Cost Estimation: Methods and Tools

ISBN-13: 9781118536131 / Angielski / Twarda / 2015 / 344 str.

Daniel A. Nussbaum; Gregory K. Mislick

Opis

Presents an accessible approach to the cost estimation tools, concepts, and techniques needed to support analytical and cost decisions Written with an easy-to-understand approach, Cost Estimation: Methods and Tools provides comprehensive coverage of the quantitative techniques needed by professional cost estimators and for those wanting to learn about this vibrant career field. Featuring the underlying mathematical and analytical principles of cost estimation, the book focuses on the tools and methods used to predict the research and development, production, and operating and support costs for successful cost estimation in industrial, business, and manufacturing processes. The book begins with a detailed historical perspective and key terms of the cost estimating field in order to develop the necessary background prior to implementing the presented quantitative methods. The book proceeds to fundamental cost estimation methods utilized in the field of cost estimation, including working with inflation indices, regression analysis, learning curves, analogies, cost factors, and wrap rates. With a step-by-step introduction to the practicality of cost estimation and the available resources for obtaining relevant data, Cost Estimation: Methods and Tools also features:

• Various cost estimating tools, concepts, and techniques needed to support business decisions
• Multiple questions at the end of each chapter to help readers obtain a deeper understanding of the discussed methods and techniques
• An overview of the software used in cost estimation, as well as an introduction to the application of risk and uncertainty analysis
• A Foreword from Dr. Douglas A. Brook, a professor in the Graduate School of Business and Public Policy at the Naval Postgraduate School, who spent many years working in the Department of Defense acquisition environment

Cost Estimation: Methods and Tools is an excellent reference for academics and practitioners in decision science, operations research, operations management, business, and systems and industrial engineering, as well as a useful guide in support of professional cost estimation training and certification courses for practitioners. The book is also appropriate for graduate-level courses in operations research, operations management, engineering economics, and manufacturing and/or production processes.

Recenzje

"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)

Spis treści

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

O autorze

Gregory K. Mislick is Senior Lecturer in the Department of Operations Research and Program Manager for the Masters Degree Program in Cost Estimating and Analysis at the Naval Postgraduate School (NPS). A retired U.S. Marine Corps Lieutenant Colonel aviator and past associate dean of the Graduate School of Operational and Information Sciences at NPS, his research interests includes life cycle cost estimating and modeling, probability and statistics, regression analysis, learning curves, and optimization.

Daniel A. Nussbaum, PhD, is Visiting Professor in the Department of Operations Research at the Naval Postgraduate School in Monterey, California. With over 30 years of professional experience providing financial estimating and analysis services to senior levels of the U.S. Federal government, Dr. Nussbaum′s research interests includes cost/benefit analyses, life cycle cost estimating and modeling, and financial modeling.

Blurb

Presents an accessible approach to the cost estimation tools, concepts, and techniques needed to support analytical and cost decisions

Written with an easy–to–understand approach, Cost Estimation: Methods and Tools provides comprehensive coverage of the quantitative techniques needed by professional cost estimators and for those wanting to learn about this vibrant career field. Featuring the underlying mathematical and analytical principles of cost estimation, the book focuses on the tools and methods used to predict the research and development, production, and operating and support costs for successful cost estimation in industrial, business, and manufacturing processes.

The book begins with a detailed historical perspective and key terms of the cost estimating field in order to develop the necessary background prior to implementing the presented quantitative methods. The book proceeds to the fundamental cost estimation methods utilized in the field of cost estimation, including working with inflation indices, regression analysis, learning curves, analogies, cost factors, and wrap rates. With a step–by–step introduction to the practicality of cost estimation and the available resources for obtaining relevant data, Cost Estimation: Methods and Tools also features:

• Various cost estimating tools, concepts, and techniques needed to support business decisions
• Multiple questions at the end of each chapter to help readers obtain a deeper understanding of the discussed methods and techniques
• An overview of the software used in cost estimation, as well as introducing the application of risk and uncertainty analysis
• A Foreword from Dr. Douglas A. Brook, a professor from the Graduate School of Business and Public Policy at the Naval Postgraduate School who spent many years working in the Department of Defense acquisition environment

Cost Estimation: Methods and Tools is an excellent reference for academics and practitioners in decision science, operations research, operations management, business, and systems and industrial engineering, as well as a useful guide in support of professional cost estimation training and certification courses for practitioners. The book is also appropriate for graduate–level courses in operations research, operations management, engineering economics, and manufacturing and/or production processes.

Gregory K. Mislick is Senior Lecturer in the Department of Operations Research and Program Manager for the Masters Degree Program in Cost Estimating and Analysis at the Naval Postgraduate School (NPS). A retired U.S. Marine Corps Lieutenant Colonel aviator and past associate dean of the Graduate School of Operational and Information Sciences at NPS, his research interests includes life cycle cost estimating and modeling, probability and statistics, regression analysis, learning curves, and optimization.

Daniel A. Nussbaum, PhD, is Visiting Professor in the Department of Operations Research at the Naval Postgraduate School in Monterey, California. With over 30 years of professional experience providing financial estimating and analysis services to senior levels of the U.S. Federal government, Dr. Nussbaum′s research interests includes cost/benefit analyses, life cycle cost estimating and modeling, and financial modeling.