Your Quality Management Data Template

The Activity Name describes a distinct action or milestone in the lifecycle of a quality event. Examples include 'Initial Assessment Completed', 'Investigation Initiated', or 'Corrective Action Implemented'. These activities represent the building blocks of the quality management process.

For process analysis, this attribute is essential for constructing the process map, which visually represents the sequence of activities and the flow of cases. It allows analysts to identify bottlenecks, discover common and rare process variants, and check for compliance against standard operating procedures. Understanding the sequence of activities is the first step toward process improvement.

This attribute defines the steps in the process, forming the nodes of the process map and enabling analysis of process flow and variations.

Usually derived from event logs, status change records, or task tables related to the main quality event object.

The Event Start Time is a timestamp that marks the beginning of each activity in the quality event's lifecycle. It provides the temporal context necessary for understanding the process flow and performance. This timestamp is critical for ordering events chronologically and for calculating durations.

In process mining, this timestamp is used to sort activities into the correct sequence for each case and to calculate key performance indicators like cycle times, waiting times, and processing times. Analyzing these timestamps helps identify delays between steps, measure resource efficiency, and monitor adherence to service level agreements. It is a cornerstone of any time-based process analysis.

This timestamp is essential for ordering events, calculating cycle times and waiting times, and discovering process bottlenecks.

Commonly found in event logs or transaction records alongside the activity name. It may be labeled as 'Creation Date', 'Event Date', or 'Timestamp'.

The Quality Event ID is a unique key that identifies a specific quality issue, such as a non-conformance, customer complaint, deviation, or audit finding. This identifier is crucial as it connects all the different steps, documents, and data points associated with the event throughout its entire lifecycle.

In process mining, this attribute is fundamental for reconstructing the end-to-end process flow for each quality event. By grouping all related activities under a single Quality Event ID, analysts can visualize the process map, calculate case durations, and analyze variations between different event paths. It enables a clear and accurate analysis of how quality issues are handled from start to finish.

This is the primary key for process mining, enabling the connection of all related events into a single process instance or case.

Typically found in the header or main table for quality notifications, events, or non-conformance records.

The Last Data Update attribute is a timestamp that records the most recent time the data was synchronized from the source system. It acts as a data freshness indicator, showing how current the information in the analysis is. This is particularly important for ongoing monitoring and near-real-time decision-making.

This attribute helps users understand the timeliness of the process mining dashboards and analyses. It ensures that stakeholders are aware of the data's currency when interpreting KPIs and process models, preventing decisions from being made on outdated information. It is a key piece of metadata for maintaining trust in the data.

Indicates the freshness of the data, ensuring users are aware of how up-to-date the process analysis and KPIs are.

This is typically metadata generated during the data extraction (ETL) process. It is usually not found within the source system's transactional tables.

The Source System attribute identifies the originating application or database where the quality management data was recorded. In complex IT landscapes, quality event data may come from multiple systems, for example, an ERP for material data and a dedicated Quality Management System for process data.

Identifying the source system is important for data governance, validation, and troubleshooting. It helps in understanding the context of the data and can be used to segment the analysis. For instance, an analyst might compare the quality processes managed in different systems or locations to identify best practices or inconsistencies.

Provides context about the data's origin, which is crucial for data validation, troubleshooting, and segmented analysis in multi-system environments.

This information might not be present in the source tables themselves but is often added during the data extraction, transformation, and loading (ETL) process.

The Event End Time is a timestamp marking the completion of an activity. Paired with the Event Start Time, it allows for the precise calculation of the processing time for individual tasks within the quality management process. For events that are considered instantaneous, the start and end times may be identical.

This attribute is crucial for performance analysis at the activity level. By calculating the duration of each task (End Time minus Start Time), analysts can identify which steps consume the most time and are prime candidates for optimization. It also enables a more accurate calculation of overall case cycle time and provides the data needed for resource workload and efficiency analysis.

Enables the calculation of activity processing times, which is essential for detailed performance analysis and identifying resource-intensive tasks.

Often found in the same event log or transaction record as the start time. In some systems, it may need to be inferred from the start time of the subsequent event.

The Quality Event Type categorizes the nature of the quality issue being addressed. Different types of events often follow distinct processes, have different levels of urgency, and are governed by different standard operating procedures.

By filtering and comparing processes based on this attribute, analysts can uncover significant variations. For instance, the process for handling a 'Customer Complaint' may be much more rigorous and time-sensitive than the process for an 'Internal Problem'. Understanding these differences is crucial for evaluating whether each process variant is operating efficiently and in compliance with its specific requirements.

Allows for the segmentation of analysis to compare and contrast how different types of quality issues are handled, revealing important process variations.

Found in the header data for the quality event, often as a 'Notification Type', 'Event Type', or 'Category' field.

The Resource attribute identifies the individual or system responsible for executing a task. This could be an investigator, a quality approver, or an automated system user. Tracking who performs each activity is fundamental to understanding workload distribution, team performance, and collaboration patterns.

Analyzing the process by resource helps uncover performance variations between individuals or teams, identify training needs, and optimize workload balancing. It can reveal overburdened resources who may be bottlenecks, or show handoff patterns between different people, which are often a source of process delays. This analysis is key for improving organizational efficiency.

This attribute is vital for resource-based analysis, including workload distribution, performance comparison, and identifying organizational bottlenecks.

Usually found in transaction or log tables, often labeled as 'User Name', 'Changed By', 'Owner', or 'Assigned To'.

The Responsible Department attribute indicates which organizational unit is accountable for a quality event or a particular step in the process. This could be 'Manufacturing', 'Quality Assurance', 'Research and Development', or 'Logistics'.

This attribute is essential for organizational analysis. It allows managers to see how work flows between different departments, measure the performance of each functional area, and identify cross-functional friction or delays. For example, analysis may reveal that handoffs between Manufacturing and Quality Assurance are a primary source of delay. Segmenting KPIs by department helps pinpoint areas for targeted process improvement initiatives.

Enables analysis of process performance by organizational unit, highlighting cross-functional delays and helping to assign accountability.

Typically located in the header data of the quality event record or derived from the user responsible for the activity.

The Root Cause Category is a classification of the fundamental reason for the quality issue, such as 'Human Error', 'Equipment Failure', 'Process Deficiency', or 'Supplier Issue'. This attribute is typically populated after an investigation and root cause analysis have been completed.

Analyzing the frequency of different root cause categories provides powerful insights for strategic improvement. If 'Process Deficiency' is a common root cause, it signals a need for process re-engineering. If 'Equipment Failure' is frequent, it may point to a need for better maintenance schedules. Process mining can correlate these categories with process behavior, for example, showing if events caused by 'Human Error' take longer to resolve.

This is crucial for strategic analysis, as it moves beyond process flow to the underlying reasons for failure, guiding targeted preventive actions.

Found in the investigation or root cause analysis section of the quality event record. May be a code or free text.

The Severity attribute categorizes quality events based on their business impact, risk, or urgency. This classification helps in prioritizing resources and attention towards the most critical issues. Severity levels are typically defined by the organization's quality policy.

This is a powerful attribute for filtering and segmentation in process mining. Analysts can compare the process flows for 'Critical' events versus 'Minor' events to ensure high-severity issues are being fast-tracked as intended. It can also reveal if 'Minor' issues are consuming a disproportionate amount of resources or if 'Critical' issues are getting stuck in the process. This helps in optimizing the process for risk-based management.

Enables risk-based process analysis, helping to prioritize investigations and verify that high-impact events are handled with appropriate urgency.

This is a standard field in the quality event header data, often labeled 'Severity Level' or 'Priority'.

The Affected Product attribute identifies the specific item, material, or product line impacted by the quality issue. This link between the process and the product is critical for root cause analysis and impact assessment.

Analyzing quality events by product allows businesses to spot trends, such as a particular product having an unusually high number of non-conformances. This can trigger deeper investigations into the product's design or manufacturing process. It also helps in prioritizing quality events based on the strategic importance or sales volume of the affected product, ensuring that critical issues are addressed first.

Links process data to product data, enabling analysis of quality issues by product line to identify trends and prioritize high-impact problems.

Found in the main record for the quality event, often as 'Material Number', 'Product ID', or 'Part Number'.

The Effectiveness Check Outcome records the result of the verification step that follows the implementation of corrective actions. The outcome is typically 'Effective' or 'Not Effective', indicating whether the action successfully resolved the root cause of the problem.

This attribute is critical for measuring the true success of the quality management process. A high rate of 'Not Effective' outcomes points to a systemic problem in the root cause analysis or action planning phases, resulting in rework and recurring issues. In process mining, this can be used to analyze rework loops. For example, cases with a 'Not Effective' outcome often loop back to the investigation or root cause analysis stage, significantly increasing cycle time and cost.

Directly measures the success of corrective actions and is essential for analyzing rework loops and the effectiveness of the root cause analysis process.

Found in the records related to corrective and preventive action (CAPA) verification or closure steps.

The Location attribute specifies the geographical or organizational site related to the quality event. This could be a manufacturing plant, a specific production line, a distribution center, or a business unit.

Analyzing process performance by location is a powerful way to benchmark and identify best practices. It can reveal if certain sites are more efficient at resolving quality issues or if specific locations are a source of recurring problems. This geographical or site-based analysis helps management allocate resources effectively and standardize high-performing processes across the organization.

Allows for comparative analysis between different sites or plants, helping to benchmark performance and identify location-specific issues or best practices.

This information is typically part of the main quality event record, often labeled as 'Plant', 'Site', or 'Business Unit'.

The Quality Event Status indicates the current state of a quality event case. This is a dynamic attribute that changes as the case progresses through its lifecycle. It provides a high-level snapshot of where an event stands at any given time.

In process mining, this attribute is useful for analyzing the current workload and backlog. By filtering for events with an 'Open' or 'In Progress' status, managers can monitor the volume of active cases. It also helps in conformance checking by comparing the actual status changes with the expected process flow. For example, an event should not be 'Closed' before 'Corrective Action' is implemented.

Provides a snapshot of the current state of a case, which is critical for monitoring backlogs, active workload, and checking process conformance.

This is a key field in the header record of the quality event and is updated as the event progresses.

The Target Resolution Date is a deadline set for the closure of a quality event. This date is often determined by regulatory requirements, customer service level agreements, or internal policies based on the event's severity.

This attribute is essential for performance monitoring and compliance analysis. By comparing the actual closure date with the target date, organizations can calculate an 'On-Time Resolution Rate' KPI. Process mining can identify which types of events or process steps are most likely to cause delays and breaches of these targets. This helps focus improvement efforts on meeting timeliness goals.

Enables performance measurement against timeliness targets, helping to calculate on-time resolution rates and identify causes for delays.

Usually found in the header or planning data of the quality event record.