Show me the money: Financials, sales and support at @OpenText Analyst Summit 2019

We started the second day of the OpenText Analyst Summit 2019 with their CFO, Madhu Ranganathan, talking about their growth via acquisitions and organic growth. She claimed that their history of acquisitions shows that M&A does work — a point with which some industry specialists may not agree, given the still overlapping collection of products in their portfolio — but there’s no doubt that they’re growing well based on their six-year financials, across a broad range of industries and geographies. She sees this as a position for continuing to scale to $1B in operating cash flow by June 2021, an ambitious but achievable target, on their existing 25-year run.

Ted Harrison, EVP of Worldwide Sales, was up next with an update on their customer base: 85 of the 100 largest companies in the world, 17 of the top 20 financial services companies, 20 of the top 20 life sciences companies, etc. He walked through the composition of the 1,600 sales professionals in their teams, from the account executives and sales reps to the solution consultants and other support roles. They also have an extensive partner channel bringing domain expertise and customer relationships. He highlighted a few customers in some of the key product areas — GM for digital identity management, Nestle for supply chain management, Malaysia Airports for AI and analytics,and British American Tobacco for SuccessFactors-OT2 integration — with a focus on customers that are using OpenText in ways that span their business operations in a significant way.

James McGourlay, EVP of Customer Operations, covered how their global technical support and professional services organization has aligned with the customer journey from deployment to adoption to expansion of their OpenText products. With 1,400 professional services people, they have 3,000 engagements going on at any given time across 30 countries. As with most large vendors’ PS groups, they have a toolbox of solution accelerators, best practices, and expert resources to help with initial implementation and ongoing operations. This is also where they partner with systems integrators such as CGI, Accenture and Deloitte, and platform partners like Microsoft and Oracle. He addressed the work of their 1,500 technical support professionals across four major centers of excellence for round-the-clock support, co-located with engineering teams to provide a more direct link to technical solutions. They have a strong focus on customer satisfaction in PS and technical support because they realize that happy customers tend to buy more stuff; this is particularly important when you have a lot of different products to sell to those customers to expand your footprint within their organizations.

Good to hear more about the corporate and operations side than I normally cover, but looking forward to this afternoon’s deeper dives into product technology.

Product Innovation session at @OpenText Analyst Summit 2019

Muhi Majzoub, EVP of Engineering, continued the first day of the analyst summit with a deeper look at their technology progress in the past year as well as future direction. I only cover a fraction of OpenText products; even in the ECM and BPM space, they have a long history of acquisitions and it’s hard to keep on top of all of them.

Their Content Services provides information integration into a variety of key business applications, including Salesforce and SAP; this allows users to work in those applications and see relevant content in that context without having to worry where or how it’s stored and secured. Majzoub covered a number of the new features of their content platforms (alas, there are still at least two content platforms, and let’s not even talk about process platforms) as well as user experience, digital asset management, AI-powered content analytics and eDiscovery. He talked about their solutions for LegalTech and digital forensics (not areas that I follow closely), then moved on to the much broader areas of AI, machine learning and analytics as they apply to capture, content and process, as well as their business network transactions.

He talked about AppWorks, which is their low-code development environment but also includes their BPM platform capabilities since they have a focus on process- and content-centric applications such as case management. They have a big push on vertical application development, both in terms of enabling it for their customers and also for building their own vertical offerings. Interestingly, they are also allowing for citizen development of micro-apps in their Core cloud content management platform that includes document workflows.

The product session was followed by a showcase and demos hosted by Stephen Ludlow, VP of Product Marketing. He emphasized that they are a platform company, but since line-of-business buyers want to buy solutions rather than platforms, they need to be able to demonstrate applications that bring together many of their capabilities. We had five quick demos:

  • AI-augmented capture using Captive capture and Magellan AI/analytics: creating an insurance claim first notice of loss from an unstructured email, while gathering aggregate analytics for fraud detection and identifying vehicle accident hotspots.
  • Unsupervised machine learning for eDiscovery to identify concepts in large sets of documents in legal investigations, then using supervised learning/classification to further refine search results and prioritize review of specific documents.
  • Integrated dashboard and analytics for supply chain visibility and management, including integrating, harmonizing and cleansing data and transactions from multiple internal and external sources, and drilling down into details of failed transactions.
  • HR application integrating SAP SuccessFactors with content management to store and access documents that make up an employee HR file, including identifying missing documents and generating customized documents.
  • Dashboard for logging and handling non-conformance and corrective/preventative actions for Life Sciences manufacturing, including quality metrics and root cause analysis, and linking to reference documentation.
  • Good set of business use cases to finish off our first (half) day of the analyst summit.

Snowed in at the @OpenText Analyst Summit 2019

Mark Barrenechea, OpenText’s CEO and CTO, kicked off the analyst summit with his re:imagine keynote here in Boston amidst a snowy winter storm that ensures a captive audience. He gave some of the current OpenText stats –100M end users over 120,000 customers, 2.8B in revenue last year — before expanding into a review of how the market has shifted over the past 10 years, fueled by changes in technology and infrastructure. What’s happened on the way to digital and AI is what he calls the zero theorem: zero trust (guard against security and privacy breaches), zero IT (bring your own device, work in the cloud), zero people (automate everything possible) and zero down time (everything always available).

Their theme for this year is to help their customers re:imagine work, re:imagine their workforce, and re:imagine automation and AI. This starts with OpenText’s intelligent information core (automation, AI, APIs and data management), then expands with both their EIM platforms and EIM applications. OpenText has a pretty varied product portfolio (to say the least) and is bringing many of these components together into a more cohesive integrated vision in both the content services and the business network spaces. More importantly, they are converging their many, many engines so that in the future, customers won’t have to decide between which ECM or BPM engine, for example.

They are providing a layer of RESTful services on top of their intelligent information core services (ECM, BPM, Capture, Business Network, Analytics/AI, IoT), then allow that to be consumed either by standard development tools in a technical IDE, or using the AppWorks low-code environment. The Cloud OT2 architecture provides about 40 services for consumption in these development environments or by OpenText’s own vertical applications such as People Center.

Barrenechea finished up with a review of how OpenText is using OpenText to transform their own business, using AI for looking at some of their financial and people management data to help guide them towards improvements. They’ll be investing $2B in R&D over the next five years to help them become even bigger in the $100B EIM market, both through the platform and more increasingly through vertical applications.

We’ll be digging into more of the details later today and tomorrow as the summit continues, so stay tuned.

Next up was Ted Harrison, EVP of Worldwide Sales, interviewing one of their customers: Gopal Padinjaruveetil, VP and Chief Information Security Officer at The Auto Club Group. AAA needs no introduction as a roadside assistance organization, but they also have insurance, banking, travel, car care and advocacy business areas, with coordinated member access to services across multiple channels. It’s this concept of the connected member that has driven their focus on digital identity for both people and devices, and how AI can help them to reduce risk and improve security by detecting abnormal patterns.

TechnicityTO 2018: Cool tech projects

The afternoon session at Technicity started with a few fast presentations on cool projects going on in the city. Too quick to grab details from the talks, but here’s who we heard from:

  • Dr. Eileen de Villa, medical officer of health at Toronto Public Health, and Lawrence ETA, deputy CIO at the city of Toronto, on using AI to drive public health outcomes.
  • Angela Chung, project director at Toronto Employment and Social Services, Children’s Services, Shelter Support and Housing, on client-centric support through service platform integration.
  • Matthew Tenney, data science and visualization team supervisor, on IoT from streetcars to urban forestry for applications such as environmental data sensing.
  • Arash Farajian, policy planning consultant, on Toronto Water’s use of GIS, smart sensors, drones (aerial and submersible) and augmented reality.

The rest of the afternoon was the 10th annual Toronto’s Got IT Awards of Excellence, but unfortunately I had to duck out for other meetings, so that’s it for my Technicity 2018 coverage.

AI and BPM: my article for @Bonitasoft on making processes more intelligent

Part of my work as an industry analyst is to write papers and articles (and present webinars), sponsored by vendors, on topics that will be of interest to their clients as well as a broader audience. I typically don’t talk about the sponsor’s products or give them any sort of promotion; it’s intended to be educational thought leadership that will help their clients and prospects to understand the complex technology environment that we work in.

I’ve recently written an article on AI and BPM for Bonitasoft that started from a discussion we had after I contributed articles on adding intelligent technologies to process management to a couple of books, as well as writing here on my blog and giving a few presentations on the topic. From the intro of the article:

In 2016, I was asked to contribute to the Workflow Management Coalition’s book “Best Practices for Knowledge Workers.” My section, “Beyond Checklists”, called for more intelligent adaptive case management to drive innovation while maintaining operational efficiency. By the next year, they published “Intelligent Adaptability,” and I contributed a section called “Machine Intelligence and Automation in ACM [Adaptive Case Management] and BPM” that carried forward these ideas further. Another year on, it’s time to take a look at how the crossover between BPM and artificial intelligence (AI) — indeed, between BPM and a wide range of intelligent technologies — is progressing.

I go on to cover the specific technologies involved and what types of business innovation that we can expect from more intelligent processes. You can read the entire article on Bonita’s website, on their LinkedIn feed and their Medium channel. If you prefer to read it in French, it’s also on the Decideo.fr industry news site, and apparently there’s a Spanish version in the works too.

Summer BPM reading, with dashes of AI, RPA, low-code and digital transformation

Summer always sees a bit of a slowdown in my billable work, which gives me an opportunity to catch up on reading and research across the topic of BPM and other related fields. I’m often asked what blogs and other websites that I read regularly to keep on top of trends and participate in discussions, and here are some general guidelines for getting through a lot of material in a short time.

First, to effectively surf the tsunami of information, I use two primary tools:

  • An RSS reader (Feedly) with a hand-curated list of related sites. In general, if a site doesn’t have an RSS feed, then I’m probably not reading it regularly. Furthermore, if it doesn’t have a full feed – that is, one that shows the entire text of the article rather than a summary in the feed reader – it drops to a secondary list that I only read occasionally (or never). This lets me browse quickly through articles directly in Feedly and see which has something interesting to read or share without having to open the links directly.
  • Twitter, with a hand-curated list of digital transformation-related Twitter users, both individuals and companies. This is a great way to find new sources of information, which I can then add to Feedly for ongoing consumption. I usually use the Tweetdeck interface to keep an eye on my list plus notifications, but rarely review my full unfiltered Twitter feed. That Twitter list is also included in the content of my Paper.li “Digital Transformation Daily”, and I’ve just restarted tweeting the daily link.

Second, the content needs to be good to stay on my lists. I curate both of these lists manually, constantly adding and culling the contents to improve the quality of my reading material. If your blog posts are mostly promotional rather than informative, I remove them from Feedly; if you tweet too much about politics or your dog, you’ll get bumped off the DX list, although probably not unfollowed.

Third, I like to share interesting things on Twitter, and use Buffer to queue these up during my morning reading so that they’re spread out over the course of the day rather than all in a clump. To save things for a more detailed review later as part of ongoing research, I use Pocket to manually bookmark items, which also syncs to my mobile devices for offline reading, and an IFTTT script to save all links that I tweet into a Google sheet.

You can take a look at what I share frequently through Twitter to get an idea of the sources that I think have value; in general, I directly @mention the source in the tweet to help promote their content. Tweeting a link to an article – and especially inclusion in the auto-curated Paper.li Digital Transformation Daily – is not an endorsement: I’ll add my own opinion in the tweet about what I found interesting in the article.

Time to kick back, enjoy the nice weather, and read a good blog!

AlfrescoDay 2018: digital business platform and a whole lot of AWS

I attended Alfresco’s analyst day and a customer day in New York in late March, and due to some travel and project work, just finding time to publish my notes now. Usually I do that while I’m at the conference, but part of the first day was under NDA so I needed to think about how to combine the two days of information.

The typical Alfresco customer is still very content-centric, in spite of the robust Alfresco Process Services (formerly Activiti) offering that is part of their platform, with many of their key success stories presented at the conference were based on content implementations and migrations from ECM competitors such as Documentum. In a way, this is reminiscent of the FileNet conferences of 20 years ago, when I was talking about process but almost all of the customers were only interested in content management. What moves this into a very modern discussion, however, is the focus on Alfresco’s cloud offerings, especially on Amazon AWS.

First, though, we had a fascinating keynote by Sangeet Paul Choudary — and received a copy of his book Platform Scale: How an emerging business model helps startups build large empires with minimum investment — on how business models are shifting to platforms, and how this is disrupting many traditional businesses. He explained how supply-side economies of scale, machine learning and network effects are allowing online platforms like Amazon to impact real-world industries such as logistics. Traditional businesses in telecom, financial services, healthcare and many other verticals are discovering that without a customer-centric platform approach rather than a product approach, they can’t compete with the newer entrants into the market that build platforms, gather customer data and make service-based partnerships through open innovation. Open business models are particularly important, and striking the right balance between an open ecosystem and maintaining control over the platform through key control points. He finished up with a digital transformation roadmap: gaining efficiencies through digitization; then using data collected in the first stage while integrating flows across the enterprise to create one view of the ecosystem; and finally externalizing and harnessing value flows in the ecosystem. This last stage, externalization, is particularly critical, since opening the wrong control points can kills you business or stifle open growth.

This was a perfect lead-in to Chris Wiborg’s (Alfresco’s VP of product marketing) presentation on Alfresco’s partnership with Amazon and the tight integration of many AWS services into the Alfresco platform: leveraging Amazon’s open platform to build Alfresco’s platform. This partnership has given this conference in particular a strong focus on cloud content management, and we are hearing more about their digitial business platform that is made up of content, process and governance services. Wiborg started off talking about the journey from (content) digitization to digital business (process and content) to digital transformation (radically improving performance or reach), and how it’s not that easy to do this particularly with existing systems that favor on-premise monolithic approaches. A (micro-) service approach on cloud platforms changes the game, allowing you to build and modify faster, and deploy quickly on a secure elastic infrastructure. This is what Alfresco is now offering, through the combination of open source software, integration of AWS services to expand their portfolio of capabilities, and automated DevOps lifecycle.

This brings a focus back to process, since their digital business platform is often sold process-first to enable cross-departmental flows. In many cases, process and content are managed by different groups within large companies, and digital transformation needs to cut across both islands of functionality and islands of technology.

They are promoting the idea that differentiation is built and not bought, with the pendulum swinging back from buy toward build for the portions of your IT that contribute to your competitive differentiation. In today’s world, for many businesses, that’s more than just customer-facing systems, but digs deep into operational systems as well. In businesses that have a large digital footprint, I agree with this, but have to caution that this mindset makes it much too easy to go down the rabbit hole of building bespoke systems — or having someone build them for you — for standard, non-differentiating operations such as payroll systems.

Alfresco has gone all-in with AWS. It’s not just a matter of shoving a monolithic code base into a Docker container and running it on EC2, which how many vendors claim AWS support: Alfresco has a much more integrated microservices approach that provides the opportunity to use many different AWS services as part of an Alfresco implementation in the AWS Cloud. This allows you to build more innovative solutions faster, but also can greatly reduce your infrastructure costs by moving content repositories to the cloud. They have split out services such as Amazon S3 (and soon Glacier) for storage services, RDS/Aurora for database services, SNS for notification, security services, networking services, IoT via Alexa, Rekognition for AI, etc. Basically, a big part of their move to microservices (and extending capabilities) is by externalizing to take advantage of Amazon-offered services. They’re also not tied to their own content services in the cloud, but can provide direct connections to other cloud content services, including Box, SharePoint and Google Drive.

We heard from Tarik Makota, an AWS solution architect from Amazon, about how Amazon doesn’t really talk about private versus public cloud for enterprise clients. They can provide the same level of security as any managed hosting company, including private connections between their data centers and your on-premise systems. Unlike other managed hosting companies, however, Amazon is really good at near-instantaneous elasticity — both expanding and contracting — and provides a host of other services within that environment that are directly consumed by Alfresco and your applications, such as Amazon RDS for Aurora, a variety of AI services, serverless step functions. Alfresco Content Services and Process Services are both available as AWS QuickStarts, allowing for full production deployment in a highly-available, highly-redundant environment in the geographic region of your choice in about 45 minutes.

Quite a bit of food for thought over the two days, including their insights into common use cases for Alfresco and AI in content recognition and classification, and some of their development best practices for ensuring reusability across process and content applications built on a flexible modern architecture. Although Alfresco’s view of process is still quite content-centric (naturally), I’m interested to see where they take the entire digital business platform in the future.

Also great to see a month later that Bernadette Nixon, who we met at the Chief Revenue Officer at the event, has moved up to the CEO position. Congrats!

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.