Process mining, task mining and task capture can streamline automation process discovery in robotic process automation (RPA).
Have you ever built automation and later discovered that you automated the wrong process? Most of the automation developers would answer yes to this question. Automation success doesn’t start with development – it starts with discovery. If I gave you 1,000 hours of digital activity from your team, could you tell me where 500 hours are wasted? If that question made you pause, you’re not alone.
We’re constantly investing in automation tools, bots and digital platforms, but have we taken a step back to understand how much time is silently slipping through the cracks? Think of all the time spent toggling between systems, re-entering the same data, waiting for approvals or searching for information buried in emails. Now, multiply that by every employee, every day and every month.
That’s where process mining, task mining and task capture step in — not as buzzwords, but as compasses that shine a light on exactly where those 500 hours are being lost.
What are process mining, task mining and task capture?
Process mining maps the actual end-to-end journey of your workflows, so you can spot bottlenecks and inefficiencies you didn’t even know existed. Task mining zooms into user-level interactions, uncovering repetitive, manual steps your team is stuck on. Task capture provides immediate documentation of tasks, revealing inconsistencies and hidden rework across departments.
So, the next time someone asks you where half your team’s time is going, don’t guess but show them with data, insight and confidence. Organizations often focus on volume, not value, in the race to automate. What if we flipped that mindset? Instead of asking “what can we automate?” let’s as “what should we automate?”
Process mining helps you discover how workflows happen, not how people think they flow. Task Mining uncovers hidden inefficiencies at the keystroke level. Task capture documents reality, not assumptions, helping us scale automation with accuracy. Great automation doesn’t start with a bot – it begins with clarity and clarity comes from visibility into your processes.
Many organizations jump into automation excitedly, only to realize they digitized inefficiency. That’s like putting a rocket engine on the wrong train track. Without process intelligence, we automate assumptions, not reality.
How process mining streamlines process discovery
Process mining helps you discover how workflows happen, not how people think they flow. Task Mining uncovers hidden inefficiencies at the keystroke level. Task capture documents reality, not assumptions, helping us scale automation with accuracy. Great automation doesn’t start with a bot – it begins with clarity and clarity comes from visibility into your processes.
Many organizations jump into automation excitedly, only to realize they digitized inefficiency. That’s like putting a rocket engine on the wrong train track. Without process intelligence, we automate assumptions, not reality.
Process mining helps us see real-time bottlenecks, spot workarounds that bypass standard operating procedures (SOPs) and discover hidden variations and compliance risks. Process mining enables businesses to streamline their operations by analyzing the processes, identifying bottlenecks and depicting the scope of automation.
Business analysts or product managers manually capture a process, list each step along with the screenshots, write a summary for each step and then glance at the steps to understand the process or have an overview of steps that need to be automated. The decision to select whether the captured process is an automation candidate is often based on an intuitive understanding or analysis of the process overview. This tedious and manual process is usually time-consuming to capture the process during the discovery phase.
Using process mining, system-generated AI insights are provided after user actions are captured for a process. Machine learning algorithms will be used to assess the complexity of the process and steps in the process and provide various metrics that could help decide whether a process can be moved to an automation pipeline. This process doesn’t need manual intervention as business users within the teams will have the .exe file for process mining installed on their systems and capture every step of the process. It doesn’t interfere with the business process and captures the steps in the background. The recorded steps can even be exported as a process definition document, saving much more time than manually designing one.
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How task mining enhances process discovery
Task mining captures user behavior at the desktop level – i.e. what happens versus what’s documented. You get the truth of the task from multiple clicks to fragmented systems. It’s like placing a magnifying glass on your digital workforce. When there’s little information about a process, and each step needs to be thoroughly analyzed, task mining is used.
It collects employee data from user desktops, including keystroke and clicks, and analyzes the data. This way, the process discovery journey will be expedited using AI-powered insights. As a first step, AI-powered task mining collects data from the user’s machine at a granular level, identifies different steps in the process and presents a process graph containing detailed metrics.
How Merck uncovered inefficiencies with task mining
Unassisted task mining helps mine unknown tasks by recording steps on the user’s desktop and discovering repetitive tasks suited for automation and process improvement. Assisted task mining captures and improves tasks that are known with variations.
Unassisted task mining enables the recording of the actions on the user’s desktop, analyzing them and exporting the results, helping to identify automation opportunities that have repetitive actions by users, understand frequent paths and variances and document the details of the process candidate. This benefits employees at all levels, including RPA leaders, business analysts, employees and developers. Users can be invited to capture the process during project setup and record actions only on applications that they wish to record and deny recording on applications that users may deem concerning.
The goal of recording the data is to understand the inefficiencies in the task in a better way and to optimize the task/process. Provide unique and relevant titles and descriptions while creating a project. Adding users who are experts in completing the process manually is recommended so that the correct data is captured without errors. It is crucial to figure out what actions can be recorded and what actions shouldn’t be recorded.
How task capture improves process discovery
Task capture is like a blueprint generator. Imagine this – your subject matter experts are doing a process instead of shadowing them, taking screenshots and writing a document with many screenshots and pages.
You say: “Go ahead. Do it once. Task Capture will do the rest.” In that one run, it records every click, every field entry, every screen and it auto-generates a process design document, with annotated steps and screenshots.
What used to take hours, including interviews, calls and back-and-forth edits, is now done in minutes. Better yet, it’s accurate. No missed steps and no misinterpretation. Just the real process, exactly as it happened. Task capture is all about manual, intentional documentation. A user performs a task once and the tool captures it – click-by-click, screen-by-screen – and turns it into a structured, exportable document.
Using task capture, employees can quickly document how they perform repetitive tasks without manually writing SOPs. Business users can record their tasks and share them with automation teams, helping identify repetitive tasks that can be automated. Once you identify potential automation candidates, use task capture to provide expertise about the particular task and help you speed up the automation process.
In conclusion, process mining, task mining and task capture are emerging product integrations that redefine business processes by identifying improvements and automation opportunities.
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