A budget estimate in project management is a prediction of the financial resources (such as money, materials, and personnel) that will be required to complete a project. It is an important tool for determining the feasibility of a project and for creating a plan for allocating resources. A budget estimate may be developed using a variety of techniques, such as historical data, expert judgment, or mathematical models. It is typically reviewed and updated regularly throughout the project to ensure that resources are being used effectively and that the project is on track to meet its financial goals.
Types of budget estimates
There are several types of budget estimates that can be used in project management, including:
- Bottom-up estimate: This type of estimate is created by breaking down the project into smaller, more manageable components and estimating the cost of each component individually.
- Top-down estimate: This type of estimate is created by starting with an overall project cost and then breaking it down into smaller components.
- Analogous estimate: This type of estimate is created by using the cost of a similar past project as a starting point.
- Parametric estimate: This type of estimate is created by using mathematical models and statistical data to estimate the cost of a project.
- Three-point estimate: This type of estimate is created by developing three different cost estimates for a project: best-case, most likely, and worst-case scenarios.
- Three-point estimate (PERT): This type of estimate is similar to Three-point estimate, but it uses a probability distribution to estimate the cost.
- Reserve analysis: This type of estimate is created by adding a contingency fund to the budget, which can be used to cover unexpected expenses.
It's important to note that there is no one-size-fits-all approach to budget estimates, and the appropriate method may depend on the specific project, organization, and industry.
- Kwon, H., & Kang, C. W. (2019). Improving project budget estimation accuracy and precision by analyzing reserves for both identified and unidentified risks. Project Management Journal, 50(1), 86-100.
- Oberlender, G. D., & Oberlender, G. D. (1993). Project management for engineering and construction (Vol. 2). New York: McGraw-Hill.
- Kwak, Y. H., & Ingall, L. (2007). Exploring Monte Carlo simulation applications for project management. Risk management, 9(1), 44-57.