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Cost Estimation
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Table of Contents

Foreword xiii About the Authors xvii Preface xix Acronyms xxiii 1 Looking Back: Reflections on Cost Estimating 1 Reference 10 2 Introduction to Cost Estimating 11 2.1 Introduction 11 2.2 What is Cost Estimating? 11 2.3 What Are the Characteristics of a Good Cost Estimate? 13 2.4 Importance of Cost Estimating in DoD and in Congress. Why Do We Do Cost Estimating? 14 2.4.1 Importance of Cost Estimating to Congress 16 2.5 An Overview of the DoD Acquisition Process 17 2.6 Acquisition Categories (ACATs) 23 2.7 Cost Estimating Terminology 24 Summary 30 References 31 Applications and Questions 31 3 Non-DoD Acquisition and the Cost Estimating Process 32 3.1 Introduction 32 3.2 Who Practices Cost Estimation? 32 3.3 The Government Accountability Office (GAO) and the 12-Step Process 33 3.4 Cost Estimating in Other Non-DoD Agencies and Organizations 38 3.4.1 The Intelligence Community (IC) 38 3.4.2 National Aeronautics and Space Administration (NASA) 38 3.4.3 The Federal Aviation Administration (FAA) 39 3.4.4 Commercial Firms 39 3.4.5 Cost Estimating Book of Knowledge (CEBOK) 40 3.4.6 Federally Funded Research and Development Centers (FFRDCs) 41 3.4.7 The Institute for Defense Analysis (IDA) 41 3.4.8 The Mitre Corporation 42 3.4.9 Rand Corporation 42 3.5 The Cost Estimating Process 43 3.6 Definition and Planning. Knowing the Purpose of the Estimate 43 3.6.1 Definition and Planning. Defining the System 47 3.6.2 Definition and Planning. Establishing the Ground Rules and Assumptions 48 3.6.3 Definition and Planning. Selecting the Estimating Approach 49 3.6.4 Definition and Planning. Putting the Team Together 51 3.7 Data Collection 52 3.8 Formulation of the Estimate 52 3.9 Review and Documentation 53 3.10 Work Breakdown Structure (WBS) 53 3.10.1 Program Work Breakdown Structure 53 3.10.2 Military-Standard (MIL-STD) 881C 56 3.11 Cost Element Structure (CES) 56 Summary 58 References 59 Applications and Questions 59 4 Data Sources 61 4.1 Introduction 61 4.2 Background and Considerations to Data Collection 61 4.2.1 Cost Data 63 4.2.2 Technical Data 63 4.2.3 Programmatic Data 64 4.2.4 Risk Data 64 4.3 Cost Reports and Earned Value Management (EVM) 65 4.3.1 Contractor Cost Data Reporting (CCDR) 65 4.3.2 Contract Performance Report (CPR) 66 4.3.3 EVM Example 70 4.4 Cost Databases 74 4.4.1 Defense Cost and Resource Center (DCARC) 75 4.4.2 Operating and Support Costs Databases 75 4.4.3 Defense Acquisition Management Information Retrieval (DAMIR) 76 Summary 76 Reference 77 Applications and Questions 77 5 Data Normalization 78 5.1 Introduction 78 5.2 Background to Data Normalization 78 5.3 Normalizing for Content 80 5.4 Normalizing for Quantity 81 5.5 Normalizing for Inflation 83 5.6 DoD Appropriations and Background 87 5.7 Constant Year Dollars (CY$) 88 5.8 Base Year Dollars (BY$) 90 5.9 DoD Inflation Indices 91 5.10 Then Year Dollars (TY$) 95 5.11 Using the Joint Inflation Calculator (JIC) 97 5.12 Expenditure (Outlay) Profile 99 Summary 103 References 103 Applications and Questions 103 6 Statistics for Cost Estimators 105 6.1 Introduction 105 6.2 Background to Statistics 105 6.3 Margin of Error 106 6.4 Taking a Sample 109 6.5 Measures of Central Tendency 110 6.6 Dispersion Statistics 113 6.7 Coefficient of Variation 117 Summary 119 References 119 General Reference 119 Applications and Questions 119 7 Linear Regression Analysis 121 7.1 Introduction 121 7.2 Home Buying Example 121 7.3 Regression Background and Nomenclature 126 7.4 Evaluating a Regression 132 7.5 Standard Error (SE) 133 7.6 Coefficient of Variation (CV) 134 7.7 Analysis of Variance (ANOVA) 135 7.8 Coefficient of Determination (R2) 137 7.9 F-Statistic and t-Statistics 138 7.10 Regression Hierarchy 140 7.11 Staying Within the Range of Your Data 142 7.12 Treatment of Outliers 143 7.12.1 Handling Outliers with Respect to X (The Independent Variable Data) 143 7.12.2 Handling Outliers with Respect to Y (The Dependent Variable Data) 144 7.13 Residual Analysis 146 7.14 Assumptions of Ordinary Least Squares (OLS) Regression 149 Summary 149 Reference 150 Applications and Questions 150 8 Multi-Variable Linear Regression Analysis 152 8.1 Introduction 152 8.2 Background of Multi-Variable Linear Regression 152 8.3 Home Prices 154 8.4 Multi-Collinearity (MC) 158 8.5 Detecting Multi-Collinearity (MC) Method #1: Widely Varying Regression Slope Coefficients 159 8.6 Detecting Multi-Collinearity Method #2: Correlation Matrix 160 8.7 Multi-Collinearity Example #1: Home Prices 161 8.8 Determining Statistical Relationships between Independent Variables 163 8.9 Multi-Collinearity Example #2: Weapon Systems 164 8.10 Conclusions of Multi-Collinearity 167 8.11 Multi-Variable Regression Guidelines 168 Summary 169 Applications and Questions 170 9 Intrinsically Linear Regression 172 9.1 Introduction 172 9.2 Background of Intrinsically Linear Regression 172 9.3 The Multiplicative Model 173 9.4 Data Transformation 174 9.5 Interpreting the Regression Results 178 Summary 178 Reference 179 Applications and Questions 179 10 Learning Curves: Unit Theory 180 10.1 Introduction 180 10.2 Learning Curve Scenario #1 180 10.3 Cumulative AverageTheory Overview 182 10.4 UnitTheory Overview 182 10.5 UnitTheory 185 10.6 Estimating Lot Costs 188 10.7 Fitting a Curve Using Lot Data 191 10.7.1 Lot Midpoint 192 10.7.2 Average Unit Cost (AUC) 194 10.8 UnitTheory Final Example (Example 10.5) 197 10.9 Alternative LMP and Lot Cost Calculations 200 Summary 202 References 202 Applications and Questions 202 11 Learning Curves: Cumulative Average Theory 204 11.1 Introduction 204 11.2 Background of Cumulative AverageTheory (CAT) 204 11.3 Cumulative AverageTheory 206 11.4 Estimating Lot Costs 210 11.5 Cumulative AverageTheory Final Example 210 11.6 UnitTheory vs. Cumulative AverageTheory 214 11.6.1 Learning Curve Selection 215 Summary 216 Applications and Questions 216 12 Learning Curves: Production Breaks/Lost Learning 218 12.1 Introduction 218 12.2 The Lost Learning Process 219 12.3 Production Break Scenario 219 12.4 The Anderlohr Method 220 12.5 Production Breaks Example 221 12.6 The Retrograde Method Example 12.1 (Part 2) 224 Summary 229 References 229 Applications and Questions 230 13 Wrap Rates and Step-Down Functions 231 13.1 Introduction 231 13.2 Wrap Rate Overview 231 13.3 Wrap Rate Components 232 13.3.1 Direct Labor Rate 233 13.3.2 Overhead Rate 233 13.3.3 Other Costs 234 13.4 Wrap Rate Final Example (Example 13.2) 235 13.5 Summary of Wrap Rates 236 13.6 Introduction to Step-Down Functions 236 13.7 Step-Down Function Theory 237 13.8 Step-Down Function Example 13.1 238 13.9 Summary of Step-Down Functions 240 Reference 240 Applications and Questions 240 14 Cost Factors and the Analogy Technique 242 14.1 Introduction 242 14.2 Cost Factors Scenario 242 14.3 Cost Factors 243 14.4 Which Factor to Use? 246 14.5 Cost Factors Handbooks 246 14.6 Unified Facilities Criteria (UFC) 247 14.7 Summary of Cost Factors 248 14.8 Introduction to the Analogy Technique 248 14.9 Background of Analogy 249 14.10 Methodology 250 14.11 Example 14.1 Part 1: The Historical WBS 250 14.12 Example 14.1 Part 2: The New WBS 253 14.13 Summary of the Analogy Technique 255 Reference 256 Applications and Questions 256 15 Software Cost Estimation 257 15.1 Introduction 257 15.2 Background on Software Cost Estimation 257 15.3 What is Software? 258 15.4 The WBS Elements in a typical Software Cost Estimating Task 259 15.5 Software Costing Characteristics and Concerns 260 15.6 Measuring Software Size: Source Lines of Code (SLOC) and Function Points (FP) 261 15.6.1 Source Lines of Code: (SLOC) 261 15.6.2 Function Point (FP) Analysis 263 15.7 The Software Cost Estimating Process 264 15.8 Problems with Software Cost Estimating: Cost Growth 265 15.9 Commercial Software Availability 267 15.9.1 COTS in the Software Environment 268 15.10 Post Development Software Maintenance Costs 268 Summary 269 References 269 16 Cost Benefit Analysis and Risk and Uncertainty 270 16.1 Introduction 270 16.2 Cost Benefit Analysis (CBA) and Net Present Value (NPV) Overview 270 16.3 Time Value of Money 273 16.4 Example 16.1. Net Present Value 277 16.5 Risk and Uncertainty Overview 281 16.6 Considerations for Handling Risk and Uncertainty 283 16.7 How do the Uncertainties Affect our Estimate? 284 16.8 Cumulative Cost and Monte Carlo Simulation 287 16.9 Suggested Resources on Risk and Uncertainty Analysis 289 Summary 290 References 290 Applications and Questions 290 17 Epilogue: The Field of Cost Estimating and Analysis 291 Answers to Questions 295 Index 309

About the Author

Gregory K. Mislick is Senior Lecturer in theDepartment of Operations Research and Program Manager for theMasters Degree Program in Cost Estimating and Analysis at the NavalPostgraduate School (NPS). A retired U.S. Marine Corps LieutenantColonel aviator and past associate dean of the GraduateSchool of Operational and Information Sciences at NPS, hisresearch interests includes life cycle cost estimating andmodeling, probability and statistics, regression analysis, learningcurves, and optimization. Daniel A. Nussbaum, PhD, is Visiting Professor in theDepartment of Operations Research at the Naval Postgraduate Schoolin Monterey, California. With over 30 years of professionalexperience providing financial estimating and analysis services tosenior levels of the U.S. Federal government, Dr. Nussbaum'sresearch interests includes cost/benefit analyses, life cycle costestimating and modeling, and financial modeling.

Reviews

"This book is a manual of how to effectively internally manage a company, and maximise operational external efficiency of a contractor. On this basis it is essential reading for anyone in a decision-taking role, even if only a relatively minor role in bringing productions to market." (Chromatographia 2016)

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