They say if you want to know how messy your business is, never check the balance sheet! Watch how long it takes Steve from accounting to find the right spreadsheet tab. That’s the issue that task mining and process mining attempt to address. They eliminate the daily confusion of processes, allowing you to identify inefficiencies, automate more intelligently, and make decisions based on actual data rather than management’s opinions.
But while both sound similar, they operate at very different levels of visibility.
Task mining zooms into the microscope view of how employees perform tasks step by step, while process mining takes the aerial view of how entire business processes flow across systems. Let’s explore the difference between task mining and process mining, including how they differ, when to use which mining strategy, and their respective use cases.
Too often, businesses rely on assumptions about how work gets done. Task mining and process mining replace guesswork with real data. Let’s find out how:
To accomplish a single task, employees can use various tools such as CRM systems, spreadsheets, messaging applications, and their own tools.
Robotic process automation (RPA), workflow orchestration, and AI assistants are investments worth considering. However, automation projects often fail due to a lack of knowledge on how to automate effectively.
Industries like banking, insurance, and healthcare face growing scrutiny over how data is used and documented.
CIOs, COOs, and CFOs are under constant pressure to justify digital investments with hard ROI.
So, what’s the task mining definition? Task mining records and examines the actions that your employees carry out step-by-step on their desktops and applications during work. In task mining, you’re placing a microscope on the actual process of task execution at the individual level, i.e, clicks on a mouse, keystrokes, copy-pasting, using an application, switching between screens, and time spent in one application.
Task mining tools such as Paxray install desktop agents to record how employees interact with systems, including keystrokes, clicks, and application usage. It’s ideal for getting a fine-grained view of how work actually happens.
And as Forrester notes in its 2023 report Task and Process Mining for Business Value:
“Companies new to process intelligence often start with task mining to uncover shadow work, then use process mining to validate where those tasks fit into the bigger picture.”
Process mining uses data mining methods to identify, analyze, and optimize business processes. It’s the intersection of business process management (BPM) and data science, offering a data-driven and objective way to analyze and evaluate the real status of workflows in a company. This mining approach is more strategic, providing a holistic view of full processes by pulling data from core systems like SAP, Oracle, or Salesforce, which can be integrated.
These tools interact with the company’s software systems to obtain process information. This information helps you discover and improve business processes. The end-to-end process view provides a wealth of data for business process improvement and can be used to improve overall business performance.
Process mining extracts event logs from IT systems, such as records of when and how something happened (e.g., an invoice sent, an approval made). These logs are pieced together to map out the actual process flows.
The two approaches rely on very different data streams.
Task mining uses its own data recording of real daily operations without disrupting them. The sources are desktop-level, like lightweight agents, UI event logs, screen recordings or snapshots, clipboard and window-focus logs, and sometimes OCR output for data captured from legacy screens. These sources enable task mining to stitch activity across multiple apps, which would otherwise leave no central trace. Data is recorded completely independently of IT systems or browsers across the entire software landscape in a specific format and defined scope. This ensures uniform quality without dependence on third-party providers.
Process mining extracts recorded event data from existing IT system logs (“event logs”). It even uses data from transaction records, database tables, audit trails, message queues, BPM/workflow logs, and API call histories from core systems (ERP, CRM, order-management, billing). This means that there is a direct dependency on the quality and structure of the recorded data from a third party. In practice, it has been shown that this can lead to the failure of numerous process mining projects or result in unplanned expenses.
Task mining captures the fine-grained details between larger process steps. Using snapshots, recordings, or other capture techniques, task mining shows the individual steps users take when working at their workstations. This detailed view enables a deeper understanding of actual workflows and reveals inefficient practices or potential improvements.
Process mining provides a macro perspective on business processes. It records important steps in the process for which event logs are available. For example, process mining can document the flow in accounts payable: from the incoming invoice to verification and approval to payment to suppliers. However, it offers only limited insight into the details between these steps.
Task mining is ideal when you need to understand the actual workflow at the desk level. By demonstrating the specific steps individuals follow, including each mouse click, keystroke, and workaround, it becomes much easier to identify tasks that might be automated, reduce unnecessary efforts, enhance the user experience, and even pinpoint areas for improvement through additional training.
Process mining is ideal when you need big-picture oversight. It’s useful in compliance and audit preparedness since it uses system event logs and transaction data. Process mining provides teams with a picture of how processes actually operate within the enterprise, enabling them more easily to monitor performance.
Task mining is a newer concept, but is rapidly gaining ground and popularity. According to Deloitte (2021), Intelligent Automation with Task Mining, task mining:
Because it captures human activity, task mining discovers the “last mile” of work that process mining often misses. Research in Information Systems Frontiers (Baryannis et al., 2019) highlights improvements in forecasting, prioritizing automation, and shortening transformation cycles.
| Process Mining | Task Mining | |
| Data Sources | IT system logs | Desktop-level data |
| Granularity | Macro perspective | Fine-grained details |
| Use Cases | Big-picture oversight | Desk-level workflow understanding |
| ROI | Good, scalable enterprise ROI | Faster, higher early ROI |
| Deployment time | Longer complex deployment | Faster simpler deployment |
Process mining consistently shows good ROI. As per a Forrester Consulting study, process mining achieved payback in six months and achieved 383% ROI. Benefits contributing to higher ROI include:
Task mining deploys faster because it requires no complex integrations, little data preparation, and is easier to pilot.
Average deployment timeline:
In process mining, deployment takes longer due to complex system integrations, extensive data mapping, and the higher level of stakeholder involvement required.
Average deployment time
Task mining records user actions (in the form of clicks and keystrokes), whereas process mining records system actions as event logs to trace end-to-end workflows.
It depends on the specific requirements. Depending on the goal and intention, a combination of task mining and process mining may be useful.
Task mining achieves higher ROI and has lower deployment time, whereas process mining is better for long-term, enterprise-wide optimization.
Task mining explains the why behind inefficiencies, and process mining shows where they affect larger processes.
Task mining is best for automation discovery, UX, and training, whereas process mining is best for compliance, audit, and enterprise monitoring.
Here’s your decision matrix: a clear guide to choosing between task mining and process mining based on what you actually need.
| What do you need? | Best fit | Why? |
| Quick automation wins with minimal setup | Task mining | Record clicks, keystrokes, and actual workflows to complete automation at a rapid pace. Deployment: 2-8 weeks to pilots, 3-6 months scale. Deployment: 2–8 weeks for pilots, 3–6 months for scale. |
| End-to-end visibility across enterprise systems | Process mining | Analyzes ERP, CRM, and finance logs to map bottlenecks and ensure compliance. |
| ROI in weeks | Task mining | Delivers faster ROI within a a few weeks. |
| Human-in-the-loop process optimization | Task mining | Shows shadow work and manual steps invisible in system logs. |
| Scalable transformation across departments | Task mining | Faster to roll out and not tied to system log quality, making it easier to scale across teams. |
| Both speed and scale | Task and process mining | Task mining finds the details, process mining puts them in context for long-term transformation. |
Task mining is your fast track to ROI. And if you need a tool that’s purpose-built for speed, simplicity, and scalability, Paxray stands out. Paxray offers faster deployment, transparent data capture, and actionable insights without the heavy integration overhead of traditional process mining platforms. Schedule a demo to know more.
No integrations. No development. Live in 1 day.
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