How to Estimate Effort and Duration in Project 2013
Developing accurate estimates — whether for resources, durations, or costs — is one of the most challenging and contentious parts of managing a project. You should understand the nature of estimating and the difference between the effort needed to accomplish the work and the duration, which indicates the number of required work periods (activity duration) in Project 2013.
Several techniques are available to help you develop estimates, depending on the nature of the work. You can start by looking at the difference between effort and duration and then at the skills you need to develop accurate estimates.
Effort is number of labor units required to complete a task. Effort is usually expressed as staff hours, staff days, or staff weeks.
Duration is the total number of work periods (not including holidays or other nonworking periods) required to complete a task. Duration is usually expressed as workdays or workweeks.
Sometimes, people seem to estimate durations by snatching them out of the air or consulting a Magic 8 Ball. Estimating is undoubtedly an art and a science.
The art stems from the expert judgment that team members and estimators bring to the process. Their experience and wisdom from past projects are invaluable in developing estimates, determining the best estimating method, and evaluating estimates (or the assumptions behind them) to assess their validity. In addition to the artful contribution of experts, team members, and estimators, a number of methods comprise the science of estimating.
Analogous estimating is the most common method of estimating. The aforementioned experts normally conduct this form of estimating. In its most basic form, this method compares past projects with the current project, determines their areas of similarity and areas of difference, and then develops an estimate accordingly.
A more robust application determines the duration drivers and analyzes the relationship between past similar projects with the current project. Duration drivers can include size, complexity, risk, number of resources, weight, or whatever other aspects of the project influence duration.
If you want to use analogous estimating effectively, your projects must be similar in fact, not simply similar in appearance. A software upgrade may sound similar to someone who is not familiar with software, but there are vast differences in what a software upgrade entails, so one software upgrade is not necessarily similar to others.
Parametric estimating uses a mathematical model to determine project duration. Though not all work can be estimated using this method, it’s quick and simple: Multiply the quantity of work by the number of hours required to accomplish it.
For example, if a painter can paint 100 square feet per hour and you have 6,000 square feet to paint, you can assume 60 hours of effort. If three people are painting (60 ÷ 3), the task should take 20 hours, or the equivalent of 2.5 days.
When a lot of uncertainty, risk, or unknown factors surround an activity or a work package, you can use three-point estimating to produce a range and an expected duration. In this method, you collect three estimates based on these types of scenarios:
Best case: In this optimistic (represented by the letter O) scenario, all required resources are available, nothing goes wrong, and everything works correctly the first time.
Most likely: The realities of project life are factored into the estimate, such as the extended unavailability of a resource, a work interruption, or an error that causes a delay. This is the most-likely (or M) scenario.
Worst case: This pessimistic (P) estimate assumes unskilled resources, or insufficient resources, a great deal of rework, and delays.
The simplest way to develop the expected duration is to sum the three estimates and divide by 3. However, this technique isn’t the most accurate one because it assumes — unrealistically — an equal probability that the best-case, most-likely, and worst-case scenarios would occur.
In reality, the most-likely estimate has a greater chance of occurring than either the best-case or worst-case scenarios. Therefore, weight the most-likely scenario and determine the weighted average.