Schedule compression is a tactic that seeks to deliver a task or activity faster than estimated or planned. This is often inefficient and costly but is sometimes required as delivering something quickly can have significant advantages. Likewise, opportunities are often time-bound such that they can pass if you don't deliver something before a deadline. The following are common types of time compression.
Fast Tracking
Completing tasks with dependencies in parallel.
Crashing
Adding more resources to key tasks.
Best Effort Basis
Asking teams and contributors to do their best to deliver faster.
Overtime
Paying teams to work longer hours.
Minimum Viable Product
Cutting back scope to what is truly required.
Pareto Analysis
Identifying the 20% of tasks that produce 80% of value.
Resource Optimization
Assigning your highest performing resources to a critical task.
Task Optimization
Identifying the most efficient way to complete a task.
Batches
Completing similar tasks together in a batch.
Debottlenecking
Removing constraints that are slowing things down such as meetings.
Last Responsible Moment
Delaying non-critical tasks until they really need to be done.
Lean Thinking
Determining how to do things the smallest and most practical way.
Charrettes
Putting a group in a room together until a task is done.
Schedule compression can increase risk, reduce quality, impact morale, reduce stakeholder support and cause a project to fail. Accountable stakeholders should sign off on the risks of schedule compression before it is undertaken.
In some cases, schedule compression will actually increase the time required to complete a task. This is particularly true of fast tracking and crashing. Fast tracking introduces the overhead of trying to resolve task dependencies in a more dynamic way. Crashing introduces the overhead of communicating and collaborating between more people. This problem is humorously summarized as "nine mothers can't have a child in one month."Next: Minimum Viable Product
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