Estimating IT projects - Guest lecture University of Twente
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The document discusses the challenges of estimating IT projects, highlighting common pitfalls such as unclear objectives and inadequate resources. It outlines a structured approach to creating reliable estimates, including definitions of key terms and methodologies, as well as the importance of understanding uncertainties and biases in the estimation process. The content concludes with a focus on evaluation and questioning the accuracy of expert estimates to improve project success.
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