Project Management Chapter 5: Direct Project Costs and Work Packages Quiz

Study Notes

Estimating is the process of forecasting or approximating the time and cost of completing project deliverables.
It's a trade-off, balancing the benefits of better accuracy against the costs of securing increased accuracy.

Top-down (macro) estimates: analogy, group consensus, or mathematical relationships
Bottom-up (micro) estimates: based on estimates of elements found in the work breakdown structure

Top-down estimates: usually derived from someone who uses experience and/or information to determine the project duration and total cost
Bottom-up estimates: can take place after the project has been defined in detail, can serve as a check on cost elements in the WBS, and provide the customer with an opportunity to compare the low-cost, efficient method approach with any imposed restrictions

Top-down approaches: consensus method, ratio method, apportion method, function point methods for software and system projects, learning curves
Bottom-up approaches: template method, parametric procedures applied to specific tasks, range estimating

The level of detail in the WBS varies with the complexity of the project, the need for control, the project size, cost, and duration, and other factors
Excessive detail: emphasizes departmental outcomes rather than deliverable outcomes, creates more unproductive paperwork
Inadequate detail: falls short of meeting the structure's needs

Direct costs: clearly chargeable to a specific work package, examples: labor, materials, equipment, and other
Direct project overhead costs: can be tied to project deliverables or work packages, examples: salary of the project manager, temporary rental space for the project team, supplies, specialized machinery
General and administrative (G&A) overhead costs: not directly linked to a specific project, examples: advertising, accounting, salary of senior management above the project level

Reasons for adjusting estimates: interaction costs are hidden in estimates, normal conditions do not apply, things go wrong on projects, project scope and plans change, people are overly optimistic, people engage in strategic misrepresentation

Database for estimating: a repository of historical data to support future estimates

Mega projects: large-scale, complex ventures that typically cost $1 billion or more, take many years to complete, and involve multiple private and public stakeholders
Examples: high-speed rail lines, airports, healthcare reform, the Olympics, development of new aircraft
Mega projects often involve a double whammy: projects cost much more than expected and under-deliver on benefits the projects were to provide
Sometimes referred to as “white elephant”: projects are over budget, under value, and the costs of maintaining the project exceed the benefits received

Three major steps: select a reference class of projects similar to your potential project, collect and arrange outcome data as a distribution, and use the distribution data to arrive at a realistic forecast
Benefits: outside empirical data mitigates human bias, politics, strategic, and promoter forces have difficulty ignoring outside RCF information, RCF serves as a reality check for funding large projects, RCF helps executives avoid unsound optimism, and RCF leads to improved accountability