Okay – so we admit that we tend to “pad” our estimates a bit in order to give a higher confidence level in the completion of our tasks, and therefore of projects. So why doesn’t it work?
Let’s look at what happens in typical project environments when it comes to task duration performance.
There are a few key phenomenon that exist in most environments:
- Student Syndrome
- Parkinson’s Law
- Multi-Tasking
Student Syndrome is essentially the “procrastination” issue – when faced with multiple possible tasks on which one can work, and if we feel we have sufficient time in a task, it will typically get prioritized lower on our “to do” list.
The student syndrome graph above shows how this phenomena occurs – at the beginning of a task we might put forth some effort – but given we have other, “hotter” issues on our plate, this one can wait given we have “plenty of time”. So, as the task due date approaches, what happens. Our activity level will begin to increase as it suddenly becomes a time priority for us – if negative variability (“Murphy”) then occurs, we are at risk of missing our task due date – as such, even though we had more than enough time allotted for this task, when negative variability hit, we no longer had the “recovery time” – and missed our due date.
Parkinson’s Law essentially states that work will stretch to fill the time available. This may not make sense to you right away, but think about a project management environment where tasks are not well defined – particularly within a development environment (software development, for instance) – it is not unusual for there not to be a clear definition of what “good enough” is for a task. If I’m a programmer working on a task, and the “completion criteria” for that task is not clearly defined, I will tend to work on it for the amount of time allotted – even if in half that time I effectively accomplished what was required for that task. The reason is if I have time remaining I will continue to “polish” – to work until the time is up and then release it into the system.
Multi-tasking is enemy number one of productivity for project management. The irony is it makes people feel very productive – but there is a difference between being productive and simply being busy. Take the following example:

The three tasks above each take one week. If we were to do them serially, one at a time, task A would finish in one week, task B would finish at end of week 2 and task C would finish at the end of week 3. However, to be really “productive”, we will work on all of them. In other words, rather than finishing one before moving on to the next, we will work on part of a task, then work on another, then another, and then come back and finish the original task. The result is the picture below.

Now, task A finishes in two weeks rather than 1, task B finishes at end of 2.5 weeks instead of 2 and task C finishes in 3 weeks (which it did in original picture as well) – but what are we forgetting? Set-up and switchover time – any time you switch from one task to another and back you have to re-orient yourself with the work. So, in fact, task C would not finish in week 3 in the second scenario but some time after.
Multi-tasking is caused, primarily, due to a lack of prioritization and synchronization within our project management system. Success or failure of a project does not rely upon the amount of safety time put into the project – it relies on the velocity with which we make progress through the project. The keys are in the execution – effective synchronization, prioritization, real-time visibility into the status of the project, and the ability to focus in on those relatively few points in a project that, at any given time, are getting the progress.
The safety issue is relatively minor – in fact, we can cut generally cut about half of the safety out of a project and still execute it on time. How? What is missing in the “conventional” approach?
A project, like any system, is a chain – a chain of dependent events. Nothing happens in isolation. So what is key is how those tasks interact and the manner in which we execute.
In short, then, regardless of how much safety time we embed within a project, the manner in which we manage resources, prioritize (or more likely don’t prioritize) tasks and release new projects into the system without regard for the load of the system is the primary reason projects fail.
Next installment – the beginning of the solution!
For now – here’s a video of the US Navy’s presentation on their success with the Critical Chain approach.