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How can task mining boost employee productivity and process optimization?

September 13, 2022 - Team EdgeVerve


The onset of the pandemic forced organizations to shift to remote working, thus transforming the dynamics of employees’ productivity monitoring techniques. Hence, companies had to reorganize priorities, rethink the way employees desire to engage, and embrace hybrid working with some sections of the staff likely to never return to usual office settings.

How can organizations enhance employee productivity in today’s remote work environment while continuing to drive efficiencies in business processes? This is where task mining, a form of Process Discovery, comes in.

Task mining and its requirement

Task mining allows the business to capture a company’s resources’ actions as they perform them, so the steps can be analyzed and provide you with loads of data to design the business process. It captures employees’ screen recordings, mouse clicks, keystrokes, and data records –desktop-level event data. It applies NLP and optical character recognition (OCR) tools to infer the data and generate actionable and profound insights.

These understandings can, in turn, help detect incompetence, improve service, and improve the employee experience. Thus, data mining tasks use AI/ML patterns to identify and contextualize the captured data to produce process maps involving last-mile variations and provide process and workforce-related insights.

Most companies lack the resources to commence their automation journey; therefore, they need sources to evaluate the process’s present status and their inclination toward automation. Process and task mining can give that very insight. Additionally, firms’ post-pandemic efforts to scale automation can get slowed down due to inefficient processes. But then, here is the task mining solution to build data from a single task that offers information to identify the holdups of their business processes.

Hence, task mining is an efficient solution to these modern problems as the granular data task mining compiles from users and facilitates businesses to know their processes and how employees work as they move into a new working style.

Benefits of task mining

Productivity: Task mining encapsulates and scrutinizes the way people interact with machines through records and snapshots, thus helping companies distinguish and have a deeper understanding of employees’ productivity user-data such as clicks, data entry, and keystrokes. The data is then transformed into user and task insights to oversee employee productivity and, consequently, to guide automation efforts. So, task mining basically enhances user-data visibility by mitigating the roadblocks in process execution.

Find automation prospects: Task mining utilizes performance, productivity, and frequency insights to identify significant automation opportunities and helps automate standard processes and inefficient, repetitive tasks.

Task mining discovers automation prospects by assembling employees’ desktop data that includes logs of user actions (mouse clicks, keystrokes, etc.) and screenshots. Following this, it operates an ML model to evaluate this data and recommend a list of processes with high-level automation potential.

It enables the clients to record some particular users’ actions, examine them and then put down the outcomes in dashboards to:

Ensure privacy for users: One of the most significant benefits of task mining is that it guarantees the utmost privacy for users. As mature products assure absolute authority over the data capture process and the apprehended business data. As a result, the processes can determine the data to be captured and the ones that can be exempted apart from the data that should be distilled and visualized. Thus, this total control over the data capture process gives businesses a clear idea of the data that can be transformed into actionable insights.

Reduce process gaps: Task mining develops tactics to diminish the most vital process gaps by focusing on the root causes. It provides businesses with a way to identify bottlenecks within their processes and scrutinizes the smallest of the gaps in a business process by identifying the task that checks the smooth progress of a network. Hence, this step assists the involved companies in finding out the systems that are decreasing the efficiency of a process, thus exploring the bottlenecks involved.

Discovery, compliance, and performance: It combines process mining (business data) and task mining (user interaction data) when conducting business process analysis to provide automated insights, like:

Performance analysis: Task mining, a complementary solution to process mining, has substantial benefits as it allows companies to discover the inadequacies of manual human labor outside of their transactional systems and to evaluate and optimize their employees’ productivity.

Thus, the ability to connect the fragmented dots between the user task data, system logs, and business data allow the companies to lower the business process friction, enhance customer service, and accelerate digital transformation by augmenting the employees’ productivity and minimizing the manual labor burden, thus reducing the time consumption of a task. This will subsequently lead to a reduction in the operational expenses of an organization.

Provides alerts on process violation: The assembled data from the selected users using the task mining automation unlocks the breaches in the actual functional process if any. These processes include sequential task steps to be implemented, time of events, and whether any step is getting repeated or missed.

Task mining – A must-have solution in the future

Task mining plays a significant role in formulating business processes for optimized automation; still, several companies have not yet incorporated this handy solution. Barely 28% of shared service organizations (SSOs) have capitalized on this technology, says Intelligent Automation 2022 Benchmarking Survey.

Task mining can aid firms in realizing how they handle tasks by accumulating and evaluating user interactions rather than business metrics and log files for scrutinizing processes. To sum up, it helps deliver a complete view of processes that enhance business productivity by connecting individuals, data, and processes and mining user interactions.

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