Principles, process and practice of professional number juggling

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Abingdon, Oxon ; Routledge, 2019.
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English
ISBN
9781315160054, 1315160056, 9781351661348, 1351661345

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Bibliography
Includes bibliographical references and index.
Description
Principles, Process and Practice of Professional Number Juggling (Volume 1 of the Working Guides to Estimating & Forecasting series) sets the scene of TRACEability and good estimate practice that is followed in the other volumes in this series of five working guides. It clarifies the difference between an Estimating Process, Procedure, Approach, Method and Technique. It expands on these definitions of Approach (Top-down, Bottom-up and'Ethereal') and Method (Analogy, Parametric and 'Trusted Source') and discusses how these form the basis of all other means of establishing an estimate. This volume also underlines the importance of 'data normalisation' in any estimating procedure, and demonstrates that the Estimating by Analogy Method, in essence, is a simple extension of Data Normalisation. The author looks at simple measures of assessing the maturity or health of an estimate, and offers a means of assessing a spreadsheet for any inherent risks or errors that may be introduced by failing to follow good practice in spreadsheet design and build. This book provides a taster of the more numerical techniques covered in the remainder of the series by considering how an estimator can potentially exploit Benford's Law (traditionally used in Fraud Detection) to identify systematic bias from third party contributors. It will be a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.
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O'Reilly,O'Reilly Online Learning: Academic/Public Library Edition

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APA Citation, 7th Edition (style guide)

Jones, A. 1. (2019). Principles, process and practice of professional number juggling . Routledge.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Jones, Alan 1953-. 2019. Principles, Process and Practice of Professional Number Juggling. Routledge.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Jones, Alan 1953-. Principles, Process and Practice of Professional Number Juggling Routledge, 2019.

MLA Citation, 9th Edition (style guide)

Jones, Alan 1953-. Principles, Process and Practice of Professional Number Juggling Routledge, 2019.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID29ddfc68-d4a7-07f1-ee26-b113168b3b45-eng
Full titleprinciples process and practice of professional number juggling
Authorjones alan
Grouping Categorybook
Last Update2024-06-04 09:42:47AM
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4901 |a Working guides to estimating & forecasting ;|v volume 1
504 |a Includes bibliographical references and index.
50500|t Foreword, 1 Introduction and Objectives, 1.1 Why write this book? Who might find it useful? Why Five Volumes? 1.1.1 Why write this series? Who might find it useful? 1.1.2 Why Five Volumes? 1.2 Features you'll find in this book and others in this series, 1.2.1 Chapter Context, 1.2.2 The Lighter Side (humour), 1.2.3 Quotations, 1.2.4 Definitions, 1.2.5 Discussions and Explanations with a Mathematical Slant for Formula-philes, 1.2.6 Discussions and Explanations without a Mathematical Slant for Formula-phobes, 1.2.7 Caveat Augur, 1.2.8 Worked Examples, 1.2.9 Useful Microsoft Excel Functions and Facilities, 1.2.10 References to Authoritative Sources, 1.2.11 Chapter Reviews, 1.3 Overview of Chapters in this Volume, 1.4 Elsewhere in the 'Working Guide to Estimating & Forecasting' Series, 1.4.1 Volume I: Principles, Process and Practice of Professional Number Juggling, 1.4.2 Volume II: Probability, Statistics and other Frightening Stuff, 1.4.3 Volume III: Best Fit Lines & Curves, and some Mathe-Magical Transformations, 1.4.4 Volume IV: Learning, Unlearning and Re-Learning Curves, 1.4.5 Volume V: Risk, Opportunity, Uncertainty and Other Random Models, 1.5 Final Thoughts and Musings on this Volume and Series, References, 2 Methods, Approaches, Techniques and Related Terms, 2.1 What is the Difference between a Method, Approach and Technique? 2.2 Estimating Process, 2.3 Estimating Approaches, 2.3.1 Top-down Approach, 2.3.2 Bottom-up Approach, 2.3.3 Ethereal Approach, 2.4 Estimating Methods, 2.4.1 Analogical Method, 2.4.2 Parametric Method, 2.4.3 'Trusted Source' Method, 2.4.4 Methods that are arguably not Methods (in their own right), 2.5 Estimating Techniques, 2.6 Estimating Procedures, 2.7 Combining Approaches and Methods, 2.7.1 Choice of Estimating Approach for a Chosen Estimating Element, 2.7.2 Choice of Estimating Method for a Chosen Estimating Approach, 2.7.3 Choice of Estimating Technique for a Chosen Estimating Method, 2.8 Chapter Review, References, 3 Estimate TRACEability and Health Checks, 3.1 Basis of Estimate, TRACEability and Estimate Maturity, 3.1.1 Building Bridges Between Two Estimates, 3.2 Estimate and Schedule Maturity Assessments, 3.2.1 Estimate Maturity Assessment (EMA), 3.2.2 Schedule Maturity Assessment (SMA), 3.2.3 Cost and Schedule Integration Maturity Assessment (CASIMA), 3.3 Good Practice Spreadsheet Modelling (GPSM), 3.3.1 Level of Documentation (T, M), 3.3.2 No Hidden Worksheets, Columns or Rows (T, M), 3.3.3 Colour Coded Cells and Worksheet Tabs (U, S), 3.3.4 Locked Calculation Cells and Protected Worksheets and Workbooks (S), 3.3.5 No Hard-Coded Constants unless Axiomatic (M), 3.3.6 Left to Right and Top to Bottom Readability Flow (U), 3.3.7 Avoid Data Generated by Macros unless there is a genuine benefit (S, T), 3.3.8 Avoid Array Formulae (T, U, M), 3.3.9 Avoid Dynamic Links to External Data (S), 3.3.10 Use Named Ranges for Frequently Used Table Arrays (M, U), 3.3.11 Use Full Syntax within Excel (M), 3.3.12 Break Complex Calculations into Smaller Simpler Steps (T, M), 3.3.13 Column and Row Alignment Across Worksheets (T), 3.3.14 Unambiguous Units of Measure (U), 3.3.15 Input Data Validation (U), 3.3.16 Independent Model Verification and Validation (S), 3.4 Inherent Risk in Spreadsheets (IRiS) , 3.5 Chapter Review, References, 4 Primary & Secondary Drivers; Accuracy & Precision, 4.1 Thank Goodness for Juran and Pareto, 4.1.1 What's the Drive behind the Drivers? 4.2 Primary Drivers, 4.2.1 Internal and External Drivers, 4.3 Secondary Drivers, 4.4 Practical Issues with Drivers, 4.4.1 Sub-Classification of Primary Drivers, 4.4.2 Avoid Pseudo-Drivers, 4.4.3 Things are rarely Black or White, 4.5 Accuracy and Precision of Primary and Secondary Drivers, 4.5.1 Accuracy, Precision and Drivers -- A Pareto Perspective, 4.5.2 Cone of Uncertainty, 4.6 3-Point Estimates as a Measure of Relative Accuracy and Uncertainty, 4.7 Precision as an Expression of Appropriate or Inappropriate Exactness, 4.8 Chapter Review, References, 5 Factors, Rates, Ratios, and Estimating by Analogy, 5.1 Estimating Metrics, 5.1.1 Where to use them, 5.1.2 The Views of Others, 5.1.3 Underlying Linear Relationship, 5.2 Rates, 5.3 Factors, 5.4 Ratios, 5.5 Dealing with Multiple Rates, Factors (and Ratios), 5.5.1 Anomalous Analogies, 5.5.2 Analogies with an Additive Model, 5.5.3 Analogies with a Multiplicative Model, 5.6 Sensitivity Analysis on Factors, Rates and Ratios, 5.6.1 Choosing a Sensitivity Range Quantitatively, 5.6.2 Choosing a Sensitivity Range around a Measure of Central Tendency, 5.6.3 The Triangulation Option, 5.6.4 Choosing a Sensitivity Range around a High-end or Low-end Metric, 5.6.5 Choosing a Sensitivity Range when all else fails, 5.7 Chapter Review, References, 6 Data Normalisation -- Levelling the Playing Field, 6.1 Classification of Data Sources -- Primary, Secondary and Tertiary Data, 6.1.1 Primary Data, 6.1.2 Secondary Data, 6.1.3 Tertiary Data, 6.1.4 Quarantined Data, 6.2 Types of Normalisation Methods and Techniques, 6.3 Normalisation can be a Multi-Dimensional Problem, 6.3.1 Error Related, 6.3.2 Volume, Quantity or Throughput Related -- Economies of Scale, 6.3.3 Scale Conversion -- Fixed and Variable Factors, 6.3.4 Date or Time Related, 6.3.5 Life Cycle Related, 6.3.6 Key Groupings -- Role Related, 6.3.7 Scope Related (Subjective), 6.3.8 Complexity -- Judgement Related (Subjective), 6.4 The Estimator as a Time Traveller, 6.4.1 Use of Time-based Indices Now and Then, 6.4.2 Time-based Weighted Indices, 6.4.3 Time-based Chain-Linked Weighted Indices, 6.4.4 The Doubling Rule for Escalation, 6.4.5 Composite Index: Is that not just a Weighted Index by another Name? 6.4.6 Using the Appropriate Appropriation Approach, 6.4.7 Use of Time as an Indicator of Other Changes, 6.5 Discounted Cash Flow -- Normalising Investment Opportunities, 6.5.1 Discounted Cash Flow -- A Form of Time Travel for Accountants, 6.5.2 Net Present Value (NPV), 6.5.3 Internal Rate of Return (IRR), 6.5.4 Payback Period, 6.5.5 Strengths and Weakness of Different DCF Techniques, 6.6 Special Types of Formulaic Normalisation Techniques, 6.7 Layering of Normalisation for differences in Analogies, 6.8 Chapter Review, References, 7 Pseudo-Quantitative Qualitative Estimating Techniques, 7.1 Delphi Technique, 7.2 Driver Cross-Impact Analysis, 7.3 A Brief Word or Two About Solution Optimisation, 7.4 Chapter Review, References, 8 Benford's Law as a Potential Measure of Cost Bias , 8.1 Scale Invariance of Benford's Law, 8.2 Potential Use of Benford's Law in Estimating, 8.3 Chapter Review, References, Glossary of Estimating Terms, Index
5203 |a Principles, Process and Practice of Professional Number Juggling (Volume 1 of the Working Guides to Estimating & Forecasting series) sets the scene of TRACEability and good estimate practice that is followed in the other volumes in this series of five working guides. It clarifies the difference between an Estimating Process, Procedure, Approach, Method and Technique. It expands on these definitions of Approach (Top-down, Bottom-up and'Ethereal') and Method (Analogy, Parametric and 'Trusted Source') and discusses how these form the basis of all other means of establishing an estimate. This volume also underlines the importance of 'data normalisation' in any estimating procedure, and demonstrates that the Estimating by Analogy Method, in essence, is a simple extension of Data Normalisation. The author looks at simple measures of assessing the maturity or health of an estimate, and offers a means of assessing a spreadsheet for any inherent risks or errors that may be introduced by failing to follow good practice in spreadsheet design and build. This book provides a taster of the more numerical techniques covered in the remainder of the series by considering how an estimator can potentially exploit Benford's Law (traditionally used in Fraud Detection) to identify systematic bias from third party contributors. It will be a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.
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