Digital business is all about creating competitive advantage –conducting business in ways that prospects and customers recognize as superior to rivals and thus award you their business. “How” an enterprise delivers customer value determines its competitive advantage, and another word for “how” is “process.”
The essential technologies for digital business treat processes as a portfolio of strategic assets. They include next-generation capabilities for process discovery, mapping/documentation and analysis, automation, and means to extract intelligence from execution to improve outcomes.
Industry-leading enterprises work hard to manage processes as assets. Their approach includes taking stock of processes, inventorying, documenting and managing them within process portfolios, where they can be classified, prioritized, documented and examined for continuous improvement. Process asset management (PAM) technology has emerged to fulfill this need.
PAM includes collaborative process mapping capabilities designed for non-technical users and process stakeholders to document, control and govern processes. PAM can assist with education, training and coaching, version control; it helps manage change, and it can be used to redesign and improve processes.
The need for and use of PAM tools is accelerating, driven by the need for enterprises to transform to digital businesses that streamline and automate business and other operational processes. However, many legacy processes are deeply embedded in multiple applications and systems. This makes them difficult to document, analyze and modernize. New means have emerged to better automate process discovery.
Process mining technology (PMT) is now available to automate the work of discovering visualizing and understanding how current business processes execute and perform. PMT solutions track, capture and aggregate the event logs recorded and stored by operational systems used to execute business processes. They organize this data to create a visual map of the process.
PMT solutions usually include analysis tools that expose critical paths (the most common or most efficient means to execute the process) and can reveal variances or deviations that can affect process performance and outcomes. PMT enables process owners and stakeholders to examine process structure, hierarchies, decisions, policies, rules and tasks to improve the quality and efficiency of process flow and outcomes.
The need for digital automation platforms
The output of PMT can be consumed by another automation tooling to improve process and software designs. The go-to technology for such capabilities is an evolving class of process-oriented application development environments we refer to as digital automation platforms (DAPs).
A DAP is a set of tools and resources structured within a uniform framework to enable developers to rapidly design, develop, deploy, manage and monitor process-oriented applications. They use low-code/no-code capabilities that include visual models, prepackaged templates, and graphical design capabilities with drag-and-drop tooling to compose rather than code software. DAPs also include resources to assist in user-interface design, leverage the new technologies found in next-generation devices, and simplify collaboration among business and IT professionals. DAPs combine both development and runtime IT environments. Changes can be made on the fly, making them highly agile DevOps platforms.
While automation changes the “how” an enterprise does things, it also changes the nature of work. Digital leaders seek to eliminate workforce task repetition and provide resources that augment human abilities to make high-quality decisions, gain insight from machine learning technology, and act quickly and consistently. Robotic process automation (RPA) technology is emerging to support such efforts.
RPA creates discrete software robots (“bots”) that can minimize or eliminate repetitive human tasks; interpret unstructured data; and automate cross-application data exchange, not otherwise enabled within DAPs or other workforce productivity software. RPA uses machine learning technology to add intelligence to bots to aid in visual perception, learning, planning, problem-solving and revealing insights into unstructured and semi-structured data (e.g., images, video and audio chat dialogs). Such bots are sometimes referred to as “digital workers” that can augment human workforces, equipping them to scale-out with accelerating growth and change.
While many other IT resources are required to enable the modern digital business, we believe process asset management (PAM), process mining technology (PMT), digital automation platforms (DAPs), and robotic process automation (RPA) are essential technologies for digital business. Collectively, they discover and manage processes as strategic assets; automate and improve operational performance by reducing errors, cost and cycle times; improve performance toward desired outcomes, and perform tasks at a scale that otherwise might overwhelm a human workforce.