“Business Process Management” was all the rage when globalization made it important for organizations to scale and optimize procedures.
Every business faced the same issues – dealing with rapid growth, maintaining quality, and ensuring that employees use their time wisely. In order to do this, managers had to move away from their cubicles and into the workspace – they had to understand what people do, when they do it and how efficient existing procedures are.
Every ‘operational process’ or sequence of actions conducted by employees was recorded manually, put into a ‘process map’ and analyzed to identify improvements. This would have to be done continuously based on verbal feedback. It wasn’t completely efficient since important details would often be left out inadvertently.
However, when the digitalization era began, the concept of computerized process mining emerged. This eliminated the need for verbal feedback, minimizing the number of errors made and making business process management way easier than ever before.
Be that as it may, there is a huge difference between traditional process mining and the process mining techniques that are emerging now. The newest trend in the advancement of process mining is the one we are discussing in this article: AI-Enhanced Process Mining.
AI (Artificial Intelligence) in itself is a new concept that not many people understand. Nevertheless, many cogs of digital transformation are now being supported by AI. To resolve any queries that one may have regarding these concepts, let us understand the ideas individually first.
The Basics – Process Mining, AI, Business Process Management
Business Process Management
Minit, a leading vendor of process mining solutions, defines Business Process Management as “the operations level view of the processes being performed by the company. The BPM lifecycle generally includes the following stages: design, modeling, execution, monitoring, optimization, and reengineering”.
Process Mining, has previously been defined as “the utilization of specialized data mining algorithms to analyze processes, isolate trends and patterns, and highlight factors that can be modified, in the form of process maps, to improve business process understanding and management as a whole.”
AI, or Artificial Intelligence, is defined as “A branch of computer science dealing with the simulation of intelligent behavior in computers. The capability of a machine to imitate intelligent human behavior.” by Merriam Webster.
The umbrella concept that ties these together is Intelligent Process Automation. Process Automation aims at making workspaces smarter, and allow humans to be freed from tedious, repetitive and uncreative tasks.
Now that the basics have been established, we can answer the important questions –
What is AI-enhanced Process Mining?
With Artificial Intelligence and Machine Learning being integrated with most technology, Process Mining is not far behind.
AI-enhanced process mining facilitates smart, intuitive and fully automated business insight by mimicking human-like analysis and identifying weak and strong areas of business operations. It is also capable of correcting procedures, eliminating unnecessary tasks and recommending alterations.
AI and Machine Learning add some exceptional features to Process Mining. Some of these are –
Multi Event Logging
There is a huge amount of processes that are interlinked in a chain pattern. One event leads to another, giving way to the third and so on. Multi-event logging takes record of every single event that is part of this domino effect of processes.
Cross-Platform Data Mining
Since we have been examining enterprises of the digital age, it goes without saying that these businesses use an array of tools and solutions for its seamless operation. Establishing manual integration between these varied platforms and a process mining tool is extremely complex. AI-enhanced process mining can adapt to various platforms, interact with different formats of data and understand relationships between various departments.
Time-stamped process logs
Real-time tracking makes way for time-stamped logs. This feature can be extremely beneficial in identifying delays and bottlenecks by highlighting how much time certain processes take.
The fusion of AI with process mining has given birth to in-built process analytics. Process mining tools can forecast breakdowns, call for maintenance and even evaluate quality of work based on large data sets and collective process maps.
Clustering is a machine learning feature that focuses on finding groups of common characteristics from large data sets. This helps analysts identify similar/ connected processes based on the grouping performed by the process mining tool.
Other features of AI-enhanced Process Mining Tools include –
- Redundancy evaluation and risk control predictions
- Time management and quality control suggestions
- Progressive improvements through training
- Unified, easy-to-understand process maps
- Enhanced event logs with more actionable data
- Connected tasks and discovering automation avenues
So, now that we’ve talked about the new features that AI brings to the table, what does this shift mean for Business Process Management?
In an article entitled ‘Enhance Process Efficiency With AI-Enabled Process Mining’ , Protik Mukhopadhyay states that “AI capabilities have evolved to a level where it can enable process flexibility without compromising on regulatory or governance compliance requirements.”
Similarly, Celonis (a pioneer of AI-enhanced Process Mining) states “Because it combines human ingenuity with artificial intelligence, Process Mining is objective where traditional efficiency methods now feel outdated and inexact. More importantly, Process Mining is a system that continually improves itself via machine learning, working at a speed that matches the rest of your company’s tech stack.”
Alongside all the uncertainty surrounding digital transformation and automation, comes a wave of excellence and rapid progress. Traditional practices need to be updated and supported to keep up with the expansion of the corporate world and the increasing complexity of organizational operations.
All-in-all, AI-enhanced Process Mining promises to make BPM swift and problem free – enhanced accuracy, reduced human effort and more elaborate insights. It truly is capable of eliminating inter-departmental friction and several pain-points to redefine, redesign and restructure BPM.