What metrics are essential for a project’s success? How do you know which parameters are the most appropriate to define and measure the successful completion of a process? What are some software development metrics examples? Read on to find out all you need to know about Process and Project Metrics for Project Management.
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Key Process and Project Metric Groups
Project managers have a wide variety of metrics to choose from. We can classify the most commonly used metrics into the following groups:
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Process Metrics
These are metrics that pertain to Process Quality. They are used to measure the efficiency and effectiveness of various processes.
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Project Metrics
These are metrics that relate to Project Quality. They are used to quantify defects, cost, schedule, productivity and estimation of various project resources and deliverables.
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Product Metrics
These are metrics that pertain to Product Quality. They are used to measure cost, quality, and the product’s time-to-market.
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Organizational Metrics
These metrics measure the impact of organizational economics, employee satisfaction, communication, and organizational growth factors of the project.
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Software Development Metrics Examples
These metrics enable management to understand the quality of the software, the productivity of the development team, code complexity, customer satisfaction, agile process, and operational metrics.
We’ll now take a closer look at the various types of the two most important categories of metrics – Project Metrics, and Process Metrics.
Top 11 Project Metrics
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Schedule Variance: Any difference between the scheduled completion of an activity and the actual completion is known as Schedule Variance.
Schedule variance = ((Actual calendar days – Planned calendar days) + Start variance)/ Planned calendar days x 100.
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Effort Variance: Difference between the planned outlined effort and the effort required to actually undertake the task is called Effort variance.
Effort variance = (Actual Effort – Planned Effort)/ Planned Effort x 100.
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Size Variance: Difference between the estimated size of the project and the actual size of the project (normally in KLOC or FP).
Size variance = (Actual size – Estimated size)/ Estimated size x 100.
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Requirement Stability Index: Provides visibility to the magnitude and impact of requirements changes.
RSI = 1- ((Number of changed + Number of deleted + Number of added) / Total number of initial requirements) x100.
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Productivity (Project): Is a measure of output from a related process for a unit of input.
Project Productivity = Actual Project Size / Actual effort expended in the project.
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Productivity (for test case preparation) = Actual number of test cases/ Actual effort expended in test case preparation.
- Productivity (for test case execution) = Actual number of test cases / actual effort expended in testing.
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Productivity (defect detection) = Actual number of defects (review + testing) / actual effort spent on (review + testing).
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Productivity (defect fixation) = actual no of defects fixed/ actual effort spent on defect fixation.
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Schedule variance for a phase: The deviation between planned and actual schedules for the phases within a project.
Schedule variance for a phase = (Actual Calendar days for a phase – Planned calendar days for a phase + Start variance for a phase)/ (Planned calendar days for a phase) x 100
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Effort variance for a phase: The deviation between a planned and actual effort for various phases within the project.
Effort variance for a phase = (Actual effort for a phase – a planned effort for a phase)/ (planned effort for a phase) x 100.
Top 7 Process Metrics:
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Cost of quality: It is a measure of the performance of quality initiatives in an organization. It’s expressed in monetary terms.
Cost of quality = (review + testing + verification review + verification testing + QA + configuration management + measurement + training + rework review + rework testing)/ total effort x 100.
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Cost of poor quality: It is the cost of implementing imperfect processes and products.
Cost of poor quality = rework effort/ total effort x 100.
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Defect density: It is the number of defects detected in the software during development divided by the size of the software (typically in KLOC or FP)
Defect density for a project = Total number of defects/ project size in KLOC or FP
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Review efficiency: defined as the efficiency in harnessing/ detecting review defects in the verification stage.
Review efficiency = (number of defects caught in review)/ total number of defects caught) x 100.
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Testing Efficiency: Testing efficiency = 1 – ((defects found in acceptance)/ total number of testing defects) x 100.
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Defect removal efficiency: Quantifies the efficiency with which defects were detected and prevented from reaching the customer.
Defect removal efficiency = (1 – (total defects caught by customer/ total number of defects)) x 100.
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Residual defect density = (total number of defects found by a customer)/ (Total number of defects including customer found defects) x 100.
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