📋 QIS (Quality Implementation Support) KPI Reference Guide

Generated on: July 09, 2025 at 05:59 PM

🎯 Executive Summary

This document provides comprehensive details for 18 Key Performance Indicators (KPIs) used to evaluate Quality Inspection Specialist performance for System Engineer role.

📈 Summary Statistics

Total KPIs: 18
Total Weightage: 100%
Automated KPIs: 10 (55.6%)
Manual KPIs: 8 (44.4%)

📊 Frequency Distribution

Monthly: 10 KPIs
Per Sprint: 4 KPIs
Post Production: 1 KPIs
Quarterly: 1 KPIs
Sit End: 2 KPIs

💾 Data Sources

JIRA: 18 KPIs

📋 Detailed KPI Specifications

⏱️ 1. Pulse Compliance

Attribute	Value
KPI ID	703
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: Ensure Pulse entries are updated regularly

🧮 Formula: % of hours utilized

📐 Calculation Details:

Purpose: Measure how accurately employees log their work hours in Pulse relative to their assigned capacity, ensuring discipline in time reporting and data integrity for planning.
Formula: Compliance Rate (%) = Total Hours Reported in Pulse / Total Assigned Capacity Hours × 100

Data Sources: BI Dashboard
Calculation Steps:
Extract the compliance data from the BI dashboard daily for each resource, which already contains the computed compliance % to date for every resource.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	pulseCompliance
🟢 4	>= (greater than or equal to)	90	pulseCompliance
🟡 3	>= (greater than or equal to)	85	pulseCompliance
🟠 2	>= (greater than or equal to)	80	pulseCompliance
🔴 1	> (greater than)	80	pulseCompliance

📅 2. Attendance

Attribute	Value
KPI ID	704
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: Compliance to attendance policies

🧮 Formula: % of working days marked

📐 Calculation Details:

Purpose: Ensure that every workday is covered by either a valid attendance record or an approved leave entry; missing both constitutes non-compliance.

Formula: NonCompliantDay = (No AttendanceRecord) AND (No LeaveRecord)

Data Sources: WebHR

Calculation Steps:
1. For each employee, check the date three days prior to today to allow for data processing.
2.
Query WebHR: is there an AttendanceRecord? is there a LeaveRecord?
3. If neither exists, mark the day as non-compliant (NonCompliantDay = true).
4. Repeat daily to maintain a running tally of non-compliant days.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	Attendance
🟢 4	>= (greater than or equal to)	90	Attendance
🟡 3	>= (greater than or equal to)	85	Attendance
🟠 2	>= (greater than or equal to)	80	Attendance
🔴 1	> (greater than)	80	Attendance

🎯 3. Test Case Effectiveness

Attribute	Value
KPI ID	705
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Per Sprint
Automation	👤 Manual
Default Score	0

📝 Description: the percentage of test cases that successfully identify defects.

🧮 Formula: % of # of Defects / # of Test Cases Executed

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	50	testCaseEffectiveness
🟢 4	>= (greater than or equal to)	40	testCaseEffectiveness
🟡 3	>= (greater than or equal to)	35	testCaseEffectiveness
🟠 2	>= (greater than or equal to)	30	testCaseEffectiveness
🔴 1	> (greater than)	30	testCaseEffectiveness

⚡ 4. QA Test Execution Time

Attribute	Value
KPI ID	706
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Per Sprint
Automation	👤 Manual
Default Score	0

📝 Description: Measures the time taken to execute a set of test cases.

🧮 Formula: # of Test Cases Executed / Total Time Taken

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	25	testExecutionTime
🟢 4	>= (greater than or equal to)	20	testExecutionTime
🟡 3	>= (greater than or equal to)	15	testExecutionTime
🟠 2	>= (greater than or equal to)	10	testExecutionTime
🔴 1	> (greater than)	10	testExecutionTime

⚡ 5. Implementation Test Execution Time

Attribute	Value
KPI ID	707
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Sit End
Automation	👤 Manual
Default Score	0

📝 Description: Measures the time taken to execute a set of test cases.

🧮 Formula: # of Test Cases Executed / Total Time Taken

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	25	testExecutionTime
🟢 4	>= (greater than or equal to)	20	testExecutionTime
🟡 3	>= (greater than or equal to)	15	testExecutionTime
🟠 2	>= (greater than or equal to)	10	testExecutionTime
🔴 1	> (greater than)	10	testExecutionTime

🐛 6. QA Invalid Bugs Count

Attribute	Value
KPI ID	708
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Per Sprint
Automation	✅ Automated
Default Score	5

📝 Description: Number of invalid bugs reported

🧮 Formula: # of Rejected Bugs

📐 Calculation Details:

Purpose: Count the number of bug reports submitted by QIS that were later rejected or marked as not a bug.

Formula: Invalid Bug Count = Number of issues where Reporter = QIS and Closing_Reason ∈ {“Reject”, “Not a Bug”}

Data Sources: Jira “POL” project; Reporter = QIS; Closing_Reason (Reject, Not a Bug); Close Timestamp

Calculation Steps:
1. Query Jira “POL” for all issues where Reporter = QIS within the reporting period.
2. From that set, filter issues whose Closing_Reason is “Reject” or “Not a Bug.”
3. Count the total number of filtered issues.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	invalidBugsCount
🟢 4	<= (less than or equal to)	4	invalidBugsCount
🟡 3	<= (less than or equal to)	6	invalidBugsCount
🟠 2	<= (less than or equal to)	8	invalidBugsCount
🔴 1	> (greater than)	8	invalidBugsCount

🐛 7. Implementation Invalid Bugs Count

Attribute	Value
KPI ID	709
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Sit End
Automation	👤 Manual
Default Score	5

📝 Description: Number of invalid bugs reported

🧮 Formula: # of Rejected Bugs

📐 Calculation Details:

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	invalidBugsCount
🟢 4	<= (less than or equal to)	4	invalidBugsCount
🟡 3	<= (less than or equal to)	6	invalidBugsCount
🟠 2	<= (less than or equal to)	8	invalidBugsCount
🔴 1	> (greater than)	8	invalidBugsCount

⏰ 8. QA SLA

Attribute	Value
KPI ID	710
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: To measure SLA of QA is met for production issues

🧮 Formula: SLA Achieved for tickets assigned

📐 Calculation Details:

Purpose: Monitor how effectively the team resolves production issues within the agreed SLA window.
Data Sources: Jira “Production Issue” tickets; Assignment Timestamp; Completion Timestamp; SLA Target (hours).
Calculation Steps:
1.
Select Tickets: Pull all “Production Issue” tickets assigned during the reporting month.
2.
Determine SLA Status: classify as non-breached (resolution duration ≤ SLA Target) or breached (duration > SLA Target).
3.
Compute Rate: SLA Achievement Rate (%) = (Number of Non-breached Tickets / Total Tickets Assigned) × 100
4.
Evaluate Performance: review the percentage of non-breached tickets to assess SLA compliance.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	qaTAT
🟢 4	>= (greater than or equal to)	90	qaTAT
🟡 3	>= (greater than or equal to)	85	qaTAT
🟠 2	>= (greater than or equal to)	80	qaTAT
🔴 1	> (greater than)	80	qaTAT

🔧 9. Production Patch Revert / Resubmission

Attribute	Value
KPI ID	711
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Quarterly
Automation	✅ Automated
Default Score	5

📝 Description: To measure number of patches that are either reverted or a subsequent patch has to be resubmitted

🧮 Formula: # of Impacted Patches / Total number of Patches sent

📐 Calculation Details:

Purpose: Measure the proportion of production patches that are reverted or require a subsequent resubmission.

Formula: Patch Revert Rate (%) = (Number of Impacted Patches / Total Patches Sent) × 100

Data Sources: Jira; Level 0 Sub-status; Status change history

Definition of Terms: Total Patches Sent = issues with Level 0 Sub-status = “Patch Dispatched to client” or “Awaiting Client Response”; Impacted Patches = those sent patches whose status changed from “Level 0 – Client End” back to “Level 2 – Support Engineer” while still in a sent sub-status.

Calculation Steps: 1. Query Jira for “sent” patches;
2. Count these as Total Patches Sent;
3. Identify reverts via status history and count as Impacted Patches;
4. Compute rate using the formula;

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	productionPatchRevert
🟢 4	<= (less than or equal to)	4	productionPatchRevert
🟡 3	<= (less than or equal to)	6	productionPatchRevert
🟠 2	<= (less than or equal to)	8	productionPatchRevert
🔴 1	> (greater than)	8	productionPatchRevert

📊 10. Test Coverage

Attribute	Value
KPI ID	712
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Per Sprint
Automation	👤 Manual
Default Score	0

📝 Description: Indicates the percentage of the software that has been tested.

🧮 Formula: % of features assigned in a sprint

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	testCoverage
🟢 4	>= (greater than or equal to)	90	testCoverage
🟡 3	>= (greater than or equal to)	85	testCoverage
🟠 2	>= (greater than or equal to)	80	testCoverage
🔴 1	> (greater than)	80	testCoverage

🚨 11. Escape Defect Count SIT

Attribute	Value
KPI ID	713
Weightage	10%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	5

📝 Description: Counts the number of defects that were not identified during testing but were discovered after the software was released.

🧮 Formula: # of Defects per feature identified during SIT

📐 Calculation Details:

Purpose: Track the number of defects identified during System Integration Testing (SIT) by each assignee.
Formula:

Formula: SIT Defect Count = Number of issues where Phase = SIT and Assigned To = target user
Formula: SIT Defect Count = Number of issues where Phase = SIT and Assigned To = target user
Data Sources: Jira “POL” project; Phase = “SIT”; Assigned To; Closed Timestamp.
Calculation Steps:
1. Query Jira “POL” for all issues where Phase = “SIT” and Assigned To = the target assignee, and Closed Timestamp falls within the reporting period.
2. Count the total number of issues returned.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	escapeDefectCountSIT
🟢 4	<= (less than or equal to)	4	escapeDefectCountSIT
🟡 3	<= (less than or equal to)	6	escapeDefectCountSIT
🟠 2	<= (less than or equal to)	8	escapeDefectCountSIT
🔴 1	> (greater than)	8	escapeDefectCountSIT

🚨 12. Escape Defect Count UAT

Attribute	Value
KPI ID	714
Weightage	10%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	5

📝 Description: Counts the number of defects that were not identified during testing but were discovered after the software was released.

🧮 Formula: # of Defects per feature identified during UAT

📐 Calculation Details:

Purpose: Track the number of defects reported during User Acceptance Testing (UAT) by each reporter.

Formula: UAT Defect Count = Number of issues where Phase = UAT and Reporter = target user

Data Sources: Jira “POL” project; Phase = “UAT”; Reporter; Creation Timestamp

Calculation Steps:
1. Query Jira “POL” for all issues where Phase = “UAT” and Reporter = the target user within the reporting period.
2. Count the total number of issues returned.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	escapeDefectCountUAT
🟢 4	<= (less than or equal to)	4	escapeDefectCountUAT
🟡 3	<= (less than or equal to)	6	escapeDefectCountUAT
🟠 2	<= (less than or equal to)	8	escapeDefectCountUAT
🔴 1	> (greater than)	8	escapeDefectCountUAT

🤖 13. QA Test Case Automation

Attribute	Value
KPI ID	715
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	👤 Manual
Default Score	0

📝 Description: To measure number of cases automated during testing

🧮 Formula: % of Unit Cases Automated

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	testCaseAutomation
🟢 4	>= (greater than or equal to)	90	testCaseAutomation
🟡 3	>= (greater than or equal to)	85	testCaseAutomation
🟠 2	>= (greater than or equal to)	80	testCaseAutomation
🔴 1	> (greater than)	80	testCaseAutomation

🤖 14. Implementation Test Case Automation

Attribute	Value
KPI ID	716
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	👤 Manual
Default Score	0

📝 Description: To measure number of cases automated during testing

🧮 Formula: % of Unit Cases Automated

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	testCaseAutomation
🟢 4	>= (greater than or equal to)	90	testCaseAutomation
🟡 3	>= (greater than or equal to)	85	testCaseAutomation
🟠 2	>= (greater than or equal to)	80	testCaseAutomation
🔴 1	> (greater than)	80	testCaseAutomation

🏭 15. Post Production Defects

Attribute	Value
KPI ID	717
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Post Production
Automation	👤 Manual
Default Score	5

📝 Description: Number of Post Production Defects after Cutover

🧮 Formula: # of bugs logged post production

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	postProductionDefects
🟢 4	<= (less than or equal to)	4	postProductionDefects
🟡 3	<= (less than or equal to)	6	postProductionDefects
🟠 2	<= (less than or equal to)	8	postProductionDefects
🔴 1	> (greater than)	8	postProductionDefects

⚡ 16. L2 SLA - S3 & S4

Attribute	Value
KPI ID	718
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: To measure SLA of Investigation once the issue is reported

🧮 Formula: SLA Achieved for tickets assigned

📐 Calculation Details:

Purpose: Measure the percentage of production tickets assigned to you that meet the defined SLA for Severity 3 and Severity 4 incidents.

Severity Levels: S3 (Level 3 – Normal), S4 (Level 4 – General)

Formula: SLA Achievement Rate (%) = (Tickets Resolved Within SLA / Total Tickets Assigned) × 100

Data Sources: Ticketing System; Severity (S3, S4);; Resolution Timestamp; SLA Target (by severity level)

Calculation Steps: 1.
Filter Tickets: select Level 3 & 4 tickets assigned in the period.
2.
Assess SLA Compliance: compare each ticket’s resolution time vs. SLA target and count those resolved within SLA.
3.
Compute Rate: apply the formula.
4.
Apply Weighting: multiply the result by the KPI’s weight.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	l2TAT
🟢 4	>= (greater than or equal to)	90	l2TAT
🟡 3	>= (greater than or equal to)	85	l2TAT
🟠 2	>= (greater than or equal to)	80	l2TAT
🔴 1	> (greater than)	80	l2TAT

🔄 17. L2 Reassignment

Attribute	Value
KPI ID	719
Weightage	5%
Measure	Count
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: Number of reassigned tickets once the issue is identified as a bug and assigned to the QIS again

🧮 Formula: # of Reassigned Tickets / # of Tickets identified as bugs

📐 Calculation Details:

KPI: Ticket Reassignment Count
Purpose: Measure how often tickets with Assignment Level 2 are reassigned back to a Level-2 role they’ve already been through (even after moving to other roles) before completion.
Formula: Ticket Reassignment Count = Total number of reassignment events where Assignment Level = 2 and Role after = any Level-2 role already in this ticket’s history
Data Sources: Ticketing System (e.g., Jira “POL” project); Assignment Level; Status History; Assignment History
Calculation Steps: 1. Query tickets where Assignment Level = 2 that reached “Completed” status within the reporting period.
2. For each ticket, retrieve its full assignment-change history in chronological order.
3. Track the sequence of Level-2 roles the ticket has been assigned to (Support, Network, Database).
4. Whenever it’s assigned to a Level-2 role that already appears earlier in that sequence, count one reassignment event (e.g., Support → Network → Database → Network (reassignment #1) → Support (reassignment #2)).
5. Sum all such events across completed Level-2 tickets to get the Ticket Reassignment Count for the period.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	<= (less than or equal to)	2	l2Reassignment
🟢 4	<= (less than or equal to)	4	l2Reassignment
🟡 3	<= (less than or equal to)	6	l2Reassignment
🟠 2	<= (less than or equal to)	8	l2Reassignment
🔴 1	> (greater than)	8	l2Reassignment

🚨 18. S1 & S2 SLA

Attribute	Value
KPI ID	720
Weightage	5%
Measure	Percentage
Data Source	JIRA
Frequency	Monthly
Automation	✅ Automated
Default Score	0

📝 Description: To measure SLA of severity incidents

🧮 Formula: SLA Achieved for severity incidents

📐 Calculation Details:

Purpose: Measure the percentage of production tickets assigned to QIS that meet the defined SLA for Severity 1 and Severity 2 incidents.

Severity Levels: S1 (Level 1 – Severe), S2 (Level 2 – Critical)

Formula: SLA Achievement Rate (%) = (Tickets Resolved Within SLA / Total Tickets Assigned) × 100

Data Sources: Ticketing System; Severity (S1, S2); Resolution Timestamp; SLA Target (by severity level)

Calculation Steps: 1.
Filter Tickets: Severity wise select Level 1 & 2 tickets assigned to a resourcein the period.
2.
Assess SLA Compliance: compare each ticket’s resolution time vs. SLA target and count those resolved within SLA.
3.
Compute Rate: apply the formula.
4.
Apply Weighting: multiply the result by the KPI’s weight.

👥 Applicability:

Designation: System Engineer

🎯 Scoring Rules:

Score	Condition	Threshold	Field
🟢 5	>= (greater than or equal to)	95	s1S2TAT
🟢 4	>= (greater than or equal to)	90	s1S2TAT
🟡 3	>= (greater than or equal to)	85	s1S2TAT
🟠 2	>= (greater than or equal to)	80	s1S2TAT
🔴 1	> (greater than)	80	s1S2TAT

This document was automatically generated from KPI specifications on July 09, 2025

🎯 Executive Summary​

📈 Summary Statistics​

📊 Frequency Distribution​

💾 Data Sources​

📋 Detailed KPI Specifications​

⏱️ 1. Pulse Compliance​

📅 2. Attendance​

🎯 3. Test Case Effectiveness​

⚡ 4. QA Test Execution Time​

⚡ 5. Implementation Test Execution Time​

🐛 6. QA Invalid Bugs Count​

🐛 7. Implementation Invalid Bugs Count​

⏰ 8. QA SLA​

🔧 9. Production Patch Revert / Resubmission​

📊 10. Test Coverage​

🚨 11. Escape Defect Count SIT​

🚨 12. Escape Defect Count UAT​

🤖 13. QA Test Case Automation​

🤖 14. Implementation Test Case Automation​

🏭 15. Post Production Defects​

⚡ 16. L2 SLA - S3 & S4​

🔄 17. L2 Reassignment​

🚨 18. S1 & S2 SLA​

🎯 Executive Summary

📈 Summary Statistics

📊 Frequency Distribution

💾 Data Sources

📋 Detailed KPI Specifications

⏱️ 1. Pulse Compliance

📅 2. Attendance

🎯 3. Test Case Effectiveness

⚡ 4. QA Test Execution Time

⚡ 5. Implementation Test Execution Time

🐛 6. QA Invalid Bugs Count

🐛 7. Implementation Invalid Bugs Count

⏰ 8. QA SLA

🔧 9. Production Patch Revert / Resubmission

📊 10. Test Coverage

🚨 11. Escape Defect Count SIT

🚨 12. Escape Defect Count UAT

🤖 13. QA Test Case Automation

🤖 14. Implementation Test Case Automation

🏭 15. Post Production Defects

⚡ 16. L2 SLA - S3 & S4

🔄 17. L2 Reassignment

🚨 18. S1 & S2 SLA