bpmNEXT 2017 (part 4)

Through a lens Starkly: transforming data into business information
E. Scott Menter – BPLogix
BPLogix is virtualizing data (possibly coming from a lot of different data sources) and aggregating it to get visibility in what is going on for business users.  The data flow analyzer allows you to drill down into your data, you can for example see how a chart is combining different queries to visualize key indicators (without knowing the technical details of the data).  Their tools allows users to define processes as a combination of activities with eligibility criteria (as they presented last year).  By combining this with their data analyzer, it allows you to clearly visualize what happened and based on what information (and to drill down further on where that data came from, etc.).
Process modeling and metrics: the next generation
Max Young – Capital Labs
Capital Labs is adding a third dimension to processes.  When performing simulation it is critical that it matches with reality.  Their tool, called BPM Scout, allows you to import processes from different tools, and then perform visual simulations on top of those.  But it allows multiple (3D) layers, where a process on the top layer can trigger for example rules on a different layer, etc.  Users can define their own advanced KPIs so you can show the value that the customer can expect.  It also interacts with management tools and allows you to generate full documentation (including simulation information) for your process.  And it allows you to export all your processes to for example IBM Blueworks (even with an application generated for you to start the process).
BPM with humans in the age of digital transformation
Francois Bonnet – ITESOFT W4
Francois is showing their tool that is trying to assist humans in their job.  At process definition time, it cannot only validate your BPMN processes, but assist the user in what the solution might be (for example adding missing elements).  The process also be simulated step by step.  Simulation can even compare the execution of a specific instance to the plan (gantt chart), giving information if you are ahead or behind the schedule.  Simulation supports concepts like timers and signal events etc.
Taking BPMN to infinity and beyond
Jakob Freund – Camunda
Camunda is presenting their next generation “Big Workflow” engine.  They have written a new version of their workflow engine with the idea of being able to scale this infinitely.  It is using publish-subscribe at it’s core: rather than storing the state of an instance as a row in a traditional database, they are generating and storing event rather than updating that one row.  The events are written to a log file on file system and in a distributed setting it is replicated. This allows them to scale to 100x the throughput of their traditional engine.
Getting to know your users with Brazos CX insights
Scott Francis and Ivan Kornienko – BP3 Global
BP3 is presenting Brazos CX insights to help developers improve the usability of their applications for end users.  The tool is continuously measuring your application (load time, how the application is used, form validation errors, etc.).  Analysis learns you how much time users spent at different parts of your application, how much each area of your application is used (or not used), what the common validation errors are, etc.  And if necessary you can drill down even further to get more detailed information, all the way up to a timeline visualization of an individual session, or get average data for a large number of sessions.  Obviously all this information should be used to improve the usability of your application.
Cognitive customer service
Pramod Sachdeva – Princeton Blue
Princeton Blue is presenting their cognitive customer service solution.  It is monitoring customer interactions (from different possible resources like calls, emails, etc.).  Rules can be used to proactively monitor this data and create escalations, that can then be handled appropriately (for example through a process).  During this escalation, it can actually recommend what the most appropriate action might be.  Reports can be generated to slice-and-dice all this information in different ways (based on topic, customer type, sentiment, etc.).


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