digital process automation

Running an event-driven health management business process through a few scenarios: Part 1

Running an event-driven health management business process through a few scenarios: Part 1

In the previous series of articles, Designing an event-driven business process at scale: A health management example (which you need to read to fully understand this one), you designed and implemented an event-driven scalable business process for the population health management use case. Now, you will run this process through a few scenarios. In this way, you will:

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Designing an event-driven process at scale: Part 3

Designing an event-driven process at scale: Part 3

In the first article in this series, Designing an event-driven business process at scale: A health management example, Part 1, you found the business use case and data model for a concrete example from the health management industry. You then began implementing the example in jBPM (an open source business automation suite) by creating the Trigger process.

In the second article, you implemented the Task subprocess and, among other things, you also configured the call parameters for the Reminder and Escalation subprocesses within the Task subprocess. Now you will implement these subprocesses.

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Designing an event-driven business process at scale: A health management example, Part 1

Designing an event-driven business process at scale: A health management example, Part 1

The concept of a business process (BP), or workflow (WF), and the discipline and practice of business process management (BPM) have been around since the early 90s. Since then, WF/BPM tools have evolved considerably. More recently, a convergence of different tools has taken place, adding decision management (DM) and case management (CM) to the mix. The ascendance of data science, machine learning, and artificial intelligence in the last few years has further complicated the picture. The mature field of BPM has been subsumed into the hyped pseudo-novelties of digital business automation, digital reinvention, digital everything, etc., with the addition of “low code” and robotic process automation (RPA).

A common requirement of business applications today is to be event-driven; that is, specific events should trigger a workflow or decision in real-time. This requirement leads to a fundamental problem. In realistic situations, there are many different types of events, each one requiring specific handling. An event-driven business application may have hundreds of qualitatively different workflows or processes. As new types of events arise in today’s ever-changing business conditions, new processes have to be designed and deployed as quickly as possible.

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Reducing data inconsistencies with Red Hat Process Automation Manager

Reducing data inconsistencies with Red Hat Process Automation Manager

Managing data reconciliation through a specific process is a common necessity for projects that require Digital Process Automation (formerly known as Business Process Management), and Red Hat Process Automation Manager helps to address such a requirement. This article provides good practices and a technique for satisfying data reconciliation in a structured and clean way.

Red Hat Process Automation Manager was formerly known as Red Hat JBoss BPM Suite, so it’s worth mentioning that jBPM is the upstream project that fuels Process Automation Manager. The blog post From BPM and business automation to digital automation platforms explains the reasons behind the new name and shares exciting news for this major release.

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