QC Metrics

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					MHE – ODC PARTNERS                                                    QC METRICS




1.0 Purpose

This document describes the different metrics that need to be calculated as part of
the QC process. Quantitative Measurement is an integral part of total quality
management and process improvement strategies.

2.0 Scope

This procedure applies to all projects carried out as part of MHE ODC by the
partners. It does not apply to research and development, Proof of Concept and
Demos.

3.0 Input

QC Procedures
Defect Reports

4.0 Definitions

 Acronyms                                   Description

 PM                                         Project Manager

 QM                                         Quality Manager

 RFC                                        Request for Change




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MHE – ODC PARTNERS                                                      QC METRICS




5.0 Procedure

This process provides a framework for collecting measures and metrics related to
defects and methods for analyzing metrics, with an aim to measure the product
quality and process capabilities of the ODC partners, and accordingly drive the
process improvement initiatives.

The following metrics are defined to be used by the QC team. The Project
Management Plan of each project would identify the actual metrics that would be
calculated for that particular project. These metrics could be updated periodically
based on the requirements of ODC functioning and operations.


   5.1 Defect Removal Effectiveness (DRE)


          Formula: DRE = (1 – (Number of defects reported by customer / Total
          number of defects))*100
          Where, Total number of defects = defects identified internally + defects
          identified by the customer
          Definition: Defect Removal Effectiveness is a measure of variance that
          indicates the removal effectiveness of the defects found while executing
          the project against the defects found by the customer. If the DRE
          percentage is high it means that the review/testing quality is also high
          and vice versa.
          Benefits:
          a. Helps in understanding the robustness of the testing.
          b. Helps in identifying the product quality.
          c. Helps in analyzing and rectifying the loopholes in testing, if any.
          Data Required: Number of Defects (internal and client reported),
          Review Comments
          Data Sources: Review Sheets, Test Reports, and Client Review Reports
          Frequency of data capture: Data will be captured at the end of a
          project and also when a project is delivered to the client.
          Units of Measure: Defects in numbers.




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MHE – ODC PARTNERS                                                      QC METRICS




  5.2 Defect Distribution

          Formula

          Defect Distribution = ∑x: 1 to n (Internal Defectsx + External Defectsx) /
          (Total number of Defects for the project)
          Where x denotes the stage of the project (e.g. analysis, design, coding
          etc) and n denotes the number of stages.

          Definition: This metric would indicate the spread of defects across every
          stage of the project. The spread would determine the most critical area of
          the project that needs to be addressed.

          Benefits:
          a. Useful to address the different modules or phases in which the number
          of defects are more
          b. Helps in setting a target for the QC team
          Data Required: Number of Defects (internal and client reported),
          Review Comments, and Effort
          Data Sources: Review Sheets, Test Reports, and Client Review Reports
          Frequency of data capture: Data will be captured at every phase
          Units of Measure: Defect numbers



  5.3 Acceptance Criteria Variance

       Formula

          Acceptance Criteria Variance = (Actual number of S1+S2+S3 bugs in
          alpha, beta and RC deliverables) – (Planned number of S1+S2+S3 bugs in
          alpha, beta and RC deliverables)/ (Planned number of S1+S2+S3 bugs in
          alpha, beta and RC deliverables)
          Where S1, S2 and S3 denote Severity 1, Severity 2 and Severity 3 type of
          bugs respectively.

          Definition: This metric would provide the quality of the project in terms
          of the acceptance criteria defined.

          Benefits:
          a. Useful to validate the performance metric in terms of acceptance
          criteria
          b. Helps the QC team to monitor the performance of the project in terms
          of the acceptance criteria
          Data Required: Number of Defects (internal and client reported),
          Review Comments, and Effort



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MHE – ODC PARTNERS                                                QC METRICS



          Data Sources: Review Sheets, Test Reports, and Client Review Reports
          Frequency of data capture: Data will be captured at the end of every
          project.
          Units of Measure: Defect numbers



6.0 Output
 QA Plan (Section of PMP)
 Metrics Data




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posted:11/9/2012
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