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 decision intelligence platforms (DIPs) as software to create decision-centric solutions that support, augment and automate decision making of humans or machines, powered by the composition of data, analytics, knowledge and AI. DIPs enable enterprises to collaboratively design and explicitly model decisions, orchestrate decision flow during execution at scale, and enable monitoring and governance of decision quality, while learning from actions and outcomes. Features can include a combination of rule- and logic-based techniques, machine learning, real-time event stream processing, business intelligence, multimodal data and analytics preparation, natural language, graph technology, optimization, simulation or AI agents for decision intelligence. DIPs provide a solution to enhance how organizations make decisions, whether by humans or machines, individually or collectively. They address the growing challenge of making timely and accurate decisions in volatile, uncertain, complex and ambiguous ecosystems, for more demanding customers in disruptive, competitive and regulated markets. DIPs help by creating executable decision models that improve decision service composition and all-source intelligence to achieve better situational awareness, better recommendations or autonomous actions, tailored to specific decisions and outcomes. They can reduce the risk of poor decisions, allow organizations to anticipate change and respond more swiftly to opportunities at scale.