An old friend, Guilhem Molines, has been working with some colleagues on a new book – Intelligent Automation with IBM Cloud Pak for Business Automation – and I got a chance to read it recently. The book covers all the components of IBM’s Cloud Pak for Business Automation. Decision Management Solutions is an IBM Business Partner and we regularly help clients adopt and use Cloud Pak for Business Automation. IBM Cloud Pak for Business Automation is expansive set of software components used by large enterprises to automate their day to day operations. Here’s how IBM describes it:
IBM Cloud Pak for Business Automation is a modular set of integrated software components, built for any hybrid cloud, designed to automate work and accelerate business growth. This end-to-end automation platform helps you analyze workflows, design AI-infused apps with low-code tooling, assign tasks to bots and track performance.
Each component can do a lot, so describing how to use the whole Cloud Pak effectively is a significant challenge – but one that this book meets.
The book itself has three parts.
- Part 1 has an overview of the Cloud Pak and a brief discussion of each element’s key components.
- Part 2 discusses a set of use cases and associated best practices – task automation and chatbots with RPA, workflow automation, decision automation, content management, document processing, business applications and workforce insights.
- Part 3 covers some deployment considerations.
The book begins with a simple but well described scenario showing how the pieces fit together and then drills into each of the core technologies. A series of brisk but thorough overviews of each technology cover key UIs and architectural patterns. These overview chapters include some good tips on approach – unusual for a technical book – that help put things in context and provide some best practices. The book strikes a nice balance between different styles of development – process modeling and process mining are contrasted along with a description of how to use both in conjunction with task mining for instance. Where necessary, as in the content management and document processing chapter, some history is shared to show readers how we got to where we are and put newer capabilities into context.
The use case and best practices drill into 8 topics in more detail. Each has a reasonably detailed walkthrough of configuring and programming the example, with some embedded best practices and observations to help you learn the software. While not every feature is described, and some descriptions are quite cursory, the chapters give a good sense of how functionality could be developed and delivered. Source code for the examples is also available so you can work on them and extend them yourself.
The book concludes with some good notes of the various installation and operation options and topologies for the Cloud Pak and a discussion of CI/CD options.
Despite having multiple authors with their own focus areas, the book is well-leveled with a similar level of detail on each piece. There’s no way even a relatively long book like this one could cover all the functionality in the Cloud Pak but the team does a great job or outlining the core functionality, showing you how to develop modern systems using this functionality and providing a nice set of best practices. Highly recommended.
You can buy the book here
The book refers to standards like Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN). I wouldn’t read the specs as a way to find out more about these standards. OMG groups write the specs for implementors of software products that support the standards – not for those intending to use them to build information systems. If you want to use BPMN and DMN, OMG recommends you buy books or pay for classes. There are many great books on BPMN and I wrote one on DMN with Jan Purchase – Real World Decision Modeling with DMN.
Because of the way IBM organizes its product portfolio, Cloud Pak for Business Automation does not include IBM’s machine learning tools. Any serious attempt to automate business operations today is going to consider how best to develop and integrate machine learning models. The detailed sections of the book do show how you can integrate machine learning with rules-based decisioning through decision models. Overall, though, discussion of machine learning is a little limited because of the focus on the specific functionality available in Cloud Pak for Business Automation.