🧭Business Intelligence: Enterprise Reporting (Part XII: Reports’ Lifecycle)

Introduction

A report’s lifecycle is the sequence of stages through which a report goes during the timespan of its ownership. The main stages resume mainly to report’s definition, development, testing and deployment, however a report’s life occurs within the context of IT processes like Change, Incident/Problem, Access, Availability, Information Security and Knowledge Management. To them can add up Data Management processes like Data Governance, Data Quality and Metadata Management. Therefore, the extended reports’ lifecycle could take the following form:

The processes can be easily tailored to an organization’s needs, even if it may take several attempts until the best mix is found. The activities introduced by the supporting processes don’t necessarily change the way reports are developed as long the processes integrate smoothing in report’s authoring.

Definition Phase

The lifecycle of a report starts with a series of steps that lead to report’s definition and the requirements associated with it:

The starting point is the identification of a need for data. It can be a business question that needs to be answered, a decision that needs to be made, data needed to keep an operational, tactical or strategical objective under control, and so on. Such business situations can be referred simple as (business) problems.

Problem definition

Problem definition (statement) is the process by which a business issue or need is clearly and concisely stated. This step might seem trivial and implied, however in praxis correlated to it lies the most important volume of overwork.

The dictum “a problem well stated is a problem half-solved” applies as well in BI field. Unfortunately, there are cases in which the users want something else than stated or they leave important details out. Sometimes the users aren’t sure what they need/want, and it comes in developer’s attributions to help clarify the problem and put it within a context.

There are cases in which the users just request a report without specifying the problem they need to solve. This might do when the user has a good understanding of the data and the problem, however this approach does not always work. Personally, I find it useful to define for each report also the underneath problem. I see it as a “win-win” situation in which the user invests some knowledge into the developer and thus the developer will better understand the business, while in time he can provide better help. A thorough understanding of the business and knowledge of the users and their needs can help minimize the volume of overwork involved in reports’ development.

Requirements definition

Requirements definition is the process by which functional and non-functional expectations, targets and specifications are elicited and documented.

Functional requirements specify what the report must do - how the report is structured or formatted, how data need to be visualized or navigated, to what file formats need to be exported, on whether needs to be printed, how the data needs to be grouped, in which order, in what currency/language needs to be displayed, what data sources need to be used, etc. The functional requirements are typically listed in the use case and test script.

Non-functional requirements refer to requirements related to report’s accessibility, availability, performance, compliance, documentation, quality, maintainability, security or testability.

The degree to which a requirement can be fulfilled depends entirely on the reporting platform. It can be differentiated between soft and hard constraints. Soft constraints can be overcome by adding more processing power, memory or other types of resources, while hard constraints can’t be easily or at all overcome. Of course, not all requirements are equally important. Important not fulfilled requirements can make a report unusable and, in extremis, can lead to choosing one reporting platform over another.

The requirements can be elicited by a developer, an analyst/consultant or defined by the business itself. Organizations can simplify the process by defining a set of guidelines and standards that need to be considered in reports’ definition. Normally, is enough to reference the document(s) where the guidelines and standards are found. In contrast to other software artifacts, the requirements for reports can be gather in a simplified version of a document. Quite often a checklist can help identify these requirements upfront with a minimum of overhead.

Report definition

Report definition is the process by which report’s content, logic and layout are explicitly defined - what attributes are needed for output and from what source, what static/dynamic parameters are needed, how the data need to be displayed/formatted, what formulas, aggregations or ordering apply.

A report’s definition can be anything between a simple statement summarizing what the report is about and complex structures (mainly in form of a mapping) reflecting in detail each attribute, constraint, formula, grouping or sorting.

A good definition should allow a developer to create the report as needed by the users, eventually with minimal deviations implied by user’s understanding. The holy grail in report’s definition is finding a structure flexible enough to cover all the aspects of a report. Even if some structures allow such flexibility, sometimes it’s almost impossible not provide additional descriptions in textual forms. The less insight the developer has into the business, the more textual descriptions and visuals are needed to be included to support the knowledge gap.

GAP Analysis

GAP Analysis is the iterative process by which the current state of a software artifact or situation is compared with the potential or desired state. It became an integrant tool from professionals’ thinking to the extent its role as separate process is quite often ignored. In the context of reporting authoring it can be used when comparing the requirements against the current infrastructure and the data available, as well while comparing the developed report against the requirements.

It can happen that the technical and data constraints don’t allow building the report as needed by the users. The differences need to be mitigated and eventually the requirements need to be changed to accommodate the reality. In extremis must be considered whether the report still make sense in the light of the modified requirements.

Solution formulation

Solution formulation is the process by which a formal (technical) solution is defined for the given requirements. It’s a conceptualization (aka concept) of the requirements, and in many cases it’s just a short description by which means the report will be build and what data sources will be used. In more complex cases it can include details about the changes needed in the infrastructure to support the report (e.g. creation/extensions of tables and other database objects, ETL jobs, components, etc.), about the data that need to be collected, etc.

Of course, the conceptualization must be considered together with report’s definition. In fact, report’s definition can be considered as part of the conceptualization. A conceptualization can cover multiple reports, as well two or more different solutions can be provided for different sets of reports. The infrastructure can make a concept futile, either when there is a single reporting platform, or when clear rules are in place.

Prototyping

Prototyping is the iterative process of building a simplified version of the report for demonstration and evaluation purposes, so that users can better define the requirements or to prove the concept. The prototype is a preliminary version that can be refined successively until user’s requirements have a final form. It can take the form of a mock-up query to verify report’s technical and logical feasibility, and/or an Excel layout to depict how the report will look like. Prototypes can facilitate the communication between the parties involved and can be considered as part of the requirements.

A prototype might be needed 1 from 5 cases or so, however this number depends also on the number of queries available or of the knowledge of the source and business processes. Because a prototype can involve additional work, it’s important to identify those cases in which a prototype makes sense and keep the effort to a minimum, especially when an approval is involved in the process. Therefore, one should consider the most important characteristics that need to be proved (e.g. if the data can be aggregated, matched, displayed at the requested level of detail, or in the requested format).

With the help of self-service tools, the business has the capabilities to play with the data and find answers by itself, being able thus to create a prototyped version of the report. Once the report met business needs it can be standardized so it can be used organization-wide. It’s recommended to standardize the reports that are used as part of organization’s processes, otherwise self-service can become a bottleneck for the organization.

Change Management

Change Management is the process of ensuring that the changes performed to a system, in this case a BI tool or the whole BI infrastructure, are performed with minimal disruption for the business and that risks are kept under control. Changes can be requested via standard requests or change requests. A standard request (SR) is a pre-approved change that involves low risks, is relatively common and follows a predefined procedure. In contrast to SRs, a change request (CR) requires the authorization of a board, e.g. the Change Advisory Board (CAB), it often involves risks, an investment and the approach is not that common.

Both are hard-copy or electronic templates that allow to capture information about the changes and allow to document the change and track its status. They include typically the problem definition together with users’ requirements, report definition and the formulation of the solution. What differentiates them thus is the approval process that can be sometimes time-consuming, and the volume of formalism needed to manage the requests (e.g. tracking status, writing status reports, handling risks, etc.).

Unless infrastructural changes are necessary, the risks involved with the creation of reports are relatively small, especially when the reports are developed in-house. Reports developed by vendors involve more risks and imply investments that in a form or other need to be approved. Considering the particularities of the two approaches, personally I think that reports that can be developed with internal resources should be done via SRs, while reports developed externally should be done via CRs. Even if this categorization has the potential of creating some confusion, the use of SRs allows reducing the volume of effort necessary to manage the requests. I suppose there can be found solutions to request external changes via SRs as well (e.g. by using contingents and a set of well-defined rules).

🤝Governance: COBIT (Definitions)

"An IT governance framework and supporting toolset that allows managers to bridge the gap between control requirements, technical issues, and business risks. COBIT enables clear policy development and good practice for IT control throughout organizations. COBIT is managed by the IT Governance Institute and the Information Systems Audit and Control Foundation® (ISACF)." (Tilak Mitra et al, "SOA Governance", 2008)

"COBIT is a set of standards from the IT Governance Institute relating to IT Governance. It defines a set of governance control objectives to help guide the IT organization in making appropriate decisions for each domain." (Martin Oberhofer et al, "Enterprise Master Data Management", 2008)

"An internationally accepted IT governance and control framework that aligns IT business objectives, delivering value and managing associated risks." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"An IT framework with a focus on governance and managing technical and business risks." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A management framework used for IT governance. COBIT 5 is based on five principles and provides organizations with a set of good practices they can apply to IT management and IT governance." (Darril Gibson, "Effective Help Desk Specialist Skills", 2014)

"A process-based information technology governance framework that represents a consensus of experts worldwide. It was codeveloped by the IT Governance Institute and ISACA." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"A framework that provides best practices for IT governance and control." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

"Provides guidance and best practice for the management of IT processes" (ITIL)

🤝Governance: Compliance (Definitions)

"(1) Conforming or acquiescing to requirements from a third party. (2) A subset of data retention policies and procedures that must adhere to more rigid and rigorous conditions." (David G Hill, "Data Protection: Governance, Risk Management, and Compliance", 2009)

"The successful fulfillment of regulations, usually set by a financial institution (for borrowing purposes) or industry standards." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"The process of conforming, completing, performing, or adapting actions to meet the rules, demands, or wishes of another party. Commonly used when discussing conformance to external government or industry regulations." (Craig S Mullins, "Database Administration: The Complete Guide to DBA Practices and Procedures 2nd Ed", 2012)

"The ability to operate in the way defined by a regulation. Many organizations are introduced to governance concepts as they begin the process of complying with business regulations, such as Sarbanes|Oxley or Basel II. These regulations are enforced by audits that determine whether business decisions were made by the appropriate staff according to appropriate policies. To pass these audits, organizations must document their decision rights, policies, and records, specifically that each of the decisions was in fact made by the appropriate person according to policy." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

"The process of conforming, completing, performing, or adapting actions to meet the rules, demands, or wishes of another party. Commonly used when discussing conformance to external government or industry regulations." (Craig S Mullins, "Database Administration", 2012)

"A general concept of conforming to a rule, standard, law, or requirement such that the assessment of compliance results in a binomial result stated as 'compliant' or 'noncompliant'." (For Dummies, "PMP Certification All-in-One For Dummies, 2nd Ed.", 2013)

"Business rules enforced by legislation or some other governing body" (Daniel Linstedt & W H Inmon, "Data Architecture: A Primer for the Data Scientist", 2014)

"Compliance refers to a strategy and a set of activities and artifacts that allow teams to apply Lean-Agile development methods to build systems that have the highest possible quality, while simultaneously assuring they meet any regulatory, industry, or other relevant standards." (Dean Leffingwell, "SAFe 4.5 Reference Guide: Scaled Agile Framework for Lean Enterprises 2nd Ed", 2018)

"Ensuring that a standard or set of guidelines is followed, or that proper, consistent accounting or other practices are being employed." (ITIL)

"The capability of the software product to adhere to standards, conventions or regulations in laws and similar prescriptions." [ISO 9126]

🤝Governance: Standard (Definitions)

"A rule, policy, principle, or measure either established by an organization or established by a recognized standards body and adopted by that organization. Adherence is expected and mandatory until revoked or revised. Exceptions are allowed provided appropriate process is followed." (Tilak Mitra et al, "SOA Governance", 2008)

"A document that provides, for common and repeated use, rules, guidelines, or characteristics for activities or their results, aimed at the achievement of the optimum degree of order in a given context." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

"A standard is something considered by an authority or by general consent as a basis of comparison; an approved model. Or it is a rule or principle that is used as a basis for judgment. Standards embody expectations in a formal manner. To standardize something means to cause it to conform to a standard; or to choose or establish a standard for something. (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement", 2012)

"Data quality standards are assertions about the expected condition of the data that relate directly to quality dimensions: how complete the data is, how well it conforms to defined rules for validity, integrity, and consistency, as well as how it adheres to defined expectations for presentation." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement", 2012)

"The principles or criteria for consistent, ultimate, superior performance outcomes or for how individuals and organizations conduct themselves (ethics)." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"A core set of common, repeatable best practices and protocols that have been agreed on by a business or industry group. Typically, vendors, industry user groups, and end users collaborate to develop standards based on the broad expertise of a large number of stakeholders. Organizations can leverage these standards as a common foundation and innovate on top of them." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A document that provides, for common and repeated use, rules, guidelines, or characteristics for activities or their results, aimed at the achievement of the optimum degree of order in a given context." (For Dummies, "PMP Certification All-in-One For Dummies" 2nd Ed., 2013)

"A document that supports a policy. It consists of mandated rules, which support the higher-level policy goals." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

"A document established by an authority, custom, or general consent as a model or example." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide )", 2017)

"[technical standard:] A specification or requirement or technical characteristic that becomes a norm for a product or process thereby ensuring compatibility." (Robert M Grant, "Contemporary Strategy Analysis 10th Ed", 2018)

"A published specification for, e.g., the structure of a particular file format, recommended nomenclature to use in a particular domain, a common set of metadata fields, etc. Conforming to relevant standards greatly increases the value of published data by improving machine readability and easing data integration." (Open Data Handbook)

" Documented agreements containing technical specifications or other precise criteria to be used consistently as rules, guidelines, or definitions of characteristics, to ensure that materials, products, processes and services are fit for their purpose." (SDMX) 

"Formal, possibly mandatory, set of requirements developed and used to prescribe consistent approaches to the way of working or to provide guidelines (e.g., ISO/IEC standards, IEEE standards, and organizational standards)." [CMMI]

"Mandatory requirements employed and enforced to prescribe a disciplined uniform approach to software development, that is, mandatory conventions and practices are in fact standards." (IEEE Std 983-1986) 

"The metric, specification, gauge, statement, category, segment, grouping, behavior, event or physical product sample against which the outputs of a process are compared and declared acceptable or unacceptable." (ASQ)

🤝Governance: Authority (Definitions)

[formal authority:] "Explicit power granted to meet an explicit set of service expectations, such as those in job descriptions or legislative mandates." (Alexander Grashow et al, "The Practice of Adaptive Leadership", 2009)

"Formal or informal power within a system, entrusted by one party to another in exchange for a service. The basic services, or social functions, provided by authorities are: (1) direction; (2) protection; and (3) order." (Alexander Grashow et al, "The Practice of Adaptive Leadership", 2009)

[informal authority:] "Power granted implicitly to meet a set of service expectations, such as representing cultural norms like civility or being given moral authority to champion the aspirations of a movement." (Alexander Grashow et al, "The Practice of Adaptive Leadership", 2009)

[Decision-making authority:] "Refers to the decisions that agents are authorized to make on behalf of principals. (585)" (Leslie G Eldenburg & Susan K Wolcott, "Cost Management 2nd Ed", 2011)

"The right to apply project resources, expend funds, make decisions, or give approvals." (Cynthia Stackpole, "PMP Certification All-in-One For Dummies", 2011)

"The explicit or implicit delegation of power or responsibility for a particular activity." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"The power vested in a person by virtue of her role to expend resources: financial, material, technical, and human." (Fred MacKenzie, "7 Paths to Managerial Leadership", 2016)

"The ability of a role incumbent to apply resources to a task without reference to another person." (Catherine Burke et al, "Systems Leadership" 2nd Ed., 2018)

"‘The right, given by constitution, law, role description or mutual agreement for one person to require another person to act in a prescribed way (specified in the document or agreement). The likelihood of exercising authority effectively will usually depend upon good Social Process Skills’. The acceptance of the exercise of authority within a work organisation is a function of the contract of employment. Is it essential that there is a clear understanding of the difference between authority and power and that authority is not a one-way process. In a correctly functioning organisation, for example, a manager has the authority to assign tasks to a direct report and the direct report has the authority to require a task performance review by the manager." (Catherine Burke et al, "Systems Leadership" 2nd Ed., 2018)

"power to direct and exact performance from others. It includes the right to prescribe the means and methods by which work will be done. However, the authority to direct is only as good as one individual’s willingness to accept direction from another. Moreover, with authority comes responsibility and accountability." (All Business, "Dictionary of Accounting Terms")

"(1) power over others by sanctioned personnel within an organization. Managers have the authority to hire and fire personnel in an organization. With authority comes responsibility for one’s actions. (2) a government corporation or agency that administers a public enterprise." (All Business, "Dictionary of Business Terms")

🤝Governance: Guideline (Definitions)

"An indication or outline of policy or conduct. Adherence to guidelines is recommended but is not mandatory." (Tilak Mitra et al, "SOA Governance", 2008)

"A kind of business rule that is suggested, but not enforced." (David C Hay, "Data Model Patterns: A Metadata Map", 2010)

"An official recommendation or advice that indicates policies, standards, or procedures for how something should be accomplished." (For Dummies, "PMP Certification All-in-One For Dummies, 2nd Ed.", 2013)

"A document that support standards and policies, but is not mandatory." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

"Non-enforced suggestions for increasing functioning and performance." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"Recommended actions and operational guides for users, IT staff, operations staff, and others when a specific standard does not apply." (Shon Harris & Fernando Maymi, "CISSP All-in-One Exam Guide" 8th Ed, 2018)

"A description of a particular way of accomplishing something that is less prescriptive than a procedure." (ISTQB)

"A description that clarifies what should be done and how, to achieve the objectives set out in policies"

(ISO/IEC 13335-1:2004)

🤝Governance: Policy (Definitions)

"A general, usually strategically focused statement, rule, or regulation that describes how a particular activity, operation, or group of operations will be carried out within a company." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"A deliberate plan of action to guide decisions and achieve rationale outcomes." (Tilak Mitra et al, "SOA Governance", 2008)

"Clear and measurable statements of preferred direction and behaviour to condition the decisions made within an organization." (ISO/IEC 38500:2008, 2008)

"The encoding of rules particular to a business domain, its data content, and the application systems designed to operate in this domain on this set of data." (Alex Berson & Lawrence Dubov, "Master Data Management and Data Governance", 2010)

"A rule or principle that guides or constrains the behavior of someone given decision rights. Policies provide guidelines, sometimes set limits, and sometimes enables behavior. Policies guide decision rights, which are generally conditional." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

"A structured pattern of actions adopted by an organization such that the organization’s policy can be explained as a set of basic principles that govern the organization’s conduct." (For Dummies, "PMP Certification All-in-One For Dummies, 2nd Ed.", 2013)

"A high-level overall plan, containing a set of principles that embrace the general goals of the organization and are used as a basis for decisions. A policy can include some specifics of processes allowed and not allowed." (Robert F Smallwood, "Information Governance: Concepts, Strategies, and Best Practices", 2014)

"The intentions of an organisation as formally expressed by its top management [1]" (David Sutton, "Information Risk Management: A practitioner’s guide", 2014)

"A document that regulates conduct through a general statement of beliefs, goals, and objectives." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

"A structured pattern of actions adopted by an organization such that the organization's policy can be explained as a set of basic principles that govern the organization's conduct." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK® Guide)" 6th Ed., 2017)

"A high-level overall plan, containing a set of principles that embrace the general goals of the organization and are used as a basis for decisions. Can include some specifics of processes allowed and not allowed." (Robert F Smallwood, "Information Governance for Healthcare Professionals", 2018)

"A statement of objectives, rules, practices or regulations governing the activities of people within a certain context." (NISTIR 4734)

"Statements, rules, or assertions that specify the correct or expected behavior of an entity." (NIST SP 1800-15B)

🤝Governance: Accountability (Definitions)

"The obligation to answer for a responsibility conferred. It is a relationship based on the obligation to demonstrate and take responsibility for performance in light of agreed expectations, whether or not those actions were within your direct control." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

"The ability to trace activities on information resources to unique individuals who accept responsibility for their activities on the network." (Mark Rhodes-Ousley, "Information Security: The Complete Reference" 2nd Ed., 2013)

"The obligation to answer for a responsibility that has been conferred. It presumes the existence of at least two parties: one who allocates responsibility and one who accepts it with the undertaking to report upon the manner in which it has been discharged." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"A component of a work relationship between two people wherein one accepts the requirement to provide an account to the other of the following three questions relating to work. What did you do? How did you do it? Why did you do it that way? The most common application of the concept of accountability is that which applies as a function of a contract of employment within an organisation and though in our experience this requirement to accept accountability is rarely articulated clearly in the contract; it should be. An effective accountability discussion includes a discussion of the three questions above including how and why the person used particular processes to turn inputs into required outputs. Accountability is not a collective noun for tasks, as in ‘your accountabilities are …’. Too often this is used in employment, contracts and in role descriptions, which confuses work and accountability. A role may describe work but we are still to discover if the person is actually held to account for that work. Accountability as a concept applying within coherent social groups is brought to the fore for society in general by the process of the courts wherein people in the witness box are required to answer, in public, questions as to what, how and why something was, or was not, done and judgement is passed as an outcome of this process." (Catherine Burke et al, "Systems Leadership", 2nd Ed., 2018)

"A security principle indicating that individuals must be identifiable and must be held responsible for their actions." (Shon Harris & Fernando Maymi, "CISSP All-in-One Exam Guide" 8th Ed., 2018)

"Assuming a transparent and appropriate level of responsibility for data assets that are under one’s care, which includes honoring obligations associated with good practice." (Kevin J Sweeney, "Re-Imagining Data Governance", 2018)

"The property of a system or system resource which ensures that the actions of a system entity may be traced uniquely to that entity, which can then be held responsible for its actions." (William Stallings, "Effective Cybersecurity: A Guide to Using Best Practices and Standards", 2018)

"Responsibility of data processing actors to put in place appropriate and effective measures to ensure compliance with the GDPR and be able to demonstrate so." (Yordanka Ivanova, "Data Controller, Processor, or Joint Controller: Towards Reaching GDPR Compliance in a Data- and Technology-Driven World", 2020)

"Principle that an individual is entrusted to safeguard and control equipment, keying material, and information and is answerable to proper authority for the loss or misuse of that equipment or information." (CNSSI-4009)

"The security goal that generates the requirement for actions of an entity to be traced uniquely to that entity. This supports nonrepudiation, deterrence, fault isolation, intrusion detection and prevention, and after-action recovery and legal action." (SP 800-27)

🔬Data Science: Evolutionary Algorithm (Definitions)

"An Evolutionary Algorithm (EA) is a general class of fitting or maximization techniques. They all maintain a pool of structures or models that can be mutated and evolve. At every stage in the algorithm, each model is graded and the better models are allowed to reproduce or mutate for the next round. Some techniques allow the successful models to crossbreed. They are all motivated by the biologic process of evolution. Some techniques are asexual (so, there is no crossbreeding between techniques) while others are bisexual, allowing successful models to swap ''genetic' information. The asexual models allow a wide variety of different models to compete, while sexual methods require that the models share a common 'genetic' code." (William J Raynor Jr., "The International Dictionary of Artificial Intelligence", 1999)

"Meta-heuristic optimization approach inspired by natural evolution, which begins with potential solution models, then iteratively applies algorithms to find the fittest models from the set to serve as inputs to the next iteration, ultimately leading to a sub-optimal solution which is close to the optimal one." (Gilles Lebrun et al, "EA Multi-Model Selection for SVM", 2009)

"Evolutionary algorithms are search methods that can be used for solving optimization problems. They mimic working principles from natural evolution by employing a population–based approach, labeling each individual of the population with a fitness and including elements of random, albeit the random is directed through a selection process." (Ivan Zelinka & Hendrik Richter, "Evolutionary Algorithms for Chaos Researchers", Studies in Computational Intelligence Vol. 267, 2010)

"Population-based optimization algorithms in which each member of the population represents a candidate solution. In an iterative process the population members evolve and are then evaluated by a fitness function. Genetic Algorithms and Particle Swarm Optimization are examples of evolutionary algorithms." (Efstathios Kirkos, "Composite Classifiers for Bankruptcy Prediction", 2014)

"A collective term for all variants of (probabilistic) optimization and approximation algorithms that are inspired by Darwinian evolution. Optimal states are approximated by successive improvements based on the variation-selection paradigm. Thereby, the variation operators produce genetic diversity and the selection directs the evolutionary search." (Harish Garg, "A Hybrid GA-GSA Algorithm for Optimizing the Performance of an Industrial System by Utilizing Uncertain Data", 2015)

🤝Governance: Criteria (Definitions)

"Standards by which alternatives are judged. Attributes that describe certain (information) characteristics." (Martin J Eppler, "Managing Information Quality" 2nd Ed., 2006)

"Conditions that enable a decision to be made, especially at a decision point within the areas of work related to New Product Planning and New Product Introduction." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"Standards, rules, or tests on which a judgment or decision can be based, or by which a product, service, result, or process can be evaluated." (Cynthia Stackpole, "PMP® Certification All-in-One For Dummies®", 2011)

"Standards or expectation specifying what should exist (what success looks like)." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

[definite criteria] "A special purpose framework using a definite set of criteria having substantial support that is applied to all material items appearing in financial statements, such as the price-level basis of accounting." (Tom Klammer, "Statement of Cash Flows: Preparation, Presentation, and Use", 2018)

[common criteria:] "A set of internationally accepted semantic tools and constructs for describing the security needs of customers and the security attributes of products." (NIST SP 800-32)

[common criteria:] "Governing document that provides a comprehensive, rigorous method for specifying security function and assurance requirements for products and systems." (CNSSI 4009-2015)

[evaluation criteria:] "The standards by which accomplishments of technical and operational effectiveness or suitability characteristics may be assessed. Evaluation criteria are a benchmark, standard, or factor against which conformance, performance, and suitability of a technical capability, activity, product, or plan is measured." (NIST SP 800-137A)

🤝Governance: Delegation (Just the Quotes)

"Failure to delegate causes managers to be crushed and fail under the weight of accumulated duties that they do not know and have not learned to delegate." (James D Mooney, "Onward Industry!", 1931)

"Delegation means the conferring of a specified authority by a higher authority. In its essence it involves a dual responsibility. The one to whom responsibility is delegated becomes responsible to the superior for doing the job. but the superior remains responsible for getting the Job done. This principle of delegation is the center of all processes in formal organization. Delegation is inherent in the very nature of the relation between superior and subordinate. The moment the objective calls for the organized effort of more than one person, there is always leadership with its delegation of duties." (James D Mooney, "The Principles of Organization", 1947)

"The only way for a large organization to function is to decentralize, to delegate real authority and responsibility to the man on the job. But be certain you have the right man on the job." (Robert E Wood, 1951)

"You can delegate authority, but you can never delegate responsibility by delegating a task to someone else. If you picked the right man, fine, but if you picked the wrong man, the responsibility is yours - not his." (Richard E Krafve, The Boston Sunday Globe, 1960)

"Centralized controls are designed to ensure that the chief executive can find out how well the delegated authority and responsibility are being exercised." (Ernest Dale, "Management: Theory and practice", 1965)

"Guidelines for bureaucrats: (1) When in charge, ponder. (2) When in trouble, delegate. (3) When in doubt, mumble." (James Boren, New York Times, 1970)

"We find that the manager, particularly at senior levels, is overburdened with work. With the increasing complexity of modern organizations and their problems, he is destined to become more so. He is driven to brevity, fragmentation, and superficiality in his tasks, yet he cannot easily delegate them because of the nature of his information. And he can do little to increase his available time or significantly enhance his power to manage. Furthermore, he is driven to focus on that which is current and tangible in his work, even though the complex problems facing many organizations call for reflection and a far-sighted perspective." (Henry Mintzberg, "The structuring of organizations", 1979)

"Do not delegate an assignment and then attempt to manage it yourself - you will make an enemy of the overruled subordinate." (Wess Roberts, "Leadership Secrets of Attila the Hun", 1985)

"Surround yourself with the best people you can find, delegate authority, and don't interfere." (Ronald Reagan, Fortune, 1986)

"People and organizations don't grow much without delegation and completed staff work because they are confined to the capacities of the boss and reflect both personal strengths and weaknesses." (Stephen Covey, "Principle Centered Leadership", 1992)

"Responsibility is a unique concept [...] You may share it with others, but your portion is not diminished. You may delegate it, but it is still with you. [...] If responsibility is rightfully yours, no evasion, or ignorance or passing the blame can shift the burden to someone else. Unless you can point your finger at the man who is responsible when something goes wrong, then you have never had anyone really responsible." (Hyman G Rickover, "The Rickover Effect", 1992)

"We accomplish all that we do through delegation - either to time or to other people." (Stephen Covey, "Daily Reflections for Highly Effective People", 1994)

"The inability to delegate is one of the biggest problems I see with managers at all levels." (Eli Broad, "The Art of Being Unreasonable: Lessons in Unconventional Thinking", 2012)

"Delegation of authority is one of the most important functions of a leader, and he should delegate authority to the maximum degree possible with regard to the capabilities of his people. Once he has established policy, goals, and priorities, the leader accomplishes his objectives by pushing authority right down to the bottom. Doing so trains people to use their initiative; not doing so stifles creativity and lowers morale." (Thornas H Moorer)

🤝Governance: Authority (Just the Quotes)

"When the general is weak and without authority; when his orders are not clear and distinct; when there are no fixed duties assigned to officers and men, and the ranks are formed in a slovenly haphazard manner, the result is utter disorganization." (Sun Tzu, "The Art of War", cca. 5th century)

"Authority is never without hate." (Euripides, "Ion", cca. 422 BC)

"In questions of science, the authority of a thousand is not worth the humble reasoning of a single individual" (Galileo Galilei, 1632)

"Authority without wisdom is like a heavy axe without an edge, fitter to bruise than polish." (Anne Bradstreet, "Meditations Divine and Moral", 1664)

"Lawful and settled authority is very seldom resisted when it is well employed." (Samuel Johnson, "The Rambler", 1750)

"The most absolute authority is that which penetrates into a man's innermost being and concerns itself no less with his will than with his actions." (Jean-Jacques Rousseau, "On the origin of inequality", 1755)

"The wise executive never looks upon organizational lines as being settled once and for all. He knows that a vital organization must keep growing and changing with the result that its structure must remain malleable. Get the best organization structure you can devise, but do not be afraid to change it for good reason: This seems to be the sound rule. On the other hand, beware of needless change, which will only result in upsetting and frustrating your employees until they become uncertain as to what their lines of authority actually are." (Marshall E Dimock, "The Executive in Action", 1915)

"No amount of learning from books or of listening to the words of authority can be substituted for the spade-work of investigation." (Richard Gregory, "Discovery; or, The Spirit and Service of Science", 1916)

"In organization it means the graduation of duties, not according to differentiated functions, for this involves another and distinct principle of organization, but simply according to degrees of authority and corresponding responsibility." (James D Mooney, "Onward Industry!", 1931)

"It is sufficient here to observe that the supreme coordinating authority must be anterior to leadership in logical order, for it is this coordinating force which makes the organization. Leadership, on the other hand, always presupposes the organization. There can be no leader without something to lead." (James D Mooney, "Onward Industry!", 1931)

"Leadership is the form that authority assumes when it enters into process. As such it constitutes the determining principle of the entire scalar process, existing not only at the source, but projecting itself through its own action throughout the entire chain, until, through functional definition, it effectuates the formal coordination of the entire structure." (James D Mooney, "Onward Industry!", 1931)

"The staff function in organization means the service of advice or counsel, as distinguished from the function of authority or command. This service has three phases, which appear in a clearly integrated relationship. These phases are the informative, the advisory, and the supervisory." (James D Mooney, "Onward Industry!", 1931)

"Human beings are compounded of cognition and emotion and do not function well when treated as though they were merely cogs in motion.... The task of the administrator must be accomplished less by coercion and discipline, and more and more by persuasion.... Management of the future must look more to leadership and less to authority as the primary means of coordination." (Luther H Gulick, "Papers on the Science of Administration", 1937)

"A person can and will accept a communication as authoritative only when four conditions simultaneously obtain: (a) he can and does understand the communication; (b) at the time of his decision he believes that it is not inconsistent with the purpose of the organization; (c) at the time of his decision, he believes it to be compatible with his personal interest as a whole; and (d) he is able mentally and physically to comply with it." (Chester I Barnard, "The Functions of the Executive", 1938)

"The fine art of executive decision consists in not deciding questions that are not now pertinent, in not deciding prematurely, in not making decision that cannot be made effective, and in not making decisions that others should make. Not to decide questions that are not pertinent at the time is uncommon good sense, though to raise them may be uncommon perspicacity. Not to decide questions prematurely is to refuse commitment of attitude or the development of prejudice. Not to make decisions that cannot be made effective is to refrain from destroying authority. Not to make decisions that others should make is to preserve morale, to develop competence, to fix responsibility, and to preserve authority.
From this it may be seen that decisions fall into two major classes, positive decisions - to do something, to direct action, to cease action, to prevent action; and negative decisions, which are decisions not to decide. Both are inescapable; but the negative decisions are often largely unconscious, relatively nonlogical, "instinctive," "good sense." It is because of the rejections that the selection is good." (Chester I Barnard, "The Functions of the Executive", 1938)

"To hold a group or individual accountable for activities of any kind without assigning to him or them the necessary authority to discharge that responsibility is manifestly both unsatisfactory and inequitable. It is of great Importance to smooth working that at all levels authority and responsibility should be coterminous and coequal." (Lyndall Urwick, "Dynamic Administration", 1942)

"All behavior involves conscious or unconscious selection of particular actions out of all those which are physically possible to the actor and to those persons over whom he exercises influence and authority." (Herbert A Simon, "Administrative Behavior: A Study of Decision-making Processes in Administrative Organization", 1947)

"Coordination, therefore, is the orderly arrangement of group efforts, to provide unity of action in the pursuit of a common purpose. As coordination is the all inclusive principle of organization it must have its own principle and foundation in authority, or the supreme coordination power. Always, in every form of organization, this supreme authority must rest somewhere, else there would be no directive for any coordinated effort." (James D Mooney, "The Principles of Organization", 1947)

"Delegation means the conferring of a specified authority by a higher authority. In its essence it involves a dual responsibility. The one to whom responsibility is delegated becomes responsible to the superior for doing the job. but the superior remains responsible for getting the Job done. This principle of delegation is the center of all processes in formal organization. Delegation is inherent in the very nature of the relation between superior and subordinate. The moment the objective calls for the organized effort of more than one person, there is always leadership with its delegation of duties." (James D Mooney, "The Principles of Organization", 1947)

"Power on the one side, fear on the other, are always the buttresses on which irrational authority is built." (Erich Fromm, "Man for Himself: An Inquiry Into the Psychology of Ethics", 1947)

"Authority is not a quality one person 'has', in the sense that he has property or physical qualities. Authority refers to an interpersonal relation in which one person looks upon another as somebody superior to him." (Erich Fromm, "The Fear of Freedom", 1950)

"The only way for a large organization to function is to decentralize, to delegate real authority and responsibility to the man on the job. But be certain you have the right man on the job." (Robert E Wood, 1951)

"[...] authority - the right by which superiors are able to require conformity of subordinates to decisions - is the basis for responsibility and the force that binds organization together. The process of organizing encompasses grouping of activities for purposes of management and specification of authority relationships between superiors and subordinates and horizontally between managers. Consequently, authority and responsibility relationships come into being in all associative undertakings where the superior-subordinate link exists. It is these relationships that create the basic character of the managerial job." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"Although organization charts are useful, necessary, and often revealing tools, they are subject to many important limitations. In the first place, a chart shows only formal authority relationships and omits the many significant informal and informational relationships that exist in a living organization. Moreover, it does not picture how much authority exists at any point in the organization." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"[...] authority for given tasks is limited to that for which an individual may properly held responsible." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"Authority delegations from a superior to a subordinate may be made in large or small degree. The tendency to delegate much authority through the echelons of an organization structure is referred tojas decentralization of authority. On the other hand, authority is said to be centralized wherever a manager tends not to delegate authority to his subordinates." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"Authority is, of course, completely centralized when a manager delegates none, and it is possible to think of the reverse situation - an infinite delegation of authority in which no manager retains any authority other than the implicit power to recover delegated authority. But this kind of delegation is obviously impracticable, since, at some point in the organization structure, delegations must stop." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"If charts do not reflect actual organization and if the organization is intended to be as charted, it is the job of effective management to see that actual organization conforms with that desired. Organization charts cannot supplant good organizing, nor can a chart take the place of spelling out authority relationships clearly and completely, of outlining duties of managers and their subordinates, and of defining responsibilities." (Harold Koontz & Cyril O Donnell, "Principles of Management", 1955)

"It is highly important for managers to be honest and clear in describing what authority they are keeping and what role they are asking their subordinates to assume." (Robert Tannenbaum & Warren H Schmidt, Harvard Business Review, 1958)

"Formal theories of organization have been taught in management courses for many years, and there is an extensive literature on the subject. The textbook principles of organization — hierarchical structure, authority, unity of command, task specialization, division of staff and line, span of control, equality of responsibility and authority, etc. - comprise a logically persuasive set of assumptions which have had a profound influence upon managerial behavior." (Douglas McGregor, 'The Human Side of Enterprise", 1960)

"If there is a single assumption which pervades conventional organizational theory, it is that authority is the central, indispensable means of managerial control." (Douglas McGregor, "The Human Side of Enterprise", 1960)

"The ingenuity of the average worker is sufficient to outwit any system of controls devised by management." (Douglas McGregor, "The Human Side of Enterprise", 1960)

"You can delegate authority, but you can never delegate responsibility by delegating a task to someone else. If you picked the right man, fine, but if you picked the wrong man, the responsibility is yours - not his." (Richard E Krafve, The Boston Sunday Globe, 1960)

"Centralized controls are designed to ensure that the chief executive can find out how well the delegated authority and responsibility are being exercised." (Ernest Dale, "Management: Theory and practice", 1965)

"In large-scale organizations, the factual approach must be constantly nurtured by high-level executives. The more layers of authority through which facts must pass before they reach the decision maker, the greater the danger that they will be suppressed, modified, or softened, so as not to displease the 'brass"' For this reason, high-level executives must keep reaching for facts or soon they won't know what is going on. Unless they make visible efforts to seek and act on facts, major problems will not be brought to their attention, the quality of their decisions will decline, and the business will gradually get out of touch with its environment." (Marvin Bower, "The Will to Manage", 1966)

"The concept of organizational goals, like the concepts of power, authority, or leadership, has been unusually resistant to precise, unambiguous definition. Yet a definition of goals is necessary and unavoidable in organizational analysis. Organizations are established to do something; they perform work directed toward some end." (Charles Perrow, "Organizational Analysis: A Sociological View", 1970)

"[Management] has authority only as long as it performs." (Peter F Drucker, "Management: Tasks, Responsibilities, Practices", 1973)

"'Management' means, in the last analysis, the substitution of thought for brawn and muscle, of knowledge for folkways and superstition, and of cooperation for force. It means the substitution of responsibility for obedience to rank, and of authority of performance for authority of rank. (Peter F Drucker, "People and Performance", 1977)

"The key to successful leadership today is influence, not authority." (Kenneth H Blanchard, "Managing By Influence", 1986)

"Strange as it sounds, great leaders gain authority by giving it away." (James B Stockdale, "Military Ethics" 1987)

"Perhaps nothing in our society is more needed for those in positions of authority than accountability." (Larry Burkett, "Business By The Book: Complete Guide of Biblical Principles for the Workplace", 1990)

"When everything is connected to everything in a distributed network, everything happens at once. When everything happens at once, wide and fast moving problems simply route around any central authority. Therefore overall governance must arise from the most humble interdependent acts done locally in parallel, and not from a central command. " (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Authority alone is like pushing from behind. What automatic reaction do you have when pushed from behind? Resistance - unless you are travelling in that direction anyway and you experience the push as helpful. When you do not know what lies ahead and you are not sure whether you want to move forward, resistance is completely understandable. [...] Authority alone pushes. Leadership pulls, because it draws people towards a vision of the future that attracts them." (Joseph O’Connor, "Leading With NLP: Essential Leadership Skills for Influencing and Managing People", 1998)

"Authority works best where you have an accepted hierarchy [...]. Then people move together because of the strong implicit accepted values that everyone shares. If you are trying to lead people who do not share similar goals and values, then authority is not enough." (Joseph O’Connor, "Leading With NLP: Essential Leadership Skills for Influencing and Managing People", 1998)

"The ultimate authority must always rest with the individual's own reason and critical analysis." (Tenzin Gyatso, "Path To Tranquility", 1998)

"The premise here is that the hierarchy lines on the chart are also the only communication conduit. Information can flow only along the lines. [...] The hierarchy lines are paths of authority. When communication happens only over the hierarchy lines, that's a priori evidence that the managers are trying to hold on to all control. This is not only inefficient but an insult to the people underneath." (Tom DeMarco, "Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency", 2001)

"A system is a framework that orders and sequences activity within the organisation to achieve a purpose within a band of variance that is acceptable to the owner of the system.  Systems are the organisational equivalent of behaviour in human interaction. Systems are the means by which organisations put policies into action.  It is the owner of a system who has the authority to change it, hence his or her clear acceptance of the degree of variation generated by the existing system." (Catherine Burke et al, "Systems Leadership" 2nd Ed., 2018)

"Responsibility means an inevitable punishment for mistakes; authority means full power to make them." (Yegor Bugayenko, "Code Ahead", 2018)

"Control is not leadership; management is not leadership; leadership is leadership. If you seek to lead, invest at least 50% of your time in leading yourself–your own purpose, ethics, principles, motivation, conduct. Invest at least 20% leading those with authority over you and 15% leading your peers." (Dee Hock)

"Delegation of authority is one of the most important functions of a leader, and he should delegate authority to the maximum degree possible with regard to the capabilities of his people. Once he has established policy, goals, and priorities, the leader accomplishes his objectives by pushing authority right down to the bottom. Doing so trains people to use their initiative; not doing so stifles creativity and lowers morale." (Thornas H Moorer)

"Leadership means that a group, large or small, is willing to entrust authority to a person who has shown judgement, wisdom, personal appeal, and proven competence." (Walt Disney)

"The teams and staffs through which the modern commander absorbs information and exercises his authority must be a beautifully interlocked, smooth-working mechanism. Ideally, the whole should be practically a single mind." (Dwight D Eisenhower)

"While basic laws underlie command authority, the real foundation of successful leadership is the moral authority derived from professional competence and integrity. Competence and integrity are not separable." (William C Westmoreland)

🤝Governance: Accountability (Just the Quotes)

"To hold a group or individual accountable for activities of any kind without assigning to him or them the necessary authority to discharge that responsibility is manifestly both unsatisfactory and inequitable. It is of great Importance to smooth working that at all levels authority and responsibility should be coterminous and coequal." (Lyndall Urwick, "Dynamic Administration", 1942)

"Complete accountability is established and enforced throughout; and if there there is any error committed, it will be discovered on a comparison with the books and can be traced to its source." (Alfred D Chandler Jr, "The Visible Hand", 1977)

"If responsibility - and particularly accountability - is most obviously upwards, moral responsibility also reaches downwards. The commander has a responsibility to those whom he commands. To forget this is to vitiate personal integrity and the ethical validity of the system." (Roger L Shinn, "Military Ethics", 1987)

"Perhaps nothing in our society is more needed for those in positions of authority than accountability." (Larry Burkett, "Business By The Book: Complete Guide of Biblical Principles for the Workplace", 1990)

"Corporate governance is concerned with holding the balance between economic and social goals and between individual and communal goals. The governance framework is there to encourage the efficient use of resources and equally to require accountability for the stewardship of those resources. The aim is to align as nearly as possible the interests of individuals, corporations and society." (Dominic Cadbury, "UK, Commission Report: Corporate Governance", 1992)

"Accountability is essential to personal growth, as well as team growth. How can you improve if you're never wrong? If you don't admit a mistake and take responsibility for it, you're bound to make the same one again." (Pat Summitt, "Reach for the Summit", 1999)

"Responsibility equals accountability equals ownership. And a sense of ownership is the most powerful weapon a team or organization can have." (Pat Summitt, "Reach for the Summit", 1999)

"There's not a chance we'll reach our full potential until we stop blaming each other and start practicing personal accountability." (John G Miller, "QBQ!: The Question Behind the Question", 2001)

"Democracy is not about trust; it is about distrust. It is about accountability, exposure, open debate, critical challenge, and popular input and feedback from the citizenry." (Michael Parenti, "Superpatriotism", 2004)

"No individual can achieve worthy goals without accepting accountability for his or her own actions." (Dan Miller, "No More Dreaded Mondays", 2008)

"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)

"Nobody can do everything well, so learn how to delegate responsibility to other winners and then hold them accountable for their decisions." (George Foreman, "Knockout Entrepreneur: My Ten-Count Strategy for Winning at Business", 2010)

"Failing to hold someone accountable is ultimately an act of selfishness." (Patrick Lencioni, "The Advantage, Enhanced Edition: Why Organizational Health Trumps Everything Else In Business", 2012)

"We cannot have a just society that applies the principle of accountability to the powerless and the principle of forgiveness to the powerful. This is the America in which we currently reside." (Chris Hayes, "Twilight of the Elites: America After Meritocracy", 2012)

"Artificial intelligence is a concept that obscures accountability. Our problem is not machines acting like humans - it's humans acting like machines." (John Twelve Hawks, "Spark", 2014)

"In order to cultivate a culture of accountability, first it is essential to assign it clearly. People ought to clearly know what they are accountable for before they can be held to it. This goes beyond assigning key responsibility areas (KRAs). To be accountable for an outcome, we need authority for making decisions, not just responsibility for execution. It is tempting to refrain from the tricky exercise of explicitly assigning accountability. Executives often hope that their reports will figure it out. Unfortunately, this is easier said than done." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Some hierarchy is essential for the effective functioning of an organization. Eliminating hierarchy has the frequent side effect of slowing down decision making and diffusing accountability." (Sriram Narayan, "Agile IT Organization Design: For Digital Transformation and Continuous Delivery", 2015)

"Accountability makes no sense when it undermines the larger goals of education." (Diane Ravitch, "The Death and Life of the Great American School System", 2016)

"[...] high-accountability teams are characterized by having members that are willing and able to resolve issues within the team. They take responsibility for their own actions and hold each other accountable. They take ownership of resolving disputes and feel empowered to do so without intervention from others. They learn quickly by identifying issues and solutions together, adopting better patterns over time. They are able to work without delay because they don’t need anyone else to resolve problems. Their managers are able to work more strategically without being bogged down by day-to-day conflict resolution." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"In a workplace setting, accountability is the willingness to take responsibility for one’s actions and their outcomes. Accountable team members take ownership of their work, admit their mistakes, and are willing to hold each other accountable as peers." (Morgan Evans, "Engineering Manager's Handbook", 2023)

"Low-accountability teams can be recognized based on their tendency to shift blame, avoid addressing issues within the team, and escalate most problems to their manager. In low-accountability teams, it is difficult to determine the root of problems, failures are met with apathy, and managers have to spend much of their time settling disputes and addressing performance. Members of low-accountability teams believe it is not their role to resolve disputes and instead shift that responsibility up to the manager, waiting for further direction. These teams fall into conflict and avoidance deadlocks, unable to move quickly because they cannot resolve issues within the team."

🤝Governance: Enterprise Risk Management (Definitions)

"A model for IT governance that is risk-based integrating internal control, the Sarbanes-Oxley Act mandates, and strategic planning." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed, 2011)

"Process of continuously identifying, assessing, mitigating, and monitoring relevant business risks in a comprehensive and integrated way." (Leslie G Eldenburg & Susan K Wolcott, "Cost Management" 2nd Ed, 2011)

"The process of planning, organizing, leading, and controlling the activities of an organization in order to minimize the effects of risk on its capital and earnings. ERM includes not only risks associated with accidental losses, but also financial, strategic, operational, and other risks." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The application of risk management approaches across an organization in a structured and disciplined manner." (Sally-Anne Pitt, "Internal Audit Quality", 2014)

"The governing process for managing risks and opportunities." (Weiss, "Auditing IT Infrastructures for Compliance" 2nd Ed., 2015)

"Enterprise risk management is a framework for risk management, including organization and governance, internal controls, key processes, systems and information and risk culture. ERM begins by identifying events or circumstances relevant to the organization's objectives (risks and opportunities), assessing them in terms of likelihood and magnitude of impact, determining a response strategy and monitoring progress." (Thomas C Wilson, "Value and Capital Management", 2015)

🔭Data Science: Big Data (Just the Quotes)

"If we gather more and more data and establish more and more associations, however, we will not finally find that we know something. We will simply end up having more and more data and larger sets of correlations." (Kenneth N Waltz, "Theory of International Politics Source: Theory of International Politics", 1979)

“There are those who try to generalize, synthesize, and build models, and there are those who believe nothing and constantly call for more data. The tension between these two groups is a healthy one; science develops mainly because of the model builders, yet they need the second group to keep them honest.” (Andrew Miall, “Principles of Sedimentary Basin Analysis”, 1984)

"Big data can change the way social science is performed, but will not replace statistical common sense." (Thomas Landsall-Welfare, "Nowcasting the mood of the nation", Significance 9(4), 2012)

"Big Data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it." (Edd Wilder-James, "What is big data?", 2012) [source]

"The secret to getting the most from Big Data isn’t found in huge server farms or massive parallel computing or in-memory algorithms. Instead, it’s in the almighty pencil." (Matt Ariker, "The One Tool You Need To Make Big Data Work: The Pencil", 2012)

"Big data is the most disruptive force this industry has seen since the introduction of the relational database." (Jeffrey Needham, "Disruptive Possibilities: How Big Data Changes Everything", 2013)

"No subjective metric can escape strategic gaming [...] The possibility of mischief is bottomless. Fighting ratings is fruitless, as they satisfy a very human need. If one scheme is beaten down, another will take its place and wear its flaws. Big Data just deepens the danger. The more complex the rating formulas, the more numerous the opportunities there are to dress up the numbers. The larger the data sets, the harder it is to audit them." (Kaiser Fung, "Numbersense: How To Use Big Data To Your Advantage", 2013)

"There is convincing evidence that data-driven decision-making and big data technologies substantially improve business performance. Data science supports data-driven decision-making - and sometimes conducts such decision-making automatically - and depends upon technologies for 'big data' storage and engineering, but its principles are separate." (Foster Provost & Tom Fawcett, "Data Science for Business", 2013)

"Our needs going forward will be best served by how we make use of not just this data but all data. We live in an era of Big Data. The world has seen an explosion of information in the past decades, so much so that people and institutions now struggle to keep pace. In fact, one of the reasons for the attachment to the simplicity of our indicators may be an inverse reaction to the sheer and bewildering volume of information most of us are bombarded by on a daily basis. […] The lesson for a world of Big Data is that in an environment with excessive information, people may gravitate toward answers that simplify reality rather than embrace the sheer complexity of it." (Zachary Karabell, "The Leading Indicators: A short history of the numbers that rule our world", 2014)

"The other buzzword that epitomizes a bias toward substitution is 'big data'. Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is usually dumb data. Computers can find patterns that elude humans, but they don’t know how to compare patterns from different sources or how to interpret complex behaviors. Actionable insights can only come from a human analyst (or the kind of generalized artificial intelligence that exists only in science fiction)." (Peter Thiel & Blake Masters, "Zero to One: Notes on Startups, or How to Build the Future", 2014)

"We have let ourselves become enchanted by big data only because we exoticize technology. We’re impressed with small feats accomplished by computers alone, but we ignore big achievements from complementarity because the human contribution makes them less uncanny. Watson, Deep Blue, and ever-better machine learning algorithms are cool. But the most valuable companies in the future won’t ask what problems can be solved with computers alone. Instead, they’ll ask: how can computers help humans solve hard problems?" (Peter Thiel & Blake Masters, "Zero to One: Notes on Startups, or How to Build the Future", 2014)

"As business leaders we need to understand that lack of data is not the issue. Most businesses have more than enough data to use constructively; we just don't know how to use it. The reality is that most businesses are already data rich, but insight poor." (Bernard Marr, Big Data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance, 2015)

"Big data is based on the feedback economy where the Internet of Things places sensors on more and more equipment. More and more data is being generated as medical records are digitized, more stores have loyalty cards to track consumer purchases, and people are wearing health-tracking devices. Generally, big data is more about looking at behavior, rather than monitoring transactions, which is the domain of traditional relational databases. As the cost of storage is dropping, companies track more and more data to look for patterns and build predictive models." (Neil Dunlop, "Big Data", 2015)

"Big Data often seems like a meaningless buzz phrase to older database professionals who have been experiencing exponential growth in database volumes since time immemorial. There has never been a moment in the history of database management systems when the increasing volume of data has not been remarkable." (Guy Harrison, "Next Generation Databases: NoSQL, NewSQL, and Big Data", 2015)

"Dimensionality reduction is essential for coping with big data - like the data coming in through your senses every second. A picture may be worth a thousand words, but it’s also a million times more costly to process and remember. [...] A common complaint about big data is that the more data you have, the easier it is to find spurious patterns in it. This may be true if the data is just a huge set of disconnected entities, but if they’re interrelated, the picture changes." (Pedro Domingos, "The Master Algorithm", 2015)

"Science’s predictions are more trustworthy, but they are limited to what we can systematically observe and tractably model. Big data and machine learning greatly expand that scope. Some everyday things can be predicted by the unaided mind, from catching a ball to carrying on a conversation. Some things, try as we might, are just unpredictable. For the vast middle ground between the two, there’s machine learning." (Pedro Domingos, "The Master Algorithm", 2015)

"The human side of analytics is the biggest challenge to implementing big data." (Paul Gibbons, "The Science of Successful Organizational Change", 2015)

"To make progress, every field of science needs to have data commensurate with the complexity of the phenomena it studies. [...] With big data and machine learning, you can understand much more complex phenomena than before. In most fields, scientists have traditionally used only very limited kinds of models, like linear regression, where the curve you fit to the data is always a straight line. Unfortunately, most phenomena in the world are nonlinear. [...] Machine learning opens up a vast new world of nonlinear models." (Pedro Domingos, "The Master Algorithm", 2015)

"Underfitting is when a model doesn’t take into account enough information to accurately model real life. For example, if we observed only two points on an exponential curve, we would probably assert that there is a linear relationship there. But there may not be a pattern, because there are only two points to reference. [...] It seems that the best way to mitigate underfitting a model is to give it more information, but this actually can be a problem as well. More data can mean more noise and more problems. Using too much data and too complex of a model will yield something that works for that particular data set and nothing else." (Matthew Kirk, "Thoughtful Machine Learning", 2015)

"We are moving slowly into an era where Big Data is the starting point, not the end." (Pearl Zhu, "Digital Master: Debunk the Myths of Enterprise Digital Maturity", 2015)

"A popular misconception holds that the era of Big Data means the end of a need for sampling. In fact, the proliferation of data of varying quality and relevance reinforces the need for sampling as a tool to work efficiently with a variety of data, and minimize bias. Even in a Big Data project, predictive models are typically developed and piloted with samples." (Peter C Bruce & Andrew G Bruce, "Statistics for Data Scientists: 50 Essential Concepts", 2016)

"Big data is, in a nutshell, large amounts of data that can be gathered up and analyzed to determine whether any patterns emerge and to make better decisions." (Daniel Covington, Analytics: Data Science, Data Analysis and Predictive Analytics for Business, 2016)

"Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit." (Cathy O'Neil, "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy", 2016)

"While Big Data, when managed wisely, can provide important insights, many of them will be disruptive. After all, it aims to find patterns that are invisible to human eyes. The challenge for data scientists is to understand the ecosystems they are wading into and to present not just the problems but also their possible solutions." (Cathy O'Neil, "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy", 2016)

"Big Data allows us to meaningfully zoom in on small segments of a dataset to gain new insights on who we are." (Seth Stephens-Davidowitz, "Everybody Lies: What the Internet Can Tell Us About Who We Really Are", 2017)

"Effects without an understanding of the causes behind them, on the other hand, are just bunches of data points floating in the ether, offering nothing useful by themselves. Big Data is information, equivalent to the patterns of light that fall onto the eye. Big Data is like the history of stimuli that our eyes have responded to. And as we discussed earlier, stimuli are themselves meaningless because they could mean anything. The same is true for Big Data, unless something transformative is brought to all those data sets… understanding." (Beau Lotto, "Deviate: The Science of Seeing Differently", 2017)

"The term [Big Data] simply refers to sets of data so immense that they require new methods of mathematical analysis, and numerous servers. Big Data - and, more accurately, the capacity to collect it - has changed the way companies conduct business and governments look at problems, since the belief wildly trumpeted in the media is that this vast repository of information will yield deep insights that were previously out of reach." (Beau Lotto, "Deviate: The Science of Seeing Differently", 2017)

"There are other problems with Big Data. In any large data set, there are bound to be inconsistencies, misclassifications, missing data - in other words, errors, blunders, and possibly lies. These problems with individual items occur in any data set, but they are often hidden in a large mass of numbers even when these numbers are generated out of computer interactions." (David S Salsburg, "Errors, Blunders, and Lies: How to Tell the Difference", 2017)

"Just as they did thirty years ago, machine learning programs (including those with deep neural networks) operate almost entirely in an associational mode. They are driven by a stream of observations to which they attempt to fit a function, in much the same way that a statistician tries to fit a line to a collection of points. Deep neural networks have added many more layers to the complexity of the fitted function, but raw data still drives the fitting process. They continue to improve in accuracy as more data are fitted, but they do not benefit from the 'super-evolutionary speedup'."  (Judea Pearl & Dana Mackenzie, "The Book of Why: The new science of cause and effect", 2018)

"One of the biggest myths is the belief that data science is an autonomous process that we can let loose on our data to find the answers to our problems. In reality, data science requires skilled human oversight throughout the different stages of the process. [...] The second big myth of data science is that every data science project needs big data and needs to use deep learning. In general, having more data helps, but having the right data is the more important requirement. [...] A third data science myth is that modern data science software is easy to use, and so data science is easy to do. [...] The last myth about data science [...] is the belief that data science pays for itself quickly. The truth of this belief depends on the context of the organization. Adopting data science can require significant investment in terms of developing data infrastructure and hiring staff with data science expertise. Furthermore, data science will not give positive results on every project." (John D Kelleher & Brendan Tierney, "Data Science", 2018)

"Apart from the technical challenge of working with the data itself, visualization in big data is different because showing the individual observations is just not an option. But visualization is essential here: for analysis to work well, we have to be assured that patterns and errors in the data have been spotted and understood. That is only possible by visualization with big data, because nobody can look over the data in a table or spreadsheet." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"With the growing availability of massive data sets and user-friendly analysis software, it might be thought that there is less need for training in statistical methods. This would be naïve in the extreme. Far from freeing us from the need for statistical skills, bigger data and the rise in the number and complexity of scientific studies makes it even more difficult to draw appropriate conclusions. More data means that we need to be even more aware of what the evidence is actually worth." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)

"Big data is revolutionizing the world around us, and it is easy to feel alienated by tales of computers handing down decisions made in ways we don’t understand. I think we’re right to be concerned. Modern data analytics can produce some miraculous results, but big data is often less trustworthy than small data. Small data can typically be scrutinized; big data tends to be locked away in the vaults of Silicon Valley. The simple statistical tools used to analyze small datasets are usually easy to check; pattern-recognizing algorithms can all too easily be mysterious and commercially sensitive black boxes." (Tim Harford, "The Data Detective: Ten easy rules to make sense of statistics", 2020)

"Making big data work is harder than it seems. Statisticians have spent the past two hundred years figuring out what traps lie in wait when we try to understand the world through data. The data are bigger, faster, and cheaper these days, but we must not pretend that the traps have all been made safe. They have not." (Tim Harford, "The Data Detective: Ten easy rules to make sense of statistics", 2020)

"Many people have strong intuitions about whether they would rather have a vital decision about them made by algorithms or humans. Some people are touchingly impressed by the capabilities of the algorithms; others have far too much faith in human judgment. The truth is that sometimes the algorithms will do better than the humans, and sometimes they won’t. If we want to avoid the problems and unlock the promise of big data, we’re going to need to assess the performance of the algorithms on a case-by-case basis. All too often, this is much harder than it should be. […] So the problem is not the algorithms, or the big datasets. The problem is a lack of scrutiny, transparency, and debate." (Tim Harford, "The Data Detective: Ten easy rules to make sense of statistics", 2020)

"The problem is the hype, the notion that something magical will emerge if only we can accumulate data on a large enough scale. We just need to be reminded: Big data is not better; it’s just bigger. And it certainly doesn’t speak for itself." (Carl T Bergstrom & Jevin D West, "Calling Bullshit: The Art of Skepticism in a Data-Driven World", 2020)

"[...] the focus on Big Data AI seems to be an excuse to put forth a number of vague and hand-waving theories, where the actual details and the ultimate success of neuroscience is handed over to quasi- mythological claims about the powers of large datasets and inductive computation. Where humans fail to illuminate a complicated domain with testable theory, machine learning and big data supposedly can step in and render traditional concerns about finding robust theories. This seems to be the logic of Data Brain efforts today. (Erik J Larson, "The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do", 2021)

"We live on islands surrounded by seas of data. Some call it 'big data'. In these seas live various species of observable phenomena. Ideas, hypotheses, explanations, and graphics also roam in the seas of data and can clarify the waters or allow unsupported species to die. These creatures thrive on visual explanation and scientific proof. Over time new varieties of graphical species arise, prompted by new problems and inner visions of the fishers in the seas of data." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)

"Visualizations can remove the background noise from enormous sets of data so that only the most important points stand out to the intended audience. This is particularly important in the era of big data. The more data there is, the more chance for noise and outliers to interfere with the core concepts of the data set." (Kate Strachnyi, "ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color", 2023)

"Visualisation is fundamentally limited by the number of pixels you can pump to a screen. If you have big data, you have way more data than pixels, so you have to summarise your data. Statistics gives you lots of really good tools for this." (Hadley Wickham)