Your SlideShare is downloading. ×
0
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Estimating IT projects - Guest lecture University of Twente
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Estimating IT projects - Guest lecture University of Twente

1,498

Published on

I have given a guest lecture on estimating IT project for master students on the University of Twente.

I have given a guest lecture on estimating IT project for master students on the University of Twente.

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,498
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
37
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Estimating IT projectsFrank VogelezangManager Pricing OfficeJune 10th 2013
  • 2. 2AgendaEstimating 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 estimatingAnd why is estimating IT projects so difficult
  • 4. IT has a bad track-record in project estimatingWhat is estimating4For a critical analysis of the Chaos reports see: www.cs.vu.nl/~x/chaos
  • 5. IT has a bad track-record in project estimatingWhat is estimatingAny idea where this bad track-record comes from?5
  • 6. IT has a bad track-record in project estimatingWhat is estimatingAny 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 is6We can doublethe estimate . . . . but then it willultimately be fourtimes as expensive!on estimating
  • 7. Definition of an estimateWhat is estimationHow would you define an estimate?An estimate is an analytical and unbiased prediction of how long it takes and what it will costThe bias comes from the interplay with targets, commitments and plans7
  • 8. Target, estimate, commitment and planWhat 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 how8
  • 9. A typical estimateWhat is estimation9ProbabilitySchedule / Cost50/50 median resultFirst likely option
  • 10. A good estimateWhat is estimationA 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 going10Software Estimation: Demystifying the black art: www.SteveMcConnell.com
  • 11. Basis of EstimateNew standard practice by NESMA and AACEi11RECOMMENDEDPRACTICEEstimationpurposeEngagementScopeDescriptionEstimatingmethodology(FP, expert,etc.)EstimateClassification(1,2,3,4,5)Design Basis(Componentslists, units, etc.)Sizing BasisRequirementsFunctionaltechnicalEffort Basisdeliveryconstraints,service levelsPlanning BasisWorking timestandbyCost Basismethods andsources , unitsAssumptionsinternal,externalAllowancesNot in the BasisExclusionsNo costsincluded for…Exceptionsanomalies orvariances onstandardRisks andOpportunitiesassumptionsContainmentscost elementsfor mitigationContingenciesUncertainty,unforeseeableelementsManagementReservechanges inscope, effortReconciliationChanges topreviousestimationBenchmarkingComparisons tosimilarengagementsLevel of detailStage, Dealsize/type, fixedprice/TMEstimateQualityAssuranceReviewsAttachments Attachments Attachments Attachments
  • 12. How good is your estimateA simple quiz with unexpected questions
  • 13. A simple quizHow good is your estimateThe 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% chanceThe objective To finish the quiz with 90% correct answers So 9 answers to the questions are within the boundaries13
  • 14. A simple quizHow good is your estimate1. What is the surface temperature of the sun in ºC2. What was the total throughput of the Port of Rotterdam in 2012 in metric tons3. 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 km25. What is the year of birth of Alexander the Great according to Christian calender6. The number of book titles in the Library of the Congress since 1776 in millions7. How heavy was the heaviest blue whale ever recorded in metric tons8. How many Euro bills were in circulation at the end of 2009 in billions9. What is the highest point in the kingdom of the Netherlands in m10.What is the total length of the coastline of the Pacific Ocean in km14
  • 15. Estimating psychologyHow good is your estimateHow 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 targets15
  • 16. Beating the estimating psychologyHow 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 uncertaintyMost IT projects deliver something else than initially intended
  • 18. Managing the devil’s triangleBalancing between cost, time and scopeCost18TimeScope or QualityRisk
  • 19. Managing the devil’s triangleBalancing between cost and time for a given size19Paul Masson’sLawParkinson’sLawBrooks’LawMinimal timeOptimal effortTimeEffort/CostRealisticProductivity
  • 20. The devil is in changeTraditional fixed price, fixed date projectsCost20TimeScope or QualityRiskRiskRiskRisk
  • 21. Let’s make room for changeThe uncertainty in agile projectsCost21TimeScope or QualityRiskDoubt
  • 22. Cost drivers for IT projectsSizing and estimating
  • 23. Estimating IT projectsTwo essential routes23ObjectiveSizeEffortCost
  • 24. 24Effort estimationEstimating IT projects Sizing by analogyHave we done something similar before?
  • 25. 25Effort estimationEstimating 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 valueCalculate the estimate by the formula (Lo + 4 * ML + Hi) / 6
  • 26. 26Effort estimationEstimating 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 valueCalculate the estimate by the formula (Lo + 4 * ML + Hi) / 6 Planning Poker:Estimate effort to produce a work item, related to a standard work itemUse cards with a Fibonacci (like) scale to reflect uncertainty for larger items
  • 27. Estimating IT projectsThe second route27ObjectiveSizeEffortCost
  • 28. 28Size estimationEstimating IT projects Sizing by proxyDefine repeatable elements Experience data per proxy element Technical elements: Lines of CodePrograms / ModulesScreensData files / ViewsInterfaces Logical elements: User Stories / Use CasesProcesses in the Data Flow DiagramFunctional Size Measurement
  • 29. 29Size estimationLines of CodeWhat does the number of lines tell me about size?13 LoC – 1 statementBackfiringTranslation to Functional SizeUncertainty range over 300%20 LoC – 3 statements
  • 30. 30Size estimationFunctional Size Measurement – Function Point Analysis FPA stands for FunctionPointAnalysis What the software should be able to do (functionality) Functionexpressed in a number Pointbased on an objectively described method Analysis Something intangible like functionality becomes a physical number that canbe used for calculations
  • 31. 31Size estimationFunctional Size Measurement – Function Point AnalysisExternal InputExternal OutputExternal InquiryExternal input filesInternallogical filesData oriented
  • 32. Size estimationFunctional Size Measurement – Function Point AnalysisCounting function points Based on established criteria each element isclassified: Each classification has its own scoresInternal files 7 10 15External interfaces 5 7 10External input 3 4 6External output 4 5 7External inquiry 3 4 6 A function point never travels alone32SimpleComplex
  • 33. 33Size estimationFunctional Size Measurement – COSMICeXitWriteEntryReadeXitReadTransaction oriented
  • 34. Size estimationFunctional Size Measurement – COSMICCounting COSMIC function points Establish Functional Processes Determine the data movements # Entries # Writes # Reads # eXits Each data movement is scoredEntry 1 CFPWrite 1 CFPRead 1 CFPeXit 1 CFP A data movement can be identified alone34
  • 35. Estimating IT projectsThe second route35SizeEffortCostObjective
  • 36. 36Translating size into effortProject size as a cost driverSize Early On time Late Failed10 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. 37Translating size into effortTeam size as a cost driverMORE PEOPLE MAKE MORE NOISE
  • 38. Translating size into effortTeam size as a cost driver38Paul Masson’sLawParkinson’sLawBrooks’LawMinimal timeOptimal effortTimeEffort/CostRealisticProductivity
  • 39. Translating size into effortWhat can you do with Functional Size39 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 effortHow to manage all the relations40
  • 41. Reliable estimationHow good do we know what we must do
  • 42. Reliable estimationCase – 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 estimate42
  • 43. 43frank.vogelezang@ordina.nlWatKostIT.blogspot.nlThePriceofIT.blogspot.com@FrankVogelezangFrankVogelezangwww.linkedin.com/in/frankvogelezang

×