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Enterprise Decision Management
Decision management, also known as enterprise decision management (EDM) or business decision management (BDM) entails all aspects of designing, building and managing the automated decision-making systems that an organization uses to manage its interactions with customers, employees and suppliers. Computerization has changed the way organizations are approaching their decision-making because it requires that they automate more decisions, to handle response times and unattended operation required by computerization, and because it has enabled "information-based decisions" – decisions based on analysis of historical behavioral data, prior decisions, and their outcomes. Overview Decision management was described in 2005 as an "emerging important discipline, due to an increasing need to automate high-volume decisions across the enterprise and to impart precision, consistency, and agility in the decision-making process". Decision management is implemented "via the use of rule-based sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Decision-making
Automated decision-making (ADM) involves the use of data, machines and algorithms to make decisions in a range of contexts, including public administration, business, health, education, law, employment, transport, media and entertainment, with varying degrees of human oversight or intervention. ADM involves large-scale data from a range of sources, such as databases, text, social media, sensors, images or speech, that is processed using various technologies including computer software, algorithms, machine learning, natural language processing, artificial intelligence, augmented intelligence and robotics. The increasing use of automated decision-making systems (ADMS) across a range of contexts presents many benefits and challenges to human society requiring consideration of the technical, legal, ethical, societal, educational, economic and health consequences. Overview There are different definitions of ADM based on the level of automation involved. Some definitions suggests ADM i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Model And Notation
In business analysis, the Decision Model and Notation (DMN) is a standard published by the Object Management Group.OMG standard "Decision Model and Notation (DMN)"current version/ref> It is a standard approach for describing and modeling repeatable decisions within organizations to ensure that decision models are interchangeable across organizations. The DMN standard provides the industry with a modeling notation for decisions that will support decision management and business rules. The notation is designed to be readable by business and IT users alike. This enables various groups to effectively collaborate in defining a decision model: * the business people who manage and monitor the decisions, * the business analysts or functional analysts who document the initial decision requirements and specify the detailed decision models and decision logic, * the technical developers responsible for the automation of systems that make the decisions. The DMN standard can be effectively u ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Engineering
Decision intelligence is an engineering discipline that augments data science with theory from social science, decision theory, and managerial science. Its application provides a framework for best practices in organizational decision-making and processes for applying machine learning at scale. The basic idea is that decisions are based on our understanding of how actions lead to outcomes. Decision intelligence is a discipline for analyzing this chain of cause and effect, and decision modeling is a visual language for representing these chains. A related field decision engineering also investigates the improvement of decision-making processes but is not always as closely tied to data science. Origins and technologies Decision intelligence is based on the recognition that, in many organizations, decision-making could be improved if a more structured approach were used. Decision intelligence seeks to overcome a decision-making "complexity ceiling", which is characterized by a mi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Making Software
Decision may refer to: Law and politics *Judgment (law), as the outcome of a legal case *Landmark decision, the outcome of a case that sets a legal precedent * ''Per curiam'' decision, by a court with multiple judges Books * ''Decision'' (novel), a 1983 political novel by Allen Drury * ''The Decision'' (novel), a 1998 book in the ''Animorphs'' series Sports *Decision (baseball), a statistical credit earned by a baseball pitcher * Decisions in combat sports *Decisions (professional wrestling), by which a wrestler scores a point against his opponent Film and TV * ''Decision'' (TV series), an American anthology TV series * ''The Decision'' (play), by the 20th-century German dramatist Bertolt Brecht * ''The Decision'' (TV special), in which NBA player LeBron James announced that he would switch teams * "The Decision" (song), by English indie rock band Young Knives Music Albums * ''Decisions'' (George Adams and Don Pullen album), 1984 * ''Decisions'' (The Winans album), 1987 Songs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Predictive Analytics
Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud det ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Business Rules
A business rule defines or constrains some aspect of business. It may be expressed to specify an action to be taken when certain conditions are true or may be phrased so it can only resolve to either true or false. Business rules are intended to assert business structure or to control or influence the behavior of the business. Business rules describe the operations, definitions and constraints that apply to an organization. Business rules can apply to people, processes, corporate behavior and computing systems in an organization, and are put in place to help the organization achieve its goals. For example, a business rule might state that ''no credit check is to be performed on return customers''. Other examples of business rules include requiring a rental agent to disallow a rental tenant if their credit rating is too low, or requiring company agents to use a list of preferred suppliers and supply schedules. While a business rule may be informal or even unwritten, documenting the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Experimentation
An experiment is a procedure carried out to support or refute a hypothesis, or determine the efficacy or likelihood of something previously untried. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale but always rely on repeatable procedure and logical analysis of the results. There also exist natural experimental studies. A child may carry out basic experiments to understand how things fall to the ground, while teams of scientists may take years of systematic investigation to advance their understanding of a phenomenon. Experiments and other types of hands-on activities are very important to student learning in the science classroom. Experiments can raise test scores and help a student become more engaged and interested in the material they are learning, especially when used over time. Experiments can vary from personal and informal natural comparisons (e. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
A/B Testing
A/B testing (also known as bucket testing, split-run testing, or split testing) is a user experience research methodology. A/B tests consist of a randomized experiment that usually involves two variants (A and B), although the concept can be also extended to multiple variants of the same variable. It includes application of statistical hypothesis testing or " two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare multiple versions of a single variable, for example by testing a subject's response to variant A against variant B, and determining which of the variants is more effective. Overview "A/B testing" is a shorthand for a simple randomized controlled experiment, in which a number of samples (e.g. A and B) of a single vector-variable are compared. These values are similar except for one variation which might affect a user's behavior. A/B tests are widely considered the simplest form of controlled experiment, especially when the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Business Rules
A business rule defines or constrains some aspect of business. It may be expressed to specify an action to be taken when certain conditions are true or may be phrased so it can only resolve to either true or false. Business rules are intended to assert business structure or to control or influence the behavior of the business. Business rules describe the operations, definitions and constraints that apply to an organization. Business rules can apply to people, processes, corporate behavior and computing systems in an organization, and are put in place to help the organization achieve its goals. For example, a business rule might state that ''no credit check is to be performed on return customers''. Other examples of business rules include requiring a rental agent to disallow a rental tenant if their credit rating is too low, or requiring company agents to use a list of preferred suppliers and supply schedules. While a business rule may be informal or even unwritten, documenting the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Model
A decision model in decision theory is the starting point for a decision method within a formal (axiomatic) system. Decision models contain at least one action axiom. An action is in the form "IF is true, THEN do ". An action axiom tests a condition (antecedent) and, if the condition has been met, then (consequent) it suggests (mandates) an action: from knowledge to action. A decision model may also be a network of connected decisions, information and knowledge that represents a decision-making approach that can be used repeatedly (such as one developed using the Decision Model and Notation standard). Excepting very simple situations, successful action axioms are used in an iterative manner. For example, for decision analysis, the sole action axiom occurs in the Evaluation stage of a four-step cycle: Formulate, Evaluate, Interpret/Appraise, Refine. Decision models are used both to model a decision being made once, as well as to model a repeatable decision-making approach that wil ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
