Algorithm economy—algorithms enable computing machines to make sense of data and use it. Developing them for purposes of distribution and resale is a recent activity. Companies are monetizing these algorithms to realize their economic value.
Analytics—“extensive use of data, statistical and quantitative analysis, exploratory and predictive models, and fact-based management to drive decisions and actions. The analytics may be input for human decisions or drive fully automated decisions” (Davenport and Harris 2007, p. 7). Analytics refers to quantitative and statistical analysis and manipulation of data to derive meaning. Analytics is a broad umbrella term that includes business analytics and data analytics.
Big data—very large data volumes that are complex and varied, and often collected and must be analyzed in real time.
Business analytics—use of data and quantitative and qualitative tools and techniques to improve operations and to support business decision making. Emphasis on using statistical and management science techniques, including data mining, to develop predictive and prescriptive models.
Business intelligence—umbrella term that describe a set of concepts and methods to improve business decision making by using fact-based decision support systems. Also, refers to a category of software tools that can be used to extract and analyze data from corporate databases.
Cloud analytics—a data analytics service provided through a public or private cloud.
Customer engagement—establishing a strong business relationship between a customer and an organization. Customer engagement may be a strategic objective of an organization’s digital transformation strategy.
Data—relevant facts, figures, and digital content captured in information systems. Raw data are the bits and bytes stored electronically.
Data analytics—applying quantitative and statistical methods to analyze large, complex data sets. See analytics and business analytics.
Data-based decision making—a broad concept that prescribes an ongoing process of collecting and analyzing different types of data to aid in making fact-based, routine and nonroutine decisions. Use of diverse data types from a variety of sources. A process where quantitative data is balanced with “softer” data that is more descriptive in nature.
Data-centric culture—data is highly valued in the organization. The importance of data is embedded in everything we do.
Data-centric organization—an organization with policies and a culture that encourage and reward the use of data in products, processes, and decision making. Also, sometimes called a data-driven or data-informed organization.
Data-driven decision making—collection and analysis of data to make decisions. Data “drives” the decision making and decisions are made using data or facts rather than intuition. Data-driven decision making is often used interchangeably with the term data-based decision making, but it often implies decision automation using artificial intelligence and algorithms.
Data governance—processes and procedures implemented by organizations to ensure data quality.
Data-informed decision making—term used when data and facts are an influential factor in decision making, but not the only factor.
Data storytelling—using a combination of data facts and a qualitative “story” that provides effective communication of a business message.
Data visualization—communication of data using visual prompts or representations such as charts, graphs, and other illustrations.
Decision support system (DSS)—a computer-based information system that supports individual or team decision making. Five primary types: communications-driven, data-driven, document-driven, knowledge-driven, and data-driven DSS.
Digital transformation—use of new information technologies such as analytics, mobile devices, social media and smart embedded devices to change and improve business processes, improve performance, alter business models, enhance products, and change customer experiences. Integration of digital technologies into all areas of an organization, fundamentally changing operations.
Digital transformation maturity—amount of progress in implementing actions reimaging or reinventing an organization, typically leveraging existing and new digital technology.
Digitalization—enabling, improving, and/or changing business operations and business processes and activities using digital data and technologies. Often used interchangeably with digitization and digital transformation.
Digitization—using digital data to automate business processes and workflows.
Ethical decision making—application of moral rules, codes, or principles to guide choices for right and truthful behavior. A process of evaluating and choosing among alternatives in a manner consistent with ethical principles. Generally part of data-based decision-making processes.
Fact—a statement or numerical value consistent with reality or that can be proven with evidence. A fact is something known to have happened or to exist. In general, a fact can be verified as true.
High velocity decision making—use of streamlined, rapid decision processes focused on issues while ensuring decision making processes are thoughtful and goal-oriented.
Internet of Things (IoT)—computing or “smart” devices often with sensor capability and the ability to collect, share, and transfer data using the Internet.
Machine Learning (ML)—a subset of AI systems that use algorithms to learn from data and improve based on experience without being explicitly reprogrammed.
Operating or function-specific decisions—day-to-day, routine decisions with a concise decision question and a clear, well-defined, and structured algorithm to make a choice among alternatives.
Predictive analytics—general term for using simple and complex models to support anticipatory decision making. Often a process of using a quantitative model and current real-time or historical data to generate a score that is predictive of future behavior.
Prescriptive analytics—manipulate large data sets to make recommendations. Decision support that prescribes or recommends an action, rather than a forecast or a summary report.
Rationality—consistent with or based on logic and facts. Behavior that demonstrates good sense and sound judgment.
Reporting analytics—Descriptive or reporting analytics describes or summarizes past results, actions, or activities.
Strategic decisions—complex, nonroutine, unstructured decisions involving many different and connected parts. Some variables may not be well understood, often information required to make the decision may be unavailable, incomplete, and in some situations information may be known to be flawed or inaccurate. These decisions usually involve a high degree of uncertainty about outcomes. If implemented, strategic decisions often result in major changes in an organization.
Tactical decisions—broader decision questions than operational decisions, semistructured in nature, some but not all information necessary to make the decision is available, primarily internally focused and made by middle-level managers.