This is a graph with unusual units. The horizontal axis measures the date. The vertical axis measures the estimated date of completion of the project I’m working on. The top line is a 95% estimate, the middle line is a 50% estimate, and the lower line is a 5% estimate.
So, for example, on Friday, September 10th, the estimate was that there was a 50% chance that I’d finish by September 24th. Today, September 14.5th, there’s a 95% chance I’ll be done by by October 29th. And, if everything goes REALLY WELL, there’s a 5% chance the project will be done by October 6th!
The completion dates keep moving up because I keep adding new tasks to complete. At the beginning (September 7th) I thought there were about 30 things to do, each taking a half-hour, so the estimates showed me finishing in a couple of days. Since then I’ve added a lot (A LOT) of things to do, many taking multiple hours, so the estimates show me finishing much later. If I complete some tasks faster than I estimated, the completion date will move closer. If I repeatedly take longer than I thought on multiple tasks, the program making these estimates starts to automatically inflate the times I enter.
What’s happening here? Will the project ever actually be completed? What should happen to the lines as the date marches on?
How would you lead your students to understand what these lines mean? They should be able to answer the following questions:
- What would the lines look like if the project was running perfectly on schedule?
- Which days seem to be the most productive?
- What is the maximum estimate/date slope that a project could have if it was going to actually be finished?
- Given the average estimate/date slope of a project, how could you figure out when the project will actually be finished?
- What makes the lines move farther apart from each other or closer together??