If there are two phrases we are hearing much too often today, they are “digital transformation” and “automation.”
This drastic change was overdue, of course, but the pandemic catapulted it, eliminating any and all excuses for procrastination. If a business has to survive this uncertainty, it has to make digital transformation its key focus, the core of which is automation.
Here’s where the problem comes – all businesses know what to do. But how should they start?
Say hello to process mining.
And why is Forrester driving this change?
Process mining is a set of approaches that discovers real processes through the use of event logs, monitors them, and work towards improving them. It is an analytical approach through which knowledge is extracted from the organization’s systems.
Through this process, organizations can detect errors and bottlenecks based on the facts instead of relying on conjectures. Overall, it covers the following:
Reports and research suggest that by 2023, the market size of process mining will inflate to $1,421.7 million!
Data mining has been a fad phrase for quite a while now. So, it is easy to confuse process mining and data mining. In fact, many organizations fail to understand the difference. This is mainly because they are both a part of business intelligence and have quite a few similarities.
The differences, however, are significant.
Process mining is definitely a technique in business intelligence. It is closely related to business process management (BPM) in that it combines data mining with BPM. So, existing data is taken, visualized, and improved.
Process mining combines analysis, control, and improvement of processes.
Once we hear that process mining and BPM are related, this question is bound to arise. You may be confused by the answer but please allow us to explain.
In short, process mining is not a component of BPM software. But why? Well, that’s because the applications of each are quite different. BPM has been around since the 1970s while process mining is relatively new. BPM speaks about designing and managing operational procedures while the latter works towards optimization and redesigning of operations through existing data.
Also read: Business Process Management – The What, Why, and How
There are 3 types of process mining and we shall explore them in detail now:
In this type of process mining, event logs come to the forefront. There’s no prior information, however. A process model is established based on the event logs and algorithms.
Here, real processes and predefined processes are compared to identify similarities and differences. This helps find out deviations and fix them accordingly.
The data of real processes are considered to improve process models. Enhancement process mining aims to improve existing processes by identifying bottlenecks, inefficiencies, or areas for optimization. It analyzes event logs to uncover opportunities for process improvement.
Extension process mining involves enriching existing process models with additional information, such as performance metrics, resource data, or cost information. It helps in gaining a more comprehensive understanding of the process and its associated factors.
There are 2 major steps –
These two steps are further broken down into multiple stages.
Santiago Aguirre did a wonderful job of explaining the methodology of process mining in detail.
When we already have BPM, which is doing an excellent job helping organizations transform digitally, do we really need process mining? How does it benefit organizations? The answer will both surprise and please you.
Some of the most significant benefits of process mining are as follows:
Let’s explore a few use cases to understand the importance of process mining:
How do you apply process mining to industries? We have a few examples to help you understand:
One of the most crucial aspects of manufacturing is timely delivery. When a business has multiple factories, delivery cannot rely on one aspect. Many differences come into the picture. Process mining will help understand the process in every single region, right down to costs, KPIs of the people involved, and the duration. This fact-based analysis will automatically help optimize the process.
Service companies offer higher efficiency and lower costs to their clients, through operational excellence. Process mining finds process inefficiencies and helps optimize the operations.
Retail business operations are very extensive. They involve logistics, order management, forecasting, supply chain, customer service, etc. Process mining provides visibility to the entire life cycle and the processes involved in each step. It helps unearth bottlenecks through facts so that they are taken care of immediately.
Rules and regulations are the driving force in the financial sector. Event data helps with process visualization in each step. If there is non-conformance to any rule, process mining will help find that out along with deviations to the said rule.
Process mining may be relatively new but it is here to stay and optimize business processes. The insights this approach provides through analytics are crucial for growth and efficiency.
Want to know how you can apply process mining to your business? Get in touch with us or request a demo now!
Process mining is a technique that analyzes data from event logs to understand and improve business processes. It’s important because it helps organizations uncover inefficiencies, bottlenecks, and areas for improvement in their processes, leading to better operational efficiency and cost reduction.
Process mining offers several benefits for businesses. It provides insights into how processes are actually executed, helps identify bottlenecks or compliance issues, enables data-driven decision-making, improves process performance, and enhances overall operational efficiency.
Yes, process mining can be applied across industries. It is useful wherever there are event logs or data capturing the execution of business processes. Industries such as manufacturing, healthcare, finance, telecommunications, and retail can all benefit from process mining.
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I wouldn’t say process mining is new. Frederick Winslow Taylor and Frank and Lillian Gilbreth were pioneering this field way back in the early 1900s. Their tools were pencil, papers and stopwatches and their name for it was different, “time studies” and “scientific management”. But their methodology was very sound, rigorous and methodical. Their productivity increases were astounding. Henry Ford built his company and Jim Casey built UPS into behemoths by obsessively studying their processes and continually improving them. UPS’s term for it was “constructive dissatisfaction”. Deming and the Japanese almost made it a religion in the 50s and 60s. The Deming Cycle of Plan, Do, Study, Act became Kaizen. So its been around a long time. What is new are computer tools to help with this, at least ones that are generally available. But good article overall.