Task mining: Key features and business use cases

A typical business process comprises myriad tasks broken into small components that are mostly executed manually. For automation to take over entirely, businesses need to identify the granular nuances in small process components and sub-tasks. Process mining proves incompetent in identifying empirical variations existing within each process. This is where task mining can genuinely make a difference.

When a combination of process mining and task mining capabilities are used, businesses can fully understand the end-to-end process, analyze handovers and resource utilization, and identify automation potentials.

What is task mining, and how does it work?

Task mining tools leverage AI capabilities like Machine Learning, Optical Character Recognition, and Natural Language Processing to understand and evaluate employees’ actions when interacting with computers or software. It identifies business outcomes patterns, allowing owners to optimize and replicate those actions at scale.

Task mining solutions help businesses to understand user interactions with software systems, analyze how tasks are executed, and identify ways to make them better.

There are specific steps that sum up the primary function of task mining.

Recording user activities: Task mining records user activities to understand employees’ core responsibilities. Installed on user systems, task mining tools work silently in the background, monitoring every single action like clicks, scrolls, time stamps, and screenshots.

Recognizing context: Task mining leverages OCR technology while recording user activities to understand the task’s context. The tools collect words, numbers, and additional text from the recordings and the screenshots captured during workflows.

Grouping similar tasks: With the help of NLP capability, task mining can better understand the context of tasks and group similar activities together. This allows its tools to capture particular actions employees implement while performing a specific task.

Matching user activity groups: The step after grouping involves matching user activities with specific business tasks. This step assesses performance metrics with the recording.

Evaluating performance: Lastly, the tools consider records against business data and KPIs. This allows owners to see how employees perform each task and how well they perform those tasks. Evaluation of each task execution can improve the performance metrics of each process.

Slack found that companies that have embraced AI are 90% more likely to report increased productivity levels than those that have not.

Task mining: Features and benefits

A typical task mining solution includes the following features:

Efficient task mining software solutions yield many benefits for organizations scaling automation growth across end-to-end processes. A few such benefits are mentioned below:

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Five use cases of task mining

Discovering automation opportunities: According to Global Market Review¹, “37% of respondents said increasing process efficiency was the biggest driver for intelligent automation in their organization.” In order to achieve that, enterprises needed data to discover automation opportunities in shared services. The current applications and use cases of Task mining are lined up perfectly to match the exact requirement. The real-time user data collected reflects how much time each employee spends on software and compares that to other users. This information benchmarks their productivity using specific software and further discovers automation opportunities in existing workflows.

Improve task efficiency: The same report showed that nearly 27% of companies listed said increasing workforce productivity is another driver for intelligent automation. And workforce productivity can be directly linked with task efficiencies. Enterprises should be able to track employees’ process efficiency as they enter a new operating model. Task mining provides data about process efficiency in real-time so owners can consider transitioning into automation to address any gaps during seamless task execution.

Removing redundant actions: Task mining helps businesses identify which activities consume the most employee time. Specific workflows are redundant and recurring but are integral to the process. However, the same tasks can be time-consuming and monotonous. Task mining track those applications to identify the total execution time and compare them against the ones that add value. Task mining software solutions not only help businesses remove redundant actions; it also assists the latter in rationalizing application implementation.

Improve user and customer experience: Task mining is adept at analyzing tasks and identifying system bottlenecks or other inefficiencies. That empowers the end user to improve the software or process, perform automated actions based on pre-defined process KPIs and improve overall process performance.

Task mining thus has long-term business value. It should not be considered a tool that businesses can use only to understand their business processes. Instead, these tools should be utilized for continuous process transformation, workforce productivity, and ensuring data privacy for employees and users. When used alongside process mining, both can work together in perfect sync to drive optimal benefits for the company. Task mining and Process mining are equally vital in helping organizations scale automation growth and achieve end-to-end process transformation.