The Technology Behind Process Mining
What is a process?
In the context of Process Mining, a process is a chain of events with a clear start and end point, made up of multiple process steps. Each step represents a specific action or event.
For example, imagine running a coffee shop: the process starts when a customer places an order and ends when they receive their cup of coffee. Everything in between—grinding the beans, brewing the espresso, steaming the milk, adding sugar or syrup—is a process step.
What is Process Mining?
Process Mining is a blend of technologies and methods within the larger field of process management. Its goal is to uncover how processes actually unfold: where they differ from the ideal, where bottlenecks appear, and what improvements can be made. The result is a clearer path to efficiency, quality, and customer satisfaction.
As long as the necessary data is captured in an accessible IT system (which is true for most digitalized processes today), Process Mining can be applied.
Today’s solutions go beyond simply mapping out a process. They allow you to:
Conduct in-depth analysis
Benchmark and compare processes
Continuously monitor performance
Trigger automated workflows
Collaborate on process improvements
How Does Process Mining Work?
Process Mining algorithms rely on event logs - structured records of activities stored in enterprise systems. These aren’t your typical IT log files but come from sources like SAP®, Salesforce, Microsoft Dynamics, Excel sheets, or even custom business applications.
From raw data to real processes
Once collected, the data is transformed into a visual process flow that shows exactly how your operations run in practice - not how you think they do. No assumptions, no guesswork - just a fact-based view of your processes.
From visualization to insights
With your process mapped, the real work begins: applying filters, running root cause analyses, drilling down into details, and uncovering what truly drives inefficiencies or bottlenecks.
AI-powered assistance
Modern tools even include AI support, guiding you toward valuable insights when you’re not sure where to start or what patterns to look for.
The Benefits of Process Mining
Process Mining delivers clear advantages over traditional process management and data analysis methods - and it also gives you a competitive edge in today’s digital-first market.
Fast
Forget lengthy interviews and endless workshops. With Process Mining, insights appear almost instantly - at the push of a button.
Objectivity
No opinions, no bias. Process Mining shows your processes exactly as they are, based on facts, not perceptions.
The Complete Picture
Most employees only see their own part of the process. Process Mining reveals the full journey from start to finish, including every step, handoff, and dependency - making it easier to spot problems and align on improvements.
Transparency into Change & Exceptions
Processes are rarely linear. With Process Mining, you see every variation: skipped steps, rework, deviations, and alternative paths. This visibility helps you decide whether to bring processes back to the model - or adopt better practices that emerge from real-world behavior.
Maximum Visibility in the Digital Age
When work happens behind screens, it’s hard to see where time is lost or bottlenecks occur. Process Mining makes the invisible visible - like shining a light on the “virtual stacks of paper” moving through your systems.
Fact-Based Decision Making
No more gut feelings or guesswork. You gain precise, data-backed insights into where to improve and what should take priority.
Continuous Optimization
Because results are fast and easy to obtain, you can quickly react to market changes, reassign priorities, and build a proactive, sustainable optimization strategy.
Ongoing Monitoring
Process Mining isn’t a one-time fix. You can continuously track KPIs, measure the impact of changes, and adapt your strategy as new challenges arise.
Who Can Use Process Mining?
Process Mining is a versatile technique applied across industries, functions, and user roles. Modern tools can handle millions of data points, meaning that - as long as the basic event log requirements are met - there is virtually no limit to the processes you can explore. Still, there are common use cases, user groups, and industries where Process Mining is already widely adopted.
Depending on the organization, Process Mining can be applied by process managers, process improvement teams, IT departments, and BI or data science teams.
Modern Process Mining platforms are designed with usability in mind. Advanced expertise can unlock deeper insights, but the tools enable even non-technical users to generate valuable outcomes. Typical user groups include end users, process analysts, BI and data analysts, data scientists, and administrators.
Today, Process Mining is driving transformation across industries such as manufacturing, services, government institutions, healthcare, Consumer goods, telecommunications, auditing & banking, financial services, and education & research.
What do you need for Process Mining?
Software
You need Process Mining software to start.
Data/Event Log
You need data to analyze. Usually, this is stored in your IT system and you shouldn’t have to worry about it. Process Mining uses data in a so-called event log. This means databases that store the following information: CaseID, Timestamp, Activity name.
Take a coffee shop as an example. A typical process captured in an event log might look like this:
Receive order → grind coffee beans → brew espresso → steam milk → prepare cup → serve drink → process payment.
CaseID
A case represents one complete journey through a process. In a coffee shop, each customer order is treated as a separate case and is assigned a unique Case ID so that all individual steps can be linked to it.
For example:
Customer A orders a cappuccino – that’s one case
Customer B orders a latte, an espresso, and an iced coffee – that’s also one case, but it contains more steps since three drinks need to be prepared instead of just one
Timestamp
A timestamp records when a process step occurs. It can mark the start, the end, or - if you capture both - the complete duration of an activity. Having both start and end timestamps provides the most accurate picture.
For example, in a coffee shop:
When you start steaming the milk, that’s the start timestamp for “Steam milk”
When you finish steaming and set the milk aside, that’s the end timestamp
If you only have the start time, you wouldn’t know how long the milk steaming actually took or whether there was a delay before moving to the next step, such as “Pour milk into cup”. Without an end timestamp, the system assumes the step lasted until the beginning of the next recorded activity.
Activity
An activity describes what was done at a specific step in your process. Activity names are usually short and precise, such as “Create PO” or “Send Invoice.”
In the coffee shop example, activity names could include: “grind beans,” “brew espresso,” “steam milk,” “prepare cup,” or “serve drink.”
You can also enrich your event log with additional information for deeper analysis. For instance, you might add the barista’s name to see who prepared each drink, or include the coffee shop location if you manage multiple branches. The more attributes you capture, the more detailed your analysis can become.
Just remember: Case ID, Timestamp, and Activity Name are mandatory. Everything else is optional—giving you the flexibility to explore your processes at the level of detail that suits your needs.
