Software Development Metrics

**Summary** __Software Development Metrics__ is a handbook for anyone who needs to track and guide software development and delivery at the team level, such as project managers and team leads. New development practices, including "agile" methodologies like Scrum, have redefined which measurements are most meaningful and under what conditions you can benefit from them. This practical book identifies key characteristics of organizational structure, process models, and development methods so that you can select the appropriate metrics for your team. It describes the uses, mechanics, and common abuses of a number of metrics that are useful for steering and for monitoring process improvement. The insights and techniques in this book are based entirely on field experience. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. **About the Book** When driving a car, you are less likely to speed, run out of gas, or suffer engine failure because of the measurements the car reports to you about its condition. Development teams, too, are less likely to fail if they are measuring the parameters that matter to the success of their projects. This book shows you how. __Software Development Metrics__ teaches you how to gather, analyze, and effectively use the metrics that define your organizational structure, process models, and development methods. The insights and examples in this book are based entirely on field experience. You'll learn practical techniques like building tools to track key metrics and developing data-based early warning systems. Along the way, you'll learn which metrics align with different development practices, including traditional and adaptive methods. No formal experience with developing or applying metrics is assumed. **What's Inside** * Identify the most valuable metrics for your team and process * Differentiate "improvement" from "change" * Learn to interpret and apply the data you gather * Common pitfalls and anti-patterns **About the Author** **Dave Nicolette** is an organizational transformation consultant, team coach, and trainer. Dave is active in the agile and lean software communities. **Table of Contents** 1. Making metrics useful 2. Metrics for steering 3. Metrics for improvement 4. Putting the metrics to work 5. Planning predictability 6. Reporting outward and upward contents 8 foreword 12 preface 14 acknowledgments 17 about this book 18 Roadmap 18 Downloadable spreadsheet 20 Who should read this book? 21 Author Online 21 About the author 22 About the cover illustration 22 1 Making metrics useful 24 1.1 Measurements and metrics 25 1.1.1 What makes a metric “pragmatic”? 26 1.1.2 Forward-facing and backward-facing metrics 27 1.2 Factors affecting the choice of metrics 28 1.2.1 Process model 28 1.2.2 Delivery mode 30 1.3 How the metrics are presented 30 Name of the metric 30 1.4 Summary 31 2 Metrics for steering 32 2.1 Metric: Percentage of scope complete 34 2.1.1 When to use percentage of scope complete 35 2.1.2 A traditional project 35 2.1.3 An adaptive project 38 2.1.4 How to use percentage of scope complete 40 2.1.5 Anti-patterns 43 2.2 Metric: Earned value 44 2.2.1 When to use earned value 44 2.2.2 A traditional project 44 2.2.3 Anti-pattern: the novice team 47 2.3 Metric: Budget burn 47 2.3.1 When to use budget burn 47 2.3.2 A traditional project 48 2.3.3 An adaptive project using beyond budgeting 49 2.3.4 Anti-pattern: agile blindness 53 2.4 Metric: Buffer burn rate 53 2.4.1 When to use buffer burn rate 54 2.4.2 How to use buffer burn rate 54 2.5 Metric: Running tested features 55 2.5.1 When to use running tested features 55 2.5.2 An adaptive project 56 2.5.3 Anti-pattern: the easy rider 57 2.6 Metric: Earned business value 57 2.6.1 When to use earned business value 58 2.6.2 An adaptive project 58 2.6.3 Anti-patterns 61 2.7 Metric: Velocity 62 2.7.1 When to use velocity 62 2.7.2 An adaptive project 63 2.7.3 Anti-patterns 65 2.8 Metric: Cycle time 70 2.8.1 When to use cycle time 70 2.8.2 An adaptive project with consistently sized work items 70 2.8.3 An adaptive project with variable-sized work items 72 2.8.4 A traditional project with phase gates 73 2.9 Metric: Burn chart 75 2.9.1 When to use burn charts 76 2.9.2 How to use burn charts 76 2.9.3 Anti-patterns 78 2.10 Metric: Throughput 79 2.10.1 When to use throughput 79 2.10.2 A mixed-model project 80 2.11 Metric: Cumulative flow 82 2.11.1 When to use cumulative flow 82 2.11.2 A traditional project 83 2.12 Not advised 85 2.12.1 Earned schedule 85 2.12.2 Takt time 86 2.13 Summary 86 3 Metrics for improvement 88 3.1 Process-agnostic metrics 88 3.2 Technical metrics 89 3.3 Human metrics 89 3.4 General anti-patterns 89 3.4.1 Treating humans as resources 89 3.4.2 Measuring practices instead of results 90 3.5 Metric: Velocity 91 3.5.1 When to use velocity 91 3.5.2 An adaptive project 92 3.5.3 Anti-patterns 93 3.6 Metric: Cycle time 94 3.6.1 When to use cycle time 94 3.6.2 Tracking improvement in predictability 95 3.6.3 Tracking improvement in flow 96 3.6.4 Tracking responsiveness to special-cause variation 97 3.7 Metric: Burn chart 98 3.7.1 When to use burn charts 99 3.7.2 Adaptive development project using a time-boxed iterative process model 99 3.8 Metric: Cumulative flow 101 3.8.1 When to use a cumulative flow diagram 102 3.8.2 An adaptive project 102 3.9 Metric: Process cycle efficiency 105 3.9.1 When to use process cycle efficiency 106 3.9.2 Non-value-add time in queues 107 3.9.3 Non-value-add time in active states 108 3.9.4 What is normal PCE? 109 3.9.5 Moving the needle 109 3.10 Metric: Version control history 111 3.10.1 When to use version control history 111 3.11 Metric: Static code-analysis metrics 112 3.11.1 When to use static code-analysis metrics 112 3.12 Metric: Niko Niko calendar 115 3.12.1 When to use the Niko Niko calendar 115 3.12.2 Examples 115 3.12.3 Happy Camper 117 3.12.4 Omega Wolf 117 3.12.5 Zombie Team 118 3.13 Metric: Emotional seismogram 119 3.13.1 When to use the emotional seismogram 119 3.13.2 Examples 120 3.14 Metric: Happiness index 120 3.14.1 When to use the happiness index 121 3.14.2 Mechanics 121 3.15 Metric: Balls in bowls 125 3.15.1 When to use the balls-in-bowls metric 125 3.15.2 Mechanics 125 3.16 Metric: Health and happiness 125 3.16.1 When to use the health-and-happiness metric 126 3.16.2 Mechanics 126 3.17 Metric: Personality type profiles 128 3.17.1 When to use personality profiles 129 3.17.2 Anti-patterns 129 3.18 Summary 130 4 Putting the metrics to work 131 4.1 Pattern 1: Periodic refactoring iterations 132 4.2 Pattern 2: Velocity looks good, but little is delivered 136 4.3 Pattern 3: Linear workflow packaged in time-boxed iterations 144 4.4 Pattern 4: Erratic velocity but stable delivery 147 4.5 Summary 152 5 Planning predictability 153 5.1 Predictability and stakeholder satisfaction 154 5.1.1 Planning and traditional methods 154 5.1.2 Planning and adaptive methods 155 5.2 Measuring predictability 155 5.2.1 Estimation 155 5.2.2 Forecasting 157 5.2.3 Predictability of traditional plans 158 5.2.4 Predictability of adaptive plans 159 5.3 Predictability in unpredictable workflows 166 5.4 Effects of high variation in work item sizes 167 5.4.1 Deployable units of work 167 5.4.2 Trackable units of work 168 5.4.3 Demonstrating the value of consistently sized work items 168 5.5 Effects of high work-in-process levels 170 5.5.1 Work in process, cycle time, process cycle efficiency, and throughput 170 5.5.2 Work in process and defect density 175 5.6 Summary 177 6 Reporting outward and upward 178 6.1 Reporting hours 179 6.1.1 An example 180 6.1.2 Aggregate numbers are approximate 181 6.2 Reporting useless but mandated metrics 181 6.2.1 Categories of problematic metrics 182 6.2.2 Recognizing what’s really happening 183 6.2.3 Beware of motivational side effects of metrics 184 6.2.4 Understanding what the numbers mean 185 6.3 Summary 186 Numerics 188 A 188 B 188 C 189 D 189 E 189 F 190 G 190 H 190 I 190 K 190 L 190 M 190 N 191 O 191 P 191 Q 192 R 192 S 192 T 192 U 192 V 192 W 193 Y 193 Z 193 index 188