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Task Mining vs. Process Mining – How do they differ

January 23, 2023


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Process mining and task mining have been crucial in driving organizations’ digital transformation initiatives to enhance their operations and customer experiences for quite some time now.  By providing a detailed understanding of processes and identifying areas for optimization, these automation solutions enable businesses to make data-driven decisions. As more organizations adopt these technologies, the data mining market will likely set a growth standard for other automated solutions to follow in the industry.

A recent report from Grand View Research suggests that the global process mining software market will exceed USD 7.95 billion by 2028.

Additionally, a report by Gartner says that the majority of companies (by 2024) that may have implemented automation technologies will most likely integrate artificial intelligence (AI), encompassing machine learning (ML), natural language processing (NLP) algorithms, process mining and task mining, and intelligent document processing functionalities. Specifically, around 65% of such organizations will introduce these advanced AI capabilities into their systems.

So, approximately one-fourth (25%) of the world’s businesses will incorporate process mining into their operations to advance toward autonomous business processes.

The rising adoption of task mining and process mining

The increasing adoption of digital transformation and the need to analyze and comprehend business processes has become a significant driving force for the growth of task mining and process mining technologies. Furthermore, the emergence of technologies such as AI and RPA further fuels this trend. In addition, the COVID-19 pandemic has also played a vital role in accelerating the demand for digital and process transformation. Moreover, the integration of process analytics and ERP applications, as well as the surge in the deployment of task-level automation, are contributing significantly to the expansion of the task and process mining market.

Understanding task mining vs. process mining

Task mining and process mining are two different, but complementary technologies used to analyze business processes.

Task mining focuses on identifying and understanding the tasks and activities that comprise a process. It provides a detailed view of the steps involved in a process, including how they are performed, and the tools and applications used. Task mining identifies the areas for automation, improving user experience, and enhancing productivity. It is the practice of recording and analyzing desktop-level event data, including employees’ screen recordings, keystrokes, mouse clicks, and data entries. The captured data is then processed using advanced NLP and optical character recognition (OCR) tools to derive valuable insights and improve business processes.

However, process mining is a data-driven methodology that involves the analysis of event logs to gain insights into how business processes perform. It helps organizations to identify inefficiencies, bottlenecks, and variations in workflows, providing a fact-based approach to process improvement. Thus, process mining provides an overview of the entire process, while task mining focuses on specific tasks. However, when used together, both technologies gain a deeper understanding of business processes and optimize them for better efficiency and productivity.

Six main differences between task mining and process mining

Category Process Mining Task Mining
Focus Entire business processes Specific tasks
Scope Broad analysis of end-to-end processes Narrow analysis of specific tasks
Data Sources Event logs, ERP systems, databases, etc. User interactions, mouse clicks, keyboard strokes, etc.
Granularity High-level process maps with many steps Detailed task flows with specific user interactions
Analysis Identifies bottlenecks, inefficiencies, and compliance issues in end-to-end processes Identifies automation opportunities and suggests improvements in specific tasks
Use Cases Operational improvement, risk management, compliance Process automation, user productivity
Implementation Data preparation and cleansing, process discovery and mapping, analysis, and visualization Software installation and configuration, user data collection, analysis, and visualization

Benefits of task mining and process mining

Task Mining and Process Mining are powerful techniques that provide companies with valuable insights into their business processes. Here are the top five benefits of each solution:

Task Mining Process Mining
Identify inefficiencies Visualize processes
Streamline processes Identify bottlenecks
Improve employee productivity Improve process efficiency
Enhance customer experience Monitor compliance
Increase compliance Make data-driven decisions

Benefits of task mining

Identify inefficiencies: Task mining can help identify inefficiencies in the business process and identify areas where processes can be improved to increase efficiency by analyzing how employees perform their tasks.

Streamline processes: Task mining can help streamline processes by identifying bottlenecks and areas of redundancy, which allows organizations to optimize their operations and remove any unnecessary steps.

Improve employee productivity: By understanding how employees perform their tasks, organizations can identify areas where employees may be struggling and provide them with the necessary support to improve their productivity.

Enhance customer experience: Task mining can help organizations understand how customers interact with their products and services. This allows organizations to improve their offerings and provide a better customer experience.

Increase compliance: By finding out how employees perform their tasks, organizations can ensure that they follow established procedures and comply with regulatory requirements.

Benefits of process mining

Visualize processes: Process mining, by leveraging the process discovery approach, enables organizations to visualize their business processes, making it easier to identify inefficiencies and areas for improvement.

Identify bottlenecks: Process mining can help identify bottlenecks in the business process, allowing organizations to focus on optimizing those areas.

Improve process efficiency: By analyzing business processes, companies can detect areas where processes can be optimized to increase efficiency and reduce costs.

Monitor compliance: Process mining can help organizations monitor compliance with regulatory requirements and ensure that established procedures are followed accordingly.

Make data-driven decisions: By evaluating process data, organizations can make data-driven decisions to improve their business processes, leading to better business outcomes.

How to identify which technique is the best for your business?

To determine whether task or process mining is the best fit for your business, you should consider your specific needs and goals first. This is because task mining focuses on understanding the individual tasks that employees perform and identifying areas for improvement in terms of efficiency, accuracy, and compliance. As a result, it is well-suited for businesses with highly manual, repetitive tasks that can benefit from automation or optimization.

On the other hand, process mining is focused on analyzing the end-to-end processes that drive business outcomes. It can help identify bottlenecks, inefficiencies, and areas for optimization in complex, cross-functional business processes. It is helpful for businesses that are looking to optimize and streamline their operations, improve customer satisfaction, or reduce costs.

Use cases of task mining and process mining

Key task mining use cases include:

Data entry: Task mining automates data entry tasks such as typing in information from physical documents, emails, or other sources into a digital system. By recording and analyzing the steps involved in the data entry process, task mining can identify opportunities for automation, such as using optical character recognition (OCR) or machine learning algorithms to extract and input data automatically.

Invoicing: Task mining can process invoicing by identifying and analyzing the steps in creating and sending invoices. By identifying repetitive tasks such as data entry or formatting, task mining can help to streamline the invoicing process and reduce errors.

Reporting: Task mining automates the reporting process by identifying and analyzing the steps in generating reports. Therefore, by automating recurring tasks such as data collection, formatting, and analysis, task mining can help to speed up the reporting process and improve accuracy.

Reconciliation: Task mining reconciles the process by identifying and analyzing the steps involved in comparing and matching data from different sources. By automating cyclic and tiresome tasks such as data entry and matching, task mining can help to speed up the reconciliation process and reduce errors.

Customer service: Task mining improves customer service by identifying and analyzing the steps involved in responding to customer inquiries or resolving issues. By systematizing repetitive tasks such as data entry or searching for information, task mining can help customer service agents to emphasize more complex or high-value tasks, improving overall efficiency and customer satisfaction.

Process mining purposes

Auditing and Compliance: Process mining analyzes and audits business processes for compliance with regulations, industry standards, and internal policies. By analyzing event logs, process mining can help identify potential compliance violations and prevent them from happening.

Order Management: Process mining can analyze the order management process, from order entry to fulfillment, to identify inefficiencies, bottlenecks, and potential delays. This can help organizations optimize their order management process and improve customer satisfaction.

Purchase-to-Pay: Process mining examines the purchase-to-pay process, from procuring goods or services to payment. By identifying bottlenecks, inefficiencies, and errors in the process, process mining can help organizations streamline the process and reduce costs.

Order-to-Cash: Process mining can analyze the order-to-cash process, from order entry to cash receipt. Process mining can help organizations optimize their order-to-cash process, reduce order fulfillment times, and improve cash flow by identifying potential bottlenecks, inefficiencies, and delays.

Lead-to-Order: Process mining can explore the lead-to-order process, from initial customer contact to order entry. Process mining can help organizations optimize their lead-to-order process and improve customer satisfaction by identifying bottlenecks, inefficiencies, and potential delays.

Logistics: Process mining examines the logistics process, from order fulfillment to delivery. Process mining can help organizations optimize their logistics process and improve delivery times by identifying bottlenecks, inefficiencies, and potential delays.

How can AssistEdge Discover help enterprises?

AssistEdge Discover, a process and task mining platform by EdgeVerve, can help organizations automate their business processes by analyzing employee work patterns. The solution captures employee activity data from various sources, such as desktops, servers, and mobile devices, and uses machine learning algorithms to identify employees’ tasks, applications, and websites.

Following this, the data is then analyzed to identify patterns, inefficiencies, and opportunities for automation. By automating repetitive and time-consuming tasks, AssistEdge Discover helps organizations improve productivity, reduce errors, and free up time for employees to focus on more strategic tasks.

Key takeaways of using the AssistEdge Discover

One perfect example of how AssistEdge Discover  has improved productivity is demonstrated through a case study that highlights the solution’s positive impact on the performance of a significant US-based telecom company. By leveraging AssistEdge, the company was able to gain insights into employee workflow, identify inefficiencies, and optimize its workforce. This led to a 20% improvement in agent productivity, allowing them to handle more customer interactions and increase efficiency.

Download the case study to learn more about how AssistEdge Discover helped a US-based telecom company.

Final thoughts

To recap, task mining and process mining are two robust business process management solutions with distinct approaches and objectives. Task mining captures user interactions with software systems to identify patterns and inefficiencies in task performance. In contrast, process mining focuses on analyzing data from IT systems to gain insights into how business processes get executed.

Adopting task mining and process mining can provide countless benefits for companies looking to optimize their business processes. Task mining and process mining can help companies identify inefficiencies, streamline operations, and make better decisions. As a result, companies can achieve better business outcomes by adopting these techniques, giving them a competitive edge in today’s digital age. Hence, it is highly recommended that companies adopt such solutions as AssistEdge Discover to stay ahead in the market.

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