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KPI Name

Representation (Single Project)

Tools

Maturity level values

Information Icon

On Hover

Ticket open vs closed rate by type (Ticket open rate by type)

Multi-select filter will have issue types 

Line + Column graph

  • Y- Axis - Count 

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Ticket open vs closed rate by type gives a comparison of new tickets getting raised vs number of tickets getting closed grouped by issue type during a defined period. 

This can be filtered based on issue type

If the No. of tickets closed are more than the No. of tickets opened in the latest time period, the KPI is considered having a positive trend

Date Range- Count

Ticket Open vs Closed rate by Priority (Ticket open rate by priority)

Multi-select filter will have Priority 

Line + Column graph

  • Y- Axis - Count (Days)

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Ticket open vs closed rate by priority gives a comparison of new tickets getting raised vs number of tickets getting closed grouped by priority during a defined period. 

This can be filtered based on priority

If the No. of tickets closed are more than the No. of tickets opened in the latest time period, the KPI is considered having a positive trend

Date Range- Count

Net Open Ticket Count By Priority (Ticket Count By Priority)

Multi-select filter will have Priorities

Line chart

  • Y- Axis - Count (Days)

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Net Open ticket count by priority measures the overall open tickets during a defined period grouped by priority. It considers the gross open and closed count during a period and then plots the net count

Decrease in net open ticket count is considered as positive

Date Range- Count

Net Open Ticket Count By RCA (Ticket Count By RCA)

Multi-select filter will have RCA values

Line chart

  • Y- Axis - Count (Days)

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Net open ticket count by RCA measures the overall open tickets during a defined period grouped by RCA. It considers the gross open and closed count during a period and then plots the net count

Decrease in net open ticket count is considered as positive

Date Range- Count

Net Open Ticket count by Status (Total Ticket Count)

Multi-select filter will have status

Line chart

  • Y- Axis - Count

  • X- Axis -Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Net open ticket count by status measures the overall open tickets during a defined period grouped by Status. It considers the gross open and closed count during a period and then plots the net count

Decrease in net open ticket count is considered as positive

Date Range- Count

Open Tickets Ageing by Priority (Total Tickets Aging)

Multi-select filter will have Priorities

Line chart

  • Y- Axis - Count (Days)

  • X- Axis - As defined currently

  • Aggregation Method - Average

Agile Project Management

  • Jira

  • Azure

N/A

Open tickets by ageing groups all the open tickets based on their ageing and priority

Date Range- Count

Regression automation Coverage

Line chart

  • Y- Axis - Percentage

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • Jira

  • Azure

  • Zephyr

M1 - <20%

M2 - 20-40%

M3 - 40-60%

M4 - 60% - 80% , 

M5 - > 80%

REGRESSION AUTOMATION COVERAGE measures progress of automation of regression test cases 

It is calculated as 

No. of regression test cases automated/Total no. of regression test cases

  • It is calculated as a ‘Percentage’. Higher the percentage, better is the ‘Quality’

  • A progress indicator shows trend of regression automation coverage between last 2 weeks. An upward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date Range: <<Percentage Value>>

Regression test cases automated: <<Value>>

Total Regression test cases: <<Value>>

Unit Test Coverage

Multiple Project: Multiple Line Graph with single-select filter

Line Graph

  • Y- Axis - Percentage

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • SonarQube

M1 - <20%

M2 - 20-40%

M3 - 40-60%

M4 - 60% - 80% , 

M5 - > 80%

UNIT TEST COVERAGE is a measurement of the amount of code that is run by unit tests - either lines, branches, or methods.

The calculation is done directly in Sonarqube

  • It is calculated in ‘Percentage’. Higher the percentage, better is the ‘Quality’

  • A progress indicator shows trend of Unit test coverage between last 2 weeks. An upward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date Range: << Percentage Value>>

Sonar Violations

Multiple Project: Stacked Clustered Column with single-select filter

Stacked Column

  • Y- Axis - Count

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • SonarQube

No Maturity Trend

SONAR VIOLATIONS highlight count of issues that exist every time a piece of code breaks a coding rule. The set of coding rules is defined through the associated Quality profile for each programming language in the project.

The calculation is done directly in Sonarqube. 

Issues are categorized in 3 types: Bug, Vulnerability and Code Smells

All these issues are categorized into 5 type of severity: Blocker, Critical, Major, Minor, Info   

Date Range:

Blocker: <<Value>>

Critical: <<Value>>

Major: <<Value>>

Minor: <<Value>>

Info: <<Value>>

Sonar Tech Debt

Multiple Project: Multiple Line Graph with single-select filter

Line Graph

  • Y- Axis - Days

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • SonarQube

M1: >100 days 

M2: 50-100 days

M3: 30-50 days,

M4: 10-30 days,

M5: <10 days

SONAR TECH DEBT explains the estimated time required to fix all Maintainability Issues/ code smells

It is calculated as effort to fix all Code Smells. The effort is calculated in minutes and converted to days by assuming 1 Day=8 Hours 

  • It is calculated in ‘Days’. Lower the days, better is the ‘Quality’

  • A progress indicator shows trend of Sonar Tech Debt between last 2 weeks. A downward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date Range:<<Days>>

Test Execution and pass percentage

Multiple Project: Multiple Line + Clustered Column chart

Line Graph

  • Y- Axis - Percentage

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • Excel

M1 - <20%

M2 - 20-40%

M3 - 40-60%

M4 - 60% - 80% , 

M5 - > 80%

TEST EXECUTION AND PASS PERCENTAGE measures the percentage of test cases that have been executed & the percentage that have passed.

It is calculated as 

No. of executed test cases out of total test cases in the latest execution during a day/week/month

No. of pass test cases out of executed test cases in  the latest execution during a day/week/month

  • It is calculated in ‘Percentage’. Higher the percentage, better is the ‘Quality’

  • A progress indicator shows trend of Test Execution and pass percentage between last 2 days/weeks/months. An upward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date Range- <<Percentage Value>>

Test Cycle

Executed test cases: <<Value>>

Pass test cases: <<Value>>

Change Failure Rate

Multiple Project: Multiple Line Graph with single-select filter

Line Graph

  • Y- Axis - Percentage

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • Jenkins

  • Bamboo

  • Azure Pipelines

M1: >50% 

M2: 30-50%,

M3: 20-30%,

M4: 10-20%,

M5: <10%

CHANGE FAILURE RATE measures the proportion of builds (changes) that have failed for whatever reason over a given period of time

It is calculated as

Total no. of failed Builds/Total number of Builds

  • It is calculated as a ‘Percentage’. Lower the percentage, better is the ‘Quality’

  • A progress indicator shows trend of Change Failure Rate between last 2 weeks. A downward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

*If the KPI data is not available for last 5 weeks, the Maturity level will not be shown

Date Range: <<Percentage>>

Total number of Changes: <<Value>>

Failed Changes: <<Value>>

Ticket Velocity

Line Graph

  • Y- Axis - Story Points

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Ticket velocity measures the size of tickets (in story points) completed in a defined duration

Date Range- <<Velocity>>

Team Capacity

Line Graph

  • Y- Axis - Hours

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

N/A

Team Capacity is sum of capacity of all team member measured in hours during a defined period 

Date Range- <<Capacity Hrs>>

 Number of Check-ins  

Line Graph

  • Y- Axis - Count 

  • X- Axis - Weeks

  • Aggregation Method - Sum

Agile Project Management

  • Repos

M1: 0-2

M2: 2-4

M3: 4-8

M4: 8-16

M5: >16

NUMBER OF CHECK-INS helps in measuring the transparency as well the how well the tasks have been broken down. 

  • It is calculated as a Count. Higher the count better is the ‘Speed’

  • A progress indicator shows trend of Number of Check-ins between last 2 weeks. An upward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date: <<Value>>

Code Build Time 

Multiple Project: Multiple Line Graph with single-select filter

Line Graph

  • Y- Axis - Min

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • Jenkins

  • Bamboo

  • Azure pipelines

M1 : > 45 min

M2 : 30-45 mins

M3 : 15-30 min

M4 : 5-15 min, 

M5 : <5 min

CODE BUILD TIME measures the time a job takes to build the code. 

  • It is calculated in  ‘Mins’. Lesser the time better is the ‘Speed’

  • A progress indicator shows trend of Code Build Time between last 2 weeks. A downward trend is considered positive

  • Maturity of the KPI is calculated based on the latest value

Date Range: <<min>>

Lead Time

The graph will have Radio buttons

Visualization: Text + Table

  • Y- Axis - Percentage

  • X- Axis - Weeks

  • Aggregation Method - Average

Agile Project Management

  • Jira

  • Azure

Lead time

M1 : > 60 days

M2 : 45-60 days

M3 : 30-45 days

M4 : 10-30 days, 

M5 : <10 days

Open to Triage

M1 : > 30 days

M2 : 20-30 days

M3 : 10-20 days

M4 : 5-10 days, 

M5 : < 5 days

Triage to Complete

M1 : > 20 days

M2 : 10-20 days

M3 : 7-10 days

M4 : 3-7 days, 

M5 : < 3 days

Complete to Live

M1 : > 30 days

M2 : 15-30 days

M3 : 5-15 days

M4 : 2-5 days, 

M5 : <2 day

LEAD TIME is the time from the moment when the request was made by a client and placed on a board to when all work on this item is completed and the request was delivered to the client

It is calculated as the sum following

Open to Triage: Time taken from ticket creation to it being refined & prioritized for development

Triage to Complete: Time taken from start of work on a ticket to it being completed by team

Complete to Live: Time taken between ticket completion to it going live.

Each of the KPIs are calculated in 'Days' 

Release Frequency

Multiple Project: Multiple Line Graph

Line Graph

  • Y- Axis - Count

  • X- Axis - Months

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

No Maturity

RELEASE FREQUENCY highlights the number of releases done in a month

It is calculated as number of fix versions in JIRA for a Project that have a Release date falling in a particular month 

  • It is calculated as a ‘Count’. Higher the Release Frequency, more valuable it is for the Business or a Project

  • A progress indicator shows trend of Release Frequency between last 2 months. An upward trend is considered positive

Month: <<Count>>

Value delivered (Cost of Delay)

Multiple Project: Multiple Line Graph

Line Graph

  • Y- Axis - Days

  • X- Axis - Months

  • Aggregation Method - Sum

Agile Project Management

  • Jira

  • Azure

No Maturity

COST OF DELAY (CoD) is a prioritization framework that helps a business quantify the economic value of completing a project sooner as opposed to later.

It is calculated by adding the following parameters for a Epic or a Feature

User-Business Value + Time Criticality + Risk Reduction and/or Opportunity Enablement.

  • It is calculated in ‘Days’. Higher the CoD for a feature or an Epic, more valuable it is for the Business or a Project

  • A progress indicator shows trend of CoD between last 2 months. An upward trend is considered positive

Month: <<Count>>

No. of Epics: <<Count>>

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