As organizations push to be more customer-focused and efficient, most are trying to streamline their operations by automating processes. Recent research shows that 92% of IT decision-makers who are involved in process automation agree that it is key to their digital transformation.

End-to-end process automation takes work, and real-world, mission-critical processes are complex. Processes need to make many different connections along their routes – engaging with APIs, RPA bots, microservices, work done by people, physical devices such as IoT, and a wide variety of systems. This makes it hard to visualize a complete business process from end to end and hard to know how to start with automating the process.

As much as organizations want to simplify processes and drive new levels of efficiency, internal and external forces are working against them. The three principal issues getting in the way are the inability to orchestrate flows across all of the endpoints processes touch. Each endpoint – each set of people, systems, and devices – has its own challenges that can only be overcome with the help of a guiding hand.

Where Processes Disconnect

People: A complete, end-to-end business process usually requires manual work to be combined with automated steps in a unified workflow. It’s important that workflows are properly orchestrated. If they’re not, for example, a customer onboarding process can get delayed because an employee doesn’t know they need to complete a task. This leads to a poor customer experience.

Systems: Processes need to integrate with SaaS and cloud-based applications either developed internally or provided by an external vendor. They also need to connect legacy systems and homegrown applications, which is time-consuming and requires extensive developer resources. While it’s nice to think legacy systems can and will be replaced, the reality is, they usually won’t be; these systems often run mission-critical parts of the business and it’s just not feasible to replace them. These systems have been in place for years and may be challenging or require specialized knowledge to integrate with. Consequently, managing the flow of work through these disparate systems becomes time-consuming and prone to errors. The lack of a consistently reliable manner to automate such systems prevents the end-to-end process from being automated. It can result in a never-ending maintenance loop that negates the benefit of automation altogether.

Devices: While people and systems serve as the main touchpoints, processes also flow through scattered and disparate sets of devices across enterprises. Devices could include scanners, smartphones, printers, IoT devices – even a parking meter. In some cases, an organization’s automated workflows could involve dozens, if not hundreds, of these devices. If processes are not connected, organized, prioritized, and authorized across devices, they can fail and threaten important components of a company’s digital transformation.   

Coordination is needed to untangle the misalignment. This has given rise to a new concept called process orchestration.

Process orchestration is the coordination of individual business tasks into a process that spans people, systems, and devices. These workflows are often complex and involve many steps and endpoints. Processes are designed across business and IT stakeholders via visual diagrams and process instances are executed by a process engine. We believe that process orchestration is critical to delivering on the promise of process automation. Using process orchestration, organizations can ensure that their end-to-end processes are operating seamlessly and gain the visibility they need to change course when processes hit a snag. 

Orchestrating Tools, Technologies, and Platforms

Process orchestration is closely related to hyperautomation. Gartner defines hyperautomation as “a business-driven, disciplined approach that organizations use to rapidly identify, vet, and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms.” In other words, process automation doesn’t hinge on a single tool’s success or failure. Instead, it’s about choosing what’s right for your organization’s people and technology systems. The operative word in Gartner’s definition is “orchestrated” because driving software is customizable and adaptable to its environment.

In the 2000s, there was an attempt to master process orchestration by introducing business process management systems (BPMSs). However, those products became inflated by the vendors’ desire to provide general-purpose, low-code application development platforms, which made them heavyweight and decreased their value for process orchestration.

As much as we’d all like to operate at the automation levels of an organization like Amazon, most organizations are relatively early in their process automation maturity journey. As companies modernize their tech stacks, undoing a legacy BPMS is often harder than starting from scratch. Many organizations turn to local automation like robotic process automation (RPA) and cloud-based integration platforms-as-a-service (iPaaS) to automate independent tasks within their applications to work around these issues. However, as time goes on and local tasks must connect to execute an end-to-end process, many organizations become frustrated with the limitations of local automation tools. 

This is where process orchestration comes in. While a process orchestration layer is almost always necessary, it’s not the only part of a process automation tech stack. It’s usually combined with other technologies to get complete coverage of an organization’s automation needs.

Organizations can be anywhere in their maturity journeys – from unwinding a legacy BPMS, to patching together disparate RPA bots, to starting process automation workflows from scratch. Regardless of where they are in their journey, a process orchestrator can drive various processes between people, systems, and devices (agnostic of where they originate). This means a universal process orchestrator can tie together SaaS applications, microservices, and legacy applications, as well as the devices and people in the automation loop. 

The word “universal” is important. Some orchestrators are only optimized to drive legacy systems, APIs, or SaaS applications. But it’s critical to have one orchestrator driving everything. For example, a single process like an insurance claim might involve multiple API-driven components, a legacy system, and a team of people. Without a standard procedure for how this process rolls out step-by-step, it can be impossible for these systems and people to interoperate efficiently and effectively. 

A developer might start by using open standards like BPMN to model their processes step by step. From there, a universal process orchestrator would hook into any endpoint to execute the process. Because most modern software development teams want to use APIs combined with homegrown components (and may be coping with residual legacy systems) – the ability to integrate with everything is key.

True Process Automation

When you can orchestrate processes across people, systems, and devices, you can transform your automation approach from isolated task automation to true process automation. The unsung superhero in this scenario is process orchestration.