Principles, Process and Practice of Professional Number Juggling

Principles, Process and Practice of Professional Number Juggling

Jones, Alan

Taylor & Francis Ltd

06/2024

262

Mole

9781032838786

Pré-lançamento - envio 15 a 20 dias após a sua edição

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List of Figures

List of Tables

Foreword






Introduction and objectives





Why write this book? Who might find it useful? Why five volumes?





Why write this series? Who might find it useful?



Why five volumes?




Features you'll find in this book and others in this series





Chapter context



The lighter side (humour)



Quotations



Definitions



Discussions and explanations with a mathematical
slant for Formula-philes




Discussions and explanations without a mathematical
slant for Formula-phobes




Caveat augur



Worked examples



Useful Microsoft Excel functions and facilities



References to authoritative sources



Chapter reviews




Overview of chapters in this volume



Elsewhere in the 'Working Guide to Estimating & Forecasting' series





Volume I: Principles, Process and Practice of Professional
Number Juggling




Volume II: Probability, Statistics and Other Frightening Stuff



Volume III: Best Fit Lines and Curves, and





Some Mathe-Magical Transformations










Volume IV: Learning, Unlearning and Re-Learning Curves



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 or Analogous 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








Combining Approaches and Methods





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 (or health checks)

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)










Colour coded cells and worksheet tabs (U, S)



Locked calculation cells and protected worksheets
and workbooks (S)




No hard-coded constants unless axiomatic (M)



Left to Right and Top to Bottom readability flow (U)



Avoid data generated by macros ... Unless there is a
genuine benefit (S,T)




Avoid Array Formulae (T, U, M)



Avoid dynamic links to external data (S)



Use Named Ranges for frequently used table arrays (M, U)



Use full syntax within Excel (M)



Break complex calculations into smaller simpler steps (T, M)



Column and row alignment across worksheets (T)



Unambiguous units of measure (U)



Input data validation (U)



Independent model verification and validation (S)












Inherent Risk in Spreadsheets (IRiS)



Chapter review



References






Primary and Secondary Drivers; Accuracy and precision





Thank goodness for Juran and Pareto





What's the drive behind the Drivers?




Primary Drivers





Internal and external Drivers




Secondary Drivers



Practical issues with Drivers





Sub-classification of Primary Drivers



Avoid pseudo-drivers



Things are rarely black or white




Accuracy and precision of Primary and Secondary Drivers





Accuracy, precision and Drivers - A Pareto perspective



Cone of Uncertainty




3-Point Estimates as a measure of relative accuracy
and uncertainty




Precision as an expression of appropriate or inappropriate exactness



Chapter review

References




Factors, Rates, Ratios and estimating by analogy





Estimating Metrics





Where to use them



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










Choosing a Sensitivity Range quantitatively



Choosing a Sensitivity Range around a measure of Central Tendency














The triangulation option



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










Error related



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










The doubling rule for escalation



Composite Index: Is that not just a Weighted Index by another name?














Using the appropriate appropriation approach



Use of time as an indicator of other changes












Discounted Cash Flow - Normalising
investment opportunities






Discounted Cash Flow - A form of time travel for accountants



Net Present Value (NPV)



Internal Rate of Return (IRR)



Payback Period



Strengths and weaknesses of different DCF techniques




Special types of formulaic normalisation techniques



Layering of normalisation for differences in analogies



Chapter review



References






Pseudo-quantitative qualitative estimating techniques





Delphi Technique



Driver Cross-Impact Analysis



A brief word or two about solution optimisation



Chapter review

References




Benford's Law as a potential measure of cost bias





Scale Invariance of Benford's Law



Potential use of Benford's Law in estimating



Chapter review



References

Glossary of estimating and forecasting terms

Legend for Microsoft Excel Worked Example Tables in Greyscale

Index
Vice Versa;Secondary Driver;Estimating;Benford's Law;Forecasting;Trusted Source;Estimating Process;Good Practice Principles;Estimating Approach;Cost Driver;Estimating Method;Functions Microsoft Excel;Estimating Technique;Driver Metrics;Estimate Maturity;Potential Cost Drivers;Data Normalisation;Leading Digit;Spreadsheet Design;VBA Code;Alan R. Jones;Cycle Time;Estimate Drivers;Paasche Indices;working guide to estimating and forecasting;Low Positive Impact;Benford's Law;Array Formulae;Factor Metrics;Monthly Discount Rate;Rate Metrics;Tertiary Data;Interquantile Ranges;Cross-Impact Analysis;Net Present;Delphi Technique;Kerb Weight;QFD