Process mining is changing the way enterprises operate and manage their processes. It tells the process ‘as-is’ and ensures that enterprises and process owners have complete knowledge of the working of their process. In their pursuit of process excellence, businesses can use process mining to truly know their process, evaluate it with the ideal process model, and optimize it when needed. Today, it is a game-changer in the business world but things were not the same just two decades back.
Let’s find out how process mining turned out to be a revolutionary idea in business process management and now digital transformation by tracing its steps in history.
It was back in the 19th century when a lot of researchers were working on standardizing and improving the business manufacturing processes. The aim was always to streamline the processes so that they could save time and effort, otherwise wasted in working a certain way. Since the 1850s, many were looking to interpret all the events in simple terms of the processes of change which lead to their creation. With process thinking, they sought to know the process and how it happened. A century later, in around the 1950s, IBM launched its database management system which gave birth to data warehousing, followed by data mining. This provided data of all types from the IT systems that could easily be used in improving the current operations.
In addition to data mining and warehousing, various other approaches in the same disciple started surfacing. These were Taylorism, Lean & Kanban, six sigma, agile, and many more. Around the same time when database management systems came to the fore, the evolution of digitized business started and mainframe, PC, ERP, BPM, and cloud followed. All of these processes had a different approach but their eyes were set on the same goal- eliminating the inefficiencies from business processes. Trying and testing different approaches, we came to the 1990s.
The need for process optimization made businesses follow the business process management approach and they were eagerly creating the process models using the traditional means.
It wasn’t long ago that businesses used to use the traditional approach of drawing a process model with their hand without any precise information to fill in it. Business analysts, process owners, and managers would sit together for hours trying to form the right process model on a whiteboard with post-it notes yet failing at it.
This would’ve been the case even today had a Dutch computer scientist at the Eindhoven University of Technology not come up with the pathbreaking idea. He has authored over 400 books, articles, and publications and is known for his work on process mining. He came up with the idea that instead of creating the process models by hand and wasting time and efforts, the data present in the information systems can be automatically used for creating models. He started working on this idea in the 1990s and realized that automated process discovery could actually be possible. He used the event data stored in systems and came up with process mining.
It remained to be an academic work and theoretical knowledge for some years until some businesses started applying this technique to gain complete and true knowledge of their processes.
Businesses started realizing that merging process mapping with data analysis could actually work wonders. It is an evolution and an advanced approach to process improvement. It uncovers and unleashes the true vision of the process, thus telling even those nuances that might go unnoticed.
Soon, it gained recognition when the Process Mining Manifesto was published by IEEE in 2011. It stated that “Process mining techniques are able to extract knowledge from event logs commonly available in today's information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains.”
According to Wil van der Aalst, the father of process mining, “Process mining bridges the gap between traditional model-based process analysis and data-centric analysis techniques such as machine learning and data mining.”
If you see the medical field, doctors use the technology of MRI (Magnetic Resource Imaging) to look through your body’s cells and gather the required information. This helps them create an image and visually diagnose your health. Process mining is similar.
It collects all the data from the minutest parts of your process activities like the event logs, time stamps, etc., and helps create a true image of your process. With a visual representation of your process in front of you, you can check the digital health of your process and diagnose the issues for a quick solution.
Process mining is a great approach that offers to bridge the gap between business process modeling and data mining. It helps in analyzing the time-stamped event logs in a process information system, analyze the data, and find the inefficiencies. A process mining software can be used to exploit the event data stored in your enterprise information system and find out bottlenecks, anticipate problems, gain insights, and provide meaningful insights into improving the process.
As technologies advanced and new benchmarks were achieved in the realm of emerging techs like Artificial Intelligence, Computer Vision, Machine Learning, Deep Neural Nets, etc., process mining evolved. It is no more about just identifying the inefficiencies of the process and providing insights for its improvement, it is more about conformance and enhancement.
You create a process model based on the event logs and take it as the ideal model. Next, you can compare the current event logs of the process with the ideal process to ensure conformance. Enhancement, on the other hand, works by helping you improve your existing process model so that you can improve productivity or even aim for a bigger transformation.
All three approaches together are now being used by enterprises to improve their business process and remove any inefficiencies. Now, it is even giving real-time inputs to the workers if they deviate from the ideal process by tracking each of their human-digital interaction with the system.
With complete knowledge of the process and process discovery, it is easier for enterprises to board the ship of digital transformation.
With time, it is certain that process mining is taking deep roots in the business world. Even Gartner has predicted that the process mining industry is set to grow triple of its current size or even bigger in the next couple of years. The next evolution of process mining is here and we can now see the process mining software requiring no specific integration into the system yet still providing highly precise information. Artificial Intelligence, computer vision, neural nets, predictive analytics, etc., are the flag-bearing technologies of this new evolved phase of process mining- a cognitive process discovery.