Dictionary · IEEE Guide for Terms and Concepts in Intelligent Process Automation

An activity, task, or input that describes or defines the beginning of a process.

The successful execution of a service, process, or transaction performed entirely through traditional application platforms with predefined interfaces (i.e., application programming interfaces [APIs]).

A subordinate process that can be included within a parent process. It can be present and/or repeated within other parent processes.

The performance of a discrete activity with a defined start, stop, and outcome that cannot be broken down to a finer level of detail.

Enactment of a process represented by a set of coordinated activities carried out by multiple systems and/or participants in accordance with defined relationships. This coordination leads to an intentional, consistent, and verifiable result across all participants.

Work that an organization performs using business processes; can be singular or compound.

Complex computational systems designed to — Sense (perceive the world and collect data); — Comprehend (analyze and understand the information collected); - Act (make informed decisions and provide guidance based on this analysis in an independent way); and — Adapt (adapt capabilities based on experience) in ways comparable to the human brain.

The beneficiary of the execution of an automated task, process, or service.

Process automation execution of intentionally segregated work processes that are able to be processed irrespective of their contextual placement within a service.

The ingestion of a corpus, application of semantic mapping, and relevant ontology of structured and/or unstructured data that yields inference and correlation leading to the creation of useful conclusive or predictive capabilities in a given knowledge domain. Strong AI learning also includes the capability of creating unique hypotheses, attributing data relevance, processing data relationships, and updating its own lines of inquiry to further the usefulness of its purpose.

The identification, assessment, and application of available machine learning algorithms for the purpose of leveraging domain knowledge and reasoning to further automate the machine learning already present in a manner that may be thought of as cognitive. With cognitive automation, the system performs corrective actions driven by knowledge of the underlying analytics tool itself, iterates its own automation approaches and algorithms for more expansive or more thorough analysis, and is thereby able to fulfill its purpose. The automation of the cognitive process refines itself and dynamically generates novel hypotheses that it can likewise assess against its existing corpus and other information resources.

Definition, constraint, dependency, or decision criteria that determine the method of execution of a task or tasks, or influences the order of execution of a task or tasks. Business rules assert control, or influence the behavior, of a business process within computing systems.

Complex, computational, cognitive automation system capable of providing descriptive, predictive, prescriptive, and limited deductive analytics with relevance and accuracy exceeding human expertise in a broad, logically related set of knowledge domains.

A defined set of business activities that represent the steps or tasks required to achieve a business objective, including the flow and use of information, participants, and human or digital resources.

Independent machine-managed choreography of the operation of one or more digital systems.

Discipline involving any combination of modeling, automation, execution, control, measurement and optimization of business activity flows, in support of enterprise goals, spanning systems, employees, customers, and partners within and beyond the enterprise boundaries.

A monitor-analyze-plan-execute (MAPE) computer system capable of sensing environments, interpreting policy, accessing knowledge (data --- information --- knowledge), making decisions, and initiating dynamically assembled routines of choreographed activity to both complete a process and update the set of environmental variables that enables the autonomic system to self-manage its own operation and the processes it oversees. An autonomic system is identified by eight characteristics: a) Knows the resources to which it has access, what its capabilities and limitations are, and how and why it is connected to other systems. b) Is able to configure and reconfigure itself depending on the changing computing environment. c) Is able to optimize its performance to ensure the most efficient computing process. d) Is able to work around encountered problems either by repairing itself or routing functions away from the trouble. e) Is able to detect, identify, and protect itself against various types of attacks to maintain overall system security and integrity. f) Is able to adapt to its environment as it changes by interacting with neighboring systems and establishing communication protocols. g) Relies on open standards and requires access to proprietary environments to achieve full performance. h) Is able to anticipate the demand on its resources transparently to users.

An ordered sequence of system-to-system message exchanges between two or more participants. In choreography, there is no central controller, responsible entity, or observer of the process.

A deliberately assembled collection of knowledge and data (structured and/or unstructured) believed to contain relevant information on a topic or topics to be used by software systems for which useful analysis, prediction, or outcome is being sought.

A computing system with sufficient knowledge regarding its purpose that it understands the source, relevance, and utility of data and inputs.

The intentional introduction of initial state conditions, influencing factors, and outcomes (both successful and unsuccessful) in a data fabric to create sufficient machine learning analysis signals to enable encouragement/discouragement to enrich deterministic relationships between data elements in a given information domain.

Digital automation of information technology systems and/or business processes that successfully delivers work output previously performed by human labor or new work output that would typically or alternatively have been performed by human labor.

A data corpus, after the application of semantic mapping, relevant ontologies, and data seeding sufficient for artificial intelligence (AI) or machine learning algorithms to provide meaningful insight, prediction, and/or prescription.

The collective suite of automation technologies delivering existing or new work output as applied in a business; the manifestation of digital labor.

Insights, reporting, and information answering the question, “Why did something happen?” Descriptive analytics determines information useful to understanding the cause(s) of an event(s).

A point within a business process where the process flow can take one of several alternative paths, including recursive.

A conclusion reached after consideration of business rules and relevant data within a given process.

The process in which one or more paths are defined and may be utilized based on the conditions present at the time of execution.

Insights, reporting, and information answering the question, "What would likely happen IF…?” Deductive analytics evaluates causes and outcomes of possible future events.

Insights, reporting, and information answering the question, “Why did something happen?” Diagnostic analytics determines information useful to understanding the cause(s) of an event(s).

An activity, task, or output that describes or defines the conclusion of a process.

An event that occurs during the performance of the process that causes a diversion from the normal flow of the process. Exceptions are generated by an unanticipated event within a process due to an undefined or unknown input, undefined or unexpected outcome, or unforeseen sequencing of a task or event.

Detection, correlation, and pattern recognition generated through machine-based observation of human operation of software systems capturing successful or unsuccessful operations to enable the creation of a useful predictive analytics capability.

A preconfigured software instance that combines business rules, experience- based context determination logic, and decision criteria to initiate and execute multiple interrelated human and automated processes in a dynamic context. The goal is to complete the execution of a combination of processes, activities, and tasks in one or more unrelated software systems that deliver a result or service with minimal or no human intervention.

Insights, reporting, and information answering the question, “What should I do about it?" Prescriptive analytics determines information that provides high confidence actions necessary to recover from an event or fulfill a need.

A computer system, data, input, business rule, human intervention, and other contributor to the flow of a process.

The sum of all information derived from diagnostic, descriptive, predictive, and prescriptive analytics embedded in or available to or from a cognitive computing system.

Machine detection and interpretation of relevant and meaningful events and conditions that impact operation of the computer system itself or other dependent mechanisms or processes essential to the purpose of the system.

A sequence or flow of activities in an organization with the objective of carrying out work, which may include a set of activities, events, tasks, and decisions in a sequenced flow that adhere to finite execution semantics. Process levels will generally follow structure at the capability maturity model integration (CMMI) level.

The intended flow of a process originating from a start event, continuing through all defined activities, and concluding successfully to its defined end event.

A set of concepts and categories in a subject area or knowledge domain that shows their properties and the relationships among them to enable interoperability among disparate elements and systems and specify interfaces to independent, knowledge-based services for the purpose of enabling certain kinds of automated reasoning.

The organization of analyses of structured and unstructured data for inference and correlation that provides a useful predictive capability to new circumstances or data.

Insights, reporting, and information answering the question, "What is likely to happen?" Predictive analytics support high confidence foretelling of future event(s).

The defined representation of the overall progression of how a process is intended to be performed, including all exceptions.

The computer application that makes available to a human operator a suite of predefined activity choreography to complete the execution of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service in the course of human-initiated or -managed workflow.

A process that may contain one or more sub-processes, activities, and tasks.

The granting of access rights and executional privilege to an agent (human or machine) within an application(s) or system(s).

The consequential outcome of completing a process.

The conversion of typically analog or human sensory perception (e.g., vision, speech) to a digital format useful for machine-to-human interaction or machine processing of traditionally analog sensory information [e.g., optical character recognition (OCR)].

A preconfigured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management.

A computing system able to perceive that it is not operating correctly and, without human intervention, make the necessary adjustments to restore itself to normalcy.

A computing platform imbued with sufficient knowledge and analytic capability to make useful conclusions about its inputs, its own processing, and the use of its output so that it is capable of self- judgment and improvement consistent with its purpose.

The ability to increase or decrease the computational resources required to execute a varying volume of tasks, processes, or services.

A strategic schema or framework of metadata labels applied to all data, data groups, data fields, data types, or data content used to introduce new or raw data into a corpus or data fabric to give machine learning algorithms direction for investigating known or potential relationships between data. A semantic map provides a structure for the introduction of new data, information, or knowledge

A collection of coordinated processes that takes one or more kinds of input, performs a value-added transformation, and creates an output that fulfills the needs of a customer [or shareholder].