Introduction
Organizations today face more automation complexity than ever before. To keep pace with their digital transformation goals, many have adopted a wide variety of tools and technologies to automate every aspect of their business. These tools might include customer relationship management (CRM), enterprise resource planning (ERP), robotic process automation (RPA), IT service management (ITSM), and more. While these solutions can deliver quick wins, if they’re implemented in a disjointed way or pushed beyond their intended capabilities, they can trap value in automation silos.
These “local” automation silos lead to technical and organizational debt, not to mention a diminishing return on investment. Automation silos also stand in the way of reaching important internal and external business goals for automation—including improving customer experience and team efficiency.
According to the 2024 State of Process Orchestration Report, 42% of IT decision-makers say a lack of integration between technologies is getting in the way of digital transformation goals. For example, a broken process might cause an insurance company’s customer to experience wait times for claims processing that are higher than industry averages. As a result, the customer might churn and seek coverage from a competitor. If they’re not addressed quickly, these types of inefficiencies can add up to lost revenue and market share.
Process orchestration solves these challenges by eliminating silos of trapped value, enabling you to coordinate the tasks that make up an end-to-end business process in a single process flow. A strategic process orchestration approach can help your organization achieve uninterrupted and frictionless automation, even when dealing with the most intricate processes.
Let’s explore more about process orchestration and the underlying complexity that drives it. In this guide, we will:
- Define process orchestration and why it’s important
- Discuss common automation challenges solved by process orchestration
- Help you understand what you need for successful process orchestration
What is process orchestration?
Process orchestration coordinates the various moving parts (or endpoints) of a business process, and sometimes even ties multiple processes together. Process orchestration helps you work with the people, systems, and devices you already have – while achieving even the most ambitious goals around end-to-end process automation.
What is the difference between orchestration vs automation?
Process orchestration, task automation, and process automation are related, but not the same.
- Task automation is the use of technology to automatically perform certain tasks without human intervention.
- Process orchestration is the coordination of the different tasks of a process, both automated and manual.
- Process automation is a mix of process orchestration and task automation to automate a process, where the degree of automation can vary.
Process orchestration is often compared to the role of a conductor in an orchestra, who makes sure everyone performs at the right time—they tell the musicians when each instrument needs to play to ensure that the song sounds as it should. The process orchestrator is the “conductor” of a process, coordinating and managing the interactions and dependencies of all the tasks in the process, whether they’re human or automated.
Today, automation is a business imperative: 96% of IT professionals in the 2024 State of Process Orchestration Report describe process automation as vital to digital transformation. Many organizations strive to automate their processes as much as possible. While this goal is ambitious, it’s far from reality. That’s because processes are often automated locally, or within a single software system, team, or device. However, most processes—even if they sound simple—span across a variety of endpoints and require complex business logic.
The Rise of Business Orchestration and Automation Technology (BOAT)
Multiple industry analysts and experts are centering on trends that identify orchestration as central to driving greater automation success and business technology integration.
As per the report, “Gartner® is observing the formation of a class of software technologies that enables enterprises to automate and orchestrate end-to-end business processes while connecting multiple enterprise systems of records via any applicable integration method. We are calling such a class of technologies—as the business orchestration and automation platform, aka BOAT.”
In other words, process orchestration is an essential part of a BOAT strategy, as organizations look to seamlessly integrate the various moving parts within their business processes.
Let’s look at a financial services process as an example
After hours of research, Kate, a first-time homebuyer, starts her mortgage application using her bank’s mobile app. She completes the initial know-your-customer (KYC) process by uploading her ID and taking a selfie for biometric verification.
The AI-powered process validates her identity and reviews her finances, but flags her application for additional verification due to a recent job change. Kate uploads the requested financial documents and receives a conditional pre-approval based on her debt-to-income ratio, spending habits, and credit score.
Excited but cautious, Kate schedules an in-person meeting with a mortgage advisor. At the branch, she learns that while her advisor can see her application, the extra due diligence isn’t complete. The bank’s compliance team has flagged her application for manual review, creating a backlog that prevents the advisor from proceeding.
Meanwhile, market volatility has prompted the risk management team to adjust lending criteria and rates using a separate system, potentially impacting Kate’s pre-approved terms.
Kate leaves the branch frustrated, unaware her application is caught between multiple disconnected systems and departments.
Gartner, “Quick Answer: Beyond RPA, BPA and Low Code — The Future Is BOAT,” by: Saikat Ray, Sachin Joshi, Akash Jain, July 11, 2024. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
Overcoming automation challenges with process orchestration
As you can see in this example, Kate’s experience was far from ideal and potentially damaged the relationship and her loyalty to the bank. This was due to delays caused by siloed automation and technologies. True end-to-end processes span many people (often working in different departments and teams), use a variety of technology (mobile apps, fraud models, legacy systems), and must adhere to strict regulatory requirements. Each of these contribute work to fulfill the process and can be thought of as a “process endpoint.”
Process orchestration coordinates all of these process endpoints, and sometimes even ties multiple processes together. Without process orchestration, you have a disconnected set of local tasks and automations, which leads to challenges such as:
- Broken end-to-end automation
- Lack of understanding
- Lack of flexibility
We’ll dive deeper into these challenges in a little bit.
When do you need process orchestration?
Simply put, you need process orchestration software when your process has:
Endpoint diversity
Process complexity
Is described by a more complex logic than just a simple sequence of steps.
Let’s dive into each of these concepts.
Endpoint diversity
Every process consists of tasks. In order to execute the process, you need to coordinate the execution of its tasks. Process orchestration software executes the process, but does not execute the tasks. Instead, tasks are executed by endpoints, which can be people, software systems, or physical devices.
People
Systems
Devices
Many organizations have complex processes that involve a variety of endpoints. According to the 2024 State of Process Orchestration Report, 60% of IT decision-makers and business leaders estimate that 26 or more systems are involved in their organization’s automation implementation. These organizations often contend with legacy systems, AI tools, other automation tools, microservices, and tasks that must be done by knowledge workers. Disparate systems and human tasks need to be integrated when automating their business processes.
The more diverse those endpoints are, the more you need powerful process orchestration software that lets you integrate those endpoints in a fast, flexible way. For example, people may be working with different front-end devices, or different applications that execute their tasks when invoked via an API.
Process complexity
To execute a process, you need to coordinate the execution of its tasks. This coordination is based on a certain logic, which in the real world is rarely just a straightforward sequence of steps.
Process logic is typically a lot more complex and needs to be described by advanced workflow patterns. In other words, sometimes the processes themselves need to follow an advanced logic. For example, multiple steps might need to be executed in parallel, or a process might require escalation after a certain amount of time. Many teams may have technologies in place that cannot support complex processes, leading to unnecessary workarounds and technical debt. Or, they may not have complete visibility into their processes’ performance at all.
Dealing with process complexity comes with two major challenges:
- IT/business alignment: Designing, operating, and improving complex end-to-end processes requires collaboration between technical and non-technical stakeholders. Ideally, this happens in the process planning and design phases. Alignment ensures that there are no communication silos—every stakeholder understands the overarching business goal of a process and how it works in the real world.
- Scalability and resilience: Executing processes across endpoints needs to happen in a reliable, scalable way. For example, an ecommerce vendor may experience a spike in orders that requires processing across systems and people. An orchestrator needs to handle transaction spikes. Or, it must offer high availability; for example, by letting the orchestration logic run in a redundant deployment across multiple data centers.
Process orchestration can align stakeholders, tame process complexity, and scale automation across the organization—all while providing teams with visibility into their processes to drive continuous improvement.
How to solve common automation challenges with process orchestration
As discussed earlier, most automation issues boil down to three key challenges.
- Broken end-to-end automation: Because local automations are not integrated with one another, the end-to-end process is not fully automated.
- Lack of understanding: The end-to-end process is not fully visible and key metrics are hard to track.
- Lack of flexibility: Changing the end-to-end process is difficult because it leads to potential changes in many different systems. Or, a lack of flexibility within existing tools may make it difficult to scale automation efforts.
Let’s look at the top three ways process orchestration technology can solve these challenges
Broken end-to-end automation
Solving the problem of broken end-to-end automation starts with alignment between IT and business stakeholders. Process planning and design using easy-to-understand industry standards can help set teams off on the right foot. Then, orchestrating processes across endpoints can break down silos caused by endpoint diversity and process complexity.
Gaining IT/business alignment
The BPMN and DMN standards help teams model and execute business processes and automated decisions. These standards provide a common language that aligns IT and business professionals. BPMN process models and DMN tables are easy to read, directly executable by process orchestration platforms, and help all stakeholders gain a shared understanding of how their processes work from start to finish.
Aligning on common standards allows teams to collaborate and communicate more effectively. A mutual understanding of BPMN and DMN can ensure that the automated process being built meets business requirements. This alignment not only reduces effort along the way (and in the future), but also helps the process achieve the desired business goals.
Knowing where to start is often as simple as choosing a small, pilot project as a proof of concept (PoC) that can demonstrate the value of end-to-end process orchestration to key stakeholders. That starts with a small group of developers who are responsible for driving the PoC. Choose a project that can be completed within the span of a month, maximum, yet can have a positive impact on a high-visibility internal process or customer experience.
With a process orchestration platform like Camunda, business and IT collaborate via an intuitive visual Modeler that adheres to BPMN and DMN standards. Modeling with Camunda reduces the time it takes to develop and maintain real-world business processes, so your business can react and adapt without costly delays. According to a new Forrester Total Economic Impact report, Camunda customers experience a reported savings of $15 million in process quality improvements and over 20,000 hours of development time.
Orchestrating processes across endpoints
Most organizations use hundreds or even thousands of off-the-shelf and homegrown applications to execute core business processes. Camunda orchestrates both automated and manual tasks across end-to-end business processes, no matter how many people, systems, or devices are involved.
Once you have collaborated to design and model processes, you can deploy those processes for execution using a workflow and decision engine. Camunda is powered by a cloud-native workflow and decision engine, Zeebe. Zeebe ensures processes run quickly and reliably by providing unlimited horizontal scalability, consistent low latency, and a failover architecture that provides rock-solid availability for mission-critical processes.
It’s easy to integrate Camunda with the technology you have. Camunda provides out-of-the-box Connectors that make it easy to integrate popular endpoints into process models, plus a Connector SDK so teams can build Connectors for legacy systems and specialty software. AI Connectors can also help to orchestrate AI services such as OpenAI, HuggingFace, and AWS SageMaker with flexibility and full auditability.
From there, Camunda can orchestrate anything from end-to-end, including legacy systems, microservices, RPA bots, APIs, AI/ML tools, IoT devices, manual tasks, and more. The process flows are based on the models you create in BPMN.
Lack of understanding
A few different things might cause a lack of visibility into your processes. For example, if your orchestration tool doesn’t provide support for advanced workflow patterns, your developers might have implemented time-consuming workarounds to support more complex processes. These workarounds can result in diminished process visibility, longer, more expensive maintenance cycles, and a lapse in collaboration between business and IT.
To contrast, a process orchestration solution like Camunda supports advanced workflow patterns, which involves reacting to events or handling complex business process logic across multiple endpoints. Some examples include:
- Compensation: Rolling back a business transaction in case of problems, or restoring business consistency.
- Dynamic parallel execution: Simultaneously coordinating multiple process branches, where the number of branches is determined in real-time.
- Message correlation: Correlating events together in a sequence (such as correlating a customer’s unique identifier with an order number on a customer service call).
- Time-based escalation: Escalating tasks that aren’t completed within a specific window of time.
Beyond advanced workflow patterns alone, a process orchestration solution like Camunda can provide visibility into the entire end-to-end process (not just the tasks a particular tool might execute). Camunda uses a consistent process model visualization across design, monitoring, and improvement activities. This “one model” approach gives a 360-degree view of all of your process execution data—making it easy to interpret information about running processes. For example, information about process status and incidents is overlaid on top of the same model used in the process design phase.
Continuous process optimization and improvement
The one model approach can help you identify bottlenecks and other areas where your organization can take action to improve processes. That way, both business and IT users can be involved in the entire process lifecycle, instead of being limited to collaboration during design time. This approach also eases cross-organization information sharing and reporting to regulatory organizations.
Camunda allows you to view heat maps that visualize process performance and bottlenecks.
Powerful reporting, dashboards and data filtering capabilities help IT teams and business stakeholders view the most important data. In addition, you can customize alerts that help stakeholders stay on top of what’s happening in real time.
Combining the power of machine learning algorithms with Camunda’s process execution data can uncover valuable insights that streamline operations, reduce costs, and elevate customer experience. Using a machine learning-ready data set provides pre-organized and pre-processed data, ready for analysis, drastically reducing the average time spent on data cleanup and preparation. With this data, business analysts and data scientists can:
- Effortlessly train new models or enhance existing ones
- Uncover patterns and trends
- Predict and optimize future process instances’ outcomes to ensure your business is poised to take advantage of opportunities for efficiency.
Lack of flexibility
Flexibility and scalability issues often stem from monolithic automation platforms—and even some process automation and iPaaS tools. These solutions are provided as a tightly integrated set of tools or components that cannot be unbundled. They promise that you can use the tool to do everything needed to automate business processes. In reality, this closed architecture approach locks the organization into the vendor’s product, reduces deployment options, makes change management more difficult, and hinders integration with other IT systems.
Using the one model approach described above, you can easily make changes to a business process, and pinpoint specific parts of a process that may not be operating as expected.
For further flexibility and scalability, Camunda offers loosely coupled components that fully integrate with one another, yet are designed to integrate seamlessly into an existing technical architecture to create a composable solution. For additional flexibility, you can deploy Camunda components to on-premises infrastructure, to public or private clouds, or in a hybrid configuration. Camunda also offers a hosted SaaS option that provides fast, massive scalability for high volume, high performance use cases.
In addition, Camunda takes advantage of distributed architectures and event stream processing to provide massive scale and resilience. An advanced workflow engine like Zeebe with a distributed architecture is ideal for delivering high availability because the software doesn’t rely on a single workflow node or a central database.
The bigger picture:
Process orchestration and the automation market
As previously discussed, process orchestration software executes a process, while the tasks that make up the process are executed by endpoints. There are many types of technologies that can execute tasks in a process. There are also tools on the market that have limited process automation capabilities, but that cannot orchestrate end-to-end processes. These are some of the key categories in the automaton market today:
- Process automation tools
- Monolithic automation platforms
- Modern monolithic automation platforms
- Microservices orchestrators
- iPaaS (Integration platforms as a service)
- Task automation tools
As referenced above, some of these solutions can deliver quick wins—but if your use cases expand or the implementation isn’t smooth, they can trap value in silos. Process orchestration eliminates this problem by coordinating the tasks that make up an end-to-end business process within a single process flow.
Read more: Camunda Compared to Alternatives
Often, the decision to use process orchestration technology isn’t binary. Process orchestration is usually combined with other technologies to get complete coverage of your organization’s automation needs. For example, some of the local automation tools (e.g. RPA products) can actually be used in combination with a true process orchestrator.
Using AI and process orchestration together
More and more organizations are relying on AI as a core part of their automation strategy. Process orchestration lies at the center of automation and is critical to AI’s success. If you use AI alongside process orchestration, you can more effectively automate complex tasks and optimize operational efficiencies to drive better business results.
Artificial intelligence (AI) and machine learning (ML) can be used in a process orchestration context in three main ways:
- Within an automated process by orchestrating AI tools and services
- To build a process and fast-track to orchestrated processes
- To improve and ultimately generate the process via intelligent execution and optimization
Here are just a few examples of how to use AI to enhance process automation and orchestration.
AI-powered copilots help boost productivity for both business and IT users by intelligently suggesting actions they can take when building processes. A copilot provides a fast-track to orchestrated processes by speeding up the design phase (enabling more business users to participate in process design) and providing immediate feedback to users, preventing process design errors that might otherwise only be detected in production.
Intelligent processes help teams get the most out of AI/ML tools and services by providing the toolset to orchestrate them in the same way as other process endpoints. In particular, intelligent processes enable teams to orchestrate generative and predictive AI functionality in a combined process. For example, an AI tool or service can interpret customer inquiries and leverage decision automation to route customer requests accurately. Operationalizing AI in this way helps organizations build in critical governance for the use of AI and data.
Autonomous process intelligence uses AI/ML to uncover hidden value in an organization’s most critical end-to-end business processes. It identifies opportunities for increased automation and drives continuous improvement of automated processes. As process automation becomes increasingly autonomous, more organizations will be able to scale their automation efforts and realize the full value of process orchestration.
Often, the decision to use process orchestration technology isn’t binary. Process orchestration is usually combined with other technologies to get complete coverage of your organization’s automation needs. For example, some of the local automation tools (e.g. RPA products) can actually be used in combination with a true process orchestrator.
Boosting productivity in process modeling and design
Camunda offers many ways to take advantage of AI to both boost productivity in the automation of business processes, and to increase the intelligence and capabilities of those processes. Here are a few examples of how fast-tracking tools can be used today:
- Modeler Copilot: Provides guidance that helps you leverage BPMN process modeling.
- AI Form Assistant: Uses natural language to describe the form you want to design, then customize and extend it for your use case.
- AI Docs Chatbot: LLM-powered search that learns from its sources and delivers quick answers to your technical questions.
- AI Connectors: Connectors for AI services and machine learning to enable businesses to orchestrate AI/ML as an endpoint in their processes.
- AI-Enabled Blueprint: Interpret customer inquiries and leverage decision automation to route customer requests accurately.
- ML-Ready Datasets: Export process execution data in a format that’s ready to import into popular ML tools and feed your data models.
Final thoughts
To sum up, by adopting process orchestration, you’ll be able to orchestrate tasks across people, systems, and devices. As a result, you’ll maximize the value from existing investments, eliminate silos, and achieve your business goals with automation. A universal process orchestrator like Camunda can be both powerful and developer-friendly—driving lasting value, transformative efficiencies, and unparalleled visibility.