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Estimating IT projects
Frank Vogelezang
Manager Pricing Office
June 10th 2013
2
Agenda
Estimating IT projects
 What is estimating
 How good is your estimate
 The only certainty is uncertainty
 Cost drivers for IT projects
 Reliable estimation
What is estimating
And why is estimating IT projects so difficult
IT has a bad track-record in project estimating
What is estimating
4
For a critical analysis of the Chaos reports see: www.cs.vu.nl/~x/chaos
IT has a bad track-record in project estimating
What is estimating
Any idea where this bad track-record comes from?
5
IT has a bad track-record in project estimating
What is estimating
Any idea where this bad track-record comes from?
 No clear project objective
 Start with an inadequate budget
 Too little time and/or resources
 No use of benchmarking
 No idea what an estimate is
6
We can double
the estimate . . . . but then it will
ultimately be four
times as expensive!
on estimating
Definition of an estimate
What is estimation
How would you define an estimate?
An estimate is
 an analytical and unbiased prediction
 of how long it takes
 and what it will cost
The bias comes from the interplay with targets, commitments and plans
7
Target, estimate, commitment and plan
What is estimation
 Target
 Desirable business objective
 When and what
 Estimate
 Analytical prediction
 With an uncertainty range
 How and what
 Commitment
 Promise to deliver
 Defined functionality and quality
 What and when
 Plan
 Bridging the gap between estimate and commitment and mitigating the risk involved
 When and how
8
A typical estimate
What is estimation
9
Probability
Schedule / Cost
50/50 median result
First likely option
A good estimate
What is estimation
A good estimate is
 a prediction
 that provides a clear enough view
 of the project reality
 to allow the project leadership to make informed decisions
 about how to control the project
 to hit its targets.
Know where you come from, where you are and where you are going
10
Software Estimation: Demystifying the black art: www.SteveMcConnell.com
Basis of Estimate
New standard practice by NESMA and AACEi
11
RECOMMENDEDPRACTICE
Estimation
purpose
Engagement
Scope
Description
Estimating
methodology
(FP, expert,
etc.)
Estimate
Classification
(1,2,3,4,5)
Design Basis
(Components
lists, units, etc.)
Sizing Basis
Requirements
Functional
technical
Effort Basis
delivery
constraints,
service levels
Planning Basis
Working time
standby
Cost Basis
methods and
sources , units
Assumptions
internal,
external
Allowances
Not in the Basis
Exclusions
No costs
included for…
Exceptions
anomalies or
variances on
standard
Risks and
Opportunities
assumptions
Containments
cost elements
for mitigation
Contingencies
Uncertainty,
unforeseeable
elements
Management
Reserve
changes in
scope, effort
Reconciliation
Changes to
previous
estimation
Benchmarking
Comparisons to
similar
engagements
Level of detail
Stage, Deal
size/type, fixed
price/TM
Estimate
Quality
Assurance
Reviews
Attachments Attachments Attachments Attachments
How good is your estimate
A simple quiz with unexpected questions
A simple quiz
How good is your estimate
The rules
 You get 10 questions, about anything but IT
 Answer each question with an upper and a lower boundary
 The answer should be within these bounds with a 90% chance
The objective
 To finish the quiz with 90% correct answers
 So 9 answers to the questions are within the boundaries
13
A simple quiz
How good is your estimate
1. What is the surface temperature of the sun in ºC
2. What was the total throughput of the Port of Rotterdam in 2012 in metric tons
3. World-wide box office receipts of the Lord of the Rings trilogy in US$
4. What is the total area of the Asian continent in km2
5. What is the year of birth of Alexander the Great according to Christian calender
6. The number of book titles in the Library of the Congress since 1776 in millions
7. How heavy was the heaviest blue whale ever recorded in metric tons
8. How many Euro bills were in circulation at the end of 2009 in billions
9. What is the highest point in the kingdom of the Netherlands in m
10.What is the total length of the coastline of the Pacific Ocean in km
14
Estimating psychology
How good is your estimate
How well did you do this quiz?
 The average score is around 3, in line with the CHAOS reports
 We are conditioned to believe that narrow ranges are more accurate
 We feel that wide ranges make us appear ignorant or incompetent
 In real projects estimates are often biased by knowledge about the targets
15
Beating the estimating psychology
How good is your estimate
 If the objective is unclear, the answer cannot be precise
 IT suppliers want to do customers a favour by promising they can deliver,
although they have no idea whether it is realistic. Is that a favour?
 There are no bad suppliers, but enough substandard customers*
16
* Joep Bröcker (KPN) : www.sogeti.nl/evenementen/2010/succesvol-aanbesteden-van-ict
The only certainty is uncertainty
Most IT projects deliver something else than initially intended
Managing the devil’s triangle
Balancing between cost, time and scope
Cost
18
Time
Scope or Quality
Risk
Managing the devil’s triangle
Balancing between cost and time for a given size
19
Paul Masson’s
Law
Parkinson’s
Law
Brooks’
Law
Minimal time
Optimal effort
Time
Effort/Cost
Realistic
Productivity
The devil is in change
Traditional fixed price, fixed date projects
Cost
20
Time
Scope or Quality
Risk
Risk
Risk
Risk
Let’s make room for change
The uncertainty in agile projects
Cost
21
Time
Scope or Quality
Risk
Doubt
Cost drivers for IT projects
Sizing and estimating
Estimating IT projects
Two essential routes
23
Objective
Size
Effort
Cost
24
Effort estimation
Estimating IT projects
 Sizing by analogy
Have we done something similar before?
25
Effort estimation
Estimating IT projects
 Ask the experts to estimate using Delphi techniques
 Original Delphi:
Individual estimates | Distributed by a facilitator | Several rounds
 Wideband Delphi:
Group discussion | Individual estimates | Consensus on large variation
 Delphi – PERT:
Use Delphi to establish lower bound, higher bound and most likely value
Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
26
Effort estimation
Estimating IT projects
 Ask the experts to estimate using Delphi techniques
 Original Delphi:
Individual estimates | Distributed by a facilitator | Several rounds
 Wideband Delphi:
Group discussion | Individual estimates | Consensus on large variation
 Delphi – PERT:
Use Delphi to establish lower bound, higher bound and most likely value
Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
 Planning Poker:
Estimate effort to produce a work item, related to a standard work item
Use cards with a Fibonacci (like) scale to reflect uncertainty for larger items
Estimating IT projects
The second route
27
Objective
Size
Effort
Cost
28
Size estimation
Estimating IT projects
 Sizing by proxy
Define repeatable elements
 Experience data per proxy element
 Technical elements: Lines of Code
Programs / Modules
Screens
Data files / Views
Interfaces
 Logical elements: User Stories / Use Cases
Processes in the Data Flow Diagram
Functional Size Measurement
29
Size estimation
Lines of Code
What does the number of lines tell me about size?
13 LoC – 1 statement
Backfiring
Translation to Functional Size
Uncertainty range over 300%
20 LoC – 3 statements
30
Size estimation
Functional Size Measurement – Function Point Analysis
 FPA stands for Function
Point
Analysis
 What the software should be able to do (functionality) Function
expressed in a number Point
based on an objectively described method Analysis
 Something intangible like functionality becomes a physical number that can
be used for calculations
31
Size estimation
Functional Size Measurement – Function Point Analysis
External Input
External Output
External Inquiry
External input files
Internallogical files
Data oriented
Size estimation
Functional Size Measurement – Function Point Analysis
Counting function points
 Based on established criteria each element is
classified:
 Each classification has its own scores
Internal files 7 10 15
External interfaces 5 7 10
External input 3 4 6
External output 4 5 7
External inquiry 3 4 6
 A function point never travels alone
32
Simple
Complex
33
Size estimation
Functional Size Measurement – COSMIC
eXit
Write
Entry
Read
eXit
Read
Transaction oriented
Size estimation
Functional Size Measurement – COSMIC
Counting COSMIC function points
 Establish Functional Processes
 Determine the data movements
 # Entries
 # Writes
 # Reads
 # eXits
 Each data movement is scored
Entry 1 CFP
Write 1 CFP
Read 1 CFP
eXit 1 CFP
 A data movement can be identified alone
34
Estimating IT projects
The second route
35
Size
Effort
Cost
Objective
36
Translating size into effort
Project size as a cost driver
Size Early On time Late Failed
10 FP 11% 81% 6% 2%
100 FP 6% 75% 12% 7%
1.000 FP 1% 61% 18% 20%
10.000 FP <1% 28% 24% 48%
100.000 FP - 14% 21% 65%
Capers Jones : Applied Software Measurement
37
Translating size into effort
Team size as a cost driver
MORE PEOPLE MAKE MORE NOISE
Translating size into effort
Team size as a cost driver
38
Paul Masson’s
Law
Parkinson’s
Law
Brooks’
Law
Minimal time
Optimal effort
Time
Effort/Cost
Realistic
Productivity
Translating size into effort
What can you do with Functional Size
39
 Translate functionality into a physical number that can be used to calculate:
 Required amount of hours / cost
 Schedule time
 Basis for a fixed price (per unit) that is still variable
 The calculation depends on the technology used (Java, eBS, . . .)
 But it is not a linear calculation!
Twice the size in function points is not twice as much hours / cost / time
Translating size into effort
How to manage all the relations
40
Reliable estimation
How good do we know what we must do
Reliable estimation
Case – Rebuild of Investment Fund Application
 Case (1 page)
 5 expert estimates (2 pages)
 Estimation approach (1 page)
1. Are the estimates complete?
2. Are the assumptions correct?
3. How relevant and reliable are the estimates?
4. Question the experts!
5. Are the estimates comparable? By accident or by design?
6. Can approaches be used to reinforce other estimates?
 Present the results of these steps
 Present the results of the final estimate
42
43
frank.vogelezang@ordina.nl
WatKostIT.blogspot.nl
ThePriceofIT.blogspot.com
@FrankVogelezang
FrankVogelezang
www.linkedin.com/in/frankvogelezang

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Estimating IT projects - Guest lecture University of Twente

  • 1. Estimating IT projects Frank Vogelezang Manager Pricing Office June 10th 2013
  • 2. 2 Agenda Estimating IT projects  What is estimating  How good is your estimate  The only certainty is uncertainty  Cost drivers for IT projects  Reliable estimation
  • 3. What is estimating And why is estimating IT projects so difficult
  • 4. IT has a bad track-record in project estimating What is estimating 4 For a critical analysis of the Chaos reports see: www.cs.vu.nl/~x/chaos
  • 5. IT has a bad track-record in project estimating What is estimating Any idea where this bad track-record comes from? 5
  • 6. IT has a bad track-record in project estimating What is estimating Any idea where this bad track-record comes from?  No clear project objective  Start with an inadequate budget  Too little time and/or resources  No use of benchmarking  No idea what an estimate is 6 We can double the estimate . . . . but then it will ultimately be four times as expensive! on estimating
  • 7. Definition of an estimate What is estimation How would you define an estimate? An estimate is  an analytical and unbiased prediction  of how long it takes  and what it will cost The bias comes from the interplay with targets, commitments and plans 7
  • 8. Target, estimate, commitment and plan What is estimation  Target  Desirable business objective  When and what  Estimate  Analytical prediction  With an uncertainty range  How and what  Commitment  Promise to deliver  Defined functionality and quality  What and when  Plan  Bridging the gap between estimate and commitment and mitigating the risk involved  When and how 8
  • 9. A typical estimate What is estimation 9 Probability Schedule / Cost 50/50 median result First likely option
  • 10. A good estimate What is estimation A good estimate is  a prediction  that provides a clear enough view  of the project reality  to allow the project leadership to make informed decisions  about how to control the project  to hit its targets. Know where you come from, where you are and where you are going 10 Software Estimation: Demystifying the black art: www.SteveMcConnell.com
  • 11. Basis of Estimate New standard practice by NESMA and AACEi 11 RECOMMENDEDPRACTICE Estimation purpose Engagement Scope Description Estimating methodology (FP, expert, etc.) Estimate Classification (1,2,3,4,5) Design Basis (Components lists, units, etc.) Sizing Basis Requirements Functional technical Effort Basis delivery constraints, service levels Planning Basis Working time standby Cost Basis methods and sources , units Assumptions internal, external Allowances Not in the Basis Exclusions No costs included for… Exceptions anomalies or variances on standard Risks and Opportunities assumptions Containments cost elements for mitigation Contingencies Uncertainty, unforeseeable elements Management Reserve changes in scope, effort Reconciliation Changes to previous estimation Benchmarking Comparisons to similar engagements Level of detail Stage, Deal size/type, fixed price/TM Estimate Quality Assurance Reviews Attachments Attachments Attachments Attachments
  • 12. How good is your estimate A simple quiz with unexpected questions
  • 13. A simple quiz How good is your estimate The rules  You get 10 questions, about anything but IT  Answer each question with an upper and a lower boundary  The answer should be within these bounds with a 90% chance The objective  To finish the quiz with 90% correct answers  So 9 answers to the questions are within the boundaries 13
  • 14. A simple quiz How good is your estimate 1. What is the surface temperature of the sun in ºC 2. What was the total throughput of the Port of Rotterdam in 2012 in metric tons 3. World-wide box office receipts of the Lord of the Rings trilogy in US$ 4. What is the total area of the Asian continent in km2 5. What is the year of birth of Alexander the Great according to Christian calender 6. The number of book titles in the Library of the Congress since 1776 in millions 7. How heavy was the heaviest blue whale ever recorded in metric tons 8. How many Euro bills were in circulation at the end of 2009 in billions 9. What is the highest point in the kingdom of the Netherlands in m 10.What is the total length of the coastline of the Pacific Ocean in km 14
  • 15. Estimating psychology How good is your estimate How well did you do this quiz?  The average score is around 3, in line with the CHAOS reports  We are conditioned to believe that narrow ranges are more accurate  We feel that wide ranges make us appear ignorant or incompetent  In real projects estimates are often biased by knowledge about the targets 15
  • 16. Beating the estimating psychology How good is your estimate  If the objective is unclear, the answer cannot be precise  IT suppliers want to do customers a favour by promising they can deliver, although they have no idea whether it is realistic. Is that a favour?  There are no bad suppliers, but enough substandard customers* 16 * Joep Bröcker (KPN) : www.sogeti.nl/evenementen/2010/succesvol-aanbesteden-van-ict
  • 17. The only certainty is uncertainty Most IT projects deliver something else than initially intended
  • 18. Managing the devil’s triangle Balancing between cost, time and scope Cost 18 Time Scope or Quality Risk
  • 19. Managing the devil’s triangle Balancing between cost and time for a given size 19 Paul Masson’s Law Parkinson’s Law Brooks’ Law Minimal time Optimal effort Time Effort/Cost Realistic Productivity
  • 20. The devil is in change Traditional fixed price, fixed date projects Cost 20 Time Scope or Quality Risk Risk Risk Risk
  • 21. Let’s make room for change The uncertainty in agile projects Cost 21 Time Scope or Quality Risk Doubt
  • 22. Cost drivers for IT projects Sizing and estimating
  • 23. Estimating IT projects Two essential routes 23 Objective Size Effort Cost
  • 24. 24 Effort estimation Estimating IT projects  Sizing by analogy Have we done something similar before?
  • 25. 25 Effort estimation Estimating IT projects  Ask the experts to estimate using Delphi techniques  Original Delphi: Individual estimates | Distributed by a facilitator | Several rounds  Wideband Delphi: Group discussion | Individual estimates | Consensus on large variation  Delphi – PERT: Use Delphi to establish lower bound, higher bound and most likely value Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
  • 26. 26 Effort estimation Estimating IT projects  Ask the experts to estimate using Delphi techniques  Original Delphi: Individual estimates | Distributed by a facilitator | Several rounds  Wideband Delphi: Group discussion | Individual estimates | Consensus on large variation  Delphi – PERT: Use Delphi to establish lower bound, higher bound and most likely value Calculate the estimate by the formula (Lo + 4 * ML + Hi) / 6  Planning Poker: Estimate effort to produce a work item, related to a standard work item Use cards with a Fibonacci (like) scale to reflect uncertainty for larger items
  • 27. Estimating IT projects The second route 27 Objective Size Effort Cost
  • 28. 28 Size estimation Estimating IT projects  Sizing by proxy Define repeatable elements  Experience data per proxy element  Technical elements: Lines of Code Programs / Modules Screens Data files / Views Interfaces  Logical elements: User Stories / Use Cases Processes in the Data Flow Diagram Functional Size Measurement
  • 29. 29 Size estimation Lines of Code What does the number of lines tell me about size? 13 LoC – 1 statement Backfiring Translation to Functional Size Uncertainty range over 300% 20 LoC – 3 statements
  • 30. 30 Size estimation Functional Size Measurement – Function Point Analysis  FPA stands for Function Point Analysis  What the software should be able to do (functionality) Function expressed in a number Point based on an objectively described method Analysis  Something intangible like functionality becomes a physical number that can be used for calculations
  • 31. 31 Size estimation Functional Size Measurement – Function Point Analysis External Input External Output External Inquiry External input files Internallogical files Data oriented
  • 32. Size estimation Functional Size Measurement – Function Point Analysis Counting function points  Based on established criteria each element is classified:  Each classification has its own scores Internal files 7 10 15 External interfaces 5 7 10 External input 3 4 6 External output 4 5 7 External inquiry 3 4 6  A function point never travels alone 32 Simple Complex
  • 33. 33 Size estimation Functional Size Measurement – COSMIC eXit Write Entry Read eXit Read Transaction oriented
  • 34. Size estimation Functional Size Measurement – COSMIC Counting COSMIC function points  Establish Functional Processes  Determine the data movements  # Entries  # Writes  # Reads  # eXits  Each data movement is scored Entry 1 CFP Write 1 CFP Read 1 CFP eXit 1 CFP  A data movement can be identified alone 34
  • 35. Estimating IT projects The second route 35 Size Effort Cost Objective
  • 36. 36 Translating size into effort Project size as a cost driver Size Early On time Late Failed 10 FP 11% 81% 6% 2% 100 FP 6% 75% 12% 7% 1.000 FP 1% 61% 18% 20% 10.000 FP <1% 28% 24% 48% 100.000 FP - 14% 21% 65% Capers Jones : Applied Software Measurement
  • 37. 37 Translating size into effort Team size as a cost driver MORE PEOPLE MAKE MORE NOISE
  • 38. Translating size into effort Team size as a cost driver 38 Paul Masson’s Law Parkinson’s Law Brooks’ Law Minimal time Optimal effort Time Effort/Cost Realistic Productivity
  • 39. Translating size into effort What can you do with Functional Size 39  Translate functionality into a physical number that can be used to calculate:  Required amount of hours / cost  Schedule time  Basis for a fixed price (per unit) that is still variable  The calculation depends on the technology used (Java, eBS, . . .)  But it is not a linear calculation! Twice the size in function points is not twice as much hours / cost / time
  • 40. Translating size into effort How to manage all the relations 40
  • 41. Reliable estimation How good do we know what we must do
  • 42. Reliable estimation Case – Rebuild of Investment Fund Application  Case (1 page)  5 expert estimates (2 pages)  Estimation approach (1 page) 1. Are the estimates complete? 2. Are the assumptions correct? 3. How relevant and reliable are the estimates? 4. Question the experts! 5. Are the estimates comparable? By accident or by design? 6. Can approaches be used to reinforce other estimates?  Present the results of these steps  Present the results of the final estimate 42