Schedule Compression Determination

I would warn him about increased cost in terms of resources/extra work and ask him if all the stakeholders are willing to do a trade off in cost/risk to cut the time down. If he agrees to this point, I would give him a date on which I can give him a detailed explanation of what I am proposing to cut the time down and the revised schedule for consideration.

There are two options which I would consider – Crashing or Fast Tracking – to perform the Schedule Compression. I would consider the following factors to do the homework –

1. Identify the critical path and find where I can apply more resources to get more work done in lesser time, so that total time on critical path is reduced

2. Identify parallel activities that can be executed at the same time.

3. Identify other important activities that takes more time and which are not there in the critical path.

I would determine which method I would use to perform schedule compression as follows –

1. If I find that there are activities in the critical path or other time consuming activities which can be assigned to more resources, I would list them down and determine revised resource allocation, revised critical path, amount of time reduced and extra cost required to maitain new resources and work coordination.

2. I would also list down activities that can be done in parallel, inherent risk on the the total project while executing activities in parallel, and extra cost involved to execute and coordinate parallel activities and total reduction in time.

3. From step 1 and step 2, I would determine which one gives me lowest cost/risk and highest reduction in overall time. If step 1 satisfies this condition, I would suggest Crashing or else I would suggest Fast Tracking. Which ever method I select, I would prepare revised project schedule and compile written procedure to follow for performing the opted method of schedule compression. For example – how many resources to be hired to be allocated for a particular task or which all activities can be executed in parallel and how.