Task Mining is a desktop-level technology that enables companies to analyze their teams’ tasks and discover opportunities for automation and improvement. In this post, we are going to see in detail how it works and how it is related to process mining.
Having greater control of processes and operations is a top priority for many organizations in different sectors. Companies today not only understand the need to implement intelligent automation models but also recognize the importance of understanding how tasks are handled by monitoring user interactions.
Task Mining is gaining prominence because it enables organizations to capture user interaction data so that they can analyze how their employees are doing their jobs and how they can do them even better.
According to Forrester, Task Mining provides insights into how a business and its processes actually work. Having originated in Process Mining, Task Mining has matured into a separate technology. However, these technologies’ insights are much more powerful when both are combined to provide an end-to-end picture.
What is Task Mining?
Task Mining is a technology that operates at the desktop level so that organizations can analyze the tasks performed by users involved in a business process.
To take advantage of this technology, it is necessary to install an application on the desktop of each user participating in the measurement. This software records user interactions, taking into account keystrokes and mouse clicks, among other actions, and combines them with context awareness to understand how users execute tasks and the variations that exist between computers.
Differences between Task Mining and Process Mining
In the words of John Wallace, head of business development at Inverbis, a distinction could in theory be made based simply on granularity. While Process Mining focuses on building processes up to level 3 (activity), Task Mining goes down to the task and step level (levels 4 and 5). In practice though, both types of solutions have specific functionalities that distinguish them from each other.
“I think there are fundamentally two types of functionalities that characterize Task Mining tools and that Process Mining tools do not have. On the one hand there is the ability to capture user interactions. Secondly, and given that the information generated in this way by users is much more random and less structured, it is necessary to have capabilities to contextualize, recognize, and clean these captures so that they can be useful.”
In turn, a Gartner report defines Task Mining as a complementary approach to Process Mining, since it infers useful information from low-level event data available in user interface logs or captured through the use of computer vision.
These explanations show that automation opportunities would be lost if only Process Mining were to be used. Task Mining provides complementary and valuable information where there is no data for Process Mining, although many of the automation opportunities Task Mining highlights are less complex than those captured by Process Mining.
“As this market evolves and becomes more mature, we cannot talk about solutions that perform Task Mining without having those user data capture and processing capabilities, although Process Mining tools can use this data (appropriately cleaned and contextualized) to represent processes at a higher level of granularity.”
Benefits of Task Mining
One of Task Mining’s main benefits is the ability to individually measure workers’ KPIs. By analyzing data on a user’s day-to-day activities, it is possible to monitor their productivity and make data-driven decisions to improve processes.
Another important benefit provided by Task Mining is the detection of automation opportunities within a company. For example, Task Mining can easily identify manual activities that are repetitive and error-prone, thus creating an ideal foundation for automation.
However there are many situations in which Task Mining is not really useful to identify automation opportunities. These are instances in which the activities that the users perform (which can also be manual) actually leave a trace in the systems that support them, making them ideal candidates for analysis using Process Mining tools. Here again we can see how both techniques can be complementary addressing specific aspects that can be combined to obtain a richer understanding. A clear example of this are initiatives where the objective is understanding end to end processes. In these projects, you can use Process Mining to give you the overall picture of the process and rely on Task Mining to fill in any gaps where there is no data on the activities performed by users.
How does Task Mining work and how to do it?
Task Mining is done through a few simple steps. First, Task Mining tools log user activities to understand how employees perform their tasks. Once installed on an employee’s device, the platform collects data, including timestamps and screenshots, on clicks, scrolls, and other actions.
In addition to capturing all the elements mentioned above, the Task Mining tool takes advantage of OCR technology to understand the task’s context. To do this, the software collects additional words, numbers, and other text from recordings and screenshots captured during user activity.
Additionally, the Task Mining platform uses natural language processing techniques to better understand the context of tasks and group similar activities together. This contextual information allows tools to understand particular actions to perform a specific task.
Finally, after grouping, the tool correlates the different tasks to specific steps within a business process. At this point you can complement the analysis with the wider view that Process Mining can supply, adding context and providing a richer perspective that can increase the number of improvement opportunities that can be identified.
Task Mining examples
Microsoft illustrates a clear example of using Task Mining in one of its official documents. The company implements this technology in a healthcare facility, which can use this tool to record patient check-in procedures. In this way, an analysis can be made of, among other topics, which activities take the longest, how variable the registration process is, and which variations and actions take the most time.
Likewise, among the most common use cases of Task Mining are improving the efficiency of processes and tasks, increasing customer and employee satisfaction, discovering opportunities for automation, and unifying process variants.
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