Process Intelligence vs Process Mining

Quiz

This chapter provides a comparative study of two very important concepts of business process automation namely, process mining and process intelligence. Although these two concepts seem similar at first glance, both are different from each other and the most significant difference between them lies in their scope and core functionality.

Process Mining is a concept of discovering, analyzing, and visualizing business processes as they are actually executed within a business organization. In contrast, Process Intelligence is an advanced approach for optimizing processes and making them more intelligent.

Let's discuss the other important differences between process mining and process intelligence.

Difference between Process Mining and Process Intelligence

The following table highlights all the major differences between process mining and process intelligence −

Parameter	Process Mining	Process Intelligence
Definition	Process mining can be defined as a data-driven technique used to understand how processes are really executed.	Process intelligence is defined as a holistic approach that combines contextual information with advanced analytics and automation to provide actionable insights and optimize processes.
Objective	Process mining is a concept meant for visualizing processes, identifying issues, and inefficiencies in existing operations.	Process intelligence is an advanced approach that not only analyzes the processes but also optimizes and makes them intelligent by predicting issues and managing them in advance.
Primary Function	Process mining provides a clear screenshot of actual processes by analyzing event log data.	Process intelligence optimizes processes and enhances decision making.
Outcome	Process mining provides performance metrics and workflow maps that highlight the actual state of processes within the organization.	Process intelligence forecasts potential challenges in processes and suggests areas for improvement.
Tools Used	Process mining uses data extraction tools to extract data from event logs and visualization tools to generate process maps and highlight inefficiencies.	Process intelligence uses artificial intelligence, machine learning, predictive analytics, and contextual data to optimize processes and enhance decision-making.
Timeframe Analyzed	Process mining analyzes only historical data from event logs to understand past and current operations and process executions.	Process intelligence provides combined analysis of historical data, current process monitoring, and predictive insights for future challenges.
Primary Focus	Process mining is primarily focused on identifying and correcting existing bottlenecks and inefficiencies in workflows.	Process intelligence focuses on continuous optimization of processes and predicting future challenges.
Core Activities	Process mining involves activities like process discovery, visualization, and process enhancement.	The key activities involved in process intelligence are real-time monitoring, predictive analysis, and proactive optimization of processes.
Frequency of Use	Process mining is used depending on the needs to audit and specific process enhancement.	Process intelligence is used continuously and embedded in daily business processes.

Conclusion

In this chapter, we highlighted all the key differences between Process Intelligence and Process Mining. The most fundamental difference is that process mining provides a view into the current execution of a specific process within a business organization and is used depending on the needs to audit processes. Process Intelligence, in contrast, provides a comprehensive solution to identify issues and optimize the processes and is used continuously and embedded in daily business operations.

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