The myInvenio tool can be used to discover processes based on data already collected.  It will derive the process (the tasks, actors, sequence, etc.) from the data and cross-check that with the cases that are already recorded (for example see which are deviating, where time is spent, etc.).

This information can then be used to derive which activities might be the best candidates for automation.  By running a simulation, you can decide for example to add two robots for automating one of the steps (at least the simple cases) and keep one employee for more complex and exceptional cases.

PMG provides drag and drop low-code processes, with pre-built connectors.  The process included human tasks for approval, but also supported integration with email, phone or text, or slack, etc.  It contacts external services (like Azure ML) for risk assessment, and included some RPA integration.

Chat is becoming more and more an important communication channel for customers.  Flowable showed an example of how banks are using lots of different channels to communicate with customers, like a chatbot, and using BPMN2 and CMMN during conversations.  

A digital assistant is constantly helping the client advisor during his conversation by creating (sub)cases, advising actions, etc.  For example, it can help enter a client address change, validate the information, ask validation, send confirmation emails, involve a compliance officer if necessary, etc. Behind the scenes, the digital assistant is backed by a process (with forms etc.).  Finally, integrating Machine Learning can be used to replace some of the manual steps.

A demo with an actual (3d printed, open-source) robot !  Francois brought a robot with video and voice recognition capabilities.  The robot could be used for example in a shop for greeting clients.  Voice recognition can be used to start a process (for example when the customer comes in).  The robot can respond to several commands, follow, do face recognition, take pictures, etc. all by configuring various processes.  The voice and face recognition isn’t always working perfectly yet, but interesting to see anyway !

Voice recognition can be used to create a chatbot.  The chatbox can for example be used to request PTO, get your tasks (and complete or even delegate them).  But chatbots aren’t great for everything.  Some data is just easier to provide in a structured form.  But even forms can be enhanced with for example sentiment analysis (to automatically update the data based on the sentiment detected from the text provided in the form).  You can then for example create standard processes for how to respond to certain sentiments.

Processes can be unstructured and rely on rules for defining when tasks should be triggered or not.  The demo is using IBM BPM state machine in combination with IBM ODM where the rules define what the next state will be based on the current state and the input.