How do you properly compare the quality of two or more software deliverables without an accurate normalizing metric? The answer: You can’t. Example: If project A has one-hundred defects and project B has fifty defects, do you automatically assume project B is a higher quality deliverable? Although the number of defects is often the end user’s quality perception, defect counts may not be the right measure. An effective normalizing metric allows you to accurately measure and compare quality levels across software deliverables. David Herron explains how to quickly and easily incorporate this important normalizing metric into your development process to start measuring and improving the quality of your software deliverables. You’ll have a new tool for managing end user expectations regarding software quality in relation to the value the software delivers. Even more, you can use this normalizing metric to predict software quality outcomes or delivery dates and to establish service levels for software quality.