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BPM moves to the next level


While the core discipline of business process management (BPM) has largely remained the same since its roots in the early 1990s, the business needs that it seeks to meet have evolved. Years ago, companies relied on it for supporting back-end business functions.

Today, BPM is widely used to automate business operations, and is considered a foundation for business-driven innovation and application development. Now, not only do companies need to continue optimizing business processes to cut costs, drive greater efficiency and improve productivity, but also to implement processes that can help them remain relevant and competitive.

Greater efficiency

In its first iteration, BPM—or workflow technology, as it was called at the time—was a fairly simple concept. Its function was to automate back-end processes to speed up what had been completely manual and paper-based workflows. In the client-server world, BPM served as the interface between the database and the people who entered transaction information into it. It electronically routed each finished step to the next link in the chain.

This contributed to greater efficiency, productivity, and cost savings, and it provided the business with a big-picture view of the state of the company, such as how many orders were in process or whether there was a problem with shipping.

One of the early innovators in the BPM space was a company called Staffware (acquired by TIBCO). The company helped evolve BPM to enable process redesign at all levels of the organization, which was important and timely as the concept of “lean management” gained popularity and companies sought to eliminate waste, redundancies and revisions. Platforms such as Staffware introduced the ability to create business process models that could graphically represent workflows in both their current “as is” state and in their future “to be” state after changes are made.

Using these graphical tools, business users could more easily define and modify processes on their own. They were essentially creating applications to feed simple business decisions—which direction to flow a process at a fork in the road, so to speak. This was important because it enabled business users to apply their particular expertise to process modeling.

During this time, decision automation was also added to workflow systems. These capabilities were powered by rules engines, which not only pushed the envelope in terms of automating more complex decisions, but also have grown to become a foundation of modern AI. BPM introduced the ability to automatically apply rules and policies to data in order to handle more complex business decisions. These rules could be expressed via business-friendly metaphors, like spreadsheets or simple English-like languages, representing yet another step forward for business users looking to automate their manual tasks.

Contributing to digital transformation

We are again at the crossroads as the industry doubles down on digitally transforming operations to deliver personalized, consistent customer experiences that are integrated across all points of interaction. In their efforts to retain customers, capture new audiences and grow revenue, long-established companies can’t afford to lag behind start-up competitors with digitally native processes.

When industry analysts first started talking about the notion of digital transformation, BPM technologies did not have an answer to these challenges. They simply were not well-suited for tasks like building customer-facing mobile apps or competing with more nimble upstarts that could tap into cloud computing resources without the burden of massive infrastructures and technical debt. Traditional BPM tools were designed to centralize and operationalize all aspects of a business' core processes—including the development, implementation and management of workflows, as well as any changes that became necessary as a result of changing market conditions or regulatory requirements.

Today, it is a different story. BPM tools are increasingly being positioned as a path to bring business expertise into the application development process. IT teams should not be expected to be solely responsible for creating impactful customer engagement applications. These apps need to capture and codify the domain expertise from business peers on the front lines of marketing, sales, product development and more. We have seen new capabilities for low-code application development emerge as part of BPM tooling to help meet this need. Now, not only can business users build and implement applications without having to write code themselves, but there are greater opportunities for business and IT professionals to collaborate on more strategic business initiatives. 

There are standards for business process modeling (such as Business Process Model and Notation  or BPMN) that ensure a consistent experience for business analysts regardless of the tools used, and a new standard for decision modeling (Decision Modeling Notation or DMN) is opening up the world of business rules to a much wider audience. It is now practical for business analysts to create powerful applications directly from models without any coding required.

Microservices and containerization

In addition, the world of application development is undergoing dramatic change. Businesses are moving away from “monolithic” applications that are difficult to manage and change, towards microservices architectures, where applications are broken into small independent parts that can be deployed, scaled, managed and updated independently of each other. BPM solutions are evolving to support these new architectures. Now instead of a large monolithic BPM platform, vendors are packaging their solutions into multiple containerized services that can be deployed independently into a modern cloud platform.

This enables greater integration between business processes and advanced technologies like robotic process automation (RPA), which adds new automation capabilities that further cut waste and inaccuracies by eliminating more manual tasks; AI which can be layered on top of BPM to automate decisions; and machine learning (ML) which can enable automated processes to learn as they go.                                             

These technologies are already in wide use today. For example, many of the recommendation engines used by streaming entertainment service providers and e-commerce businesses are powered by a combination of process automation and ML. These systems can prioritize the content and products they suggest to the customer based not only on the individual's viewing, search and purchase history, but also based on the patterns of other customers. The amount and types of information that these systems can automatically process and adapt to is staggering, and providers are constantly seeking to improve the algorithms in order to provide customers with more accurate, relevant and valuable results.

Moving forward

Moving forward, there will be some bumps in the road as IT wrestles with questions related to the security, scalability, and reliability of cloud-native applications built using BPM tools, as well as understanding how to govern business-driven apps in ways that are consistent with traditionally developed applications. However, these developments are exciting and there should be optimism about the opportunities ahead. BPM has successfully been through several stages of reinvention over the years. We are already seeing the next phase of this technology unfold in fascinating and valuable ways, and it will continue to rise to the challenges ahead.


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