The Genesis and Evolution of Process Mining

Process mining is a powerful tool that helps businesses gain insights into their actual workflows by analyzing data from computer systems. This technology can reveal inefficiencies and areas for improvement. Newer process discovery techniques, like those offered by Skan, use artificial intelligence to directly observe how people work with digital systems, providing a more holistic view of processes.

Process mining and process discovery are relatively new techniques businesses use to achieve greater transparency into operations, consequently impacting customer satisfaction, revenue, profits, and growth. Process mining and its next evolution, process discovery, gives an organization the tools it needs to discover, evaluate, and optimize its business processes.

The pursuit of process excellence is not new. As the Industrial Revolution dawned on the world, luminaries such as Frederick Taylor, Henry Ford, and others began looking at the processes involved in manufacturing. Gradually, that led companies to focus on non-manufacturing processes. Today, process mining has become one of the most powerful tools a company can use to evaluate and optimize its daily operations.  This blog post is a historical perspective of how it all began.

The Roots of Process Optimization

Efforts to optimize workflows began in the 19^th century with time and motion studies that aimed to standardize and optimize manufacturing processes. Over time, scholars and business leaders, each in their own way, sought to streamline business processes to avoid wasting time, money, and resources.

Such efforts led to other disciplines — Lean manufacturing, Six Sigma, Agile manufacturing, and others — each working from a different perspective, yet all focused on eliminating inefficient processes.

With IBM's invention of the hard disk in the 1950s, the first database management systems began coming to market, followed eventually by data warehousing and data mining. Gradually, companies came to realize that their IT systems were producing data that could be useful in improving the company's operation.

For instance, database management systems, enterprise software from companies like SAP and Oracle, call center ACDs, and many other applications produce log files (aka transaction or event files) that capture a wealth of information. While those often-massive files didn't figure into process mining until much later, vendors brought BI tools to market that used stored data to highlight business performance. Those tools gave birth to KPI dashboards and increased management focus on the processes used to achieve various business objectives.

Process mining, as we know it now, is still not a thing.

The Genesis of Process Mining (and Process Discovery)

Business process management (BPM) became a formally recognized approach to process enhancement when the Association of Business Process Management Professionals convened its first meeting in 2003.

However, we can thank Wil Van der Aalst, a Dutch computer scientist and author of more than 400 books, articles, and publications, for his ground-breaking work as the originator of process mining. As process mining gained recognition, the IEEE published its Process Mining Manifesto in 2011, seeking "to promote the research, development, education, implementation, evolution, and understanding of process mining."

The Era of Process Mining and Process Discovery

Now, as we enter the second decade of the 21^st century, process mining has become a required tool for every company that intends to survive and prospers in the digital transformation that has touched consumers and businesses around the globe. Wil Van der Aalst points out that process mining is useful in three areas.

Discovering how processes actually work by using event logs that store historical information.  (Or observing work and documenting the processes.) Then, conformance, which looks at how well the reality of things recorded in the event log reflects what happens in the real world. Finally, enhancement looks at how management can improve and enhance business processes to eliminate inefficiencies.

While the initial start involved looking at event logs, now the focus is shifting to understanding digital worker's work as it happens through mass observation of human interactions with digital systems – at a vast scale, high precision, and without systems integration.  This is the next evolution of process mining – the AI-driven process discovery such as Skan process discovery platform.

Skan's cognitive process discovery and management platform represents the latest evolution in process mining that uses artificial intelligence and computer vision to observe work, and then to decipher human process patterns that you can integrate with event logs — all without any backend integration.