MANGT 515 Prospective Students
Sample Syllabus
Sample Lesson
Introduction
2.1 Reasons for Forecasting in Project Management
2.2 Forecasting Methods for Projects
2.2.1 Qualitative Forecasting Methods
2.2.2 Quantitative Forecasting Methods
Time Series Analysis
Short Term Forecasting Methods
Naïve Approach
Simple Averages
Moving Averages
Exponential Smoothing
Example of Exponential Smoothing
Trend-Adjusted Exponential Smoothing
Example of Trend-Adjusted Exponential Smoothing
2.3 Intermediate Term Forecasting
Example of Linear Regression
Evaluating the "Fit" of the Regression Line
2.3.2 The Correlation Coefficient (r)
2.3.3. The Standard Error of the Estimate (syx)
2.3.4 Limitations in Forecasting Using Linear Regression
2.3.4 Limitations in Forecasting Using Linear Regression (continued)
2.4 Forecasting the Project End Conditions
2.5 S-curve Forecasting
2.6 Technological Forecasting*

Lesson 2: Forecasting Methods in Project Management

Introduction

Forecasting is a critical and a fundamental process for any business, and project organizations are no exceptions. Forecasting is at the front end of the project environment. Forecasts of demand, activity times and the associated cost of these activities are prime inputs for planning the project and controlling project progress. Forecasting is the also one of the primary means for tracking project progress or for changing its direction if one is needed due to changes in the project environment. For example, forecasting technology will enable a project organization to rapidly respond to changes in the technological environment of the project is to ensure that changes in technology do not make the current project's facility obsolete. In this lesson, you will learn about the types of forecasts that are needed in a project environment and some of the important techniques that can be used to generate such forecasts.

Objectives

After completing this lesson you should be able to: