Hope project management!
The sooner you move away from project management activities based upon hope, the sooner your organization makes a recovery to the efficient enterprise you desire.
I have noticed a rash of project schedules wherein each task lays end to end as if the prediction of the; task start, progress, and completion times are known without question. When asked how the project team arrives at the schedule, invariably the tasks must fit like this to make the delivery date. Asking what information they have to support the duration estimates, for example, historical record, no one can provide any such information. This method of project management delays disappointment and ultimately is not a recipe for continued success.
Use what you learn as you execute the individual activities within the project. Learn of the possible duration from the previous work history. If you do not have the history because this is a new activity there are other solutions to the “fixed date debacle” that has no logical source (other than because I hope it to be so). The close monitoring of key areas of progress is what gives the agile methodologies one of the perceived benefits. With that method, we learn and adjust our project plan, as we understand what is possible or more importantly – probable. In our book Total Quality Management for Project Managers, we show how metrics and historical execution can tell you the things you need to know about your company’s ability to deliver. Use these key TQM tools to understand the range of performance of the stations within your organization. Apply these same tools used for manufacturing toward your project activities to assess process performance, identify the problem areas, and prioritize those areas for improvement. Use the information to put schedules together that have some historical ranges behind them.
Instead of making up, dates and duration with little knowledge and hoping things will work out, monitor performance and predict the outcome. Quit pretending that it is possible to predict the delivery day or duration as a single point source date or time 1-2 years out.