Today is Ada Lovelace Day — marking the contributions of the world’s first “programmer” — and the perfect day for Bizagi to launch their Ask Ada generative AI that helps knowledge workers find answers to questions about their organization’s data. Check out the short video clip on the AI product page to see how it looks to a user; basically, this is conversational analytics out of the box without having to predefine the analytics.
I had a sneak peak a few days ago with the always-informative Rachel Brennan, Bizagi’s VP of Product and Solutions Marketing, and she pointed out some of the important governance and privacy safeguards that they have put in place:
Ada uses Azure Private OpenAI GPT Service, rather than the public service
Ada is trained on Bizagi’s data structure and does not share any private data
Ada filters information to present only what is authorized and relevant to the user’s role and context
This focus on governance and privacy is something that a lot of companies are struggling with, but Bizagi seems to be moving in the right direction.
Many companies are choosing to focus on genAI for “co-pilot” developer tasks, including creating process models, or for replacing human steps in processes; having Ada as a trusted advisor for knowledge workers is a different angle to how AI can be used in the context of business processes. I’m imagining many other types of “user assist” tasks where AI can be applied, such as summarizing a long-running customer transaction so that the worker don’t have to read through every piece of content associated with that customer.
Ask Ada will be released this month, and is free to Bizagi customers until June 30, 2024. Looking forward to see how they expand these capabilities in the months to come.
Bennet Krause of Holisticon, an IT consultancy, presented some of the integrations that they’ve created between Camunda and GPT, which could be applied to other Large Language Models (LLMs). Camunda provides an OpenAI connector, but there are many other LLMs that may provide better functionality depending on the situation. Holisticon has created an open source GPT connector, which Bennet demonstrated in a scenario for understanding an inbound customer email and constructing an outbound response after the issue has been resolved by a customer service representative.
They have a number of foundational connectors — extract structured data from unstructured data, make decisions or classifications, compose text from instructions and templates, and natural language translation — as well as what he calls agentic connectors, which are automated agents interacting with the outside world.
The addition of the agentic connector allowed some paths in his customer service example to become completely automated, replacing the customer service representative with an automated agent. These connectors include a database connector to query SQL databases, an OpenAI connector to interact with REST services, a Q&A retrieval connector to answer questions based on documentation, a process connector to dynamically model and execute processes, and a plan and execute connector.
He warned of some of the potential issues with replacing human decisions and actions with AI, including bias in the LLMs, then finished with their plans for new and experimental connectors. In spite of the challenges, LLMs can help to automate or assist many BPM tasks and you can expect to see much more interaction between AI and BPM in the future.
This is the last session I’ll be at on-site for this edition of CamundaCon: we have the afternoon break now, then I need to head for the airport shortly after. I’ll catch up on the last couple of sessions that I missed when the on-demand comes out next week, and will post a link to the slides and presentations in case you want to (re)view any of the sessions.
Steven Gregory of Cardinal Health™ Sonexus™ Access and Patient Support, a healthcare technology provider, presented on some of the current US healthcare trends — including value-based care and telemedicine — and the technology trends that are changing healthcare, from IoT wearable devices to AI for clinical decisioning. Healthcare is a very process-driven industry, but many of the processes are manual, or embedded within forms, or within legacy systems: scheduling, admin/discharge, insurance, and health records management. As with many other industries, these “hidden” workflows are critical to patient outcomes but it’s not possible to see how the flows work at any level, much less end-to-end.
There’s some amount of history of clinical workflow automation; I worked with Siemens Medical Systems (now Cerner) on their implementation of TIBCO’s workflow more than 10 years ago, and even wrote a paper on the uses of BPM in healthcare back in 2014. What Steven is talking about is a much more modern version of that, using Camunda and a microservice architecture to automate processes and link legacy systems.
They implemented a number of patient journey workflows effectively: appointment creating, rescheduling and cancellation; benefits verification and authorization; digital enrollment; and some patient-facing chatbot flows. Many of these are simply automation of the existing manual processes, but there’s a lot of benefit to be gained as long as you recognize that’s not the final version of the flow, but a milestone on the journey to process improvement.
He discussed a really interesting use case of cell and gene therapy: although they haven’t rolled this out this yet, it’s a complex interaction of systems integration, data tracking across systems, unique manufacturing processes while providing personalized care to patients. He feels that Camunda is key for orchestrating complex processes like this. In the Q&A, he also spoke about the difference in ramp-up time for their developers, and how much faster it is to learn Camunda and individual microservices than a legacy system.
Great examples of moving beyond straightforward process orchestration for improving critical processes.
The second day of CamundaCon started with a keynote by Camunda co-founder and chief technologist Bernd Ruecker and CTO Daniel Meyer. They started with the situation that plagues many organizations: point-to-point integrations between heterogeneous legacy systems and a lot of manual work, resulting in inefficiencies and fragile system architecture. News flash: your customers don’t care about your aging IT infrastructure, they just want to be served in a way that works for them.
You can swap all of this with a “big bang” approach that changes everything at once, but that’s usually pretty painful and doesn’t work that well. Instead, they advocate starting with a gradual modernization which looks more like the following.
First, model your process and track the flow as it moves through different systems and steps. This allows you to understand how things work without making any changes, and identify the opportunities for change. You can actually run the modeled processes, with someone manually moving them through the steps as the work completes on other systems, and tracking the work as it passes through the model.
Next, start orchestrating the work by taking the flow that you have, identifying the first best point to integrate, and doing the integration to the system at that step. Once’s that’s working, continue integrating and automating until all the steps are done and the legacy systems are integrated into this simple flow.
Then, start improving the process by adding more logic, rearranging the steps, and integrating/automating other systems that may be manually integrated.
That’s a great approach for a first project, or when you’re just focused on automating a couple of processes, but you also need to consider the broader transformation goals and how to drive it across your entire organization. There are a number of different components of this: establishing a link between value chains, orchestrations and down through to business and technical capabilities; driving reuse within your organization using the newly-launched Camunda Marketplace; and providing self-service deployment of Camunda to remove any barriers to getting started.
An important part of your modernization journey will be the use of connectors, while allow you to expose integrations into a wide variety of system types directly into a process model without the modeler needed to understand the technical intricacies of the system being called. This, and the use of microservices to provide additional plug-in functionality, makes it easier for developers and technical analysts to build and update process-centric applications quickly. Underpinning that is how you structure development teams within your organization (autonomy versus centralization) and support them with a CoE, smoothing the path to successful implementations.
In short, the easier you make it for teams to build new applications that fit into corporate standards and meet business goals, the less likely you are to have business teams be forced go out and try to solve the problem themselves when they really need a more technical approach, or just suffer with a manual approach. You’ll be able to categorize your use cases to understand when a business-driven low-code solution will work, and what you need the technical developers to focus on.
Camunda now includes a much friendlier out of the box user interface, rich(er) forms support and testing directly in the process modeler; this allows more of the “yellow” areas in the diagram above to be implemented by less-technical developers and analysts. They are also looking at how AI can be used for generating simple process models or provide help to a person who is building a model, as well as the more common use of predictive decisioning. They’ve even had a developer in the community create BpmnGPT to demonstrate how an AI helper can assist with model development.
They wrapped up with a summary of the journey from your first project to scaling adoption to a much broader transformation framework. Definitely some good goals for those on any process automation journey.
I feel like I’m barely back from the academic research BPM conference in Utrecht, and I’m already at Camunda’s annual CamundaCon, being held in New York (Brooklyn, actually) — the first time for the main conference outside of Germany. The location change from Berlin is a bit of a tough call since they will lose some of the European customers who don’t have a budget for international travel, but the opportunity to see their North American customers will make up for it. They’re also running the conference virtually for those of you who can’t be here in person, and you can sign up for free to attend the presentations online.
Although I don’t blog about anything that happens after the bar is open, I did have a couple of interesting conversations at the networking event last night about my relationship with Camunda. I’m here this week as an independent analyst, and although they are covering my travel expenses, I’m not being paid for my time and (as usual) the opinions that I write here are my own. This is the same arrangement I have with any vendor whose conference I attend, although I have got a bit pickier about which locations I’m willing to travel to (hint: not Vegas). I’ve been covering Camunda a long time, starting 10 years ago with their fork from Activiti, back when they didn’t capitalize their name. They’ve been a client of mine in the past for creating white papers, webinars and speaking at their conference. I’ve also worked with some of their clients on technical strategy and architecture, which is the other side of my business.
The first day opened with a keynote from Camunda CEO Jakob Freund giving a brief retrospective of the last 10 years of their growth and especially their current presence in North America. There’s over 200 people attending today in person at the 74Wythe event space, plus an online contingent of attendees. He started with a vision of the automated enterprise, and how this is made difficult by the complexity of mission-critical processes that cross multiple silos of systems and organizational departments. Process orchestration allows for automation of the end-to-end processes by acting a a controller that can invoke the right resource — whether a person or a system — at the right time while maintaining end-to-end visibility and management. If you’re not embracing process orchestration, you run the risk of having broken processes that have a significant impact on your customer satisfaction, efficiency and innovation.
Camunda has more than 500 customers globally now, and has amassed over 5000 use cases for how those organizations are using Camunda’s software. This has allowed them to develop a process orchestration maturity model: from single projects, to broader initiatives, to distributed adoption, to a strategic scaled adoption of process orchestration. Although obviously Jakob sees the Camunda Process Orchestration Platform as a foundational platform, he looked at a number of other non-technical components such as stakeholder buy-in, plus technical add-ons and integration partners. I like that he started with strategic alignment and ended with value monitoring wrapping back to the alignment; this type of alignment between strategic goals and operational metrics is something that I strongly believe in and have written about quite a bit.
Since we’re in New York, his process orchestration in action part was focused on financial services, although with lessons for many other industries. I work a lot with my own financial services clients, and the challenges listed are very familiar. He walked through case studies of Desjardins (legacy BPMS replacement), Truist (merging systems from two merged banks), National Bank of Canada (automation CoE to radically reduce project development time), and NatWest (CoE to aid self-service projects).
He moved on to talk about the innovation that Camunda is introducing through their technology. They now address more of the BPM lifecycle than they started out with — which was purely as a developer tool — and now provide more tools for business and IT to collaborate on process improvement/automation projects. They are also addressing the accelerating of solutions through some low-code aspects; this was a necessary move for them in the face of the current market. Their challenge will be keeping the low code tooling from getting in the way of the developers, and keeping the technical details from getting in the way of the business people.
No technical conference today is complete without at least one slide on AI, and Jakob did not disappoint. He walked through how they see AI as it applies to process orchestration: predictive AI (e.g., process mining and decisioning), generative AI (e.g., form generator from simple language), and assistive AI (e.g., knowledge worker helper).
He described their connectors marketplace, which includes connectors created by them but also curated from their partners. Connectors are essential for integration, but their roadmap also includes process templates, internal marketplaces within an organization, and entire industry solutions and applications. This is an ambitious undertaking that a lot of vendors have done badly, and I’ll be very interested in seeing how this develops.
He finished up with some larger architecture issues: cloud support, security and compliance, multi-tenancy and how this allows them to support organizations both big and small. Their roadmap shows a lot of components that are targeted at broadening their reach while still supporting their long-term technical customers.
After the keynote, I attended the Journal First session, which was a collection of eight 15-minute presentations of papers that have been accepted by relevant journals (in contrast to the regular research papers seen in other presentations). It was like the speed-dating of presentations and I didn’t take any specific notes, but did snap a few photos and linked to the papers where I could find them. Lots of interesting ideas, in small snippets.
The second day of the main conference kicked off with a keynote by Marta Kwiatkowska, Professor of Computer Science at Oxford, on AI and machine learning in BPM. She started with some background on AI and deep learning, and linked this to automated process model discovery (process mining), simulation, what-if analysis, predictions and automated decisions. She posed the question of whether we should be worried about the safety of AI decisions, or at least advance the formal methods for provable guarantees in machine learning, and the more challenging topic of formal verification for neural networks.
She has done significant research on robustness for neural networks and the development of provable guarantees, and offered some recent directions of these applications in BPM. She showed the basics of calculating and applying robustness guarantees for image and video classification, and also for text classification/replacement. In the BPM world, she discussed using language-type prediction models for event logs, evaluating the robustness of decision functions to causal interventions, and the concept of reinforcement learning for teaching agents how to choose an action.
As expected, much of the application of AI to process execution is to the decisions within processes – automating decisions, or providing “next best action” recommendations to human actors at a particular process activity. Safety assurances and accountability/explainability are particularly important in these scenarios.
Given the popularity of AI in general, a very timely look at how it can be applied to BPM in ways that maintain robustness and correctness.
I’ve been remiss with blogging the past couple of months, mostly because I’ve been involved in several pretty cool projects that have been keeping me busy. As I mentioned in yesterday’s post, I recently wrote a paper for Flowable about end-to-end automation and the business model transformation that it enabled.
I’ve been working on a video series for a process mining startup, Futuroot, which specializes in process intelligence for SAP systems. We’re doing these as conversational videos between me and a couple of the Futuroot team, each video about 20 minutes of free-ranging conversation. In the first episode, I talk with Rajee Bhattacharyya, Futuroot’s Chief Innovation Officer, and Anand Argade, their Director of Product Development. Here’s a short teaser from the video:
I recently created a paper for Flowable on end-to-end automation, including a look at how the Gartner “hyperautomation” term fits into the picture. End-to-end automation is really about enabling business model transformation, not just making the same widgets a little bit faster, and I walk through some of the steps and technologies that are required.
Check it out on the Flowable site at the link above (registration required).
I have a long history working with insurance companies on their digitization and process automation initiatives, and there’s a lot of interesting things happening in insurance as a result of the pandemic and associated lockdown: more automation of underwriting and claims, increased use of digital documents instead of paper, and trying to discover the “new normal” in insurance processes as we move to a world that will remain, at least in part, with a distributed workforce for some time in the future. At the same time, there is an increase in some types of insurance business activity, and decreases in other areas, requiring reallocation of resources.
On June 17, I’ll be presenting a webinar for ABBYY on some of the ways that insurance companies can navigate this perfect storm of business and societal disruption using digital intelligence technologies including smarter content capture and process intelligence. Here’s what we plan to cover:
Helping you understand how to transform processes, instead of falling into the trap of just automating existing, often broken processes
Getting your organization one step further of your competition with the latest content intelligence capabilities that help transform your customer experience and operational effectiveness
Completely automating your handling of essential documents used in onboarding, policy underwriting, claims, adjudication, and compliance
Having direct overview of your processes as living in real time to discover where bottlenecks and repetitions occur, where content needs to be processed, and where automation can be most effective