What is process mining?
Process mining performs by extracting event log data from a company's database or business management tools like CRM software, ERP systems, and electronic health records, or EHR software. These event logs help a business look closely at its "as-is" processes.
With a process mining tool, enterprises create ideal work models or graphs by examining the end-to-end trail for discrepancies and bottlenecks. These specialized algorithms identify the root causes of deviations from the norm, provide resources to fix them, and build a more robust and efficient process.
Types of process mining
Depending on the use case or the industry a company is in, one of the three different types of process mining will be utilized.
- Automated business process discovery: During discovery, process mining software traces the entire business workflow from end to end and provides an ideal blueprint to its users. As the name suggests, automated business process discovery (ABPD) automates this process discovery stage by incorporating artificial intelligence (AI), computer vision, and computational logic.
- Conformance checking business processes: This method systematically evaluates the current process flow and compares event logs with the reference or target models. Conformance check assists in discovering and correcting any inefficiencies that might occur in the execution of the ongoing processes by measuring their performance against the ideal performance requirements.
- Model analysis and enhancement: The objective behind model analysis and enhancement is to determine how to optimize the target process model to its optimum potential. The enhanced model minimizes the risk of existing bottlenecks, making the overall process more efficient with automated workflow.
Benefits of using process mining
Process mining solutions enable professionals to visualize the practical layout of a process and identify real-time problems instead of working with solutions based on assumptions. Process mining software brings the best of both worlds with the perfect combination of business process management (BPM) techniques and data mining algorithms.
- Process intelligence: With the help of process mining software, organization stakeholders better understand processes, evaluate suggested fixes, and make smarter unified decisions based on data-backed insights.
- Increase transparency: Process mining serves as a guide to internal processes, allowing full disclosure about how functions carry out in a business workflow. This increased transparency makes it possible for decision makers to comprehend the reality of their operations and find opportunities to improve and fix them.
- Lower costs: Organizations can reduce operating costs drastically by identifying opportunities to automate tasks and fixing problem areas beforehand. Process mining lets businesses analyze event log data and minimizes wasted time and resources.
Impacts of using process mining
The potential of process mining is not limited to any specific industry or business model. Any enterprise that follows processes can use this technology to reach maximum efficiency. And as long as they meet the fundamental requirement of event logs, there is no limit to how much they can explore processes in depth.
- Sales: Since complex sales processes depend on external factors, process mining allows business leaders to envision discrepancies and resolve them to meet fixed targets. Companies can increase conversion rates, enhance strategies, and improve sales performance across the board.
- IT: IT professionals benefit from sorting out disorganized engineering processes by gaining clarity and managing the complexity of ERP migrations and implementation. They can also monitor systems in real time to ensure everything is running smoothly.
- Customer Experience: With process mining technology, businesses can identify which customer processes are taking longer to resolve and pinpoint their root causes while providing solutions to fix the delay.
Basic elements of process mining
The goal of acquiring process mining software is to incorporate it with the existing software in a company's IT infrastructure. Minimally, process mining solutions should include the following:
- Event log monitoring: They should be able to read, analyze, and monitor event logs from information systems and databases to understand the current business process.
- Process insights: They should be able to deliver data-driven insights into which methods are not meeting the set standards, down to individual employees deviating from the business model.
- Integrations: Without the ability to integrate with other systems, process mining would not be possible. Process mining must minimally integrate with business systems to analyze their logs, but it should also integrate with other systems to help improve processes.
Process mining best practices
To make process mining work, follow these best practices:
- Think broadly: Business leaders often choose specific places to optimize using process mining techniques, like processes when employees might lack the required skill set or departments have alarming deficiencies. However, when an organization gains transparency into its business processes, it’s profitable to apply those insights across the board.
- Look to the future: Once you understand your business systems and KPIs, take a moment to identify the end goal that you wish to achieve with process mining. Each process mining tool helps with conformance checks, process discovery, model analysis, and enhancement. However, there might be a better-suited tool for you that meets distinct specifications appealing to your bottom line.
- Find the right solution: Business owners must oversee their enterprise functions, what it takes to process them, and if they are well equipped to meet those requirements. Once one has a clear vision of which functions to optimize, choose a process mining tool that best fits one’s business goals.
Process mining vs. task mining
Process mining and task mining are complementary elements that share the same purpose: to help organizations get the most out of their operations on multiple levels and achieve better results. However, there is a slight difference in how each of these techniques works.
While process mining revolves around discovering, analyzing, and optimizing end-to-end processes, task mining focuses on smaller tasks that define said processes. These include sub processes that employees perform manually, like uploading files or copying data.
Hence, task mining describes how companies run their tasks, and process mining identifies user interactions to determine the accuracy of those tasks.
Matthew Miller
Matthew Miller is a research and data enthusiast with a knack for understanding and conveying market trends effectively. With experience in journalism, education, and AI, he has honed his skills in various industries. Currently a Senior Research Analyst at G2, Matthew focuses on AI, automation, and analytics, providing insights and conducting research for vendors in these fields. He has a strong background in linguistics, having worked as a Hebrew and Yiddish Translator and an Expert Hebrew Linguist, and has co-founded VAICE, a non-profit voice tech consultancy firm.
