Your Quality Management Data Template

This attribute describes a single step or milestone in the quality event lifecycle, such as 'Issue Categorized And Prioritized' or 'Root Cause Analysis Performed'. Each activity represents a distinct action taken to move the quality event toward resolution.

Analyzing activities is the core of process mining. This attribute is used to build the process map, showing the flow of work. It allows for the identification of bottlenecks, deviations from the standard process, and rework loops, which are critical for process improvement.

It defines the steps of the process, which is necessary for visualizing the process flow, discovering bottlenecks, and analyzing deviations.

This information is typically derived from event logs, workflow status changes, or audit trails within ETQ Reliance modules.

The Event Timestamp marks the exact moment an activity was recorded in the system. Each activity in a quality event's lifecycle has its own timestamp, creating a chronological sequence of events.

This attribute is fundamental for all time-based analysis in process mining. It is used to calculate cycle times between activities, identify waiting times and bottlenecks, and measure the overall duration of a quality event. It also enables analysis of performance trends over time.

This attribute is essential for calculating durations, ordering events chronologically, and performing any time-based analysis, such as identifying bottlenecks.

This is typically found in audit trail tables or as a 'last modified' or 'status change' date field associated with each activity or workflow step in ETQ Reliance.

The Quality Event is the primary case identifier for the quality management process. It represents a single, distinct quality issue, such as a non-conformance, customer complaint, or deviation, as it moves through investigation and resolution.

In process mining analysis, this attribute is essential for reconstructing the end-to-end journey of each quality event. It allows analysts to visualize process maps, measure cycle times from start to finish, and analyze variants to understand how different events are handled. All activities and data points are grouped by this identifier to provide a complete view of the case.

This is the fundamental attribute for process mining, as it connects all related process steps into a single case, enabling end-to-end analysis of the quality resolution lifecycle.

This is the primary key in the main Quality Event or Non-conformance module within ETQ Reliance. Consult ETQ Reliance documentation for the specific table and field name.

This attribute identifies the individual or system user responsible for completing a task within the quality event lifecycle. It links process activities to the people or teams performing them.

Analyzing performance by user helps in understanding workload distribution, identifying training needs, and recognizing high-performing individuals or teams. It is also essential for compliance and audit purposes, providing a clear record of who performed each action.

This attribute allows for analysis of resource performance, workload balancing, and identification of training opportunities.

This information is typically stored in audit trail logs or transaction details, often linked to a user ID field in ETQ Reliance.

The Event End Time marks the completion of an activity. Paired with the Event Timestamp (Start Time), it defines the duration of a single process step. Not all systems explicitly record an end time for every event, in which case it may be derived from the start time of the subsequent event.

This attribute is crucial for calculating the processing time of individual activities, which is different from the waiting time between them. It helps identify which specific tasks are time-consuming, enabling targeted improvements to make the process more efficient.

It enables the calculation of processing time for individual activities, helping to distinguish between active work time and waiting time.

Some ETQ Reliance modules may log both start and end times for certain tasks. If not available, it can be derived during data preparation.

This attribute indicates the organizational unit assigned to manage the quality event or execute certain steps, such as 'Quality Assurance', 'Engineering', or 'Production'. This can be assigned at the case level or change as the case moves between departments.

This attribute is key for the Departmental Performance Analysis dashboard. It allows for filtering and comparing process performance, such as cycle times and event volumes, across different departments. This helps identify departmental bottlenecks, resource constraints, or areas of excellence.

It enables performance comparison and bottleneck analysis across different business units, helping to optimize resource allocation.

This is typically a field on the main quality event form in ETQ Reliance, indicating the owner or responsible group.

After a root cause analysis is performed, the underlying reason for the issue is often categorized. Examples include 'Equipment Failure', 'Human Error', 'Process Deficiency', or 'Supplier Issue'.

This attribute is essential for the Root Cause Category Trends dashboard. By analyzing the frequency of different root cause categories over time, organizations can identify systemic problems and focus their improvement efforts on the most common sources of quality issues. It helps shift from reactive problem solving to proactive prevention.

It enables strategic analysis of recurring problems, helping to identify systemic issues and prioritize long-term corrective and preventive actions.

This is typically a field completed during the Root Cause Analysis stage of the workflow in ETQ Reliance.

The Severity Level is an assessment of the potential impact of the quality issue on customers, products, or regulatory compliance. It is used to prioritize resources and determine the urgency of the response.

This attribute is critical for the Issue Triage and Prioritization and High Severity Event Resolution dashboards. It allows for segmenting quality events to analyze if high-severity issues are being resolved faster than low-severity ones and helps ensure that critical problems receive immediate attention.

It allows for prioritization and segmentation of cases to ensure that the most critical quality issues are addressed with the appropriate urgency.

This is a standard field in most quality management modules in ETQ Reliance, often part of the initial issue intake form.

After a corrective action is implemented, a verification step is often performed to confirm that the action actually solved the problem. This attribute records the outcome of that verification, typically as 'Effective' or 'Not Effective'.

This attribute is central to the Corrective Action Effectiveness dashboard and the CAPA Effectiveness Verification Rate KPI. It directly measures the success of the resolution process, helping to identify recurring issues and improve the quality of corrective action plans.

This directly measures the success of corrective actions, helping to reduce rework and prevent the recurrence of quality issues.

This would be a field in the effectiveness verification section of the CAPA or Quality Event module in ETQ Reliance.

This attribute identifies the specific product or part number associated with the quality issue. It links the process data to the product master data.

Analyzing quality events by product allows the business to identify if certain products have higher rates of quality issues, pointing to potential design or manufacturing problems. It helps focus improvement efforts on the products that need it most.

It connects the quality process to specific products, allowing for analysis of which products are most prone to issues.

This is typically a key field on the quality event form, often linked to a product master data table within ETQ Reliance or an integrated ERP system.

This attribute links a quality event to a particular regulatory requirement or industry standard, such as ISO 9001, FDA 21 CFR Part 820, or internal corporate policies. This is especially important in regulated industries.

This is the key attribute for the Quality Compliance Overview dashboard. Analyzing events by the associated standard helps monitor compliance, identify areas with frequent deviations, and ensure that all regulatory requirements are being met in a timely manner.

It enables analysis of quality events in the context of compliance, helping to ensure adherence to specific industry regulations and standards.

This may be a dedicated field or a selectable list on the quality event form in ETQ Reliance, particularly in compliance-focused modules.

This attribute assigns the quality event to a specific business unit within the organization, such as 'Consumer Electronics' or 'Medical Devices'. It provides a higher level of organizational context than the department.

This allows for high-level performance comparisons across different parts of the business. It can help senior leadership understand which business units are facing the most significant quality challenges and allocate resources accordingly.

It enables high-level comparison of quality process performance across different divisions of the company.

This information might be a field on the quality event form or derived from other attributes like the responsible department or product.

This attribute tracks the state of the Corrective Action Plan (CAP) itself, which is a key milestone within the overall quality event. It shows whether a proposed solution has been reviewed and accepted.

Analyzing this attribute can highlight bottlenecks in the approval process. A high number of rejected plans or long delays between 'Proposed' and 'Approved' statuses can indicate issues with the quality of root cause analysis or misalignment among stakeholders.

It helps identify delays and inefficiencies in the approval cycle for corrective actions, a common bottleneck in quality management.

This would be a status field within the Corrective and Preventive Action (CAPA) section or module of ETQ Reliance.

This boolean attribute is derived to identify when a process loop occurs, such as when an effectiveness verification fails and triggers a new investigation, or when a corrective action plan is rejected and sent back for revision. It flags activities that are repetitions of earlier steps.

This attribute is used to calculate the 'Rework Rate for Corrective Actions' KPI. Highlighting rework is crucial for understanding process inefficiencies, as rework consumes resources and extends cycle times without advancing the case toward resolution.

It quantifies process inefficiency by flagging repeated work, helping to identify the root causes of process failures and reduce waste.

This attribute is not in the source system. It is calculated based on the sequence of activities within a case during data transformation.

This attribute contains the detailed, narrative description of the quality problem. It provides qualitative context that structured data fields cannot capture.

While not typically used directly in process flow visualization, the issue description is invaluable for detailed case reviews. It can also be used with text mining techniques to identify common themes or keywords associated with certain types of process deviations or delays.

It provides crucial qualitative context for understanding the specifics of a quality event, which is useful for deep-dive analysis of individual cases.

This is a standard text box or memo field on the initial quality event reporting form in ETQ Reliance.

This attribute records the date and time of the most recent data extraction from the source system. It is a metadata field that applies to the entire dataset rather than individual events.

In any process analysis, understanding the freshness of the data is critical. This attribute helps users know how current the analysis is, ensuring that decisions are based on up-to-date information and managing expectations about data latency.

It indicates the freshness of the data, which is critical for understanding the timeliness of the analysis and insights.

This value is generated during the data extraction, transformation, and loading (ETL) process, recording the timestamp of when the job was run.

This attribute links a quality event to one or more preventive actions that were created to address the root cause and prevent recurrence in other areas. A single quality event might lead to multiple preventive actions.

This ID is important for the Preventive Action Management dashboard. It helps track the implementation rate of identified preventive actions and can be used to identify duplicate or redundant efforts, ensuring that proactive improvements are managed efficiently.

It connects reactive quality events to proactive improvement initiatives, allowing for analysis of how effectively the organization prevents future issues.

This would be a related record or a field in the Preventive Action section of the CAPA module in ETQ Reliance.

This is a calculated metric that represents the end-to-end duration of a single quality event. It is computed by finding the difference between the timestamp of the first activity (e.g., 'Quality Issue Identified') and the last activity (e.g., 'Quality Event Closed').

This attribute directly supports the 'Average Quality Event Cycle Time' KPI and is a primary measure of overall process efficiency. It is used in dashboards to track performance against cycle time reduction goals and to compare durations across different categories of events.

This is a key performance indicator that measures the overall efficiency of the quality management process from start to finish.

This attribute is not directly available in ETQ Reliance. It is calculated in the process mining tool or during ETL by subtracting the first event timestamp from the last event timestamp for each case.

This attribute provides a high-level summary of where the quality event is in its lifecycle. It indicates whether the case is actively being worked on, has been successfully resolved, or was canceled for some reason.

In process analysis, this is used to filter for active versus completed cases. It is fundamental for calculating the backlog of open quality events and for ensuring that analyses, such as cycle time, are performed only on cases that have reached a definitive end state.

It allows for filtering between open and closed cases, which is essential for calculating backlogs and analyzing completed process flows accurately.

This is a primary status field on the main quality event object in ETQ Reliance.

This metric measures the duration of a specific phase of the quality process. It is calculated as the time difference between the 'Investigation Initiated' activity and the 'Root Cause Analysis Performed' activity.

This attribute is essential for the 'Average Root Cause Analysis Time' KPI and the 'Root Cause Analysis Bottlenecks' dashboard. It helps pinpoint delays in the analytical phase of the process, which is often a major contributor to long overall cycle times.

It isolates the performance of a critical sub-process, helping to identify and address delays in problem analysis and investigation.

This attribute is not in the source system. It is calculated during data transformation by finding the time difference between the timestamps of specific activities.

This attribute is a calculated field that compares the current or total cycle time of a quality event against predefined targets. For example, a critical issue might have an SLA for resolution within 15 days. The state could be 'On Track', 'At Risk', or 'Breached'.

This is valuable for the Quality Compliance Overview dashboard, as it provides an immediate visual indicator of timeliness and compliance. It helps managers proactively address events that are at risk of missing their deadlines, rather than only reacting after a breach has occurred.

It provides a clear, at-a-glance view of performance against timeliness targets, enabling proactive management of cases at risk of delay.

This attribute is calculated during data transformation by comparing the elapsed time of a case against business rules for SLAs, which may be based on attributes like Severity Level.

This attribute identifies the origin of the quality management data. For this process view, the value will be constant, indicating that the data comes from ETQ Reliance.

While it may not vary within a single dataset, this attribute is crucial for data governance and in scenarios where data from multiple systems is merged. It ensures clarity on data provenance and helps in managing data integration efforts.

It provides essential context about the data's origin, which is important for data governance, validation, and integration with other systems.

This is typically a static value added during the data extraction, transformation, and loading (ETL) process to label the source of the data.