From Product Description to Cost: A Practical Approach: Volume 2: Building a Specific Model PDF
Preview From Product Description to Cost: A Practical Approach: Volume 2: Building a Specific Model
Decision Engineering SeriesEditor DrRajkumarRoy DepartmentofEnterpriseIntegration SchoolofIndustrialandManufacturingScience CranfieldUniversity Cranfield Bedford MK430AL UK Othertitlespublishedinthisseries CostEngineeringinPractice JohnMcIlwraith IPA–ConceptsandApplicationsinEngineering JerzyPokojski StrategicDecisionMaking NavneetBhushanandKanwalRai ProductLifecycleManagement JohnStark FromProductDescriptiontoCost:APracticalApproach Volume1:TheParametricApproach PierreFoussier Decision-MakinginEngineeringDesign YotaroHatamura IntelligentDecision-makingSupportSystems:Foundations,Applications andChallenges JatinderN.D.Gupta,GuisseppiA.ForgionneandManuelMora PublicationdueApril2006 Metaheuristics:AComprehensiveGuidetotheDesignandImplementation ofEffectiveOptimisationStrategies ChristianPrins,MarcSevauxandKennethSörensen PublicationdueDecember2006 Context-awareEmotion-basedMulti-agentSystems RajivKhosla,NadiaBianchi-Berthouse,MelSeigelandToyoakiNishida PublicationdueJuly2006 Pierre Foussier From Product Description to Cost: A Practical Approach Volume 2: Building a Specific Model With171Figures 123 PierreFoussier,MBA 3f,15,ruedesTilleuls 78960VoisinsleBretonneux France BritishLibraryCataloguinginPublicationData Foussier,Pierre Fromproductdescriptiontocost:apracticalapproach Volume2:Buildingaspecificmodel.-(Decisionengineering) 1.Productionplanning-Mathematicalmodels2.Start-upcosts Mathematicalmodels3.Newproducts-Decision-making I.Title 658.1’552’015118 ISBN-10:1846280427 LibraryofCongressControlNumber:2005937146 DecisionEngineeringSeriesISSN1619-5736 ISBN-10: 1-84628-042-7 e-ISBN 1-84628-043-5 Printedonacid-freepaper ISBN-13: 978-1-84628-042-9 ©Springer-VerlagLondonLimited2006 Apartfromanyfairdealingforthepurposesofresearchorprivatestudy,orcriticismorreview,as permittedundertheCopyright,DesignsandPatentsAct1988,thispublicationmayonlybereproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers,orinthecaseofreprographicreproductioninaccordancewiththetermsoflicencesissued bytheCopyrightLicensingAgency.Enquiriesconcerningreproductionoutsidethosetermsshouldbe senttothepublishers. Theuseofregisterednames,trademarks,etc.inthispublicationdoesnotimply,evenintheabsenceof aspecificstatement,thatsuchnamesareexemptfromtherelevantlawsandregulationsandtherefore freeforgeneraluse. Thepublishermakesnorepresentation,expressorimplied,withregardtotheaccuracyoftheinfor- mationcontainedinthisbookandcannotacceptanylegalresponsibilityorliabilityforanyerrorsor omissionsthatmaybemade. Typesetting:GrayPublishing,TunbridgeWells,UK Production:LE-TEXJelonek,Schmidt&VöcklerGbR,Leipzig,Germany PrintedinGermany 9 8 7 6 5 4 3 2 1 SpringerScience+BusinessMedia springer.com To my daughter Pierrine, without whom this book could not have been written. Preface Volume 1 was dedicated first (Part I) to a general understanding ofthe cost forecast- ing,generally called “cost estimating”,and then to the important concept ofdata nor- malization (Part II), which is a prerequisite for comparing cost data, as it was remindedthat the only way the human mind found for forecasting the future was to extrapolate the results ofprevious “experiences”,which implies the necessity to com- pare them.Such a comparison can only be made on comparable,or normalized,data. Then (Part III) introduced the concept of what we called “general”models and eventually (Part IV) the use ofmodels in the cost-estimating process.Taking into account the “risk”in cost forecasting was an important chapter ofthis Part IV. By “general models”we mean that these models can estimate the cost ofanything – at least in a given “class”ofproduct,a class representing an industrial sector.These models,ofwhich number is limited,are difficult to build;they represent,ifthey are really general,a large investment. This volume (Volume 2) deals with the building of “specific”cost estimating models (sometimes also called “in-house models”).A specific cost model explicitly refers to a “product family”,which is a set of products fulfilling the same func- tion(s) and manufactured about the same way. A short word at the history of science helps illustrate the fundamental differ- ences between specific and general models. Any science first looks at the facts and records them:in our modern language, any science starts by building databases.In the domain ofastronomy the fantastic amount ofdata accumulated by great observers,such as Copermic,Tycho Brahé,… deserves our admiration. The second step – not necessarily carried out by the same persons – is to try to establish and quantify correlations between variables which,apparently,may seem different.Once a good correlation has been demonstrated between these variables – this involves what is called in this volume “data analysis”– it is rather tempting a build a mathematical relationship between these variables;these relationships do not “explain”anything;they are just a tentative to group in a few equations what we know about the facts.The nice thing about them is that they make us able to predict values of one variable when the other one(s) is (are) known,as long as the previ- sionist remains in the same area (we would say,in the domain ofcost,in the same “product family”).These relationships are called “laws”(we would say in the cost domain cost-estimating relationships (CERs)).There are plenty of such relation- ships in all sciences;just remember:the three Kepler laws,the Kirchoff laws,the Van der Walls law,the law of light emission by the black body,etc.The authors of these laws did not know the regression analysis and generally work by curve fitting, but the idea is the same. viii Preface The third step is far more recent;it implies to look “below the facts”in order to understand them (which means explaining by investigation things more in depth and finding reasons for their behavior).1This is done by finding abstract concepts (such as the forces in the description ofmotion,the fields in electrodynamics,the entropy in thermodynamics,the quanta in light emission,etc.) from which the facts could be “explained”.The mathematical support then becomes a must,as it is the only way the human mind can work with abstract concepts.The great names (the “giants” to cite a word used by Newton)2 in this respect are Newton, Maxwell, Boltzman,Planck,Einstein,etc.The set of equations they developed,generally a very limited set from which all phenomena can be predicted,3is generally called a “theory”. In the cost domain,the abstract concept that throws a powerful light on the cost behavior is the “product structure”.This concept was described by Lucien Géminard in France and maybe others.This concept,which is developed in Part III ofVolume 1,helped create a general “theory”ofcost behavior.But it is the only time I will use this term of“theory”in our domain and for three reasons: 1.The first reason is that human behavior is far less predictable than natural phe- nomena in the physical sciences.Therefore the fantastic level ofprecision often attained in the physical sciences cannot be obtained in the domain ofcost.The word “theory”in the domain ofcost could therefore be misleading and rejected, although it correctly describes the human look at the things. 2.The second reason is that – as it was said by Karl Popper – a theory can neither be considered as finished:it has always to be checked with the results ofnature and just one phenomenon which does not fit with the theory seriously questions its validity:remember the experience carried out by Morley and Michelson,or the advance of Mercury perihelion.One single experience can force people to adopt another theory.But in the current language,theory is considered as the truth and,again,the common word could be misleading in the domain ofcost. 3.The third reason is related to semantics:in the ordinary language,the word “the- ory”has two opposite meanings.First ofall it is used,with great respect,to qualify the work ofthe giants who preceded us.But the second usage is rather dangerous: ifyou arrive in a meeting with a cost estimate adding that it was prepared with such or such theory,you may be sure that somebody will demolish your estimate, saying it is just a “theoretical”approach ….The word “model”is much more accepted than the word “theory”and we will use it. As the techniques for building such models are now well understood (even ifthey can still be improved),preparing these models can be done by any company,and the cost analyst has just to follow the documented procedures.This does not mean that the process can be fully automated:during his/her work,the cost analyst will have to make decisions,which require a good understanding ofthese procedures. 1It is well known that we never “understand”nature fully,by a step-by-step analysis requiring less and lesshypothesis:understanding nature really means reducing the number ofthe hypotheses which are necessary for predictions. 2IfI could see farther than the other ones,it is because I was sitting on the shoulders ofthe giants who preceded me. 3This illustrates the power ofboth the concepts and the mathematics which use them! Preface ix The major advantage ofthese specific models is that they are built from the com- pany own data (this obviously requires that the company was organized for capturing and saving its data,and this is the major constraint).Therefore: 1.The cost analyst can choose the variables, or “parameters”, he/she wants to include in the model,depending on the purpose of it (for instance he/she may prefer to use functional or physical variables). 2.The credibility (and credibility is an important concept in cost forecasting!) ofa cost forecast prepared by a specific model is higher that any forecast made by a general model,because the source ofthe forecast is clear. 3.The way the forecast was prepared is easy to explain to a decision-maker,even if only a few minutes are available. For these reasons cost estimators are strongly encouraged to start parametric cost estimating following this path. Using general models should come afterwards,for instance for cost estimating new products for which no comparison is possible with existing products (“first of a kind”),and therefore no specific model is available or even possible. Understanding the procedures is the key word for creating successful specific mod- els.For this reason all these procedures are fully described in this volume.Classical methods and new ones (such as the “Bootstrap”) will be described and illustrated. Cost estimating requires 30% of data,30% of tools and 40% of judgment and thinking,with a minimum of 80% in total.EstimLab™ – with which most of the computations which illustrate this book have been performed – was designed to get all these 30% oftools with a minimum ofeffort,freeing time for collecting data and making use of judgment,which is always the most important component in cost estimating. Paris Pierre Foussier February 2005 Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxv What You to Need to Know About Matrices Algebra . . . . . . . . . . . . . . . . . . . . . . xxxi Part I Population and Sample 1 From the Sample to the Population . . . . . . . . . . . . . . . . . . . 5 1.1 The Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.1.1 The Concept ofProduct Family . . . . . . . . . . . . . . . . . . 6 1.1.2 The Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.1.3 Formula or Analogy? . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.1.4 Breaking the Symmetry . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.1.5 What Could,Should,be the Causal Variables? . . . . . . 12 1.2 The Distribution (cid:1)ofYfor the Population . . . . . . . . . . . . . . 13 1.3 Drawing a Sample from the Population . . . . . . . . . . . . . . . . . 14 1.4 Using the Sample Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.4.1 The Three Possibilities . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.4.2 The Logic ofthe “Frequentist”Approach . . . . . . . . . . 17 1.5 How Do Probabilities Creep into Our Business? . . . . . . . . . . 19 1.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2 Describing the Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.1 The Center ofa Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.1.1 A First Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.1.2 Other Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.1.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.2 The Spread ofa Distribution Around the Center . . . . . . . . . . 26 2.2.1 The Standard Deviation . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2.2 Other Measures ofthe Spread . . . . . . . . . . . . . . . . . . . . 28 2.3 The Shape ofthe Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.3.1 The Level ofAsymmetry (Skewness) . . . . . . . . . . . . . . 29 2.3.2 The Level ofFlatness (Kurtosis) . . . . . . . . . . . . . . . . . . 29 2.3.3 Using Higher Moments . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.4 The Concept ofDegrees ofFreedom . . . . . . . . . . . . . . . . . . . . 30 3 Typical Distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.1 The “Normal”,or Laplace–Gauss,Distribution . . . . . . . . . . . 31 3.1.1 Mathematical Expression . . . . . . . . . . . . . . . . . . . . . . . 31
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