A major challenge for software professionals interpreting data is deciding what's real and what isn't, what matters and what doesn't. A useful way to think about it is that you are trying to find the signal in the noise produced by random variation and error. Here is advice on how to extract the useful information from the "noise."

When you approach a process problem in the way your workgroup functions, you're implementing an organizational change. Organizations are systems of complex interrelationships. Explicit models can help you make strategic changes.

Tracking your project goals lets you know how well your improvement program is going, provides visibility early to detect problems, and gives you data to make your future plans more effective. Here's how to measure improvement based on your project's goals and problems.

Your numbers are solid and your graphs are works of art. Now boost your metrics' value through the roof with some simple annotations that will put all that data in context.