Gartner defines business processes as the coordination of the behavior of people, systems and things to produce specific business outcomes. 'Things' in this context refers to devices that are part of the Internet of Things (IoT). A BPM platform minimally includes: a graphical business process and/or rule modeling capability, a process registry/repository to handle the modeling metadata, a process execution engine and a state management engine or rule engine (or both). The three types of BPM platforms — basic BPM platforms, business process management suites (BPMSs), and intelligent business process management suites (iBPMSs) — can help solution architects and business outcome owners accelerate application development, transform business processes, and digitalize business processes to exploit business moments by providing capabilities that manage different aspects of the business process life cycle.
Gartner defines the market for enterprise architecture (EA) tools as tools that allow users to capture the interrelationships and interdependencies within and across the ecosystem of partners, operating models, capabilities, people, processes, information, applications and technologies. EA tools provide a central repository to capture data and metadata about artifacts that describe the enterprise. Models can be built to represent the relationships between these artifacts that help describe and shape the future of the enterprise. Through modeling features, EA tools enable scenario analysis of trends and disruptions and other drivers of enterprise change, to deliver realistic roadmaps.
EBPA is a comprehensive approach toward business and process modeling aimed at transforming and improving business performance with an emphasis on cross-viewpoint (strategy, analysis, architecture, automation), cross-functional analysis to support strategic and operational decisions.
Process mining platforms are designed to discover, monitor and improve processes by extracting knowledge from events captured in information systems to continuously deliver visibility and insights. Process mining includes automated process discovery (extracting process models from an event log), conformance checking (monitoring deviations by comparing model and log), social network/organizational mining, automated construction of simulation models, model extension, model repair, case prediction and history-based recommendations. Process mining platforms extend process mining capabilities by advanced process analytics, process improvement detection and process improvement recommendations, partly driven by AI and generative AI (GenAI).