Companies run on money. There is nothing more frustrating than not being to start a fun project because there is no money in the budget. So running "under budget" is good, no?

It depends on why you are running under budget. Often it means you do not have enough staffing in place to do the work forecasted. If that is the case, then your schedule is in peril, and you will probably go over budget to complete the forecasted work.

Most times, budgets are compared to the calendar (were you over budget or under this month?). This is a convenient way a company can keep score overall. However, in addition to watching money spending versus calendar, each manager should also be looking at money spent compared to work completed. If you have spent 40% of your budget and 50% of the work is done (and you are still on schedule), then you should be congratulated. If you have spent 50% of your budget and 40% of the work is done, then you have a problem, even if the 50% of the budget you spent is less than projected on a calendar basis. (Or if you have spent 50% of your budget and 50% of the work is done but you are still running under budget on a calendar basis, that points to slips in the schedule—also bad). These examples show another way of measuring performance that can give you an early warning of schedule problems.

This comparison of spending to work completed highlights the reason it is important to monitor task progress. Most good program managers will break down a project into tasks and then monitor completion progress (are you now 30% complete on this task? 40%?). Sometimes this is formalized through the company accounting system by assigning separate charge numbers for each task (sometimes called a WBS or work breakdown schedule). However, the comparison to work completed is seldom collected by a formal system. It is still up the manager to periodically ask how much of each task is done, then check that against the dollars spent.

And as is often the case with data collection, accuracy of the data can wildly affect the results. In other words, if the task completion status data collected is not accurate, the conclusions drawn are likely wrong.

-Don Burtis