Organizations are constructed out of processes, and their performance is heavily influenced by the performance of these processes. Efficient and effective processes can lead to increased productivity, reduced costs, and improved customer satisfaction. On the other hand, poorly designed or executed processes can result in delays, waste, and frustrated customers. To assess and improve performance, organizations often adopt process improvement methodologies using process modeling and process mining.
Process modeling and process mining are two distinct yet complementary practices in the field of business process management. However, many people mistakenly believe that they are separate and unrelated and in some extreme cases see process mining as a replacement for process modeling. Process modeling involves creating a visual representation of a process to understand its flow and identify areas for improvement. Process mining, on the other hand, uses data from the process to discover actual process behavior, deviations, and inefficiencies. Both approaches can enhance process understanding and drive improvement but combining them results in a more complete and accurate view of the process. In this post, I shortly explain process modeling and mining and bring a few examples of how they can support and/or impact each other.
Process Modeling
Process modeling is one of the long-standing concepts in process management that helps create graphical representations of work/business processes in order to understand and analyze them. The goal of process modeling is to provide a clear and comprehensive understanding of the process flow, the different activities and tasks involved, the actors or resources involved, and the information and data that flow through the process.
Process modeling can be used for a variety of purposes such as business optimization, design and redesign of processes, automation, and documentation. In addition, it supports incremental business needs like training and onboarding of new employees, business process standardization, and alignment with compliance requirements. By creating a graphical representation of a process, it can be easier to understand, communicate, and analyze the process, and identify areas for improvement and optimization.
Process Mining
Process mining is a technique for discovering, monitoring, and enabling data-driven improvement of real-life processes by extracting knowledge from event logs recorded by the IT systems which support process execution. The goal of process mining is to analyze the “digital footprints” that the process execution leaves within IT systems, and automatically derive graphical representations of the process flows, that display all the different ways in which the process was actually executed. This analytical view can then be used as a basis to create or update process models, and to drive process improvement initiatives. Process mining is therefore an important technique in process transformation initiatives as it can provide organizations with the information they need to understand and optimize their processes and achieve better results, making the organizations more efficient, effective, and compliant.
Process mining can be used for a variety of purposes such as (1) discovery of actual process flows and performance, which can be used to validate the process model and identify areas for improvement, (2) analyzing process performance metrics, such as durations, process flows, and resource utilization, to identify areas for improvement, (3) monitoring compliance with laws, regulations, and industry standards, and (4) assessing experience of customers and employees with the way processes are running among other use cases of process mining.
Process Modeling and Mining, two complementary members of the process management family
Modeling and mining are both needed for successful process transformation because they provide complementary perspectives on the process. Process modeling is essential for creating a clear and comprehensive representation of the desired process flow, which can be used as a reference for process mining to effectively guide analysis and investigations. Process mining, on the other hand, provides insights into the actual process flows and performance, which can be used to measure the conformance of the process reality to the desired model, analyze the deviations and identify areas for improvement.
There are various ways that process modeling and mining can complement each other. A Few examples of how process modeling supports mining are:
A Few examples of how process mining supports modeling are:
Conformance checking in SAP Signavio Process Intelligence using a reference process modeled in SAP Signavio Process Manager
Together, process modeling and process mining can provide a more complete and accurate picture of the business process, which can be used to improve process efficiency and effectiveness. Without process modeling, it would be difficult to have a clear understanding of the desired process flow, and without process mining, it would be difficult to understand how the process is actually being executed and identify areas for improvement. Together, they provide a comprehensive approach to process transformation. Read more about the relation between process modeling and process mining here, and understand the role they play in an end-to-end process improvement methodology.
Summary
Process modeling and process mining are not mutually exclusive but rather complement each other. They work together to gain a deeper understanding and analysis of business processes. Process modeling offers a clear and detailed view of the intended process flow, which can be verified by process mining by analyzing actual process flows (e.g., via conformance checking). On the other hand, process mining provides valuable insights into the actual process flows and performance, which can be used to validate the process model and identify areas for improvement. By combining both techniques, a more comprehensive and accurate understanding of the business process can be obtained, leading to more efficient and effective process improvements.
Process modeling and process mining are two distinct yet complementary practices in the field of business process management. However, many people mistakenly believe that they are separate and unrelated and in some extreme cases see process mining as a replacement for process modeling. Process modeling involves creating a visual representation of a process to understand its flow and identify areas for improvement. Process mining, on the other hand, uses data from the process to discover actual process behavior, deviations, and inefficiencies. Both approaches can enhance process understanding and drive improvement but combining them results in a more complete and accurate view of the process. In this post, I shortly explain process modeling and mining and bring a few examples of how they can support and/or impact each other.
Process Modeling
Process modeling is one of the long-standing concepts in process management that helps create graphical representations of work/business processes in order to understand and analyze them. The goal of process modeling is to provide a clear and comprehensive understanding of the process flow, the different activities and tasks involved, the actors or resources involved, and the information and data that flow through the process.
Process modeling can be used for a variety of purposes such as business optimization, design and redesign of processes, automation, and documentation. In addition, it supports incremental business needs like training and onboarding of new employees, business process standardization, and alignment with compliance requirements. By creating a graphical representation of a process, it can be easier to understand, communicate, and analyze the process, and identify areas for improvement and optimization.
Process Mining
Process mining is a technique for discovering, monitoring, and enabling data-driven improvement of real-life processes by extracting knowledge from event logs recorded by the IT systems which support process execution. The goal of process mining is to analyze the “digital footprints” that the process execution leaves within IT systems, and automatically derive graphical representations of the process flows, that display all the different ways in which the process was actually executed. This analytical view can then be used as a basis to create or update process models, and to drive process improvement initiatives. Process mining is therefore an important technique in process transformation initiatives as it can provide organizations with the information they need to understand and optimize their processes and achieve better results, making the organizations more efficient, effective, and compliant.
Process mining can be used for a variety of purposes such as (1) discovery of actual process flows and performance, which can be used to validate the process model and identify areas for improvement, (2) analyzing process performance metrics, such as durations, process flows, and resource utilization, to identify areas for improvement, (3) monitoring compliance with laws, regulations, and industry standards, and (4) assessing experience of customers and employees with the way processes are running among other use cases of process mining.
Process Modeling and Mining, two complementary members of the process management family
Modeling and mining are both needed for successful process transformation because they provide complementary perspectives on the process. Process modeling is essential for creating a clear and comprehensive representation of the desired process flow, which can be used as a reference for process mining to effectively guide analysis and investigations. Process mining, on the other hand, provides insights into the actual process flows and performance, which can be used to measure the conformance of the process reality to the desired model, analyze the deviations and identify areas for improvement.
There are various ways that process modeling and mining can complement each other. A Few examples of how process modeling supports mining are:
- Process modeling can provide a clear and comprehensive representation and documentation of the desired process flow, which can be used as a reference for process mining to ensure that the discovered process flows are accurate and complete, and guide analysis and investigations to measure the most relevant metrics.
- Process modeling can be used to identify potential areas of improvement in the process, which can then be analyzed using process mining to confirm or disprove the need for improvement.
- Process modeling can be used to define the process boundaries and scope, which can help to focus the process mining efforts on the relevant parts of the process.
- Process modeling can provide a clear and consistent notation for describing the process, which can make it easier to perform a process mining analysis, and understand and communicate its results.
- Process modeling can be used to evaluate the impact of process improvements identified through process mining, by simulating the process before and after the change.
A Few examples of how process mining supports modeling are:
- Process mining can be used to discover the actual process flows from event logs, which can then be compared to the process model to identify discrepancies and areas for improvement.
- Process mining can be used to automatically generate an initial baseline of a process model, based on the event logs, to reduce effort for those processes that have to be modeled from scratch.
- Process mining can be used to detect and analyze process performance issues and process modeling can be used to redesign the process to address the issues.
- Process mining can be used to measure the conformance of the actual process to the model, to determine whether the process is being executed as intended, and what is the impact of the deviations.
- Process mining can be used to detect patterns and trends in the process, which can be used as input for process redesign and improvement efforts.
Conformance checking in SAP Signavio Process Intelligence using a reference process modeled in SAP Signavio Process Manager
Together, process modeling and process mining can provide a more complete and accurate picture of the business process, which can be used to improve process efficiency and effectiveness. Without process modeling, it would be difficult to have a clear understanding of the desired process flow, and without process mining, it would be difficult to understand how the process is actually being executed and identify areas for improvement. Together, they provide a comprehensive approach to process transformation. Read more about the relation between process modeling and process mining here, and understand the role they play in an end-to-end process improvement methodology.
Summary
Process modeling and process mining are not mutually exclusive but rather complement each other. They work together to gain a deeper understanding and analysis of business processes. Process modeling offers a clear and detailed view of the intended process flow, which can be verified by process mining by analyzing actual process flows (e.g., via conformance checking). On the other hand, process mining provides valuable insights into the actual process flows and performance, which can be used to validate the process model and identify areas for improvement. By combining both techniques, a more comprehensive and accurate understanding of the business process can be obtained, leading to more efficient and effective process improvements.
- SAP Managed Tags:
