Statistical Techniques for Project Control

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.

Fundamentals of Project ManagementWhy Projects FailManagement by ProjectIntegrated Project ImplementationCritical Factors for Project SuccessEarly Systems EngineeringDODAF Systems Architecture for Project ManagementProject Management Body of Knowledge (PMBOK®) Project Systems Structure Project Systems Implementation Outline Value of Lean Times Project Decision AnalysisSystems Group Decision-Making ModelsHierarchy of Project ControlStatistics for Project Control Modeling Project Environment Use of Statistics in Project ControlNormal DistributionRelationship to Six SigmaStatistical AveragesStatistical Thinking: Computational ExamplesFactors of Project Control Examples of Statistics for Project ControlStatistics for Production ChangeoversGeneral Control StepsFormal and Informal ControlSchedule ControlPerformance ControlContinuous Performance ImprovementCost ControlInformation Required for Project Control Control ChartsProject Time ControlCritical Path MethodDetermination of Critical ActivitiesUsing 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 DiagrammingReverse 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 TechniqueActivity-Based CostingReferences 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 SigmaLean Principles and ApplicationsLean Six Sigma in Project Management Lean Principles for Project Control Lean and Six Sigma Pull TechniqueLean Action PlanSix Sigma and Statistical Modeling Six Sigma and Statistics Selecting Proper Statistical TechniquesSix Sigma MethodologyHypothesis Testing t Testing Confidence Interval Capability AnalysisGage R&RProject Control Case Studies Gage R&R Capability Studies Analytical Studies Multivariate Studies Management Support for Project ControlLeadershipSigmSResource Allocation by ManagementAppendix: Useful Statistical DistributionsIndex

Adedeji B. Badiru, Tina Agustiady