All of the bpmNEXT video coverage

I was scrolling through some of my unread RSS feeds and saw Kris Verlaenen’s posts about last month’s bpmNEXT conference: like me, he was live-blogging the event. However, he also went back and added in each of the videos for the presentation to his posts – nice touch!

His posts:

You can also go to the bpmNEXT YouTube channel and see all of the videos including those from previous years, and read my coverage of the event here.

bpmNEXT 2018: Last session with a Red Hat demo, Serco presentation and DMN TCK review

We’re on the final session of bpmNEXT 2018 — it’s been an amazing three days with great demos and wonderful conversations.

Exploiting Cloud Infrastructure for Efficient Business Process Execution, Red Hat

Kris Verlaenen, project lead for jBPM as part of Red Hat, presented on cloud BPM infrastructure, specifically for execution and monitoring. Cloud makes BPM lightweight, scalable, embedable and able to take advantage of the larger cloud app ecosystem. They are introducing some new cloud infrastructure, including a controller for managing server deployments, a smart router for delegating and aggregating requests from applications to servers, and monitoring that aggregates process statistics across servers and containers. The demo showed using Red Hat’s OpenShift container application platform (actually MiniShift running on his laptop) to create a new environment and deploy an IT hardware ordering BPM application. He walked through using the application to create a new order and see the milestone-based monitoring of the order, then the hardware provider’s view of their steps in the process to provide information and advance the process to the next stage. The process engine and monitoring engine can be deployed in different containers on different hardware, in any combination of cloud providers and on-premise infrastructure. Applications and servers can be bundled into a single immutable image for easy provisioning — more of a microservices style — or can be deployed independently. Multiple versions of the same application can be deployed, allowing current instances to play out in the original version while new instances use the most recent version, or other strategies that would allow new instances of any version to be created, while monitoring can aggregate instance data from all versions in all containers.

Kris is also live-blogging the conference, check out his posts. He has gone back and included the video of each presentation when they are released (something that I didn’t do for page load performance reasons) as well as providing his commentary on each presentation.

Dynamic Work Assignment, Serco

Lloyd Dugan of Serco has the unenviable position of being the last presenter of the conference, although he gave a presentation of dynamic work assignment implementation rather than an actual demo (with a quick view of the simple process model in the Trisotech animator near the end, plus an animation of the work assignment in action). His company is a call center business process outsourcer, where knowledge workers use a case management application implemented in BPMN, driven by events such as inbound calls and documents, as well as timers. Real-time work prioritization and assignment is necessary because of SLAs around inbound calls, and the task management model is moving from work being selected (and potentially cherry-picked) by workers, to push assignments. Tasks are scored and assigned using decision models that include task type and SLAs, and worker eligibility based on each individual’s skills and training. Although work assignment products exist, this one is specifically for the complex rules around the US Affordable Care Act administration, which requires a combination of decision tables, database table-driven rules, and lower-level coding to provide the right combination of flexibility and performance.

DMN TCK (Technical Compatibility Kit) Working Group

Keith Swenson of Fujitsu (but presenting here in his role on the DMN standards) started on the idea of a set of standardized DMN technical compatibility tests based on conversations at bpmNEXT in 2016, and he presented today on where they’re at with the TCK. Basically, the TCK provides a way for DMN vendors to demonstrate their compliance with the standard by providing a set of DMN models, input data, and expected results, testing decision tables, boxed expressions and FEEL. Vendors who can demonstrate that they pass all of the TCK tests are listed on a github site along with information about individual test results, providing a way for DMN customers to assess the compliance level of vendors. Keith wrote an update on this last September that provides a good summary up to that point, and in today’s presentation he walked through some of the additional things that they’ve done including identifying sections of the DMN specification that require clarifications or additions due to ambiguity that can lead to different implementations. DMN 1.2 is coming out this year, which will require a new set of tests specifically for that version while maintaining the previous version tests; they are also trying to improve testing of error cases and introducing more real-world decision models. If you create and use DMN models, or make a DMN-compliant decision management product, or you’re otherwise interested in the DMN TCK, you can find out here how to get involved in the working group.

That’s it for bpmNEXT 2018. There will be voting for the best in show and some wrapup after lunch, but we’re pretty much done for this year. Another amazing year that makes me proud to be a part of this community.

bpmNEXT 2018: Bonitasoft, Know Process

We’re in the home stretch here at bpmNEXT 2018, day 3 has only a couple of shorter demo sessions and a few related talks before we break early to head home.

When Artificial Intelligence meets Process-Based Applications, Bonitasoft

Nicolas Chabanoles and Nathalie Cotte from Bonitasoft presented on their integration of AI with process applications, specifically for predictive analytics for automating decisions and making recommendations. They use an extension of process mining to examine case data and activity times in order to predict, for example, if a specific case will finish on time; in the future, they hope to be able to accurately predict the end time for individual cases for better feedback to internal users and customers. The demo was a loan origination application built on Bonita BPM, which was fairly standard, with the process mining and machine learning coming in with how the processes are monitored. Log data is polled from the BPM system into an elastic search database, then machine learning is applied to instance data; configuration of the machine learning is based (at this point) only on the specification of an expected completion time for each instance type to build the predictions model. At that point, predictions can be made for in-flight instances as to whether each one will complete on time, or its probability of completing on time for those predicted to be late — for example, if key documents are missing, or the loan officer is not responding quickly enough to review requests. The loan officer is shown what tasks are likely to be causing the late prediction, and completing those tasks will change the prediction for that case. Priority for cases can be set dynamically based on the prediction, so that cases more likely to be late are set to higher priority in order to be worked earlier. Future plans are to include more business data and human resource data, which could be used to explicitly assign late cases to individual users. The use of process mining algorithms, rather than simpler prediction techniques, will allow suggestions on state transitions (i.e., which path to take) in addition to just setting instance priority.

Understanding Your Models and What They Are Trying To Tell You, KnowProcess

Tim Stephenson of KnowProcess spoke about models and standards, particularly applied to their main use case of marketing automation and customer onboarding. Their ModelMinder application ingests BPMN, CMMN and DMN models, and can be used to search the models for activities, resources and other model components, as well as identify and understand extensions such as calling a REST service from a BPMN service task. The demo showed a KnowProcess repository initially through the search interface; searching for “loan” or “send memo” returned links to models with those terms; the model (process, case or decision) can be displayed directly in their viewer with the location of the search term highlighted. The repository can be stored as files or an engine can be directly indexed. He also showed an interface to Slack that uses a model-minder bot that can handle natural language requests for certain model types and content such as which resources do the work as specified in the models or those that call a specific subprocess, providing a link directly back to the models in the KnowProcess repository. Finishing up the demo, he showed how the model search and reuse is attached to a CRM application, so that a marketing person sees the models as functions that can be executed directly within their environment.

Instead of a third demo, we had a more free-ranging discussion that had started yesterday during one of the Q&As about a standardized modeling language for RPA, led by Max Young from Capital BPM and with contributions of a number of others in the audience (including me). Good starting point but there’s obviously still a lot of work to do in this direction, starting with getting some of the major RPA vendors on board with standardization efforts. The emerging ideas seem to center around defining a grammar for the activities that occur in RPA (e.g., extract data from an Excel file, write data to a certain location in an application screen), then an event and flow language to piece together those primitives that might look something like BPMN or CMMN. I see this as similar to the issue of defining page flows, which are often done as a black box function that is performed within a human activity in a BPMN flow: exposing and standardizing that black box is what we’re talking about. This discussion is a prime example of what makes bpmNEXT great, and keeps me coming back year after year.

bpmNEXT 2018: Intelligence and robots with ITESOFT, K2, BeeckerCo

We’re finishing up day 2 of bpmNEXT with a last section of demos.

Robotics, Customer Interactions and BPM, ITESOFT

Francois Bonnet from ITESOFT presented on customer interactions and automation, and the use of BPMN-driven robots to guide customer experience. In a first for bpmNEXT, the demo included an actual physical human-shaped robot (which was 3D-printed from an open source project) that can do voice recognition, text to speech, video capture, movement tracking and facial recognition. The robot’s actions were driven by a BPMN process model, with activities such as searching for humans, recognizing faces, speaking phrases, processing input and making branching decisions. The process model was shown simultaneously, with the execution path updated in real time as it moved through the process, with robot actions shown as service activities. The scenario was the robot interacting with a customer in a mobile phone shop, recognizing the customer or training a new facial recognition, asking what service is required, then stepping through acquiring a new phone and plan. He walked through how the BPMN model was used, with both synchronous and asynchronous services for controlling the robot and invoking functions such as classifier training, and human activities for interacting with the customer. Interesting use of BPMN as a driver for real robot actions, showing integration of recognition, RPA, AI, image capture and business services such as customer enrolment and customer ID validation.

The Future of Voice in Business Process Automation, K2

Brandon Brown from K2 looked at a more focused use case for voice recognition, and some approaches to voice-first design that is more than just speech-to-text by adding cognitive services through commodity AI services from Google, Amazon and Microsoft. Their goal is to make AI more accessible through low/no-code application builders like K2, creating voice recognition applications such as chatbots. He demonstrated a chatbot on a mobile phone that was able to not just recognize the words that he spoke, but recognize the intent of the interaction and request additional data: essentially a replacement for filling out a form. This might be a complete interaction, or just an assist for starting a more involved process based on the original voice input. He switched over to a computer browser interface to show more of the capabilities, including sentiment analysis based on form input that could adjust the priority of a task or impact process execution. From within their designer environment, cognitive text analytics such as sentiment analysis can be invoked as a step in a process using their Smart Objects, which are effectively wrappers around one or more services and data mapping actions that allow less-technical process designers include cognitive services in their process applications. Good demo of integrating voice-related cognitive services into processes, showing how third-party services make this much more accessible to any level of developer skill.

State Machine Applied to Corporate Loans Process, BeeckerCo

Fernando Leibowich Beker from BeeckerCo finished up the day with a presentation on their process app suite BeBOP based on IBM BPM/ODM focused on financial services customers, followed by a “demo” of mostly prerecorded screencams. Their app generates state tables for processes using ODM business rules, then allows business users to change the state table in order to drive the process execution. The demo showed a typical IBM BPM application for processing a loan origination, but the steps are defined as ad hoc tasks so not part of a process flow; instead, the process flow is driven by the state table to determine which task to execute in which order, and the only real flow is to check the state table, then either invoke the next task or complete the process. Table-driven processes aren’t a new concept — we’ve been doing this since the early days of workflow — although using an ODM decision table to manage the state transition table is an interesting twist. This does put me in mind of the joke I used to tell when I first started giving process-focused presentations at the Business Rules Forum, about how a process person would model an entire decision tree in BPMN, while a rules person would have a single BPMN node that called a decision tree to execute all of the process logic: just because you can do something using a certain method doesn’t mean that you should do it.

We’re done with day 2; tomorrow is only a half-day of sessions with the awards after lunch (which I’ll probably have to monitor remotely since I’ll be headed for the airport by mid-afternoon).

bpmNEXT 2018: All about bots with Cognitive Technology, PMG.net, Flowable

We’re into the afternoon of day 2 of bpmNEXT 2018, with another demo section.

RPA Enablement: Focus on Long-Term Value and Continuous Process Improvement, Cognitive Technology

Massimiliano Delsante of Cognitive Technology presented their myInvenio product for analyzing processes to determine where gaps exist and create models for closing those gaps through RPA task automation. The demo started with loading historical process data for process mining, which created a process model from the data together with activity resources, counts and other metrics; then comparing the model for conformance with a reference model to determine the frequency and performance of conformant and non-conformant cases. The process discovery model can be transformed to a BPMN model, and simulated performance. With a baseline data set of all manual activities, the system identified the cost of each activity, helping to identify which activities would result in the greatest savings if automated, and fed the data for actual resources used into the simulation scenario; adjusting the resources required by specifying the number of RPA robots that could be deployed at specific tasks allows for a what-if simulation for the process performance with an RPA implementation. An analytics dashboard provides visualization of the original process discovery and the simulated changes, with performance trends over time. Predictive analytics can be applied to running processes to, for example, predict which cases will not meet their deadlines, and some root cause analysis for the problems. Doing this analysis requires that you have information about the cost of the RPA robots as well as being able to identify which tasks could be automated with RPA. Good integration of process discovery, simulation, analysis and ongoing monitoring.

Integration is Still Cool, and Core in your BPM Strategy, PMG.net

Ben Alexander from PMG.net focused on integration within BPM as a key element for driving innovation by increasing the speed of application development: integrating services for RPA, ML, AI, IoT, blockchain, chatbots and whatever other hot new technologies can be brought together in a low-code environment such as PMG. His demo showed a vendor onboarding application, adding a function/subprocess for assessing probability of vendor approval using machine learning by calling AzureML, user task assignment using Slack integration or SMS/phone support through a Twilio connector, and RPA bot invocation using a generic REST API. Nice demo of how to put all of these third-party services together using a BPM platform as the main application development and orchestration engine.

Making Process Personal, Flowable

Paul Holmes-Higgin and Micha Keiner from Flowable presented on their Engage product for customer engagement via chat, using chatbots to augment rather than replace human chat, and modeling the chatbot behavior using standard modeling tools. In particular, they have found that a conversation can be modeled as a case with dynamic injection of processes, with the ability to bring intelligence into conversations, and the added benefit of the chat being completely audited. The demo was around the use case of a high-wealth banking client talking to their relationship manager using chat, with simultaneous views of both the client and relationship manager UI in the Flowable Engage chat interface. The client mentioned that she moved to a new home, and the RM initiated the change address process by starting a new case right in the chat by invoking a context-sensitive digital assistant. This provided advice to the RM about address change regulatory rules, and provided a form in situ to collect the address data. The case is now progressed through a combination of chat message to collaborate between human players, forms filled directly in the chat window, and confirmation by the client via chat by presenting them with information to be updated. Potential issues, such as compliance regulations due to a country move, are raised to the RM, and related processes execute behind the scenes that include a compliance officer via a more standard task inbox interface. Once the compliance process completes, the RM is informed via the chat interface. Behind the scenes, there’s a standard address change BPMN diagram, where the chat interface is integrated through service activities. They also showed replacing the human compliance decision with a decision table that was created (and manually edited if necessary) based on a decision tree generated by machine learning on 200,000 historical address change cases; rerunning the scenario skipped the compliance officer step and approved the change instantaneously. Other chat automated tasks that the RM can invoke include setting reminders, retrieving customer information and more using natural language processing, as well as other types of more structured cases and processes. Great demo, and an excellent look at the future of chat interfaces in process and case management.

bpmNEXT 2018: Application Development with ProcessMaker, Capital BPM, Camunda

Next-Generation Backendless Workflow Orchestration API for ISVs, ProcessMaker

Brian Reale and Taylor Dondich from ProcessMaker presented their new ProcessMaker.io product for a BPMN 2.0 workflow microservice API in the cloud, targeted at ISVs to add process management capabilities into their vertical products. This is intended to solve the problem of software vendors who want customized workflow features without having to embed a full BPMS platform. They provide a simplified Javascript process designer that ISVs can use to present to their end users, although a full BPMN designer could be used and the results imported into the environment, and there’s a simple task invocation interface that can be called from pretty much any language or environment via language-specific SDKs and generalized REST APIs. The demo showed creating a new environment, and walked through a Slack integration application where Slack becomes the task list user interface, and simple HTML forms are used as the task processing UI (which could be any UI environment). This is a developer tool, not an end-user or low-code tool; check out their github for SDK and connector code as well as samples, and their own site for videos and descriptions of use cases. There was some pushback on the use of the term “microservice”; it’s really a lean cloud-based BPPM engine in the cloud that provides fast, scalable, enterprise-grade workflow capabilities. Although I haven’t done any direct comparison, there’s at least some overlap with Camunda’s Zeebe.io offering.

CapBPM’s IQ no-code BPM development – Turning Ideas into Value, Capital BPM

Max Young from Capital BPM talked about their no-code code generator: a graphical environment that can import industry-standard models (including BPMN, but also from IBM BPM’s application format), augment with functions such as service calls and user interfaces, and export as a BPM application in a number of different formats including those that can be imported into BPMS vendors’ products, or open source code. The demo showed how they can start with an application template that includes process and data models, then have the tool use AI to suggest UI layouts and other application parameters. There are a number of analysis tools for simulating processes, visualizing interactions between components (such as between a process model and a decision model). He created a process application from scratch, defining data fields, allowing auto-layout to suggest a visual form which he then modified to add logic to fields, and defining a BPMN process model to create an application shell. He then exported to both IBM BPM and Camunda BPM, which deployed the application to each of those environments and created application dashboards. The goal of this product appears to be to allow a broader range of people to rapidly develop BPM apps without being trained in the specific target BPM tool, with the resulting application passed off to a development team that will maintain it in the long term. For low-code tools such as IBM BPM, that may not be a perfect use case, but for products that are targeted at developers, such as Camunda, it might be a better fit as a UI and application code generator.

Monitoring Transparency for High-Volume, Next-Generation Workflows, Camunda

Ryan Johnston of Camunda presented on their Zeebe.io product, which (like the new ProcessMaker.io offering discussed above), is a microservice orchestration engine, but more specifically monitoring the performance of Zeebe by pairing it with Camunda Optimize to create heatmaps and other reports. The demo is based on a stock market pairs trading arbitrage use case, where a third-party process detects arbitrage opportunities and sends a signal that instantiates a Zeebe process; this process calls services to calculate the risk, calculate the long/short positions, and execute the trade. Speed and volume are key since rapidly changing market conditions could impact the effectiveness of the trade, hence the requirement for a high-performance engine like Zeebe, but also the need to monitor performance. The Zeebe Simple Monitor is the first of the administration tools being ported to this environment from the main Camunda product, providing a lighter-weight version of Cockpit. Camunda Optimize is used directly to view Zeebe performance, with the ability to create reports and assemble them into dashboards that show metrics such as flow node distribution (in pie chart, heatmap and tabular format), process instance count, and raw process instance data. He also demonstrated alerts, which can notify (by email) when specific values hit certain milestones, such as process instance count exceeding a value. He finished with one of Camunda’s fun add-ons, which is a video game view of a process model that allows you to walk through a 3D representation and shoot to kill process instances. Interesting audience question on using Zeebe as a smart event bus in addition to standard process applications at high volume.

bpmNEXT 2018 day 2 keynote with @NathanielPalmer

Nathaniel Palmer kicked off day 2 of bpmNEXT 2018 with his ever-prescient views on the next five years of BPM. Bots, decisions and automation are key, with the three R’s (robots, rules and relationships) defining BPM in the years to come. More and more, commercial transactions (or services that form part of those transactions) will happen on servers outside your organization, and often outside of your control; robots and intelligent agents will be doing a big part of that work. He also believes that we’re seeing the beginning of the death of smartphones, to be replaced with other devices and other interfaces such as conversational UI and wearable technology. This is going to radically change how apps have to be designed, and will leave a lot of companies scrambling to catch up with this change as people move more of their interactions off smartphones and laptops. Although more conservative organizations — including government agencies — will continue to support the least common denominator in interaction style (probably email and traditional websites), commercial organizations don’t have that luxury, and need to rethink sooner. He envisions that your fastest-growing competitors will have fewer employees than robots, although some interesting news out of Tesla this week may indicate that it’s premature to replace some human functions.

He spoke about how this will refine application architecture to four tiers: a client tier unique to each platform, a separate delivery tier that optimizes delivery for the platforms, an aggregation tier that integrates services and data, and a services tier that pulls data from both internal and external source. This creates an abstraction between what a task is and how it is performed, and even whether it is automated or performed by a person. Decision as a service for both commercial and government services will become a primary delivery model, allowing decisions (and the automation enabled by them) to be easily plugged into applications; this will require more of a business-first, model-driven approach rather than having decisions built in code by developers.

His Future-Proof BPM architecture — what others are calling a digital transformation platform — brings together a variety of capabilities that can be provided by many vendors or other organizations, and fed by events. In fact, the core capabilities (automation, machine learning, decision management, workflow management) also generate events that feed back into the data flooding into these processes. BPM platforms have the ability to become the orchestrating platforms for this, which is possibly why many of the BPMS vendors are rebranding as low-code application development environments, but be aware of fundamental differences in the underlying architecture: do they support modularity and microservices, or are they just lifting and shifting to monolithic containers in the cloud?

Finishing up, he returned to the concept that intelligent agents can act autonomously in complex transactions, and this will be becoming more common over the next few years. Interestingly, an interview that I did for a European publication is being translated into German, and the translator emailed me this morning to tell me that they needed to change some of my comments on automating loan transactions since that’s not permitted in Germany. My response: not yet, but it will be. We all need to be prepared for a more automated future.

Great audience discussion at the end on how this architecture is manifesting, how to model/represent some of these automation concepts, the role of a smarter event bus, the future of the word “bot” and more. Max Young from Capital BPM took over to discuss the development of a grammar for RPA, with an invitation for the brain trust in the room to start thinking about this in more detail. RPA vendors are creating their own notation, but a vendor-agnostic standard would go a long ways towards helping business people to directly specify automation.

Since they’re pumping out the video on the same day as the presentations, check the bpmNEXT YouTube channel later for a replay of Nathaniel’s presentation.

bpmNEXT 2018 day 1 videos are up!

In an amazing feat of real-time editing, the videos from yesterday’s sessions were posted yesterday evening. I tweeted a link to the YouTube channel, but here’s the full list sent to us by Nathaniel Palmer. In his words, “It is a rougher product than we’ve had in the past, and we will continue to edit after the event.  But we’re excited to have these videos available immediately” – as are we all.

The Future of Process in Digital Business: Jim Sinur, Aragon Research
https://youtu.be/iBJBbXeVYUA

A New Architecture for Automation: Neil Ward-Dutton, MWD Advisors
https://youtu.be/-AeijpL4b98

Secure, Private, Decentralized Business Processes for Blockchains: Vanessa Bridge, ConsenSys
https://youtu.be/oww8zMzxvZA

Turn IoT Technology into Operational Capability: Pieter van Schalkwyk, XMPro
https://youtu.be/G7C01e8qyac

Business Milestones as Configuration: Joby O’Brien and Scott Menter, BPLogix
https://youtu.be/D_heO33fyC0

Timing the Stock Market with DMN: Bruce Silver, methodandstyle.com
https://youtu.be/vHCIC1HGbHQ

Smarter Contracts with DMN: Edson Tirelli, Red Hat
https://youtu.be/tdpZgbQbF9Q

Decision as a Service (DaaS): The DMN Platform Revolution: Denis Gagné, Trisotech
https://youtu.be/sYAIcBhVhIc

Designing the Data-Driven Company: Elmar Nathe, MID GmbH
https://youtu.be/zb__xVsOEA0

Using Customer Journeys to Connect Theory with Reality: Till Reiter and Enrico Teterra, Signavio
https://youtu.be/ov0SqJCMmoY

Discovering the Organizational DNA: Jude Chagas Pereira, IYCON; Frank Kowalkowski, KCI
https://youtu.be/NsCDgKPsTCs

bpmNEXT 2018: Complex Modeling with MID GmbH, Signavio and IYCON

The final session of the first day of bpmNEXT 2018 was focused on advanced modeling techniques.

Designing the Data-Driven Company, MID GmbH

Elmar Nathe of MID GmbH presented on their enterprise decision maps, which provides an aggregated visualization of strategic, tactical and operational decisions with business events. They provide a variety of modeling tools, but see decisions as key to understanding how organizations are driven by data and events. Clearly a rich decision modeling environment, including support for PMML for including predictive models and other data scientist analysis tools, plus links to other model types such as ERDs that can show what data contributes to which decision model, and business process models. Much more of an enterprise architecture approach to model-driven design that can incorporate the work of data scientists.

Using Customer Journeys to Connect Theory with Reality, Signavio

Till Reiter and Enrico Teterra of Signavio started with a great example of an Ignite presentation, with few words, lots of graphics and a bit of humor, discussing their new notation for modeling an outside-in view of the customer journey rather than just having an undifferentiated “customer” swimlane in a BPMN diagram. The demo walked through their customer journey mapping tool, and how their collaboration hub overlays on that to allow information about each component of the journey map to be discussed amongst process modeling users. The journey map contains a lot of information about KPIs and other process metrics in a form most consumable by process owners and modelers, but also has a notebook/dashboard view for analysts to determine problems with the process and identify potential resolution actions. This includes a variety of analysis tools including process discovery, where process mining techniques are applied to determine which paths in the process model may be contributing to specific problems such as cycle time, then overlay this on the process model to assist with root cause analysis. Although their product does a good job of combing CJMs, process models and process analysis, this was more of a walkthrough of a set of pre-calculated dashboard screens rather than an actual demo — a far cry from the experimental features that Gero Decker showed off in their demo at the first bpmNEXT.

Discovering the Organizational DNA, IYCON and Knowledge Consultants

The final presentation of this section was with Jude Chagas Pereira of IYCON and Frank Kowalkowski of Knowledge Consultants presenting IYCON’s Afterspyre modeling tool for creating a catalog of complex business objects, their attributes and their linkages to create organizational DNA diagrams. Ranking these with machine learning algorithms for semantic and sentiment analysis allows identification of process improvement opportunities. They have a number of standard business analysis techniques built in, and robust analytics focused on problem solving. The demo walked through their catalog, drilling down into the “Strategy DNA” section and into “Technology Solutions” subsection to show an enumeration of the platforms currently in place together with attributes such as technology risk and obsolescence, which can be used to rank technology upgrade plans. Relationships between business objects can be auto-detected based on existing data. Levels including Objectives, Key Processes, Technology Solutions, Database Technology and Datacenter and their interrelationships are mapped into a DNA diagram and an alluvial diagram, starting at any point in the catalog and drilling down a specific number of levels as selected by the modeling analyst. These diagrams can then be refined further based on factors such as scaling the individual markers based on actual performance. They showed sentiment analysis for a hotel rank on a review site, which included extracting specific phrases that related to certain sentiments. They also demonstrated a two-model comparison, which compared the models for two different companies to determine the overlap and unique processes; a good indicator for a merger/acquisition (or even divestiture) level of difficulty. They finished up with affinity modeling, such as the type used by Amazon when they tell you what books that other people bought who also bought the book that you’re looking at: easy to do in a matrix form with a small data set, but computationally intensive once you get into non-trivial amounts of data. Affinity modeling is most commonly used in marketing to analyze buying habits and offering people something that they are likely to buy, even if that’s what they didn’t plan to buy at first — this sort of “would you like fries with that” technique can increase purchase value by 30-40%. Related to that is correlation modeling, which can be used as a first step for determining causation. Impressive semantic data-driven analytics tool for modeling a lot of different organizational characteristics.

That’s it for day one; if everyone else is as overloaded with information as I am, we’re all ready for tonight’s wine tasting! Check the Twitter stream for opinions and photos from other attendees.

bpmNEXT 2018: All DMN all the time, with Trisotech, Bruce Silver Associates and Red Hat

First session of the afternoon on the first day of bpmNEXT 2018, and this entire section is on DMN (decision management notation) and the requirement for decision automation based on DMN.

Decision as a Service (DaaS): The DMN Platform Revolution, Trisotech

Denis Gagne of Trisotech, who knows as much about DMN and other related standards as anyone around, started off the session with his ideas on the need for decision automation driven by requirements such as GDPR. He walked through their suite of decision-related products that can be used to create decision services to be consumed by other applications, as well as their conformance to the DMN standards. His demo showed a decision model for determining the best price to offer a rental vehicle customer, and walked through the capabilities of their platform with this model: DMN style check, import/export, execution, team collaboration, and governance through versioning. He also showed how decision models can be reused, so that elements from one model can be used in another model. Then, he showed how to take portions of the model and define them as a service using a visual wrapper, much like a subprocess wrapper visualization in BPMN, where the relationship lines that cross the service boundary become the inputs and outputs to the service. Cool. The service can then be deployed as an executable service using (in his demo) the Red Hat platform, test its execution using from a generated HTML form, generate the REST API or Open API interface code, run predefined test cases based on DMN TCK, promote the service from test to production, and publish it to an API publisher platform such as WSO2 for public consumption. The execution environment includes debugging and audit logs, providing traceability on the decision services.

Timing the Stock Market with DMN, Bruce Silver Associates

Bruce Silver, also a huge contributor to BPMN and DMN standards, and author of the BPMN Method & Style books and now the DMN M&S, presented an application for buying a stock at the right time based on price patterns. For investors who time the market based the pricing, the best way to do this is to look at daily min/max trends and fit them to one of several base type models. Bruce figured that this could be done with a decision table applied to a manipulated version of the data, and automated this for a range of stocks using a one-year history, processing in Excel, and decision services in the Trisotech cloud. This is a practical example of using decision services in a low-code environment by non-programmers to do something useful. His demo showed us the decision model for doing this, then the data processing (smoothing) done in Excel. However, for an application that you want to run every day, you’re probably not going to want to do the manual import/export of data, so he showed how to automate/orchestrate this with Microsoft Flow, which can still use the Excel sheet for data manipulation but automate the data import, execute the decision service, and publish the results back to the same Excel file. Good demonstration of the democratization of creating decisioning applications by through easy-to-use tools such as the graphical DMN modeler, Excel and Flow, highlighting that DMN is an execution language as well as a requirement language. Bruce has also just published a new book, DMN Cookbook, co-authored with Edson Tirelli of Red Hat, on getting started DMN business implementations using lightweight stateless decision services called via REST APIs.

Smarter Contracts with DMN, Red Hat

Edson Tirelli of Red Hat, Bruce Silver’s co-author on the above-mentioned DMN Cookbook, finished this section of DMN presentations with a combination of blockchain and DMN, where DMN is used to define the business language for calculations within a smart contract. His demo showed a smart land registry case, specifically a transaction for selling a property involving a seller, a buyer and a settlement service created in DMN that calculates taxes and insurance, with the purchase being executed using cryptocurrency. He mentioned Vanessa Bridge’s demo from earlier today, which showed using BPMN to define smart contract flows; this adds another dimension to the same problem, and likely no reason why you wouldn’t use them all together given the right situation. Edson said that he was inspired, in part, by this post on smart contracts by Paul Lachance, in which Lachance said “a visual model such as a BPMN and/or DMN diagram could be used to generate the contract source code via a process-engine”. He used Ethereum for the blockchain smart contract and the Ether cryptocurrency, Trisotech for the DMN models, and Drools for the rules execution. All in all, not such a far-fetched idea.

I’m still catching flak for suggesting the now-ubiquitous Ignite style for presentations here at bpmNEXT; my next lobbying effort will be around restricting the maximum number of words per slide. 🙂