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Digital Transformation with Internet of Things in Intelligent BPM

By Setrag Khoshafian, Chief Evangelist & VP of BPM Technology, Pegasystems


Setrag Khoshafian, Chief Evangelist & VP of BPM Technology, Pegasystems

The disruptive forces of digitization are tremendous. With the emerging role of CIOs for digital transformation, IT needs to regain its relevance and become a catalyst for change in this new digital milieu. The digitization trends are social, mobile, cloud, big data and most importantly the Internet of Things.It is estimated anywhere between 20 billion to 50 billion and maybe even a trillion connected devices on the Internet by the year 2020! Connected smart devices and Things are transforming IT precisely because of the ubiquitous and increasingly seamless integration of connectivity within the enterprise. However, isolated Things could pose challenges and potential problems for IT. Devices as well as the accompanying applications and systems could become yet another silo that IT needs to deal with from integration to security as well as maintenance perspective. More important, Things by themselves add little business value if they are not integrated in end-to-end solutions solving business challenges.

Process of Everything

Intelligent Business Process Management (iBPM) is a digital transformation discipline with the associated automation platform that aligns business objectives to execution. There are a number of trends that have influenced the evolution of iBPM – making it the core engine of transformation for digital enterprises. Two of these trends are the process participants and process intelligence.

• Process Participants: BPM has its roots in human participant-focused workflow systems. The coordination in this category is human-to-human. While some BPM technologies and methods are still purely workflow-focused, iBPM is much more than that. Other significant categories of software that have influenced the evolution of iBPM include Enterprise Application Integration (EAI) and Business-to-Business (B2B) integration. With the Internet of Things (aka IoT) as well as Internet of Everything (IoE), Industrial Internet and machine-to-machine (M2M)) iBPM now includes Things as active participants in end-to-end digitized and automated processes that connect the edge devices to the digital enterprise.

• Process Intelligence: The intelligence in processes emanates from a number of core capabilities in an iBPM system. These include a rich collection of business rule types, predictive analytics, adaptive (learning) decisioning, event rules, and 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 iBPM

Things (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 (potentially 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 addressed through maintenance 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 andBig 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 aggregateoperational 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.

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