Process Mining and Task Mining:
Are they better together?
What is process mining?
Process mining describes a combination of technologies and methods belonging to a broader business process management category. It uses actual business data (extracted from IT system event logs) to visualise the process. The primary purpose of process mining is to analyse how digital processes happen, how they deviate from the ideal model, when or what problems occur, what optimisation measures need to be taken, and finally, start to improve the process.
Process mining allows you to optimise processes with the click of a button instead of conducting employee interviews and analysing results. It allows you to view your actual process objectively and truthfully. Designing the entire process from start to finish makes it easy to identify problems and locate optimisation potential. The best tools combine these fingerprints with powerful analysis techniques to clearly present the process and its variants and even suggest opportunities for optimisation and automation.
The benefits of process mining are not just limited to highlighting automation opportunities but can also directly improve employee experience and customer satisfaction through better resource allocation.
What is task mining?
Task mining takes a closer look at the tasks in process mining end-to-end processes simplification and automation. It typically consists of a series of steps that employees perform manually. The working principle of task mining software is to record user operations and personal keystrokes in order to understand operations, improve operations, and even perform tasks automatically.
Some everyday business tasks include copying and entering data, uploading or downloading files, and navigating business systems. For example, when processing an invoice (an end-to-end process), one task is to extract information from the invoice. This requires manually opening emails, invoice attachments, copying the total amount, etc.
Although process mining is a powerful tool for an in-depth understanding of business-level processes, task mining runs at the desktop level to discover and analyse tasks performed by users in business-level processes. This is achieved by installing a local agent on each desktop that records user interactions (key presses, mouse clicks, etc.) and combines it with context awareness to understand how tasks are run and how they exist between teams Variety.
Should you use them together?
Task mining and process mining both have a place in the organisation, and both focus on optimising and automating your processes. Although both helped achieve high-level results, such as increased automation and efficiency, they serve different use cases, so it cannot be said that one is better than the other. Process mining is usually used for O2C, P2P, audit and compliance verification, process optimisation and management, etc. Task mining is used to improve the user experience and continue to discover automation opportunities.
Process Mining shows you what the company is doing by extracting event logs and displaying data maps. In contrast, Task Mining shows you what users are doing by recording keystrokes and extracting logs at the data level. Depending on your RPA (robotic process automation plan, you can implement one or the other to achieve your specific goals. However, it is a reasonable strategy to adopt task mining and process mining simultaneously, and its goal is to improve in all aspects continuously. Used in combination, they can help companies discover, analyse, and automate processes that will provide the most meaningful results and help you identify imperfect process execution.
Combining process mining and task mining tools such as Celonis, Minit, or UiPath Process Gold with intelligent automation tools such as RPA, Chatbots, and digital intelligence effectively combines discovery, analysis, and execution capabilities. This increasingly enables organisations to move seamlessly from identifying opportunities for improvement to delivering improvements and efficiencies in real-time.
Visit here to learn more about RPA.