In our experience the mistake of “waiting for perfect data” probably kills more projects than any other. Here’s a typical scenario:
The project starts out well. The management team defines the goals, calculates the potential return on investment, develops a project plan, gets a budget approved, assembles the team, and launches the project. The trouble starts with a desire to make sure that the data is in “good” condition.