Thursday, May 16, 2013

Metrics for Agile Product Development


Metrics play an important part in any project. They provide data points to analyse performance and identify improvement areas . They help us study the trend so that we can assess  how we are doing.






Why Care for Metrics

  • Metrics provide important feedback to the team which is important promote continuous improvement
  • Metrics helps project team evolve to get maximum output 
  • Metrics provide facts based on data collected and can be used for strategic decisions making
  • Its impossible to optimize a process if you don't know how to measure it.

Reasons why metrics fail

  • Measuring unnecessary data
  • Measuring too much data
  • Failure to define  a compact set of metrics that are aligned with business priorities

Business Metrics

Business metrics are focused on measuring how we are doing and how we can get better. Here are some useful hints :
  • Time to market : Time taken for each feature from introduction till deployment
  • Return on investment : Revenue vs Costs of production 
  • Product quality : Number of post deployment defects reported
  • Product Design : Number of UI related enhancement requests received 

Development Metrics

Metric
How to collect
Why Collect this metric
Mean Velocity
Average of story points completed in each sprint
Long term strategic release planning
Actual Velocity vs Mean Velocity
Actual velocity in a sprint compared to team mean velocity
Determines the deviation from average productivity
Sprint Burn Down
Starting from day one of the sprint  till end of the sprint effort  remaining after end of each day
Monitor  health of ongoing sprint
Release Burn Down
Starting from first sprint , story points remaining till present day
Monitor progress for release
Defect Density
Defects in following buckets compared to total number of defects
   -  Missed Requirement
-   Defect as per priority
-  Code Review
-   UI

Analyze the root cause of problems in development
Effort Breakdown
Breakdown of effort in following buckets vs Total Effort
-  Feature Development
-  Big Fixing
-  Refactoring
-  Enhancements

Analyze and enhance productivity of team
Product Backlog Tracking
-  Pending user stories after each sprint
-  Number of new user stories added /deleted after each sprint
-  Number of user stories without estimation
Monitor work completed and new requirements which are added

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