Book 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.
Table of contents
- Cover
- Title
- Copyright
- Dedication
- Contents
- List of Figures
- List of Tables
- Foreword
-
1 Introduction and objectives
- 1.1 Why write this book? Who might find it useful? 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 and 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
-
3 Estimate TRACEability and health checks
- 3.1 Basis of Estimate, TRACEability and estimate maturity
- 3.2 Estimate and Schedule Maturity Assessments (or health checks)
-
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 and Secondary Drivers; Accuracy and precision
- 4.1 Thank goodness for Juran and Pareto
- 4.2 Primary Drivers
- 4.3 Secondary Drivers
- 4.4 Practical issues with Drivers
- 4.5 Accuracy and precision of Primary and Secondary Drivers
- 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
-
6 Data normalisation – Levelling the playing field
- 6.1 Classification of data sources – Primary, Secondary and Tertiary 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
- 6.6 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
- 8 Benford's Law as a potential measure of cost bias
- Glossary of estimating and forecasting terms
- Legend for Microsoft Excel Worked Example Tables in Greyscale
- Index
Product information
- Title: Principles, Process and Practice of Professional Number Juggling
- Author(s):
- Release date: September 2018
- Publisher(s): Routledge
- ISBN: 9781351661355
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