Statistical Techniques for Project Control
Features
- Presents qualitative managerial tools for project control
- Covers statistical tools in a non-intimidating way
- Includes conventional project network analysis
- Contains practical case studies
- Uses graphical representations and figures generously to convey knowledge
Summary
Winner of the IIE Book of the Month for June 2012
A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control.
The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitative human judgment that makes project control nebulous but also offers opportunities to innovate and be creative in achieving control. The authors then discuss the three factors (time, budget, and performance) that form the basis of the operating characteristics of a project that also help determine the basis for project control. They then focus on computational network techniques for project schedule (time) control.
Although designed as a practical guide for project management professionals, the book also appeals to students, researchers, and instructors.
Table of Contents
Fundamentals of Project Management
Why Projects Fail
Management by Project
Integrated Project Implementation
Critical Factors for Project Success
Early Systems Engineering
DODAF Systems Architecture for Project Management
Project Management Body of Knowledge (PMBOK®)
Project Systems Structure
Project Systems Implementation Outline
Value of Lean Times
Project Decision Analysis
Systems Group Decision-Making Models
Hierarchy of Project Control
Statistics for Project Control
Modeling Project Environment
Use of Statistics in Project Control
Normal Distribution
Relationship to Six Sigma
Statistical Averages
Statistical Thinking: Computational Examples
Factors of Project Control
Examples of Statistics for Project Control
Statistics for Production Changeovers
General Control Steps
Formal and Informal Control
Schedule Control
Performance Control
Continuous Performance Improvement
Cost Control
Information Required for Project Control
Control Charts
Project Time Control
Critical Path Method
Determination of Critical Activities
Using Forward Pass to Determine Critical Path
Subcritical Paths
Gantt Chart
Activity Crashing and Schedule Compression
PERT Network Analysis
Modeling Activity Times
Beta Distribution
Triangular Distribution
Uniform Distribution
Statistical Analysis of Project Duration
Precedence Diagramming
Reverse Criticality in PDM Networks
References
Project Performance Control
Importance of Work Performance Measurement
Basic Techniques of Performance Work Sampling
Performance Confidence Interval
Sample Size Calculations
Control Charts for Performance Control
Applications of Work Sampling
Learning Curve Analysis for Performance Control
Univariate Learning Curve Models
Impacts of Multivariate Learning Curves
Summary of Cost, Time, and Performance Formulas
References
Project Cost Control
Cost Concepts and Definitions
Project Cash Flow Analysis
Effects of Inflation
Breakeven Analysis
Profit Ratio Analysis
Amortization of Capital
Project Cost Estimation
Budgeting and Capital Allocation
Cost Monitoring
Project Balance Technique
Activity-Based Costing
References
Project Quality Control
Quality Management: Step-By-Step Implementation
Six Sigma and Quality Management
Taguchi Loss Function
Identification and Elimination of Sources of Defects
Roles and Responsibilities for Six Sigma
Process Capability Analysis for Six Sigma
Lean Principles and Applications
Lean Six Sigma in Project Management
Lean Principles for Project Control
Lean and Six Sigma
Pull Technique
Lean Action Plan
Six Sigma and Statistical Modeling
Six Sigma and Statistics
Selecting Proper Statistical Techniques
Six Sigma Methodology
Hypothesis Testing
t Testing
Confidence Interval
Capability Analysis
Gage R&R
Project Control Case Studies
Gage R&R
Capability Studies
Analytical Studies
Multivariate Studies
Management Support for Project Control
Leadership
SigmSResource Allocation by Management
Appendix: Useful Statistical Distributions
Index
