Utsav Turray, Head of Product Marketing, Newgen Software

Utsav has over 15 years of experience in product marketing and management, go-to-market, solution consulting, and software development. He has been instrumental in successfully launching enterprise products through effective positioning, messaging, and marketing programs. A technology enthusiast, Utsav brings to the table a good understanding of technology, business, and customer needs. He has deep domain expertise in enterprise content management, business process automation, and low-code application development.


Processes are the foundation of every business. The way processes are organized, analyzed, measured, and enhanced influences key business performance indicators. Process automation software, traditionally known as business process management (BPM), automates and streamlines business processes to improve efficiency, bring agility, and generate better output. According to Forrester, “BPM empowers businesses to run more efficiently and eliminates confusion and confliction.”

Evolution of BPM

BPM has evolved a lot since its inception. Below are three main stages of its transformation:

The Traditional BPM

The term “business process management suite” was first coined by Gartner in the 2000s to describe a solution that primarily handles process modeling and management. Initially, BPM was considered as a solution to improve process efficiencies and reduce overall costs. The “Six Sigma” strategies developed by Motorola and “lean manufacturing” principles derived from Toyota demonstrate the usage of traditional BPM. Despite the advantages presented by these strategies, they had little to offer beyond process improvement and cost reduction in some cases.

With evolving market dynamics and technological interventions, IT became the mainstay of most enterprises, and the business goals shifted from productivity and cost optimization to customer experience.

Intelligent BPM

While early BPM was limited to production quality improvements, it relied on significant human interventions. A modern BPM solution was needed to handle complex business processes, process high data volumes including social, and optimize human effort.

Intelligent Business Process Management Suite (iBPMS) provided enterprises the capability to tie analytics and content management to help the workforce access required information and content regardless of the source. It brought together technologies like artificial intelligence (AI), machine learning (ML), and social, mobile, analytics and cloud (SMAC). This helped break process and information silos, connect organizational resources, enable holistic process experience, and drive contextual customer engagement.

In a nutshell, iBPMS was a significant improvement over traditional BPM, as enterprises could:

  • Ensure automatic data processing and utilize predictive analytics for accelerating their workflows
  • Leverage volumes of data to derive valuable insights and facilitate intelligent decision-making
  • Ensure continuous process improvement through self-learning systems
  • Drive meaningful engagement with customers and provide enhanced offerings with SMAC capabilities

Hyperautomation: Modern-age BPM

Hyperautomation is the latest advancement in the series of BPM evolution. It drives a holistic, enterprise-wide digital transformation by automating the entire range of business processes. Furthermore, it leverages robust technologies such as robotic process automation (RPA), AI and ML, process mining, and low code to provide an end-to-end automated solution for business users. According to Gartner, “hyperautomation often results in the creation of a digital twin of the organization (DTO), allowing organizations to visualize how functions, processes, and key performance indicators interact to drive value.”

Hyperautomation is a significant shift from BPM as it goes well beyond process excellence. It combines cutting-edge technologies to empower enterprises by offering the following advantages:

  • Enterprises can significantly optimize the effort of knowledge workers by leveraging RPA for automating mundane tasks and operational workflows. RPA can also be leveraged for handling exceptions and inconsistencies through the deployment of trained bots.
  • AI-enabled tools can be utilized for examining, interpreting, and processing data. AI and ML can be used with cognitive tools like natural language processing and optical character reader to cater to specific use cases and realize business value.
  • Process mining enables monitoring and analysis of process performance for continuous improvement. It can be leveraged to explore the current state of business processes and identify new opportunities for optimization and automation.

By leveraging low code capability, enterprises can rapidly develop and deploy business-critical applications without compromising on governance. Low code can help foster powerful collaboration between business and IT, free up knowledge workers’ bandwidth, and facilitate deployment of other technologies, thereby democratizing hyperautomation across enterprises.

On Top of Customer Expectations; Ahead of the Competition

BPM has come a long way, but with changing business goals and challenges, it will be critical for enterprises to remain open to new BPM advancements. And utilize it to stay future-ready, on top of customer expectations, and ahead of the competition.

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