📊Business Intelligence: Business Intelligence [BI] (Definitions)

"Throughout Holland, Flanders, France, and Germany, he maintained a complete and perfect train of business intelligence. The news of the many battles fought was thus received first by him, and the fall of Namur added to his profits, owing to his early receipt of the news." (Richard M Devens, "Cyclopaedia of Commercial and Business Anecdotes", 1865) [first usage of the term] 

"An automatic system is being developed to disseminate information to the various sections of any industrial, scientific or government organization. This intelligence system will utilize data-processing machines for auto-abstracting and auto-encoding of documents and for creating interest profiles for each of the ‘action points’ in an organization. Both incoming and internally generated documents are automatically abstracted, characterized by a word pattern, and sent automatically to appropriate action points. […] All of these techniques are based on statistical procedures which can be performed on present-day data processing machines. Together with proper communication facilities and input-output equipment a comprehensive system may be assembled to accommodate all information problems of an organization. We call this a Business Intelligence System." (Hans P Luhn, "A Business Intelligence System", IBM Journal, 1958)  [first usage of the term in modern context] 

"The communication facility serving the conduct of a business (in the broad sense) may be referred to as an intelligence system. The notion of intelligence is also defined here, in a more general sense, as ‘the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal’." (Hans P Luhn,"A Business Intelligence System", IBM Journal, 1958)

"The process of accessing and analyzing data and using it to make better business decisions. Business intelligence distinguishes the use of data, which may or may not be valuable, with the use of information, which is always of value in business decisions." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"A generic term to describe leveraging the organization’s internal and external information assets for making better business decisions." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"The processes, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business action. Business intelligence encompasses data warehousing, business analytic tools, and content/knowledge management." (Data Warehousing Institute, 2002)

"Thinking abstractly about an organization, reasoning about the business, organizing large quantities of information about the business in order to define and execute a strategy." (William A Giovinazzo, "Internet-Enabled Business Intelligence", 2002)

"Business intelligence is the set of processes and data structures used to analyze data and information used in strategic decision support. The components of Business Intelligence are the data warehouse, data marts, the DSS interface and the processes to 'get data in' to the data warehouse and to 'get information out'." (Claudia Imhoff et al, "Mastering Data Warehouse Design", 2003)

"The set of products or services used to access and analyze data to turn them into information or knowledge enhancement. It includes decision support and data warehousing." (Margaret Y Chu, "Blissful Data", 2004)

"A category of applications and technologies to guide the analysis and use of detailed business data for improved business decision making. The term is sometimes used synonymously with decision support, though business intelligence is technically much broader." (Jill Dyché & Evan Levy, "Customer Data Integration", 2006)

"An approach to management that allows an organization to define what information is useful and relevant to its corporate decision making. Business intelligence helps decision makers make better decisions faster by converting data into information." (Reed Jacobsen & Stacia Misner, "Microsoft SQL Server 2005 Analysis Services Step by Step", 2006)

"Business Intelligence is defined as getting the right information to the right people at the right time. The term encompasses all the capabilities required to turn data into intelligence that everyone in your organization can trust and use for more effective decision making."(Stefanie V Gerlach et al, "Business Intelligence Competency Centers", 2006)

"The part of information technology that focuses on reporting and analysis currently goes by the name business intelligence (BI)." (Stephen Few, "Information Dashboard Design", 2006)

"Business information and business analyses within the context of key business processes that lead to decisions and actions and which result in improved business performance." (Steve Williams & Nancy Williams, "The Profit Impact of Business Intelligence", 2007)

"The activity of converting data into information." (William H Inmon & Anthony Nesavich, "Tapping into Unstructured Data", 2007)

"Business Intelligence is a method of storing and presenting key enterprise data so that anyone in your company can quickly and easily ask questions of accurate and timely data. Effective BI allows end users to use data to understand why your business got the particular results that it did, to decide on courses of action based on past data, and to accurately forecast future results." (Lynn Langit, "Foundations of SQL Server 2005 Business Intelligence", 2007)

"A generic term to describe leveraging the organization’s internal and external information assets to support improved business decision making. Some commentators use the term business intelligence to refer only to the reporting and analysis of data stored in the data warehouse. Because the industry has not reached agreement, we consistently use the phrase data warehouse/business intelligence (DW/BI) to mean the complete end-to-end system. Though some would argue that you can theoretically deliver BI without a data warehouse, and vice versa, that is ill-advised from our perspective. Linking the two together in the DW/BI acronym further reinforces their dependency." (Ralph Kimball, "The Data Warehouse Lifecycle Toolkit", 2008)

"A method used to analyze and interpret business performance data so that fact-based business decisions can be made. The business data referred to in BI is usually extracted from a variety of domains and databases, and presented in a way to bring about more efficient analysis." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"A somewhat generic term used for computer programs that store, analyze, and broadcast data to users to answer business questions."  (Stuart Mudie et al, "BusinessObjects™ XI Release 2 for Dummies", 2008)

"Business intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision making." (Boris Evelson, Forrester Research, 2008)

"Skills and technologies used to help organizations make better decisions by better understanding their business, their market, and their customers." (Tony Fisher, "The Data Asset", 2009)

"The collection of one or more reports or analyses, using data from the data warehouse, that provide insight into the performance of a business organization. These reports and analyses are typically interactive to enable further understanding of specific areas of interest. They are used to support business professionals in their decision-making processes." (Laura Reeves, "A Manager's Guide to Data Warehousing", 2009)

"BI combines products, technology, and methods to organize key information that management needs to improve profit and performance. More broadly, we think of BI as business information and business analyses within the context of key business processes that lead to decisions and actions and that result in improved business performance. In particular, BI means leveraging information assets within key business processes to achieve improved business performance." (Nancy Williams & Steve Williams, "The Profit Impact of Business Intelligence", 2010)

"Focuses on the collection of those transactions and forming them into a database structure that facilitates analysis." (Anthony D Giordano, "Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture", 2010)

"Generally used synonymously with the information available in an enterprise for making strategic decisions." (Paulraj Ponniah, "Data Warehousing Fundamentals for IT Professionals", 2010)

"Using computer software systematically, throughout an organization, to get a handle on the mountains of data that flow from modern business. BI turns the raw data into ready-to-use business information that becomes an ongoing part of strategic decision-making." (Ken Withee, "Microsoft Business Intelligence For Dummies", 2010)

"Software that enables users to obtain enterprise-wide information for reporting, analytics, data mining, benchmarking, business performance management, and predictive analytics in order to support business decision making." (Janice M Roehl-Anderson, "IT Best Practices for Financial Managers", 2010)

"This is a term that describes a broad variety of analytical applications used by an enterprise to get intelligent and meaningful insight into how the business performed in the past or is currently performing. This insight is typically used to make decisions, giving a business a competitive advantage. BI covers a broad field such as Data Warehousing, data marts, text analytics, data mining, or business reporting to name just a few." (Martin Oberhofer et al, "The Art of Enterprise Information Architecture", 2010)

"A collection of data analysis methods and techniques used by businesses to improve decision making, forecasting, and operational processes in order to gain a competitive advantage in the marketplace." (John R Talburt, "Entity Resolution and Information Quality", 2011)

"A comprehensive, cohesive, and integrated set of tools and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information used to support business decision making." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"Category of applications for gathering, storing, analyzing, and providing access to data to help enterprise users make better decisions." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Software products that create integrated systems across an organization or between an organization and its customers and suppliers to improve management of employee teams, customer service, and supply chains. May be used for strategic planning, budgeting, financial consolidation, decision support, and reporting to support diagnostic and interactive controls." (Leslie G Eldenburg & Susan K Wolcott, "Cost Management 2nd Ed", 2011)

[Strategic BI:] The application of BI tools to provide metrics to executives, often in conjunction with some formal method of business performance management, to help determine if a corporation is on target for meeting its goals and objectives. Used to support long-term corporate goals and objectives." (DAMA International, "The DAMA Dictionary of Data Management" 1st Ed., 2010)

"Business intelligence (BI) is a set of techniques that takes business data and creates information from those data so that managers can make decisions. In that way, organizations create business intelligence." (Michael S Gendron, "Business Intelligence Applied", 2012)

"Business intelligence taps information systems to extract and report data in organized ways that are helpful to decision makers." (John R Schermerhorn Jr, "Management" 12th Ed., 2012)

"Computer-based techniques used in identifying, extracting, and analyzing business data. Common functions of BI technologies are reporting, online analytical processing (OLAP), analytics, data and process mining, complex event processing, business performance management, benchmarking, and predictive analytics." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures" 2nd Ed., 2012)

"A broad classification of information-systems-based technologies that support the identification and presentation of insight. Common historical usage referred primarily to reporting-focused systems, but usage of the term has been broadened by some to include all forms of insight generation (including exploratory data analysis and predictive analytics)." (Evan Stubbs, Delivering Business Analytics: Practical Guidelines for Best Practice, 2013)

"A term often used to describe the range of analysis approaches used to process business data." (Kenneth A Shaw, "Integrated Management of Processes and Information", 2013)

"A broad category of applications and technologies for reporting, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support systems, query and reporting, and online analytical processing (OLAP)." (Jim Davis & Aiman Zeid, "Business Transformation", 2014)

"A process for improving the decision-making process through enhanced data analysis." (Owen P. Hall Jr., "Teaching and Using Analytics in Management Education", 2014)

"Business intelligence is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information for business purposes."(Keith Holdaway, "Harness Oil and Gas Big Data with Analytics", 2014)

"The ability to collect, integrate, and organize the data in a way which received by the right source, at the right time, and via the right tool. It provides basic insights about the data by regenerating reports, queries, alerts, etc." (Shokoufeh Mirzaei, Defining a Business-Driven Optimization Problem, 2014) 

"The practice of reporting what has happened, analyzing contributing data to determine why it happened, and monitoring new data to determine what is happening now. It may include data summarization, visualization, and data interactions capability. Also known as descriptive analytics and reporting." (Brenda L Dietrich et al, "Analytics Across the Enterprise", 2014)

"A broad category of applications, technologies, and processes for integrated acquisition, interpretation, collation, analysis, and exploitation of data to help business users make better decisions in order to improve business operations, reduce uncertainty and apply past experience to develop an exact understanding of business dynamics." (Mandana Farzaneh et al, "Using Fuzzy Logic for Optimizing Business Intelligence Success in Multiple Investment Combinations", 2015)

"Business Intelligence, the set of tools and structures related to the management and the use of data for operational or analytical (decision-making) purposes." (Fernando Iafrate, "From Big Data to Smart Data", 2015)

"Business intelligence is a broad set of information technology (IT) solutions that includes tools for gathering, analyzing, and reporting information to the users about performance of the organization and its environment." (Anil K. Maheshwari, "Business Intelligence and Data Mining", 2015)

"Raw data derived from manufacturing and other business processes that has been organized and structured into meaningful information on which decisions can be based." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"Business intelligence is the process of delivering actionable business decisions from analytical manipulation and presentation of data within the confines of a business environment." (Ahmed Sherif, "Practical Business Intelligence", 2016)

"BI is a popularized, umbrella term that describes a set of concepts and methods used to improve business decision making by using fact-based support systems. The term is sometimes used interchangeably with briefing books and executive information systems. A Business Intelligence system is a data-driven DSS." (Daniel J Power & Ciara Heavin, "Decision Support, Analytics, and Business Intelligence" 3rd Ed., 2017)

"Umbrella term that describe a set of concepts and methods to improve business decision making by using fact-based ­decision support systems. Also, refers to a category of software tools that can be used to extract and analyze data from corporate databases." (Daniel J. Power & Ciara Heavin, "Data-Based Decision Making and Digital Transformation", 2018)

"Business intelligence is getting the right information to the right people at the right time so they can make decisions that ultimately improve performance." (Satyadhyan Chickerur et al, "Forecasting the Demand of Agricultural Crops/Commodity Using Business Intelligence Framework", 2019)

"A technological driven process for analyzing data and presenting information, in such a way that user can take immediate actions and unable decision making." (Neha Garg & Kamlesh Sharma, "Machine Learning in Text Analysis", 2020)

"A set of processes, technologies and tools comprising data warehousing, On-Line Analytical Processing, and information delivery in order to turn data into information and information into knowledge." (Nenad Stefanovic, "Big Data Analytics in Supply Chain Management", 2021)

"A catchall term encompassing a variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources. BI can be used to prepare data for analysis, develop and run queries, and create reports, dashboards and visualizations with the end goal of providing results to decision makers and end users." (Insight Software)

"A process for analyzing data and presenting actionable insights to stakeholders in order to help them make more informed business decisions." (Solutions Review)

"A set of methodologies, processes, architectures, and technologies - supported by organizational structures, roles, and responsibilities - that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision making that contribute to improving overall enterprise performance." (Forrester)

"Encompasses the technologies, applications and practices used in the collection, integration, analysis, and presentation of business information to support better business decision-making." (Accenture)

"Uses technologies, processes, and applications to analyze mostly internal, structured data and business processes to support decision-making. Common functions are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, benchmarking, text mining, predictive analytics, and prescriptive analytics." (Board International)

"The activity of taking data from source systems and turning it into valuable information for business users." (BI System Builders)

"The applications, infrastructure, tools or processes for analyzing data and presenting information to help company executives, managers and others make more informed business decisions." (KDnuggets)

"Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions." (Tableau) [source]

"Business Intelligence (BI) encompasses the technologies, applications and practices used in the collection, integration, analysis, and presentation of business information to support better business decision-making." (Accenture)

"Business intelligence (BI) includes the applications, infrastructure, tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance." (Tibco) [source]

"Business intelligence involves using software to analyze data so companies can make informed decisions." (Xplenty) [source]

"Business Intelligence (BI), is a methodology which covers the compiling, analyzing and interpreting of business data in order to make better-informed decisions. BI data tends to be put together through extensive research across a wide range of sources like industry reports, customer feedback, actual usage data of the company’s products, and competitive research." (kloudless)

"Business intelligence is actually an environment in which business users receive data that is reliable, consistent, understandable, easily manipulated and timely. With this data, business users are able to conduct analyses that yield overall understanding of where the business has been, where it is now and where it will be in the near future. Business intelligence serves two main purposes. It monitors the financial and operational health of the organization (reports, alerts, alarms, analysis tools, key performance indicators and dashboards). It also regulates the operation of the organization providing two-way integration with operational systems and information feedback analysis." (Information Management)

"BI is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analytics. BI parses all the data generated by a business and presents easy-to-digest reports, performance measures, and trends driving management decisions. Business intelligence addresses the needs of casual users, including executives, managers, front-line workers, customers and suppliers. It delivers reports, dashboards and scorecards that are tailored to each user’s role and populated with metrics aligned with strategic objectives and goals. This top-down style is powered by a classic data warehousing structure that consolidates enterprise data and enforces information consistency by transforming shared data into a common data model (schema) and BI semantic layer (metadata)." (Teradata) [source]

"Business intelligence is a data-driven process for analyzing and understanding how organizations work and make better decisions based on real insights. Business intelligence, or BI, has become a popular term across industries, but it is a catch-all term that encompasses various processes, tools, and methodologies that let companies capture data, analyze it, and derive better answers to key questions." (Sisense) [source]

"Business intelligence is a software-driven process allowing organizations to analyze raw data from multiple sources, extracting insights that lead to more effective business decisions.  […] While the term 'business intelligence' describes both a methodology and a category of enterprise software, the primary activity in business intelligence is data analysis. Business intelligence tools and applications correlate data about business performance and process it to determine the best course of action for a wide range of business functions." (Informatica) [source]

"Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information which helps executives, managers and other corporate end users make informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against that data and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers." (Techtarget) [source]

"Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business." (CIO) [source]

"Business intelligence (BI) is the collection of processes, technologies, skills, and applications used to make informed, data-driven business decisions. BI includes data collection, data aggregation, analysis, and meaningful presentation that facilitates decision-making." (Talend) [source]

"Business intelligence is the process by which enterprises use strategies and technologies for analyzing current and historical data, with the objective of improving strategic decision-making and providing a competitive advantage." (OmiSci) [source]

"[...] business intelligence is the process of collecting business data and turning it into information that is meaningful and actionable towards a strategic goal. Or put even more simply, BI is the effective use of data and information to make sound business decisions." (Logi Analytics) [source]

🕸Systems Engineering: Information Theory (Just the Quotes)

"[…] information theory is characterised essentially by its dealing always with a set of possibilities; both its primary data and its final statements are almost always about the set as such, and not about some individual element in the set." (W Ross Ashby, "An Introduction to Cybernetics", 1956)

"The general notion in communication theory is that of information. In many cases, the flow of information corresponds to a flow of energy, e. g. if light waves emitted by some objects reach the eye or a photoelectric cell, elicit some reaction of the organism or some machinery, and thus convey information." (Ludwig von Bertalanffy, "General System Theory", 1968) 

"The 'flow of information' through human communication channels is enormous. So far no theory exists, to our knowledge, which attributes any sort of unambiguous measure to this 'flow'." (Anatol Rapoport, "Modern Systems Research for the Behavioral Scientist", 1969)

"Probability plays a central role in many fields, from quantum mechanics to information theory, and even older fields use probability now that the presence of 'noise' is officially admitted. The newer aspects of many fields start with the admission of uncertainty." (Richard Hamming, "Methods of Mathematics Applied to Calculus, Probability, and Statistics", 1985)

"The field of 'information theory' began by using the old hardware paradigm of transportation of data from point to point." (Marshall McLuhan & Eric McLuhan, Laws of Media: The New Science, 1988)

"Without an understanding of causality there can be no theory of communication. What passes as information theory today is not communication at all, but merely transportation." (Marshall McLuhan & Eric McLuhan, "Laws of Media: The New Science", 1988)

"If quantum communication and quantum computation are to flourish, a new information theory will have to be developed." (Hans Christian von Baeyer, "Information, The New Language of Science", 2003)

"In fact, an information theory that leaves out the issue of noise turns out to have no content." (Hans Christian von Baeyer, "Information, The New Language of Science", 2003)

"In an information economy, entrepreneurs master the science of information in order to overcome the laws of the purely physical sciences. They can succeed because of the surprising power of the laws of information, which are conducive to human creativity. The central concept of information theory is a measure of freedom of choice. The principle of matter, on the other hand, is not liberty but limitation - it has weight and occupies space." (George Gilder, "Knowledge and Power: The Information Theory of Capitalism and How it is Revolutionizing our World", 2013)

"Information theory leads to the quantification of the information content of the source, as denoted by entropy, the characterization of the information-bearing capacity of the communication channel, as related to its noise characteristics, and consequently the establishment of the relationship between the information content of the source and the capacity of the channel. In short, information theory provides a quantitative measure of the information contained in message signals and help determine the capacity of a communication system to transfer this information from source to sink over a noisy channel in a reliable fashion." (Ali Grami, "Information Theory", 2016)

🕸Systems Engineering: Systems Thinking (Just the Quotes)

"A systems approach begins when first you see the world through the eyes of another." (C West Churchman, "The Systems Approach", 1968) 

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

“The notion of ‘system’ has gained central importance in contemporary science, society and life. In many fields of endeavor, the necessity of a ‘systems approach’ or ‘systems thinking’ is emphasized, new professions called ‘systems engineering’, ‘systems analysis’ and the like have come into being, and there can be little doubt that this this concept marks a genuine, necessary, and consequential development in science and world-view.” (Ervin László, “Introduction to Systems Philosophy: Toward a New Paradigm of Contemporary Thought”, 1972)

"A company is a multidimensional system capable of growth, expansion, and self-regulation. It is, therefore, not a thing but a set of interacting forces. Any theory of organization must be capable of reflecting a company's many facets, its dynamism, and its basic orderliness. When company organization is reviewed, or when reorganizing a company, it must be looked upon as a whole, as a total system." (Albert Low, "Zen and Creative Management", 1976)

"There is a strong current in contemporary culture advocating ‘holistic’ views as some sort of cure-all […] Reductionism implies attention to a lower level while holistic implies attention to higher level. These are intertwined in any satisfactory description: and each entails some loss relative to our cognitive preferences, as well as some gain [...] there is no whole system without an interconnection of its parts and there is no whole system without an environment." (Francisco Varela, "On being autonomous: The lessons of natural history for systems theory", 1977)

"Systems thinking is a special form of holistic thinking - dealing with wholes rather than parts. One way of thinking about this is in terms of a hierarchy of levels of biological organization and of the different 'emergent' properties that are evident in say, the whole plant (e.g. wilting) that are not evident at the level of the cell (loss of turgor). It is also possible to bring different perspectives to bear on these different levels of organization. Holistic thinking starts by looking at the nature and behaviour of the whole system that those participating have agreed to be worthy of study. This involves: (i) taking multiple partial views of 'reality' […] (ii) placing conceptual boundaries around the whole, or system of interest and (iii) devising ways of representing systems of interest." (C J Pearson and R L Ison, "Agronomy of Grassland Systems", 1987) 

"Systems thinking is a discipline for seeing the 'structures' that underlie complex situations, and for discerning high from low leverage change. That is, by seeing wholes we learn how to foster health. To do so, systems thinking offers a language that begins by restructuring how we think." (Peter Senge, "The Fifth Discipline", 1990)

"Systems thinking is a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static 'snapshots'. It is a set of general principles- distilled over the course of the twentieth century, spanning fields as diverse as the physical and social sciences, engineering, and management. [...] During the last thirty years, these tools have been applied to understand a wide range of corporate, urban, regional, economic, political, ecological, and even psychological systems. And systems thinking is a sensibility for the subtle interconnectedness that gives living systems their unique character." (Peter Senge, "The Fifth Discipline", 1990)

"Systems thinking is a framework for seeing interrelationships rather than things, for seeing patterns rather than static snapshots. It is a set of general principles spanning fields as diverse as physical and social sciences, engineering and management." (Peter Senge, "The Fifth Discipline", 1990)

"Systems philosophy brings forth a reorganization of ways of thinking. It creates a new worldview, a new paradigm of perception and explanation, which is manifested in integration, holistic thinking, purpose-seeking, mutual causality, and process-focused inquiry.” (Béla H. Bánáthy, "Systems Design of Education”, 1991)

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

"In the new systems thinking, the metaphor of knowledge as a building is being replaced by that of the network. As we perceive reality as a network of relationships, our descriptions, too, form an interconnected network of concepts and models in which there are no foundations. For most scientists such a view of knowledge as a network with no firm foundations is extremely unsettling, and today it is by no means generally accepted. But as the network approach expands throughout the scientific community, the idea of knowledge as a network will undoubtedly find increasing acceptance." (Fritjof Capra," The Web of Life: a new scientific understanding of living systems", 1996)

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

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

"[...] information feedback about the real world not only alters our decisions within the context of existing frames and decision rules but also feeds back to alter our mental models. As our mental models change we change the structure of our systems, creating different decision rules and new strategies. The same information, processed and interpreted by a different decision rule, now yields a different decision. Altering the structure of our systems then alters their patterns of behavior. The development of systems thinking is a double-loop learning process in which we replace a reductionist, narrow, short-run, static view of the world with a holistic, broad, long-term, dynamic view and then redesign our policies and institutions accordingly." (John D Sterman, "Business dynamics: Systems thinking and modeling for a complex world", 2000)

"Systems thinking is based on the theory that a system is, in essence, circular. Using a systems approach in your strategic management, therefore, provides a circular implementing structure that can evolve, with continuously improving, self-checking, and learning capabilities [...]" (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"The systems approach, on the other hand, provides an expanded structural design of organizations as living systems that more accurately reflects reality." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

"This is what systems thinking is all about: the idea of building an organization in which each piece, and partial solution of the organization has the fit, alignment, and integrity with your overall organization as a system, and its outcome of serving the customer." (Stephen G Haines, "The Systems Thinking Approach to Strategic Planning and Management", 2000)

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

"Systems thinking is a mental discipline and framework for seeing patterns and interrelationships. It is important to see organizational systems as a whole because of their complexity. Complexity can overwhelm managers, undermining confidence. When leaders can see the structures that underlie complex situations, they can facilitate improvement. But doing that requires a focus on the big picture." (Richard L Daft, "The Leadership Experience", 2008)

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

"Deep change in mental models, or double-loop learning, arises when evidence not only alters our decisions within the context of existing frames, but also feeds back to alter our mental models. As our mental models change, we change the structure of our systems, creating different decision rules and new strategies. The same information, interpreted by a different model, now yields a different decision. Systems thinking is an iterative learning process in which we replace a reductionist, narrow, short-run, static view of the world with a holistic, broad, long-term, dynamic view, reinventing our policies and institutions accordingly." (John D Sterman, "Learning in and about complex systems", Systems Thinking Vol. 3 2003)

"There exists an alternative to reductionism for studying systems. This alternative is known as holism. Holism considers systems to be more than the sum of their parts. It is of course interested in the parts and particularly the networks of relationships between the parts, but primarily in terms of how they give rise to and sustain in existence the new entity that is the whole whether it be a river system, an automobile, a philosophical system or a quality system." (Michael C. Jackson, "Systems Thinking: Creative Holism for Manager", 2003) 

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

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

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

"Systems thinking focuses on optimizing for the whole, looking at the overall flow of work, identifying what the largest bottleneck is today, and eliminating it." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

More on "Systems Thinking" at the-web-of-knowledge.blogspot.com.

🕸Systems Engineering: Cognitive Maps (Just the Quotes)

"[…] learning consists not in stimulus-response connections but in the building up in the nervous system of sets which function like cognitive maps […] such cognitive maps may be usefully characterized as varying from a narrow strip variety to a broader comprehensive variety." (Edward C Tolman, "Cognitive maps in rats and men", 1948)

"A person is changed by the contingencies of reinforcement under which he behaves; he does not store the contingencies. In particular, he does not store copies of the stimuli which have played a part in the contingencies. There are no 'iconic representations' in his mind; there are no 'data structures stored in his memory'; he has no 'cognitive map' of the world in which he has lived. He has simply been changed in such a way that stimuli now control particular kinds of perceptual behavior." (Burrhus F Skinner, "About behaviorism", 1974)

"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 concepts a person uses are represented as points, and the causal links between these concepts are represented as arrows between these points. This gives a pictorial representation of the causal assertions of a person as a graph of points and arrows. This kind of representation of assertions as a graph will be called a cognitive map. The policy alternatives, all of the various causes and effects, the goals, and the ultimate utility of the decision maker can all be thought of as concept variables, and represented as points in the cognitive map. The real power of this approach ap pears when a cognitive map is pictured in graph form; it is then relatively easy to see how each of the concepts and causal relation ships relate to each other, and to see the overall structure of the whole set of portrayed assertions." (Robert Axelrod, "The Cognitive Mapping Approach to Decision Making" [in "Structure of Decision: The Cognitive Maps of Political Elites"], 1976)

"The cognitive map is not a picture or image which 'looks like' what it represents; rather, it is an information structure from which map-like images can be reconstructed and from which behaviour dependent upon place information can be generated." (John O'Keefe & Lynn Nadel, "The Hippocampus as a Cognitive Map", 1978)

"A fuzzy cognitive map or FCM draws a causal picture. It ties facts and things and processes to values and policies and objectives. And it lets you predict how complex events interact and play out. [...] Neural nets give a shortcut to tuning an FCM. The trick is to let the fuzzy causal edges change as if they were synapses in a neural net. They cannot change with the same math laws because FCM edges stand for causal effect not signal flow. We bombard the FCM nodes with real data. The data state which nodes are on or off and to which degree at each moment in time. Then the edges grow among the nodes."  (Bart Kosko, "Fuzzy Thinking: The new science of fuzzy logic", 1993)

"Under the label 'cognitive maps', mental models have been conceived of as the mental representation of spatial aspects of the environment. A mental model, in this sense, comprises the topology of an area, including relevant districts, landmarks, and paths." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"Bounded rationality simultaneously constrains the complexity of our cognitive maps and our ability to use them to anticipate the system dynamics. Mental models in which the world is seen as a sequence of events and in which feedback, nonlinearity, time delays, and multiple consequences are lacking lead to poor performance when these elements of dynamic complexity are present. Dysfunction in complex systems can arise from the misperception of the feedback structure of the environment. But rich mental models that capture these sources of complexity cannot be used reliably to understand the dynamics. Dysfunction in complex systems can arise from faulty mental simulation-the misperception of feedback dynamics. These two different bounds on rationality must both be overcome for effective learning to occur. Perfect mental models without a simulation capability yield little insight; a calculus for reliable inferences about dynamics yields systematically erroneous results when applied to simplistic models." (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

"Even if our cognitive maps of causal structure were perfect, learning, especially double-loop learning, would still be difficult. To use a mental model to design a new strategy or organization we must make inferences about the consequences of decision rules that have never been tried and for which we have no data. To do so requires intuitive solution of high-order nonlinear differential equations, a task far exceeding human cognitive capabilities in all but the simplest systems."  (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

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

"Eliciting and mapping the participant's mental models, while necessary, is far from sufficient [...] the result of the elicitation and mapping process is never more than a set of causal attributions, initial hypotheses about the structure of a system, which must then be tested. Simulation is the only practical way to test these models. The complexity of the cognitive maps produced in an elicitation workshop vastly exceeds our capacity to understand their implications. Qualitative maps are simply too ambiguous and too difficult to simulate mentally to provide much useful information on the adequacy of the model structure or guidance about the future development of the system or the effects of policies." (John D Sterman, "Learning in and about complex systems", Systems Thinking Vol. 3 2003)

"When an individual uses causal mapping to help clarify their own thinking, we call this technique cognitive mapping, because it is related to personal thinking or cognition. When a group maps their own ideas, we call it oval mapping, because we often use oval-shaped cards to record individuals’ ideas so that they can be arranged into a group’s map. Cognitive maps and oval maps can be used to create a strategic plan, because the maps include goals, strategies and actions, just like strategic plans." (John M Bryson et al, "Visible Thinking: Unlocking Causal Mapping For Practical Business Results", 2004)

🕸Systems Engineering: Emergence (Just the Quotes)

"[Hierarchy is] the principle according to which entities meaningfully treated as wholes are built up of smaller entities which are themselves wholes […] and so on. In hierarchy, emergent properties denote the levels." (Peter Checkland, "Systems Thinking, Systems Practice", 1981)

"[…] 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)

"It may not be obvious at first, but the study of emergence and model-building go hand in hand. The essence of model-building is shearing away detail to get at essential elements. A model, by concentrating on selected aspects of the world, makes possible the prediction and planning that reveal new possibilities. That is exactly the problem we face in trying to develop a scientific understanding of emergence." (John H Holland, "Emergence" , Philosophica 59, 1997)

"When the behavior of the system depends on the behavior of the parts, the complexity of the whole must involve a description of the parts, thus it is large. The smaller the parts that must be described to describe the behavior of the whole, the larger the complexity of the entire system. […] 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)

"Emergent self-organization in multi-agent systems appears to contradict the second law of thermodynamics. This paradox has been explained in terms of a coupling between the macro level that hosts self-organization (and an apparent reduction in entropy), and the micro level (where random processes greatly increase entropy). Metaphorically, the micro level serves as an entropy 'sink', permitting overall system entropy to increase while sequestering this increase from the interactions where self-organization is desired." (H Van Dyke Parunak & Sven Brueckner, "Entropy and Self-Organization in Multi-Agent Systems", Proceedings of the International Conference on Autonomous Agents, 2001)

"The phenomenon of emergence takes place at critical points of instability that arise from fluctuations in the environment, amplified by feedback loops." (Fritjof Capra, "The Hidden Connections", 2002)

"This spontaneous emergence of order at critical points of instability is one of the most important concepts of the new understanding of life. It is technically known as self-organization and is often referred to simply as ‘emergence’. It has been recognized as the dynamic origin of development, learning and evolution. In other words, creativity-the generation of new forms-is a key property of all living systems. And since emergence is an integral part of the dynamics of open systems, we reach the important conclusion that open systems develop and evolve. Life constantly reaches out into novelty." (Fritjof  Capra, "The Hidden Connections", 2002)

"Emergence is not really mysterious, although it may be complex. Emergence is brought about by the interactions between the parts of a system. The galloping horse illusion depends upon the persistence of the human retina/brain combination, for instance. Elemental gases bond in combination by sharing outer electrons, thereby altering the appearance and behavior of the combination. In every case of emergence, the source is interaction between the parts - sometimes, as with the brain, very many parts - so that the phenomenon defies simple explanation." (Derek Hitchins, "Advanced Systems Thinking, Engineering and Management", 2003)

"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)

"Another typical feature of theories of emergence is the layered view of nature. On this view, all things in nature belong to a certain level of existence, each according to its characteristic properties. These levels of existence constitute a hierarchy of increasing complexity that also corresponds to their order of appearance in the course of evolution." (Markus Eronen, "Emergence in the Philosophy of Mind", 2004)

"The basic concept of complexity theory is that systems show patterns of organization without organizer (autonomous or self-organization). Simple local interactions of many mutually interacting parts can lead to emergence of complex global structures. […] Complexity originates from the tendency of large dynamical systems to organize themselves into a critical state, with avalanches or 'punctuations' of all sizes. In the critical state, events which would otherwise be uncoupled became correlated." (Jochen Fromm, "The Emergence of Complexity", 2004)

"Complexity arises when emergent system-level phenomena are characterized by patterns in time or a given state space that have neither too much nor too little form. Neither in stasis nor changing randomly, these emergent phenomena are interesting, due to the coupling of individual and global behaviours as well as the difficulties they pose for prediction. Broad patterns of system behaviour may be predictable, but the system's specific path through a space of possible states is not." (Steve Maguire et al, "Complexity Science and Organization Studies", 2006)

"The beauty of nature insists on taking its time. Everything is prepared. Nothing is rushed. The rhythm of emergence is a gradual, slow beat; always inching its way forward, change remains faithful to itself until the new unfolds in the full confidence of true arrival. Because nothing is abrupt, the beginning of spring nearly always catches us unawares. It is there before we see it; and then we can look nowhere without seeing it. (John O'Donohue, "To Bless the Space Between Us: A Book of Blessings", 2008)

"Although the potential for chaos resides in every system, chaos, when it emerges, frequently stays within the bounds of its attractor(s): No point or pattern of points is ever repeated, but some form of patterning emerges, rather than randomness. Life scientists in different areas have noticed that life seems able to balance order and chaos at a place of balance known as the edge of chaos. Observations from both nature and artificial life suggest that the edge of chaos favors evolutionary adaptation." (Terry Cooke-Davies et al, "Exploring the Complexity of Projects", 2009)

"If universality is one of the observed characteristics of complex dynamical systems in many fields of study, a second characteristic that flows from the study of these systems is that of emergence. As self-organizing systems go about their daily business, they are constantly exchanging matter and energy with their environment, and this allows them to remain in a state that is far from equilibrium. That allows spontaneous behavior to give rise to new patterns." (Terry Cooke-Davies et al, "Exploring the Complexity of Projects", 2009)

"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)

"System theorists know that it's easy to couple simple-to-understand systems into a ‘super system’ that's capable of displaying behavioral modes that cannot be seen in any of its constituent parts. This is the process called ‘emergence’." (John L Casti, [interview with Austin Allen], 2012)

"Every system that has existed emerged somehow, from somewhere, at some point. Complexity science emphasizes the study of how systems evolve through their disorganized parts into an organized whole." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"Things evolve to evolve. Evolutionary processes are the linchpin of change. These processes of discovery represent a complexity of simple systems that flux in perpetual tension as they teeter at the edge of chaos. This whirlwind of emergence is responsible for the spontaneous order and higher, organized complexity so noticeable in biological evolution - one–celled critters beefing up to become multicellular organisms." (Lawrence K Samuels, "Defense of Chaos: The Chaology of Politics, Economics and Human Action", 2013)

"This spontaneous emergence of order at critical points of instability, which is often referred to simply as 'emergence', is one of the hallmarks of life. It has been recognized as the dynamic origin of development, learning, and evolution. In other words, creativity-the generation of new forms-is a key property of all living systems." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

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

🕸Systems Engineering: Connectedness (Just the Quotes)

"The first attempts to consider the behavior of so-called 'random neural nets' in a systematic way have led to a series of problems concerned with relations between the 'structure' and the 'function' of such nets. The 'structure' of a random net is not a clearly defined topological manifold such as could be used to describe a circuit with explicitly given connections. In a random neural net, one does not speak of 'this' neuron synapsing on 'that' one, but rather in terms of tendencies and probabilities associated with points or regions in the net." (Anatol Rapoport, "Cycle distributions in random nets", The Bulletin of Mathematical Biophysics 10(3), 1948)

"A NETWORK is a collection of connected lines, each of which indicates the movement of some quantity between two locations. Generally, entrance to a network is via a source (the starting point) and exit from a network is via a sink (the finishing point); the lines which form the network are called links (or arcs), and the points at which two or more links meet are called nodes." (Cecil W Lowe, "Critical Path Analysis by Bar Chart", 1966)

"The essential vision of reality presents us not with fugitive appearances but with felt patterns of order which have coherence and meaning for the eye and for the mind. Symmetry, balance and rhythmic sequences express characteristics of natural phenomena: the connectedness of nature - the order, the logic, the living process. Here art and science meet on common ground." (Gyorgy Kepes, "The New Landscape: In Art and Science", 1956)

"In fact, it is empirically ascertainable that every event is actually produced by a number of factors, or is at least accompanied by numerous other events that are somehow connected with it, so that the singling out involved in the picture of the causal chain is an extreme abstraction. Just as ideal objects cannot be isolated from their proper context, material existents exhibit multiple interconnections; therefore the universe is not a heap of things but a system of interacting systems." (Mario Bunge, "Causality: The place of the casual principles in modern science", 1959)

"To say a system is 'self-organizing' leaves open two quite different meanings. There is a first meaning that is simple and unobjectionable. This refers to the system that starts with its parts separate (so that the behavior of each is independent of the others' states) and whose parts then act so that they change towards forming connections of some type. Such a system is 'self-organizing' in the sense that it changes from 'parts separated' to 'parts joined'. […] In general such systems can be more simply characterized as 'self-connecting', for the change from independence between the parts to conditionality can always be seen as some form of 'connection', even if it is as purely functional […]  'Organizing' […] may also mean 'changing from a bad organization to a good one' […] The system would be 'self-organizing' if a change were automatically made to the feedback, changing it from positive to negative; then the whole would have changed from a bad organization to a good." (W Ross Ashby, "Principles of the self-organizing system", 1962)

"Information is recorded in vast interconnecting networks. Each idea or image has hundreds, perhaps thousands, of associations and is connected to numerous other points in the mental network." (Peter Russell, "The Brain Book: Know Your Own Mind and How to Use it", 1979)

"All certainty in our relationships with the world rests on acknowledgement of causality. Causality is a genetic connection of phenomena through which one thing (the cause) under certain conditions gives rise to, causes something else (the effect). The essence of causality is the generation and determination of one phenomenon by another." (Alexander Spirkin, "Dialectical Materialism", 1983)

"When loops are present, the network is no longer singly connected and local propagation schemes will invariably run into trouble. [...] If we ignore the existence of loops and permit the nodes to continue communicating with each other as if the network were singly connected, messages may circulate indefinitely around the loops and process may not converges to a stable equilibrium. […] Such oscillations do not normally occur in probabilistic networks […] which tend to bring all messages to some stable equilibrium as time goes on. However, this asymptotic equilibrium is not coherent, in the sense that it does not represent the posterior probabilities of all nodes of the network." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference", 1988)

"A self-organizing system not only regulates or adapts its behavior, it creates its own organization. In that respect it differs fundamentally from our present systems, which are created by their designer. We define organization as structure with function. Structure means that the components of a system are arranged in a particular order. It requires both connections, that integrate the parts into a whole, and separations that differentiate subsystems, so as to avoid interference. Function means that this structure fulfils a purpose." (Francis Heylighen & Carlos Gershenson, "The Meaning of Self-organization in Computing", IEEE Intelligent Systems, 2003)

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

"If a network is solely composed of neighborhood connections, information must traverse a large number of connections to get from place to place. In a small-world network, however, information can be transmitted between any two nodes using, typically, only a small number of connections. In fact, just a small percentage of random, long-distance connections is required to induce such connectivity. This type of network behavior allows the generation of 'six degrees of separation' type results, whereby any agent can connect to any other agent in the system via a path consisting of only a few intermediate nodes." (John H Miller & Scott E Page, "Complex Adaptive Systems", 2007)

"Networks may also be important in terms of view. Many models assume that agents are bunched together on the head of a pin, whereas the reality is that most agents exist within a topology of connections to other agents, and such connections may have an important influence on behavior. […] Models that ignore networks, that is, that assume all activity takes place on the head of a pin, can easily suppress some of the most interesting aspects of the world around us. In a pinhead world, there is no segregation, and majority rule leads to complete conformity - outcomes that, while easy to derive, are of little use." (John H Miller & Scott E Page, "Complex Adaptive Systems", 2007)

"Complexity theory embraces things that are complicated, involve many elements and many interactions, are not deterministic, and are given to unexpected outcomes. […] A fundamental aspect of complexity theory is the overall or aggregate behavior of a large number of items, parts, or units that are entangled, connected, or networked together. […] In contrast to classical scientific methods that directly link theory and outcome, complexity theory does not typically provide simple cause-and-effect explanations." (Robert E Gunther et al, "The Network Challenge: Strategy, Profit, and Risk in an Interlinked World", 2009)

"The simplest basic architecture of an artificial neural network is composed of three layers of neurons - input, output, and intermediary (historically called perceptron). When the input layer is stimulated, each node responds in a particular way by sending information to the intermediary level nodes, which in turn distribute it to the output layer nodes and thereby generate a response. The key to artificial neural networks is in the ways that the nodes are connected and how each node reacts to the stimuli coming from the nodes it is connected to. Just as with the architecture of the brain, the nodes allow information to pass only if a specific stimulus threshold is passed. This threshold is governed by a mathematical equation that can take different forms. The response depends on the sum of the stimuli coming from the input node connections and is 'all or nothing'." (Diego Rasskin-Gutman, "Chess Metaphors: Artificial Intelligence and the Human Mind", 2009)

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

"We are beginning to see the entire universe as a holographically interlinked network of energy and information, organically whole and self-referential at all scales of its existence. We, and all things in the universe, are non-locally connected with each other and with all other things in ways that are unfettered by the hitherto known limitations of space and time." (Ervin László, "Cosmos: A Co-creator's Guide to the Whole-World", 2010)

"Information is recorded in vast interconnecting networks. Each idea or image has hundreds, perhaps thousands, of associations and is connected to numerous other points in the mental network." (Peter Russell, "The Brain Book: Know Your Own Mind and How to Use it", 2013) 

✨Performance Management: Mastery (Just the Quotes)

"Excellence is an art won by training and habituation. We do not act rightly because we have virtue or excellence, but we rather have those because we have acted rightly. We are what we repeatedly do. Excellence, then, is not an act but a habit." (Aristotle)

"With regard to excellence, it is not enough to know, but we must try to have and use it." (Aristotel, "Nochomachean Ethics", cca. 340 BC)

"It takes a long time to bring excellence to maturity." (Publilius Syrus, "Moral Sayings", cca. 1st century BC)

"One has attained to mastery when one neither goes wrong nor hesitates in the performance." (Friedrich Nietzsche, "Thoughts on the Prejudices of Morality", 1881)

"Order and simplification are the first steps toward the mastery of a subject - the actual enemy is the unknown." (Thomas Mann, "The Magic Mountain", 1924)

"To improve is to change; to be perfect is to change often." (Winston Churchill, [Speech, House of Commons] 1925)

"Creating a new theory is not like destroying an old barn and erecting a skyscraper in its place. It is rather like climbing a mountain, gaining new and wider views, discovering unexpected connections between our starting point and its rich environment. But the point from which we started out still exists and can be seen, although it appears smaller and forms a tiny part of our broad view gained by the mastery of the obstacles on our adventurous way up." (Albert Einstein & Leopold Infeld, "The Evolution of Physics", 1938)

"Civilization is that mode of conduct which points out to man the path of duty. Performance of duty and observance of morality are convertible terms. To observe morality is to attain mastery over our mind and our passions. So doing, we know ourselves." (Mahatma Gandhi, "Hindu Dharma", 1950)

"Leaders value learning and mastery, and so do people who work for leaders. Leaders make it clear that there is no failure, only mistakes that give us feedback and tell us what to do next." (Warren G Bennis, Training and Development Journal, 1984)

"No talent in management is worth more than the ability to master facts - not just any facts, but the ones that provide the best answers. Mastery thus involves knowing what facts you want; where to dig for them; how to dig; how to process the mined ore; and how to use the precious nuggets of information that are finally in your hand. The process can be laborious - which is why it is so often botched." (Robert Heller, "The Supermanagers", 1984)

"The source of good management is found in the imagination of leaders, persons who form new visions and manifest them with a high degree of craft. The blending of vision and craft communicates the purpose. In the arts, people who do that well are masters. In business, they are leaders." (Henry M. Boettinger, Harvard Business Review on Human Relations, 1986)

"People with a high level of personal mastery are able to consistently realize the results that matter most deeply to them-in effect, they approach their life as an artist would approach a work of art. The do that by becoming committed to their own lifelong learning." (Peter M Senge, "The Fifth Discipline: The Art and Practice of the Learning Organization", 1990)

"Personal mastery is the discipline of continually clarifying and deepening our personal vision, of focusing our energies, of developing patience, and of seeing reality objectively." (Peter M Senge, "The Fifth Discipline: The Art and Practice of the Learning Organization", 1990)

"The discipline of personal mastery [...] starts with clarifying the things that really matter to us (and) living our lives in the service of our highest aspirations." (Peter M Senge, "The Fifth Discipline: The Art and Practice of the Learning Organization", 1990)

"Mastery means responsibility, ability to respond in real time to the need of the moment." (Stephen Nachmanovitch, "Free Play: Improvisation in Life and Art", 1991

"At the heart of it, mastery is practice. Mastery is staying on the path." (George Leonard, "Mastery: The Keys to Success and Long-Term Fulfillment", 1992)

"Find the heart of it. Make the complex simple, and you can achieve mastery." (Dan Millman, "Living on Purpose: Straight Answers to Life's Tough Questions", 2000)

"Change always implies abandonment. What you're abandoning is an old way of doing things. You're abandoning it because it's old, because time has made it no longer the best way. But it is also (again because it's old) a familiar way. And more important, it is an approach that people have mastered. So the change you are urging upon your people requires them to abandon their mastery of the familiar, and to become novices once again, to become rank beginners at something with self-definitional importance." (Tom DeMarco, "Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency", 2001)

"Mastery is an elusive concept. You never know when you achieve it absolutely and it may not help you to feel you've attained it. We can recognize it more readily in others than we can in ourselves. We have to discover our own definition of it." (Twyla Tharp, 'The Creative Habit: Learn It and Use It for Life", 2003)

"Leaders should be aware of how their mental models affect their thinking and may cause 'blind spots' that limit understanding. Becoming aware of assumptions is a first step toward shifting one’s mental model and being able to see the world in new and different ways. Four key issues important to expanding and developing a leader’s mind are independent thinking, open-mindedness, systems thinking, and personal mastery." (Richard L Daft, "The Leadership Experience" 4th Ed., 2008)

"Mastery is not a function of genius or talent. It is a function of time and intense focus applied to a particular field of knowledge." (Robert Greene, "Mastery" 2012)

"Models are formal structures represented in mathematics and diagrams that help us to understand the world. Mastery of models improves your ability to reason, explain, design, communicate, act, predict, and explore." (Scott E Page, "The Model Thinker", 2018)

"Art calls for complete mastery of techniques, developed by reflection within the soul." (Bruce Lee)

"In the pursuit of excellence, there is no finish line." (Robert H Farman)

"Only one who devotes himself to a cause with his whole strength and soul can be a true master. For this reason mastery demands all of a person." (Albert Einstein)

"The performance of public duty is not the whole of what makes a good life; there is also the pursuit of private excellence." (Bertrand Russell)

🕸Systems Engineering: Sensitivity (Just the Quotes)

"An exceedingly small cause which escapes our notice determines a considerable effect that we cannot fail to see, and then we say the effect is due to chance. If we knew exactly the laws of nature and the situation of the universe at the initial moment, we could predict exactly the situation of that same universe at a succeeding moment. But even if it were the case that the natural laws had no longer any secret for us, we could still only know the initial situation 'approximately'. If that enabled us to predict the succeeding situation with 'the same approximation', that is all we require, and we should say that the phenomenon had been predicted, that it is governed by laws. But it is not always so; it may happen that small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. Prediction becomes impossible, and we have the fortuitous phenomenon. (Jules H Poincaré, "Science and Method", 1908)

"The predictions of physical theories for the most part concern situations where initial conditions can be precisely specified. If such initial conditions are not found in nature, they can be arranged." (Anatol Rapoport, "The Search for Simplicity", 1956)

"[...] the influence of a single butterfly is not only a fine detail - it is confined to a small volume. Some of the numerical methods which seem to be well adapted for examining the intensification of errors are not suitable for studying the dispersion of errors from restricted to unrestricted regions. One hypothesis, unconfirmed, is that the influence of a butterfly's wings will spread in turbulent air, but not in calm air." (Edward N Lorenz, [talk] 1972)

"Everywhere […] in the Universe, we discern that closed physical systems evolve in the same sense from ordered states towards a state of complete disorder called thermal equilibrium. This cannot be a consequence of known laws of change, since […] these laws are time symmetric- they permit […] time-reverse. […] The initial conditions play a decisive role in endowing the world with its sense of temporal direction. […] some prescription for initial conditions is crucial if we are to understand […]" (John D Barrow, "Theories of Everything: The Quest for Ultimate Explanation", 1991)

"In nonlinear systems - and the economy is most certainly nonlinear - chaos theory tells you that the slightest uncertainty in your knowledge of the initial conditions will often grow inexorably. After a while, your predictions are nonsense." (M Mitchell Waldrop, "Complexity: The Emerging Science at the Edge of Order and Chaos", 1992)

"In the everyday world of human affairs, no one is surprised to learn that a tiny event over here can have an enormous effect over there. For want of a nail, the shoe was lost, et cetera. But when the physicists started paying serious attention to nonlinear systems in their own domain, they began to realize just how profound a principle this really was. […] Tiny perturbations won't always remain tiny. Under the right circumstances, the slightest uncertainty can grow until the system's future becomes utterly unpredictable - or, in a word, chaotic." (M Mitchell Waldrop, "Complexity: The Emerging Science at the Edge of Order and Chaos", 1992)

"Symmetry breaking in psychology is governed by the nonlinear causality of complex systems (the 'butterfly effect'), which roughly means that a small cause can have a big effect. Tiny details of initial individual perspectives, but also cognitive prejudices, may 'enslave' the other modes and lead to one dominant view." (Klaus Mainzer, "Thinking in Complexity", 1994)

"How surprising it is that the laws of nature and the initial conditions of the universe should allow for the existence of beings who could observe it. Life as we know it would be impossible if any one of several physical quantities had slightly different values." (Steven Weinberg, "Life in the Quantum Universe", Scientific American, 1995)

"Unlike classical mathematics, net math exhibits nonintuitive traits. In general, small variations in input in an interacting swarm can produce huge variations in output. Effects are disproportional to causes - the butterfly effect." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Swarm systems generate novelty for three reasons: (1) They are 'sensitive to initial conditions' - a scientific shorthand for saying that the size of the effect is not proportional to the size of the cause - so they can make a surprising mountain out of a molehill. (2) They hide countless novel possibilities in the exponential combinations of many interlinked individuals. (3) They don’t reckon individuals, so therefore individual variation and imperfection can be allowed. In swarm systems with heritability, individual variation and imperfection will lead to perpetual novelty, or what we call evolution." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Chaos theory reconciles our intuitive sense of free will with the deterministic laws of nature. However, it has an even deeper philosophical ramification. Not only do we have freedom to control our actions, but also the sensitivity to initial conditions implies that even our smallest act can drastically alter the course of history, for better or for worse. Like the butterfly flapping its wings, the results of our behavior are amplified with each day that passes, eventually producing a completely different world than would have existed in our absence!" (Julien C Sprott, "Strange Attractors: Creating Patterns in Chaos", 2000)

"A sudden change in the evolutive dynamics of a system (a ‘surprise’) can emerge, apparently violating a symmetrical law that was formulated by making a reduction on some (or many) finite sequences of numerical data. This is the crucial point. As we have said on a number of occasions, complexity emerges as a breakdown of symmetry (a system that, by evolving with continuity, suddenly passes from one attractor to another) in laws which, expressed in mathematical form, are symmetrical. Nonetheless, this breakdown happens. It is the surprise, the paradox, a sort of butterfly effect that can highlight small differences between numbers that are very close to one another in the continuum of real numbers; differences that may evade the experimental interpretation of data, but that may increasingly amplify in the system’s dynamics." (Cristoforo S Bertuglia & Franco Vaio, "Nonlinearity, Chaos, and Complexity: The Dynamics of Natural and Social Systems", 2003)

"[…] we would like to observe that the butterfly effect lies at the root of many events which we call random. The final result of throwing a dice depends on the position of the hand throwing it, on the air resistance, on the base that the die falls on, and on many other factors. The result appears random because we are not able to take into account all of these factors with sufficient accuracy. Even the tiniest bump on the table and the most imperceptible move of the wrist affect the position in which the die finally lands. It would be reasonable to assume that chaos lies at the root of all random phenomena." (Iwo Białynicki-Birula & Iwona Białynicka-Birula, "Modeling Reality: How Computers Mirror Life", 2004)

"Yet, with the discovery of the butterfly effect in chaos theory, it is now understood that there is some emergent order over time even in weather occurrence, so that weather prediction is not next to being impossible as was once thought, although the science of meteorology is far from the state of perfection." (Peter Baofu, "The Future of Complexity: Conceiving a Better Way to Understand Order and Chaos", 2007)

"The butterfly effect demonstrates that complex dynamical systems are highly responsive and interconnected webs of feedback loops. It reminds us that we live in a highly interconnected world. Thus our actions within an organization can lead to a range of unpredicted responses and unexpected outcomes. This seriously calls into doubt the wisdom of believing that a major organizational change intervention will necessarily achieve its pre-planned and highly desired outcomes. Small changes in the social, technological, political, ecological or economic conditions can have major implications over time for organizations, communities, societies and even nations." (Elizabeth McMillan, "Complexity, Management and the Dynamics of Change: Challenges for practice", 2008)

"The 'butterfly effect' is at most a hypothesis, and it was certainly not Lorenz’s intention to change it to a metaphor for the importance of small event. […] Dynamical systems that exhibit sensitive dependence on initial conditions produce remarkably different solutions for two initial values that are close to each other. Sensitive dependence on initial conditions is one of the properties to exhibit chaotic behavior. In addition, at least one further implicit assumption is that the system is bounded in some finite region, i.e., the system cannot blow up. When one uses expanding dynamics, a way of pull-back of too much expanded phase volume to some finite domain is necessary to get chaos." (Péter Érdi, "Complexity Explained", 2008)

"One of the remarkable features of these complex systems created by replicator dynamics is that infinitesimal differences in starting positions create vastly different patterns. This sensitive dependence on initial conditions is often called the butterfly - effect aspect of complex systems - small changes in the replicator dynamics or in the starting point can lead to enormous differences in outcome, and they change one’s view of how robust the current reality is. If it is complex, one small change could have led to a reality that is quite different." (David Colander & Roland Kupers, "Complexity and the art of public policy : solving society’s problems from the bottom up", 2014)

More quotes on the "Sensitivity of initial conditions" (aka "The Butterfly Effect") at the-web-of-knowledge.blogspot.com.

🕸Systems Engineering: Boundaries (Just the Quotes)

"A state of equilibrium in a system does not mean, further, that the system is without tension. Systems can, on the contrary, also come to equilibrium in a state of tension (e.g., a spring under tension or a container with gas under pressure).The occurrence of this sort of system, however, presupposes a certain firmness of boundaries and actual segregation of the system from its environment (both of these in a functional, not a spatial, sense). If the different parts of the system are insufficiently cohesive to withstand the forces working toward displacement (i.e., if the system shows insufficient internal firmness, if it is fluid), or if the system is not segregated from its environment by sufficiently firm walls but is open to its neighboring systems, stationary tensions cannot occur. Instead, there occurs a process in the direction of the forces, which encroaches upon the neighboring regions with diffusion of energy and which goes in the direction of an equilibrium at a lower level of tension in the total region. The presupposition for the existence of a stationary state of tension is thus a certain firmness of the system in question, whether this be its own inner firmness or the firmness of its walls." (Kurt Lewin, "A Dynamic Theory of Personality", 1935)

"A system is difficult to define, but it is easy to recognize some of its characteristics. A system possesses boundaries which segregate it from the rest of its field: it is cohesive in the sense that it resists encroachment from without […]" (Marvin G Cline, "Fundamentals of a theory of the self: some exploratory speculations‎", 1950)

"In the minds of many writers systems engineering is synonymous with component selection and interface design; that is, the systems engineer does not design hardware but decides what types of existing hardware shall be coupled and how they shall be coupled. Complete agreement that this function is the essence of systems engineering will not be found here, for, besides the very important function of systems engineering in systems analysis, there is the role played by systems engineering in providing boundary conditions for hardware design." (A Wayne Wymore, "A Mathematical Theory of Systems Engineering", 1967)

"To model the dynamic behavior of a system, four hierarchies of structure should be recognized: closed boundary around the system; feedback loops as the basic structural elements within the boundary; level variables representing accumulations within the feedback loops; rate variables representing activity within the feedback loops." (Jay W Forrester, "Urban Dynamics", 1969)

"General systems theory is the scientific exploration of 'wholes' and 'wholeness' which, not so long ago, were considered metaphysical notions transcending the boundaries of science. Hierarchic structure, stability, teleology, differentiation, approach to and maintenance of steady states, goal-directedness - these are a few of such general system properties." (Ervin László, "Introduction to Systems Philosophy", 1972)

"Systems thinking is a special form of holistic thinking - dealing with wholes rather than parts. One way of thinking about this is in terms of a hierarchy of levels of biological organization and of the different 'emergent' properties that are evident in say, the whole plant (e.g. wilting) that are not evident at the level of the cell (loss of turgor). It is also possible to bring different perspectives to bear on these different levels of organization. Holistic thinking starts by looking at the nature and behaviour of the whole system that those participating have agreed to be worthy of study. This involves: (i) taking multiple partial views of 'reality' […] (ii) placing conceptual boundaries around the whole, or system of interest and (iii) devising ways of representing systems of interest." (C J Pearson and R L Ison, "Agronomy of Grassland Systems", 1987)

"Autopoietic systems, then, are not only self-organizing systems, they not only produce and eventually change their own structures; their self-reference applies to the production of other components as well. This is the decisive conceptual innovation. […] Thus, everything that is used as a unit by the system is produced as a unit by the system itself. This applies to elements, processes, boundaries, and other structures and, last but not least, to the unity of the system itself." (Niklas Luhmann, "The Autopoiesis of Social Systems", 1990)

"Systems, acting dynamically, produce (and incidentally, reproduce) their own boundaries, as structures which are complementary (necessarily so) to their motion and dynamics. They are liable, for all that, to instabilities chaos, as commonly interpreted of chaotic form, where nowadays, is remote from the random. Chaos is a peculiar situation in which the trajectories of a system, taken in the traditional sense, fail to converge as they approach their limit cycles or 'attractors' or 'equilibria'. Instead, they diverge, due to an increase, of indefinite magnitude, in amplification or gain." (Gordon Pask, "Different Kinds of Cybernetics", 1992)

"When a system has more than one attractor, the points in phase space that are attracted to a particular attractor form the basin of attraction for that attractor. Each basin contains its attractor, but consists mostly of points that represent transient states. Two contiguous basins of attraction will be separated by a basin boundary." (Edward N Lorenz, "The Essence of Chaos", 1993)

"To avoid policy resistance and find high leverage policies requires us to expand the boundaries of our mental models so that we become aware of and understand the implications of the feedbacks created by the decisions we make. That is, we must learn about the structure and dynamics of the increasingly complex systems in which we are embedded." (John D Sterman, "Business dynamics: Systems thinking and modeling for a complex world", 2000)

"[…] our mental models fail to take into account the complications of the real world - at least those ways that one can see from a systems perspective. It is a warning list. Here is where hidden snags lie. You can’t navigate well in an interconnected, feedback-dominated world unless you take your eyes off short-term events and look for long-term behavior and structure; unless you are aware of false boundaries and bounded rationality; unless you take into account limiting factors, nonlinearities and delays. You are likely to mistreat, misdesign, or misread systems if you don’t respect their properties of resilience, self-organization, and hierarchy." (Donella H Meadows, "Thinking in Systems: A Primer", 2008)

"You can’t navigate well in an interconnected, feedback-dominated world unless you take your eyes off short-term events and look for long term behavior and structure; unless you are aware of false boundaries and bounded rationality; unless you take into account limiting factors, nonlinearities and delays." (Donella H Meadow, "Thinking in Systems: A Primer", 2008)

✨Performance Management: Teams [Sports] (Just the Quotes)

"A team divided against itself can break down at any moment. The least bit of pressure or adversity will crack it apart." (Bill Parcells, "Finding a Way to Win: The Principles of Leadership, Teamwork, and Motivation", 1995)

"Bringing together disparate personalities to form a team is like a jigsaw puzzle. You have to ask yourself: what is the whole picture here? We want to make sure our players all fit together properly and complement each other, so that we don't have a big piece, a little piece, an oblong piece, and a round piece. If personalities work against each other, as a team you'll find yourselves spinning your wheels." (Pat Summitt, "Reach for the Summit", 1999)

"Never set a goal that involves number of wins - never. Set goals that revolve around playing together as a team. Doing so will put you in a position to win every game." (Mike Krzyzewski, "Leading with the Heart", 2000)

"In putting together your standards, remember that it is essential to involve your entire team. Standards are not rules issued by the boss; they are a collective identity. Remember, standards are the things that you do all the time and the things for which you hold one another accountable." (Mike Krzyzewski, "The Gold Standard: Building a World-Class Team", 2009)

"A leader may be the most knowledgeable person in the world, but if the players on his team cannot translate that knowledge into action, it means nothing."  (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"Encourage members of your team to take the initiative and act on their own." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"Goals should be realistic, attainable, and shared among all members of the team." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"If a team cannot perform with excellence at a moment's notice, they probably will fail in the long run." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"In leadership, there are no words more important than trust. In any organization, trust must be developed among every member of the team if success is going to be achieved." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"Leaders have to search for the heart on a team, because the person who has it can bring out the best in everybody else." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"Mutual commitment helps overcome the fear of failure - especially when people are part of a team sharing and achieving goals. It also sets the stage for open dialogue and honest conversation." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"People want to be on a team. They want to be part of something bigger than themselves. They want to be in a situation where they feel that they are doing something for the greater good." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"There are five fundamental qualities that make every team great: communication, trust, collective responsibility, caring and pride. I like to think of each as a separate finger on the fist. Any one individually is important. But all of them together are unbeatable." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"When you first assemble a group, it's not a team right off the bat. It's only a collection of individuals." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"You develop a team to achieve what one person cannot accomplish alone. All of us alone are weaker, by far, than if all of us are together." (Mike Krzyzewski, "Leading with the Heart: Coach K's Successful Strategies for Basketball, Business, and Life", 2010)

"In climbing, having confidence in your partners is no small concern. One climber's actions can affect the welfare of the entire team." (Jon Krakauer, "Into Thin Air: A personal account of the Everest disaster", 2011)

"Basketball is a great mystery. You can do everything right. You can have the perfect mix of talent and the best system of offense in the game. You can devise a foolproof defensive strategy and prepare your players for every possible eventuality. But if the players don't have a sense of oneness as a group, your efforts won't pay off. And the bond that unites a team can be so fragile, so elusive." (Phil Jackson, "Eleven Rings", 2015)