# Principles, Process and Practice of Professional Number Juggling

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Principles, Process and Practice of Professional Number Juggling

Jones, Alan

Taylor & Francis Ltd

06/2024

262

Mole

9781032838786

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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

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

**Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.**

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

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