Do you know how many steps it takes you to complete a simple task like adding data to a record? What about how long it takes to send a follow-up email?
For most of us, efficiency in our work is something we strive toward but not something we track. That’s where task mining and process mining can help. These tools enable you to see how work can be improved and where to optimize the larger process in which it’s involved. The more complex the process, the more the benefits add up.
In this blog, we’ll explore process mining vs. task mining including the definition of each term, including the definition of each term, the key differences between process mining and task mining, and when to use each approach as part of a process automation strategy.
Process mining uses system event logs to discover, monitor, and improve processes. It’s an objective way to visualize how business processes work that enables end-to-end process optimization, uncovers automation potential, and delivers continuous process improvement. This approach can be used in any industry for any process, and it’s often used in manufacturing, financial services, insurance, and life sciences for processes like order-to-cash (O2C) and procure-to-pay (P2P).
[ Get the Process Mining Guide for tips on starting your process discovery journey. ]
Task mining uses desktop data, or user interaction data, to measure efficiency and analyze how people get work done. It can be used during process discovery (a part of process mining) to provide further context about the work that happens outside of systems by evaluating data like mouse clicks, keystrokes, data entry, and time spent in applications. This approach can be applied to a wide range of industries and is particularly useful in instances where human workers do digital work. For example, in customer service, task mining can be used to track service agents' interactions with customers (like via email and chat) and identify opportunities to shorten response times.
Process mining and task mining share a common goal of optimization, but they approach it from different angles.
The granularity of task mining is helpful for providing insights about how specific work within a process is getting done. But it’s limited when it comes to providing recommendations for end-to-end process optimization. This is why it’s considered a part of the process discovery phase in process mining.
Since process mining is about discovering and optimizing an end-to-end process, it relies on data from systems like ERP and CRM software that can provide a complete picture of the process. Task mining relies on micro-level data about user actions to provide analysis for specific tasks within a process.
Because task mining relies only on user interaction data, it’s limited to providing insights about human work. Since process mining uses system data, it can pinpoint inefficiencies anywhere in a process, regardless of whether they result from human or computer work.
Task mining and process mining are both valuable tools for improving business processes, but there are specific situations where each is more appropriate. In general, use a task mining solution when you need to optimize specific tasks within a larger process, and use a process mining solution when you need to optimize an entire end-to-end process.
Task mining is ideal for analyzing and optimizing specific tasks within a larger process. For example, if you're looking to improve data entry, task mining software can help identify areas where employees may require additional support or where automation could be implemented to streamline the task. It can help improve employee experience, increase human efficiency, and reduce human error, and it’s especially useful for tasks that are repetitive, time-consuming, or require a high degree of accuracy.
Process mining is more suitable for analyzing and optimizing an entire end-to-end process. For example, if you're looking to improve the supply chain management process, process mining tools can identify bottlenecks and inefficiencies across all stages of the process, from procurement to delivery. It can help reduce waste, optimize resource allocation, and improve customer satisfaction, and it’s particularly useful for identifying improvement areas, analyzing the cause of inefficiencies, and monitoring process efficiency over time.
Want expert advice? Get the Process Mining Guide for tips on process optimization success.