What Can Task Mining Do For You?

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14th November 2022
7 Minute Read

In most organizations processes are made up of many small steps and despite digitization, they are still conducted manually by employees. Task mining focuses on these smaller process components, often on desktop applications where, for example, customer records are manually transferred from one application to another.


What Is Task Mining?


Task mining is still an evolving technology that enables organizations to track desktop-level activities and interactions. The tracking is achieved by installing plug-ins on each desktop, where all keystrokes and clicks are recorded and aggregated. 

Optical character recognition (OCR), Natural Language Processing (NPL), and machine-learning algorithms also all play a part in recording the activities.

The consolidated insight data is used to examine how end-users manage operations, as well as identify tasks that can be automated and highlight the most frequent errors for correction.

The insights from the data demonstrate how processes are executed individually, as well as variations that may exist across similar teams. Issues surrounding data privacy and related issues are addressed at this stage to reassure all parties.

The interpretation of the resulting data is then formulated to streamline automation processes and ultimately enhance the company’s operations.


Task Mining Software


Task mining software typically employs Optical Character Recognition (OCR), Natural Language Processing (NPL), and Machine Learning (ML) algorithms to collect and understand the actions employees take on their desktops.

  • OCR technology is used to detect desktop interactions during the task mining recording process, and this is then converted into contextual information related to the user’s various tasks. In its contextual form, it is much easier to interpret as research data.
  • NLP is a subset of artificial intelligence (AI). It enables software to process and understand human language so that it can be converted into a more research-friendly context. NLP in task mining is a particularly useful tool because it can analyze and convert large volumes of text data, such as social media comments, and online reviews.
  • ML is also a subset of artificial intelligence (AI). ML helps process systems to analyze and improve their efficiency through experience, without any programming intervention. ML focuses mainly on programs that access data, which it can use to learn and improve.

In all three technologies the aim is to find patterns in the data that improve business outcomes the most, so these can be used to optimize processes and replicate these at scale.


How does task mining work?

  1. Planning

To ensure the greatest success with task mining it is vital to plan, by understanding the full scope and the parties to be involved. All stakeholders should be encouraged to focus on the task of interest only.

Similarly, only employee actions that are related to the business processes of interest should be recorded. Employees should also be asked to concentrate on one task, from start to finish, at a time. The noise of extraneous data will confuse the result and slow task definition.


  1. Recording

Task mining plug-ins are installed on all relevant employee desktops. Data such as mouse clicks, scrolls, screenshots, and timestamps will all be recorded. Before recording the user’s privacy needs to be addressed.

Task mining consultants make it a priority to remove personally identifiable information from any data that is collected. OCR technology is employed to understand the context of the task under scrutiny.

NLP aids task mining tools to interpret the context of tasks better, which enables the grouping of similar activities. This helps tools understand individual actions used in performing a specific task.


  1. Activity groups are matched with business tasks

Employee activities are then matched with specific business tasks. So, the record of completing the employee onboarding form is matched with its associated task of employee onboarding form filling. The linking of these two elements ensures the accurate assessment of performance metrics against the recording.


  1. Use performance metrics to evaluate the performance

In the final analysis, recorded data is evaluated using KPI measures. Organizations subsequently have an accurate measure of the performance of their tasks. Organizations can then create an action plan, based on the results, which will improve the performance metrics. Actions can include:

  • Identifying why the performance of some tasks is inefficient
  • Highlighting common errors and showing employees how to avoid them
  • Identifying automation opportunities


What differences are there between task mining and process mining?


Task mining can be seen as complementary to process mining, and they both aim for improved process efficiency, however, there are differences.

 In task mining, the aim is to evaluate how an organization undertakes different process steps by monitoring desktop activity. The process highlights the interaction between employees and the desktop, from which data can be analyzed for improvement.

Process mining concentrates more on the organization’s performance metrics and the order of process steps to gain insight into how processes are handled. Process mining operates through log files, through which the steps to perform a process can be identified.

 This data can be related to KPIs to highlight bottlenecks, process improvements, and the identification of automation opportunities.


What are the benefits of task mining?


The tracking of KPIs in overlooked tasks is enabled

Task mining can identify individual, overlooked tasks, and track their KPIs. From the aggregated data task productivity can be analyzed and improvements formulated. This leads to improved process effectiveness and better compliance.


Easily spot RPA automation opportunities

Task mining highlights RPA automation opportunities by discovering manual, repetitive, and error-prone tasks, which are ideal for automation.


Combine task and process mining to ensure comprehensive process management

Combine task and process mining strengths to create a comprehensive snapshot of your processes. Covered from every angle there are no more process gaps or hidden efficiencies. Other benefits of combined mining include:


Full Transparency

Combined, task and process mining complete any gaps between task analysis and an end-to-end process perspective.


Productivity Improvements

Task and process mining highlights hidden tasks and detects poor handovers, overutilized and underutilized resources, whose processes can be improved.


Increased Compliance

With a total overview of processes, employee activity is transparent, and any compliance issues are highlighted.


Accelerated Automation via RPA

Combining process and task mining catalyzes automation by highlighting repetitive, manual, and error-prone tasks.


In Conclusion


Task mining focuses on smaller process components within organizations, where desktop applications are tracked using plug-ins. The resulting data is then formulated to streamline automation processes and ultimately enhance the company’s operations.

When combined with process mining the two technologies are complimentary, offering a comprehensive process audit.

Considering its effectiveness, the take-up of task mining is still sluggish, often being described as an emerging technology. This is most likely down to lack of awareness rather than any ominous factor.

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