In project management there are two levels of opportunities and risks. Because a project is the pursuit of an opportunity, the first category, the macro opportunity, is the project opportunity itself. The approach to achieving the project opportunity and the mitigation of associated project-level risks are structured into the strategy and tactics of the project cycle, the selected decision gates, the teaming arrangements, key personnel selected, and so on. The second level encompasses the tactical opportunities and risks within the project that become apparent at lower levels of decomposition and as project cycle phases are planned and executed. This can include emerging, unproven technology; incremental and evolutionary methods that promise high returns; and the temptation to circumvent proven practices in order to deliver better, faster, and cheaper." (Kevin Forsberg et al, "Visualizing Project Management: Models and frameworks for mastering complex systems" 3rd Ed., 2005)

"Opportunities and risks are endemic to the project environment. However well planned a project may be, there will always be residual project risk." (Kevin Forsberg et al, "Visualizing Project Management: Models and frameworks for mastering complex systems" 3rd Ed., 2005)

"When we pursue opportunity, we normally incur risk. The opportunity to experience the thrill of an exciting sport like hang gliding or scuba diving brings with it the attendant risks. Many people instinctively make the trade that the thrill is worth the risks. Others decline." (Kevin Forsberg et al, "Visualizing Project Management: Models and frameworks for mastering complex systems" 3rd Ed., 2005)

"For most projects there will be many sources of risk. Assumptions that seem quite reasonable at the start of a project may be proven otherwise if and when conditions in internal or external environments change during the project duration." (Roger Jones & Neil Murra, "Change, Strategy and Projects at Work", 2008)

"Routine tasks are, by their nature, familiar to us. The outcomes of performing routine tasks are therefore usually highly predictable. Project work by contrast includes elements of risk and uncertainty associated with the uniqueness and unfamiliarity of some of the work or the context in which it is carried out. Murphy’s Law expresses a ‘tongue-in-cheek’ but fallacious certainty of things going wrong, if it is possible for them to go wrong." (Roger Jones & Neil Murra, "Change, Strategy and Projects at Work", 2008)

"Whilst culture can help create a sense of belonging and shared destiny, it can also prove to be an obstacle to change especially where the existing culture is risk averse or if the change strategy is perceived by some to challenge prevailing group values. Where radical change is proposed, the achievement of cultural change may actually be a major objective of the proposed change." (Roger Jones & Neil Murra, "Change, Strategy and Projects at Work", 2008)

"A project is usually considered a failure if it is late, is over budget, or does not meet the customer’s expectations. Without the control that project management provides, a project is more likely to have problems with one of these areas. A problem with only one constraint (scope, schedule, cost, resources, quality, and risk) can jeopardize the entire project." (Sandra F Rowe, "Project Management for Small Projects" 3rd Ed., 2020)

🚧Project Management: Laws (Just the Quotes)

"Nothing will ever be attempted if all possible objections must first be overcome." (Samuel Johnson, 1759)

"Remember, if you fail to prepare you are preparing to fail." (H K Williams, 1919)

"If we fail to prepare we prepare to fail." (James H Hope, 1929)

"In anything at all, perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away [...]" (Antoine de Saint Exupéry, "Wind, Sand and Stars", 1939) 

"Work expands so as to fill the time available for its completion." (C Northcote Parkinson, "Parkinson’s Law", 1957) 

"Adding manpower to a late software project makes it later." (Fred Brooks, "The Mythical Man-Month", 1975)

"By failing to plan, you will free very little, if any, time, and by failing to plan you will almost certainly fail […] Exactly because we lack time to plan, we should take time to plan." (Alan Lakein, "How to get control of your time and your life", 1974) 

"Program advocates like to keep bad news covered up until they have spent so much money they can advance the sunk-cost argument; that it's too late to cancel the program because we've spent too much already." (James P Stevenson, "The Pentagon Paradox: The development of the F-18 Hornet", 1993)

Graham's Law: "If they know nothing of what you are doing, they suspect you are doing nothing." (Robert J Graham et al, "The Complete Idiot's Guide to Project Management", 2007) 

O'Brochta's Law: "Project management is about applying common sense with uncommon discipline." (Michael O'Brochta, "Great Project Managers", 2008) 

"No project should be allowed to proceed without clear specification and acceptance  criteria, that are understood by all participants." (Tony Martyr, "Why Projects Fail", 2018)

Augustine's Law: "A bad idea executed to perfection is still a bad idea." (Norman R Augustine)

Cohn's Law: "The more time you spend in reporting on what you are doing, the less time you have to do anything. Stability is achieved when you spend all your time doing nothing but reporting on the nothing you are doing."

Dobbins’ Law: "When in doubt, use a bigger hammer."

Fitzgerald's Law: "There are two states to any large project: Too early to tell and too late to stop." (Ernest Fitzgerald)

Hoggarth's Law: "Attempts to get answers early in a project fail as there are many more wrong questions than right ones. Activity during the early stages should be dedicated to finding the correct questions. Once the correct questions have been identified correct answers will naturally fall out of subsequent work without grief or excitement and there will be understanding of what the project is meant to achieve."

Kinser's Law: "About the time you finish doing something, you know enough to start." (James C Kinser) 

Wolf ’s Law of Management: "The tasks to do immediately are the minor ones; otherwise, you’ll forget them. The major ones are often better to defer. They usually need more time for reflection. Besides, if you forget them, they’ll remind you."

Operations Management: Operations Research (Just the Quotes)

"No science has ever been born on a specific day. Each science emerges out of a convergence of an increased interest in some class of problems and the development of scientific methods, techniques, and tools which are adequate to solve these problems. Operations Research (O. R.) is no exception. Its roots are as old as science and the management function." (C West Churchman et al., "Introduction to Operations Research", 1957)

"An objective of O.R. as it emerged from this evolution of industrial organization, is to provide managers of the organizations with a scientific basis for solving problems involving the interaction of the components of the organization in the best interest of the organization as a whole. A decision which is best for the organization as a whole is called optimum decision." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"The systems approach to problems does not mean that the most generally formulated problem must be solved in one research project. However desirable this may be, it is seldom possible to realize it in practice. In practice, parts of the total problem are usually solved in sequence. In many cases the total problem cannot be formulated in advance but the solution of one phase of it helps define the next phase. For example, a production control project may require determination of the most economic production quantities of different items. Once these are found it may turn out that these quantities cannot be produced on the available equipment in the available time. This, then, gives rise to a new problem whose solution will affect the solution obtained in the first phase." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"The concern of OR with finding an optimum decision, policy, or design is one of its essential characteristics. It does not seek merely to define a better solution to a problem than the one in use; it seeks the best solution... [It] can be characterized as the application of scientific methods, techniques, and tools to problems involving the operations of systems so as to provide those in control of the operations with optimum solutions to the problems." (C West Churchman et al, "Introduction to Operations Research", 1957) 

"Operational research is the application of methods of the research scientist to various rather complex practical operations." (John F T Hassell, "The Scientific Approach", 1965) 

"Operations research (OR) is the securing of improvement in social systems by means of scientific method." (C West Churchman, "Operations research as a profession", 1970)

"Decision theory, as it has grown up in recent years, is a formalization of the problems involved in making optimal choices. In a certain sense - a very abstract sense, to be sure - it incorporates among others operations research, theoretical economics, and wide areas of statistics, among others." (Kenneth Arrow, "The Economics of Information", 1984) 

"The lag between knowing the facts and knowing the system which generates the facts can be considerable. […] Similarly there is a lag in passing from the stage in which sets of empirical observations constitute exciting discoveries, to the stage of insight into underlying mechanism, in every field of management today. In controlling the economy and diplomacy and society at large, in controlling business and industry and commerce, we have collected facts and perhaps identified systems. But we have barely begun to explain their underlying mechanism. This is what operational research is for." (Stanford Beer, "Decision and Control", 1994)

🎓Knowledge Management: Knowledge (Just the Quotes)

"There are two modes of acquiring knowledge, namely, by reasoning and experience. Reasoning draws a conclusion and makes us grant the conclusion, but does not make the conclusion certain, nor does it remove doubt so that the mind may rest on the intuition of truth unless the mind discovers it by the path of experience." (Roger Bacon, "Opus Majus", 1267)

"Knowledge being to be had only of visible and certain truth, error is not a fault of our knowledge, but a mistake of our judgment, giving assent to that which is not true." (John Locke, "An Essay Concerning Human Understanding", 1689)

"[…] the highest probability amounts not to certainty, without which there can be no true knowledge." (John Locke, "An Essay Concerning Human Understanding", 1689)

"It is your opinion, the ideas we perceive by our senses are not real things, but images, or copies of them. Our knowledge therefore is no farther real, than as our ideas are the true representations of those originals. But as these supposed originals are in themselves unknown, it is impossible to know how far our ideas resemble them; or whether they resemble them at all. We cannot therefore be sure we have any real knowledge." (George Berkeley, "Three Dialogues", 1713)

"Our knowledge springs from two fundamental sources of the mind; the first is the capacity of receiving representations (receptivity for impressions), the second is the power of knowing an object through these representations (spontaneity [in the production] of concepts)." (Immanuel Kant, "Critique of Pure Reason", 1781)

"Knowledge is only real and can only be set forth fully in the form of science, in the form of system." (G W Friedrich Hegel, "The Phenomenology of Mind", 1807)

"One may even say, strictly speaking, that almost all our knowledge is only probable; and in the small number of things that we are able to know with certainty, in the mathematical sciences themselves, the principal means of arriving at the truth - induction and analogy - are based on probabilities, so that the whole system of human knowledge is tied up with the theory set out in this essay." (Pierre-Simon Laplace, "Philosophical Essay on Probabilities", 1814) 

"We [...] are profiting not only by the knowledge, but also by the ignorance, not only by the discoveries, but also by the errors of our forefathers; for the march of science, like that of time, has been progressing in the darkness, no less than in the light." (Charles C Colton, "Lacon", 1820)

"Our knowledge of circumstances has increased, but our uncertainty, instead of having diminished, has only increased. The reason of this is, that we do not gain all our experience at once, but by degrees; so our determinations continue to be assailed incessantly by fresh experience; and the mind, if we may use the expression, must always be under arms." (Carl von Clausewitz, "On War", 1832)

"All knowledge is profitable; profitable in its ennobling effect on the character, in the pleasure it imparts in its acquisition, as well as in the power it gives over the operations of mind and of matter. All knowledge is useful; every part of this complex system of nature is connected with every other. Nothing is isolated. The discovery of to-day, which appears unconnected with any useful process, may, in the course of a few years, become the fruitful source of a thousand inventions." (Joseph Henry, "Report of the Secretary" [Sixth Annual Report of the Board of Regents of the Smithsonian Institution for 1851], 1852)

"Isolated facts and experiments have in themselves no value, however great their number may be. They only become valuable in a theoretical or practical point of view when they make us acquainted with the law of a series of uniformly recurring phenomena, or, it may be, only give a negative result showing an incompleteness in our knowledge of such a law, till then held to be perfect." (Hermann von Helmholtz, "The Aim and Progress of Physical Science", 1869)

"Simplification of modes of proof is not merely an indication of advance in our knowledge of a subject, but is also the surest guarantee of readiness for farther progress." (William T Kelvin, "Elements of Natural Philosophy", 1873)

"The whole value of science consists in the power which it confers upon us of applying to one object the knowledge acquired from like objects; and it is only so far, therefore, as we can discover and register resemblances that we can turn our observations to account." (William S Jevons, "The Principles of Science: A Treatise on Logic and Scientific Method", 1874)

"[…] when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of science." (William T Kelvin, "Electrical Units of Measurement", 1883)

"The smallest group of facts, if properly classified and logically dealt with, will form a stone which has its proper place in the great building of knowledge, wholly independent of the individual workman who has shaped it." (Karl Pearson, "The Grammar of Science", 1892)

"Without a theory all our knowledge of nature would be reduced to a mere inventory of the results of observation. Every scientific theory must be regarded as an effort of the human mind to grasp the truth, and as long as it is consistent with the facts, it forms a chain by which they are linked together and woven into harmony." (Thomas Preston, "The Theory of Heat", 1894)

"Knowledge is the distilled essence of our intuitions, corroborated by experience." (Elbert Hubbard, "A Thousand & One Epigrams, 1911)

"It is experience which has given us our first real knowledge of Nature and her laws. It is experience, in the shape of observation and experiment, which has given us the raw material out of which hypothesis and inference have slowly elaborated that richer conception of the material world which constitutes perhaps the chief, and certainly the most characteristic, glory of the modern mind." (Arthur J Balfour, "The Foundations of Belief", 1912)

"We have discovered that it is actually an aid in the search for knowledge to understand the nature of the knowledge we seek." (Arthur S Eddington, "The Philosophy of Physical Science", 1938)

"Science usually advances by a succession of small steps, through a fog in which even the most keen-sighted explorer can seldom see more than a few paces ahead. Occasionally the fog lifts, an eminence is gained, and a wider stretch of territory can be surveyed - sometimes with startling results. A whole science may then seem to undergo a kaleidoscopic ‘rearrangement’, fragments of knowledge being found to fit together in a hitherto unsuspected manner. Sometimes the shock of readjustment may spread to other sciences; sometimes it may divert the whole current of human thought." (James H Jeans, "Physics and Philosophy" 3rd Ed., 1943)

"Every bit of knowledge we gain and every conclusion we draw about the universe or about any part or feature of it depends finally upon some observation or measurement. Mankind has had again and again the humiliating experience of trusting to intuitive, apparently logical conclusions without observations, and has seen Nature sail by in her radiant chariot of gold in an entirely different direction." (Oliver J Lee, "Measuring Our Universe: From the Inner Atom to Outer Space", 1950)

"The essence of knowledge is generalization. That fire can be produced by rubbing wood in a certain way is a knowledge derived by generalization from individual experiences; the statement means that rubbing wood in this way will always produce fire. The art of discovery is therefore the art of correct generalization." (Hans Reichenbach, "The Rise of Scientific Philosophy", 1951)

"Knowledge rests on knowledge; what is new is meaningful because it departs slightly from what was known before; this is a world of frontiers, where even the liveliest of actors or observers will be absent most of the time from most of them." (J Robert Oppenheimer, "Science and the Common Understanding", 1954)

"Knowledge is not something which exists and grows in the abstract. It is a function of human organisms and of social organization. Knowledge, that is to say, is always what somebody knows: the most perfect transcript of knowledge in writing is not knowledge if nobody knows it. Knowledge however grows by the receipt of meaningful information - that is, by the intake of messages by a knower which are capable of reorganising his knowledge." (Kenneth E Boulding, "General Systems Theory - The Skeleton of Science", Management Science Vol. 2 (3), 1956)

"Incomplete knowledge must be considered as perfectly normal in probability theory; we might even say that, if we knew all the circumstances of a phenomenon, there would be no place for probability, and we would know the outcome with certainty." (Félix E Borel, Probability and Certainty", 1963)

"Knowing reality means constructing systems of transformations that correspond, more or less adequately, to reality. They are more or less isomorphic to transformations of reality. The transformational structures of which knowledge consists are not copies of the transformations in reality; they are simply possible isomorphic models among which experience can enable us to choose. Knowledge, then, is a system of transformations that become progressively adequate." (Jean Piaget, "Genetic Epistemology", 1968)

"Scientific knowledge is not created solely by the piecemeal mining of discrete facts by uniformly accurate and reliable individual scientific investigations. The process of criticism and evaluation, of analysis and synthesis, are essential to the whole system. It is impossible for each one of us to be continually aware of all that is going on around us, so that we can immediately decide the significance of every new paper that is published. The job of making such judgments must therefore be delegated to the best and wisest among us, who speak, not with their own personal voices, but on behalf of the whole community of Science. […] It is impossible for the consensus - public knowledge - to be voiced at all, unless it is channeled through the minds of selected persons, and restated in their words for all to hear." (John M Ziman, "Public Knowledge: An Essay Concerning the Social Dimension of Science", 1968)

"Models constitute a framework or a skeleton and the flesh and blood will have to be added by a lot of common sense and knowledge of details."(Jan Tinbergen, "The Use of Models: Experience," 1969)

"Human knowledge is personal and responsible, an unending adventure at the edge of uncertainty." (Jacob Bronowski, "The Ascent of Man", 1973)

"Knowledge is not a series of self-consistent theories that converges toward an ideal view; it is rather an ever increasing ocean of mutually incompatible (and perhaps even incommensurable) alternatives, each single theory, each fairy tale, each myth that is part of the collection forcing the others into greater articulation and all of them contributing, via this process of competition, to the development of our consciousness." (Paul K Feyerabend, "Against Method: Outline of an Anarchistic Theory of Knowledge", 1975)

"Knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone 'memorizes' information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987)

"We admit knowledge whenever we observe an effective (or adequate) behavior in a given context, i.e., in a realm or domain which we define by a question (explicit or implicit)." (Humberto Maturana & Francisco J Varela, "The Tree of Knowledge", 1987)

"We live on an island surrounded by a sea of ignorance. As our island of knowledge grows, so does the shore of our ignorance." (John A Wheeler, Scientific American Vol. 267, 1992)

"Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge." (William E Deming, "The New Economics for Industry, Government, Education", 1993) 

"Discourses are ways of referring to or constructing knowledge about a particular topic of practice: a cluster (or formation) of ideas, images and practices, which provide ways of talking about, forms of knowledge and conduct associated with, a particular topic, social activity or institutional site in society. These discursive formations, as they are known, define what is and is not appropriate in our formulation of, and our practices in relation to, a particular subject or site of social activity." (Stuart Hall, "Representation: Cultural Representations and Signifying Practices", 1997)

"An individual understands a concept, skill, theory, or domain of knowledge to the extent that he or she can apply it appropriately in a new situation." (Howard Gardner, "The Disciplined Mind", 1999)

"Knowledge is factual when evidence supports it and we have great confidence in its accuracy. What we call 'hard fact' is information supported by  strong, convincing evidence; this means evidence that, so far as we know, we cannot deny, however we examine or test it. Facts always can be questioned, but they hold up under questioning. How did people come by this information? How did they interpret it? Are other interpretations possible? The more satisfactory the answers to such questions, the 'harder' the facts." (Joel Best, Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists, 2001)

"Knowledge is in some ways the most important (though intangible) capital of a software engineering organization, and sharing of that knowledge is crucial for making an organization resilient and redundant in the face of change. A culture that promotes open and honest knowledge sharing distributes that knowledge efficiently across the organization and allows that organization to scale over time. In most cases, investments into easier knowledge sharing reap manyfold dividends over the life of a company." (Titus Winters, "Software Engineering at Google: Lessons Learned from Programming Over Time", 2020)

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

🎓Knowledge Management: Information Overload (Just the Quotes)

"Everybody gets so much information all day long that they lose their common sense." (Gertrude Stein, "Reflection on the Atomic Bomb", 1946)

"Every person seems to have a limited capacity to assimilate information, and if it is presented to him too rapidly and without adequate repetition, this capacity will be exceeded and communication will break down." (R Duncan Luce, "Developments in Mathematical Psychology", 1960)

"Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur." (Bertram Gross, "The Managing of Organizations", 1964)

"My experience indicates that most managers receive much more data (if not information) than they can possibly absorb even if they spend all of their time trying to do so. Hence they already suffer from an information overload." (Russell L Ackoff, "Management misinformation systems", 1967)

"One of the effects of living with electric information is that we live habitually in a state of information overload. There's always more than you can cope with." (Marshall McLuhan, "The Best of Ideas", 1967)

"Unless the information overload to which managers are subjected is reduced, any additional information made available by an MIS cannot be expected to be used effectively." (Russell L Ackoff, "Management misinformation systems", 1967)

"People today are in danger of drowning in information; but, because they have been taught that information is useful, they are more willing to drown than they need be. If they could handle information, they would not have to drown at all." (Idries Shah, "Reflections", 1968)

"Faced with information overload, we have no alternative but pattern-recognition."(Marshall McLuhan, "Counterblast", 1969)

"We live in and age of hyper-awareness, our senses extend around the globe, but it's the case of aesthetic overload: our technical zeal has outstripped our psychic capacity to cope with the influx of information." (Gene Youngblood, "Expanded Cinema", 1970)

"[...] in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it." (Herbert Simon, "Designing Organizations for an Information-Rich World", 1971)

"Everyone spoke of an information overload, but what there was in fact was a non-information overload." (Richard S Wurman, "What-If, Could-Be", 1976)

"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)

"We are drowning in information but starved for knowledge." (John Naisbitt, "Megatrends: Ten New Directions Transforming Our Lives", 1982)

"In the Information Age, the first step to sanity is FILTERING. Filter the information: extract for knowledge. Filter first for substance. Filter second for significance. […] Filter third for reliability. […] Filter fourth for completeness." (Marc Stiegler, "David’s Sling", 1988)

"Intuition becomes increasingly valuable in the new information society precisely because there is so much data." (John Naisbit, "Re-Inventing the Corporation", 1988)

"What about confusing clutter? Information overload? Doesn't data have to be ‘boiled down’ and  ‘simplified’? These common questions miss the point, for the quantity of detail is an issue completely separate from the difficulty of reading. Clutter and confusion are failures of design, not attributes of information." (Edward R Tufte, "Envisioning Information", 1990)

"Traditional ways to deal with information - reading, listening, writing, talking - are painfully slow in comparison to 'viewing the big picture'. Those who survive information overload will be those who search for information with broadband thinking but apply it with a single-minded focus." (Kathryn Alesandrini, "Survive Information Overload: The 7 Best Ways to Manage Your Workload by Seeing the Big Picture", 1992)

"'Point of view' is that quintessentially human solution to information overload, an intuitive process of reducing things to an essential relevant and manageable minimum. [...] In a world of hyperabundant content, point of view will become the scarcest of resources." (Paul Saffo, "It's The Context, Stupid", 1994) 

"We live in a world where there is more and more information, and less and less meaning." (Jean Baudrillard, "Simulacra and simulation", 1994)

"Specialization, once a maneuver methodically to collect information, now is a manifestation of information overloads. The role of information has changed. Once justified as a means of comprehending the world, it now generates a conflicting and contradictory, fleeting and fragmentation field of disconnected and undigested data." (Stelarc, From Psycho-Body to Cyber-Systems: Images as Post-human Entities, 1998)

"We all would like to know more and, at the same time, to receive less information. In fact, the problem of a worker in today's knowledge industry is not the scarcity of information but its excess. The same holds for professionals: just think of a physician or an executive, constantly bombarded by information that is at best irrelevant. In order to learn anything we need time. And to make time we must use information filters allowing us to ignore most of the information aimed at us. We must ignore much to learn a little." (Mario Bunge, "Philosophy in Crisis: The Need for Reconstruction", 2001)

"One of the effects of living with electric information is that we live habitually in a state of information overload. There's always more than you can cope with." (Marshall McLuhan, "Understanding Me: Lectures and Interviews" , 2003)

"What’s next for technology and design? A lot less thinking about technology for technology’s sake, and a lot more thinking about design. Art humanizes technology and makes it understandable. Design is needed to make sense of information overload. It is why art and design will rise in importance during this century as we try to make sense of all the possibilities that digital technology now affords." (John Maeda, "Why Apple Leads the Way in Design", 2010) 

"The instinctual shortcut that we take when we have 'too much information' is to engage with it selectively, picking out the parts we like and ignoring the remainder, making allies with those who have made the same choices and enemies of the rest." (Nate Silver, "The Signal and the Noise", 2012)

"Complexity has the propensity to overload systems, making the relevance of a particular piece of information not statistically significant. And when an array of mind-numbing factors is added into the equation, theory and models rarely conform to reality." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"In this time of 'information overload', people do not need more information. They want a story they can relate to." (Maarten Schafer, "Around the World in 80 Brands", 2014)

"Today, technology has lowered the barrier for others to share their opinion about what we should be focusing on. It is not just information overload; it is opinion overload." (Greg McKeown, "Essentialism: The Disciplined Pursuit of Less", 2014)

"There is so much information that our ability to focus on any piece of it is interrupted by other information, so that we bathe in information but hardly absorb or analyse it. Data are interrupted by other data before we've thought about the first round, and contemplating three streams of data at once may be a way to think about none of them." (Rebecca Solnit, "The Encyclopedia of Trouble and Spaciousness", 2014) 

"While having information is a crucial first step, more information isn't necessarily better. Take a look at your bookshelves and the list of seminars you have attended. If you have read more than one book about a subject or attended more than one seminar but still haven’t reached your goals, then your problem is not lack of information but rather lack of implementation." (Gudjon Bergmann)

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

🎓Knowledge Management: Data, Information, Knowledge, Wisdom (Just the Quotes)

 "Knowledge is of two kinds. We know a subject ourselves, or we know where we can find information upon it." (Samuel Johnson, 1775)

"It is almost as difficult to make a man unlearn his errors as his knowledge. Mal-information is more hopeless than non-information; for error is always more busy than ignorance. Ignorance is a blank sheet, on which we may write; but error is a scribbled one, on which we must first erase. Ignorance is contented to stand still with her back to the truth; but error is more presumptuous, and proceeds in the same direction. Ignorance has no light, but error follows a false one. The consequence is, that error, when she retraces her footsteps, has further to go, before she can arrive at the truth, than ignorance." (Charles C Colton, “Lacon”, 1820)

"In every branch of knowledge the progress is proportional to the amount of facts on which to build, and therefore to the facility of obtaining data." (James C Maxwell, [Letter to Lewis Campbell] 1851) 

"[The information of a message can] be defined as the 'minimum number of binary decisions which enable the receiver to construct the message, on the basis of the data already available to him.' These data comprise both the convention regarding the symbols and the language used, and the knowledge available at the moment when the message started." (Dennis Gabor, "Optical transmission" in Information Theory : Papers Read at a Symposium on Information Theory, 1952)

"Knowledge is not something which exists and grows in the abstract. It is a function of human organisms and of social organization. Knowledge, that is to say, is always what somebody knows: the most perfect transcript of knowledge in writing is not knowledge if nobody knows it. Knowledge however grows by the receipt of meaningful information - that is, by the intake of messages by a knower which are capable of reorganising his knowledge." (Kenneth E Boulding, "General Systems Theory - The Skeleton of Science", Management Science Vol. 2 (3), 1956)

"The idea of knowledge as an improbable structure is still a good place to start. Knowledge, however, has a dimension which goes beyond that of mere information or improbability. This is a dimension of significance which is very hard to reduce to quantitative form. Two knowledge structures might be equally improbable but one might be much more significant than the other." (Kenneth E Boulding, "Beyond Economics: Essays on Society", 1968)

"In perception itself, two distinct processes can be discerned. One is the gathering of the primary, sensory data or simple sensing of such things as light, moisture or pressure, and the other is the structuring of such data into information." (Edward Ihnatowicz, "The Relevance of Manipulation to the Process of Perception", 1977) 

"Data, seeming facts, apparent asso­ciations-these are not certain knowledge of something. They may be puzzles that can one day be explained; they may be trivia that need not be explained at all. (Kenneth Waltz, "Theory of International Politics", 1979)

"Knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone 'memorizes' information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"Information is data that has been given meaning by way of relational connection. This 'meaning' can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)

"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987) 

"Probabilities are summaries of knowledge that is left behind when information is transferred to a higher level of abstraction." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Network of Plausible, Inference", 1988)

"Information engineering has been defined with the reference to automated techniques as follows: An interlocking set of automated techniques in which enterprise models, data models and process models are built up in a comprehensive knowledge-base and are used to create and maintain data-processing systems." (James Martin, "Information Engineering, 1989)

"Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge." (William E Deming, "The New Economics for Industry, Government, Education", 1993)

"Knowledge, truth, and information flow in networks and swarm systems. I have always been interested in the texture of scientific knowledge because it appears to be lumpy and uneven. Much of what we collectively know derives from a few small areas, yet between them lie vast deserts of ignorance. I can interpret that observation now as the effect of positive feedback and attractors. A little bit of knowledge illuminates much around it, and that new illumination feeds on itself, so one corner explodes. The reverse also holds true: ignorance breeds ignorance. Areas where nothing is known, everyone avoids, so nothing is discovered. The result is an uneven landscape of empty know-nothing interrupted by hills of self-organized knowledge." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995) 

"Now that knowledge is taking the place of capital as the driving force in organizations worldwide, it is all too easy to confuse data with knowledge and information technology with information." (Peter Drucker, "Managing in a Time of Great Change", 1995)

"Data is discrimination between physical states of things (black, white, etc.) that may convey or not convey information to an agent. Whether it does so or not depends on the agent's prior stock of knowledge." (Max Boisot, "Knowledge Assets", 1998)

"The unit of coding is the most basic segment, or element, of the raw data or information that can be assessed in a meaningful way regarding the phenomenon." (Richard Boyatzis, "Transforming qualitative information", 1998)

"While hard data may inform the intellect, it is largely soft data that generates wisdom." (Henry Mintzberg, "Strategy Safari: A Guided Tour Through The Wilds of Strategic Management", 1998)

"Information is just bits of data. Knowledge is putting them together. Wisdom is transcending them." (Ram Dass, "One-Liners: A Mini-Manual for a Spiritual Life (ed. Harmony", 2007)

"Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon."(Judea Pearl, "Causal inference in statistics: An overview", Statistics Surveys 3, 2009)

"We also use our imagination and take shortcuts to fill gaps in patterns of nonvisual data. As with visual input, we draw conclusions and make judgments based on uncertain and incomplete information, and we conclude, when we are done analyzing the patterns, that out picture is clear and accurate. But is it?" (Leonard Mlodinow, "The Drunkard's Walk: How Randomness Rules Our Lives", 2009) 

"We reach wisdom when we achieve a deep understanding of acquired knowledge, when we not only 'get it', but when new information blends with prior experience so completely that it makes us better at knowing what to do in other situations, even if they are only loosely related to the information from which our original knowledge came. Just as not all the information we absorb leads to knowledge, not all of the knowledge we acquire leads to wisdom." (Alberto Cairo, "The Functional Art", 2011)

"Any knowledge incapable of being revised with advances in data and human thinking does not deserve the name of knowledge." (Jerry Coyne, "Faith Versus Fact", 2015)

"The term data, unlike the related terms facts and evidence, does not connote truth. Data is descriptive, but data can be erroneous. We tend to distinguish data from information. Data is a primitive or atomic state (as in ‘raw data’). It becomes information only when it is presented in context, in a way that informs. This progression from data to information is not the only direction in which the relationship flows, however; information can also be broken down into pieces, stripped of context, and stored as data. This is the case with most of the data that’s stored in computer systems. Data that’s collected and stored directly by machines, such as sensors, becomes information only when it’s reconnected to its context."  (Stephen Few, "Signal: Understanding What Matters in a World of Noise", 2015)

"Real wisdom is not the knowledge of everything, but the knowledge of which things in life are necessary, which are less necessary, and which are completely unnecessary to know." (Lev N Tolstoy)

"The Information Age offers much to mankind, and I would like to think that we will rise to the challenges it presents. But it is vital to remember that information - in the sense of raw data - is not knowledge, that knowledge is not wisdom, and that wisdom is not foresight. But information is the first essential step to all of these." (Arthur C Clark)

🎓Knowledge Management: Domains (Just the Quotes)

"Great discoveries which give a new direction to currents of thoughts and research are not, as a rule, gained by the accumulation of vast quantities of figures and statistics. These are apt to stifle and asphyxiate and they usually follow rather than precede discovery. The great discoveries are due to the eruption of genius into a closely related field, and the transfer of the precious knowledge there found to his own domain." (Theobald Smith, Boston Medical and Surgical Journal Volume 172, 1915)

"Learning is any change in a system that produces a more or less permanent change in its capacity for adapting to its environment. Understanding systems, especially systems capable of understanding problems in new task domains, are learning systems." (Herbert A Simon, "The Sciences of the Artificial", 1968)

"A cognitive system is a system whose organization defines a domain of interactions in which it can act with relevance to the maintenance of itself, and the process of cognition is the actual (inductive) acting or behaving in this domain. Living systems are cognitive systems, and living as a process is a process of cognition. This statement is valid for all organisms, with and without a nervous system." (Humberto R Maturana, "Biology of Cognition", 1970)

"No theory ever agrees with all the facts in its domain, yet it is not always the theory that is to blame. Facts are constituted by older ideologies, and a clash between facts and theories may be proof of progress. It is also a first step in our attempt to find the principles implicit in familiar observational notions." (Paul K Feyerabend, "Against Method: Outline of an Anarchistic Theory of Knowledge", 1975)

"A cognitive map is a specific way of representing a person's assertions about some limited domain, such as a policy problem. It is designed to capture the structure of the person's causal assertions and to generate the consequences that follow front this structure. […]  a person might use his cognitive map to derive explanations of the past, make predictions for the future, and choose policies in the present." (Robert M Axelrod, "Structure of Decision: The cognitive maps of political elites", 1976)

"The thinking person goes over the same ground many times. He looks at it from varying points of view - his own, his arch-enemy’s, others’. He diagrams it, verbalizes it, formulates equations, constructs visual images of the whole problem, or of troublesome parts, or of what is clearly known. But he does not keep a detailed record of all this mental work, indeed could not. […] Deep understanding of a domain of knowledge requires knowing it in various ways. This multiplicity of perspectives grows slowly through hard work and sets the state for the re-cognition we experience as a new insight." (Howard E Gruber, "Darwin on Man", 1981)

"Metaphor [is] a pervasive mode of understanding by which we project patterns from one domain of experience in order to structure another domain of a different kind. So conceived metaphor is not merely a linguistic mode of expression; rather, it is one of the chief cognitive structures by which we are able to have coherent, ordered experiences that we can reason about and make sense of. Through metaphor, we make use of patterns that obtain in our physical experience to organise our more abstract understanding." (Mark Johnson, "The Body in the Mind", 1987)

"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987)

"[…] a mental model is a mapping from a domain into a mental representation which contains the main characteristics of the domain; a model can be ‘run’ to generate explanations and expectations with respect to potential states. Mental models have been proposed in particular as the kind of knowledge structures that people use to understand a specific domain […]" (Helmut Jungermann, Holger Schütz & Manfred Thuering, "Mental models in risk assessment: Informing people about drugs", Risk Analysis 8 (1), 1988)

"Algorithmic complexity theory and nonlinear dynamics together establish the fact that determinism reigns only over a quite finite domain; outside this small haven of order lies a largely uncharted, vast wasteland of chaos." (Joseph Ford, "Progress in Chaotic Dynamics: Essays in Honor of Joseph Ford's 60th Birthday", 1988)

"When partitioning a domain, we divide the information model so that the clusters remain intact. [...] Each section of the information model then becomes a separate subsystem. Note that when the information model is partitioned into subsystems, each object is assigned to exactly one subsystem."  (Stephen J Mellor, "Object-Oriented Systems Analysis: Modeling the World In Data", 1988) 

"While a small domain (consisting of fifty or fewer objects) can generally be analyzed as a unit, large domains must be partitioned to make the analysis a manageable task. To make such a partitioning, we take advantage of the fact that objects on an information model tend to fall into clusters: groups of objects that are interconnected with one another by many relationships. By contrast, relatively few relationships connect objects in different clusters." (Stephen J Mellor, "Object-Oriented Systems Analysis: Modeling the World In Data", 1988) 

"A law explains a set of observations; a theory explains a set of laws. […] a law applies to observed phenomena in one domain (e.g., planetary bodies and their movements), while a theory is intended to unify phenomena in many domains. […] Unlike laws, theories often postulate unobservable objects as part of their explanatory mechanism." (John L Casti, "Searching for Certainty: How Scientists Predict the Future", 1990)

"Generally speaking, problem knowledge for solving a given problem may consist of heuristic rules or formulas that comprise the explicit knowledge, and past-experience data that comprise the implicit, hidden knowledge. Knowledge represents links between the domain space and the solution space, the space of the independent variables and the space of the dependent variables." (Nikola K Kasabov, "Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering", 1996)

"Inference is the process of matching current facts from the domain space to the existing knowledge and inferring new facts. An inference process is a chain of matchings. The intermediate results obtained during the inference process are matched against the existing knowledge. The length of the chain is different. It depends on the knowledge base and on the inference method applied." (Nikola K Kasabov, "Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering", 1996)

"An individual understands a concept, skill, theory, or domain of knowledge to the extent that he or she can apply it appropriately in a new situation." (Howard Gardner, "The Disciplined Mind", 1999)

"Knowledge maps are node-link representations in which ideas are located in nodes and connected to other related ideas through a series of labeled links. They differ from other similar representations such as mind maps, concept maps, and graphic organizers in the deliberate use of a common set of labeled links that connect ideas. Some links are domain specific (e.g., function is very useful for some topic domains...) whereas other links (e.g., part) are more broadly used. Links have arrowheads to indicate the direction of the relationship between ideas." (Angela M. O’Donnell et al, "Knowledge Maps as Scaffolds for Cognitive Processing", Educational Psychology Review Vol. 14 (1), 2002) 

"We build models to increase productivity, under the justified assumption that it's cheaper to manipulate the model than the real thing. Models then enable cheaper exploration and reasoning about some universe of discourse. One important application of models is to understand a real, abstract, or hypothetical problem domain that a computer system will reflect. This is done by abstraction, classification, and generalization of subject-matter entities into an appropriate set of classes and their behavior." (Stephen J Mellor, "Executable UML: A Foundation for Model-Driven Architecture", 2002)

"A domain model is not a particular diagram; it is the idea that the diagram is intended to convey. It is not just the knowledge in a domain expert’s head; it is a rigorously organized and selective abstraction of that knowledge." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Domain experts are usually not aware of how complex their mental processes are as, in the course of their work, they navigate all these rules, reconcile contradictions, and fill in gaps with common sense. Software can’t do this. It is through knowledge crunching in close collaboration with software experts that the rules are clarified, fleshed out, reconciled, or placed out of scope." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Effective domain modelers are knowledge crunchers. They take a torrent of information and probe for the relevant trickle. They try one organizing idea after another, searching for the simple view that makes sense of the mass. Many models are tried and rejected or transformed. Success comes in an emerging set of abstract concepts that makes sense of all the detail. This distillation is a rigorous expression of the particular knowledge that has been found most relevant." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Perception and memory are imprecise filters of information, and the way in which information is presented, that is, the frame, influences how it is received. Because too much information is difficult to deal with, people have developed shortcuts or heuristics in order to come up with reasonable decisions. Unfortunately, sometimes these heuristics lead to bias, especially when used outside their natural domains." (Lucy F Ackert & Richard Deaves, "Behavioral Finance: Psychology, Decision-Making, and Markets", 2010)

"This is always the case in analogical reasoning: Relations between two dissimilar domains never map completely to one another. In fact, it is often the salient similarities between the base and target domains that provoke thought and increase the usefulness of an analogy as a problem-solving tool." (Robbie T Nakatsu, "Diagrammatic Reasoning in AI", 2010)

"Conceptual models are best thought of as design-tools - a way for designers to straighten out and simplify the design and match it to the users’ task-domain, thereby making it clearer to users how they should think about the application. The designers’ responsibility is to devise a conceptual model that seems natural to users based on the users’ familiarity with the task domain. If designers do their job well, the conceptual model will be the basis for users’ mental models of the application." (Jeff Johnson & Austin Henderson, "Conceptual Models", 2011)

"A model or conceptual model is a schematic or representation that describes how something works. We create and adapt models all the time without realizing it. Over time, as you gain more information about a problem domain, your model will improve to better match reality." (James Padolsey, "Clean Code in JavaScript", 2020)

"Knowledge graphs use an organizing principle so that a user (or a computer system) can reason about the underlying data. The organizing principle gives us an additional layer of organizing data (metadata) that adds connected context to support reasoning and knowledge discovery. […] Importantly, some processing can be done without knowledge of the domain, just by leveraging the features of the property graph model (the organizing principle)." (Jesús Barrasa et al, "Knowledge Graphs: Data in Context for Responsive Businesses", 2021)