Organizations are increasingly embracing digital transformation and need efficient methods of monitoring and analyzing their business processes, like process mining, RPA, ML or AI. While traditional, manual-based processing models can be effective, they are often cumbersome and omit valuable data. This article will explain what process mining is and how you can get the most out of it.
What is Process Mining?
Like Robotic Process Automation, process mining is similar to data mining and is used to analyze business processes. This software allows organizations to collect data from enterprise transactions and gives valuable insights into how business processes perform.
Improvement of processes is a major component of business management. However, stakeholders need to first identify the issues and decide if it is worth making improvements.
Process mining solutions analyze all data from the systems involved in a business process to create complete end-to-end processes models. It is a three-step process. Systems capture the activities of people and automation solutions within an organization. Process mining then converts these data into event logs. This solution provides powerful insight into the discovery and development of new processes models to stakeholders.
A Brief History
The concept of process mining was developed by Wil van der Aalst, a Dutch scientist who sought an alternative to manual processes modeling. He discovered that process models could be optimized using data from IT systems. This technique was an academic endeavor until 2011 when the Process Mining Manifesto got published by IEEE.
Process mining has gained importance with the emergence of powerful business process management tools like machine learning (ML), artificial intelligence (AI), and iBPMS. Similar solutions will be crucial in helping organizations meet growing data requirements as they pursue digital transformation.
Process Mining has many advantages:
The process mining technology can offer many benefits to organizations, including:
• Lower costs - Organizations can reduce operating costs by identifying inefficiencies and bottlenecks and automating tasks that are most likely to benefit from automation.
• More transparency - Process mining allows stakeholders to find the right data and generate actionable insights, allowing for greater transparency at both the process and organizational levels.
• Performance management - Automating key performance indicators collection. Monitoring processes can be done in real-time by stakeholders.
• Better customer experiences. Companies can quickly identify the root cause of problems and offer better customer service.
• Increased compliance. Auditing can be expensive and time-consuming. This technology allows for faster analysis of data and can help stakeholders identify compliance issues immediately.
Capabilities in Process Mining
Process mining provides three main capabilities: Automated Business Process Discovery, Enhancement, and Business Process Conformance Checking.
Automated Business Process Discovery
ABPD takes event logs and creates process models without additional information. These models are used by analysts to identify performance issues.
Enhancement
A process mining technique that can be used to improve an existing model by using data from event logs. A process model can be enhanced by including performance data.
Compliance Checking for Business Processes
Analysts can compare an existing process model with an event log from the same process model. For checking if real-time log data matches a process model, conformance checks can be useful.
Process Mining and iBPMS
Process mining is a complement to an iBPMS solution and supports key stages in the BPM lifecycle. It is helpful to examine the four phases of the typical BPM lifecycle to better understand the role that process mining is playing.
Discovery
Stakeholders seek out information about the process during the discovery phase. A process is traced from beginning to end using process mining, helping them to create a process map.
Redesign
Stakeholders identify improvement opportunities based on the information they have gathered during the discovery phase. Low-code iBPM solutions that offer process modeling capabilities allow organizations to design multiple iterations and choose the most efficient for implementation.
Implementation
Organizations must choose and identify KPIs, as well as process mining functionality, to track these metrics during the implementation process. iBPMS platforms have reporting and analytics features that make it simple to collect, interpret and share data across the organization. iBPMS platforms can also be used by organizations to automate and optimize their processes.
Monitoring
Data mining technology collects data in real-time during the monitoring phase. Stakeholders can quickly identify bottlenecks and other performance issues, so they can take corrective actions immediately.
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