We often hear of project management and design patterns in computer science, but less frequently in statistical analysis. However, it seems that a decisive step toward designing an effective and durable statistical project is to keep things organized.
I often advocate the use of R and a consistent organization of files in separate folders (raw data file, transformed data file, R scripts, figures, notes, etc.). The main reason for this approach is that it may be easier to run your analysis later (when you forgot how you happened to produce a given plot, for instance).
What are the best practices for statistical project management, or the recommendations you would like to give from your own experience? Of course, this applies to any statistical software. (one answer per post, please)