Processes and subprocesses consist of many small steps. These are often performed by employees, and despite the very digitized world we live in, many of those tasks are still done manually. Different than process mining, task mining concentrates on these smaller process components, i.e. those tasks of the process that are performed by employees using desktop applications, such as transferring customer records from a spreadsheet to a web form.
Using task mining not only improves overall transparency but also ensures that automation potentials are correctly identified and bottlenecks, as well as poor handovers, are eliminated. Combining task mining with process mining allows businesses to understand end-to-end processes fully and analyze handovers, resource utilization and more.
How does Task Mining Software work?
Task mining requires user interaction data as input to gain a clear understanding of how the work at the task level is done and how overall business process improvements can be achieved. But what is user interaction data?
Insights for business analysis usually come from one of two main sources: business data and user interaction data, a.k.a. desktop data. The first, business data, is what we describe as event logs. These logs are the input for all process mining tools. The data contains information and timestamps of when, for instance, an invoice has been created, sent and also paid. The other, often overlooked source of information, is user interaction data. This type of data focuses on the steps that are performed within a single process task. Examples of these steps include filling out a form, checking whether inserted data entries focused on amounts are correct, or consulting a checklist, for example in Microsoft Excel®.
Clearly, by only focusing on the business data, crucial information may be overlooked. This does not only have negative effects on productivity and efficiency, but can also hinder automation opportunities, such as those provided by RPA (Robotic Process Automation) solutions. How task mining works is that it collects and analyzes the user interaction data of your employees in a secure and privacy-aware way, to understand how work is actually done in your organization. This way, you do not have to rely on how you think work within each task is done, but you can use data to support your understanding. Here is how task mining technology works:
- Collect data: User interaction data is collected and ingested into Apromore.
- Gain a basic overview: This data is then displayed in Apromore to instantly provide a visual overview in the form of a process map of the routines followed within a given process task: the steps performed within, their duration, resource productivity and utilization, and more.
- Identify bottlenecks: Apromore’s user-friendly process analysis capabilities make it easy to identify bottlenecks, ping-pong behavior, and rework loops using the task’s routines as a starting point. This is the ideal base to analyze process tasks and keep an eye on key performance indicators.
- Optimize: Insights gained from the analysis of task routines can then be used to optimize the task within an end-to-end process. For example, you can discover a BPMN model out of these routines and use that to simulate different what-if scenarios, in order to assess the benefits of different process improvement interventions.
Differences between Task Mining and Process Mining
Both process mining and task mining are valuable capabilities to understand your business processes. Data is extracted from different sources and their focus differs. By complementing process mining solutions with task mining capabilities, a comprehensive picture of your organization is painted and your improvement efforts are based on all relevant process data.
Check out the different scope of task mining to understand the value it can bring to process mining initiatives:
|Process Mining||Task Mining|
|Overall scope||Full end-to-end processes||Individual tasks and how they are done|
|Source of data||Event logs generated by enterprise systems,
such as SAP®, Salesforce®, or ServiceNow®
|User interaction data from tasks that are performed
by desktop applications, such as MS Outlook® or Excel®
|Focus||Overall process optimization||Optimization of individual tasks|
The Benefits of Task Mining
Task mining enables organizations to track KPIs of individual, often overlooked tasks. By analyzing user interaction data, businesses can track task productivity and make data-informed process improvement decisions while ensuring compliance is increased. With the power and insights of task mining, organizations can also spot RPA automation opportunities easier than ever. Manual, repetitive and error-prone tasks are identified with ease, building an ideal foundation for automation.
Combined, process mining and task mining solutions set up your business for success! Both approaches have their own space and distinct capabilities, as seen above, but it is important to highlight that task mining and process mining should be seen and used as complementary techniques. Learn more about the benefits of combining the two approaches here.
Use Cases for Task Mining
While process mining focuses on the optimization of overall, especially end-to-end business processes, task mining enables businesses to dig even deeper. By first identifying and then analyzing user interactions data (a.k.a. desktop data), task mining offers new ways to improve processes. It creates a more in-depth view of how work is done and, hence, allows organizations to significantly improve their efficiency. In doing that, both customer experience and employee satisfaction can be raised.
Task mining also opens up vast opportunities to kick-start automation initiatives by discovering routine tasks. Using these insights, businesses can focus automation efforts where they can have the biggest impact on business metrics, and free up their human resources from tedious work, such as data entry, which can be done by RPA.
On top of that, businesses can use a combined process mining and task mining approach to unify process variants by identifying the most productive users. The most common use cases for task mining are:
- Improve process and task efficiency
- Increase customer and employee satisfaction
- Discover automation potential
- Unify process variants