| | June 2015 19CIOReviewIT finds itself running at three speeds at the same time: the maintenance speed, the efficiency speed to do more with less, and the digital innovation speedSetrag Khoshafian"recommendations from Big Data. Business rules--such as constraints, decision trees/tables, expressions, etc.--are an integral part of business process solutions. Often this process intelligence is harvested from knowledge workers. Predictive and self-learning adaptive analytics mine these data sources (from people, applications, and Things) to create actionable predictive models.Four Use Cases of Internet of Things in iBPMThings (including robots and smart devices) are becoming active participants in intelligent processes, often seamlessly. Business process tasks that were assigned to humans such as measuring temperature, pollution levels, or updating software are increasingly being assigned to Things. There are four main use cases of Things in iBPM:Things as Participants in Processes: Traditionally, the participants in BPM were humans (roles, skills, teams, etc.), systems (back-end applications or services), and business partners (for B2B processes). With IoT and the Process of Everything, Things (including Robots) are also participants in processes. In iBPM solutions Things (e.g. Vehicle components) will start to diagnose and maintain themselves. Similarly Robots will become active performers of maintenance tasks. Dynamic Processes Instantiated from Thing events: One of the most pervasive use cases for Process of Everything is the instantiation of an iBPM solutions (for instance a maintenance case) when sensing (through IoT sensors) a failure or critical issue with the device. This happens for example when detecting elevated temperature levels, or abnormal sounds or motions. The intelligent Thing autonomously senses and then activates an exception process or case. Real-Time Complex Event Correlation for PoE. The previous use case elucidated an adverse event or state that was sensed ( p o te n t i a ll y analyzed at the edge or the device) to instantiate a process. Often it is not just an individual event but a stream of events that could indicate a potential problem that need to be a dd re ss e d t h r o u g h ma i n t e na n c e cases. For example if two temperature peaks occurred within, say, five minutes it could indicate a serious problem that needs to be addressed through a Process of Everything solution. Predictive and Big Data analytics for Process of Everything: Connected Things are generating enormous amounts of data. Big Data will increasingly become Thing Data. This data could be mined and analyzed to better understand the digitized processes' as well as devices' behavioral characteristics. The data is aggregated over time and subsequently visualized and analyzed using predictive analytics models. The discovered knowledge and predictive models are then digitized in iBPM Process of Everything solutions.CIOs have tremendous challenges and opportunities in this new digital era. Process of Everything allows IT to aggregate operational technologies on the edges with Information technology. Increasingly intelligent devices and Things become activity participants in end-to-edn digitized processes, collaborating and assisting humans to achieve transformative business objectives.1234
<
Page 9 |
Page 11 >