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Towards a knowledge-based assessment of conceptual cost estimates

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Towards a knowledge-based assessment of conceptual cost estimates
  See discussions, stats, and author profiles for this publication at: Towards a knowledge-based assessment of conceptual cost estimates  Article   in  Building Research and Information · March 2004 DOI: 10.1080/0961321032000172373 CITATIONS 19 READS 81 1 author:Some of the authors of this publication are also working on these related projects: Managing Project Risks for Competitive Advantage in Changing Business Environments   View projectAlfredo SerpellPontifical Catholic University of Chile 52   PUBLICATIONS   227   CITATIONS   SEE PROFILE All content following this page was uploaded by Alfredo Serpell on 22 October 2014. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the srcinal documentand are linked to publications on ResearchGate, letting you access and read them immediately.  Towardsaknowledge-basedassessmentofconceptualcostestimates  AlfredoF.Serpell Department ofConstructionEngineering andManagement,PontificiaUniversidadCato ¤lica deChile,Vicu•aMackenna4860,Santiago,ChileE-mail: aserpell @ Conceptual cost estimates are critical inputs for owners’ decision-making in the early planning stages of constructionprojects. However, a recurrent problem associated with conceptual estimating is how to assess the quality of theestimates, i.e. the expected accuracy and reliability of cost figures given the uncertainty and risk that every project willface during its development. One of the approachesused to assess the quality of an estimate is the application of expertiseand experience. This paper examines the problem of the quality of conceptual estimating, proposes a model of thisproblem based on existing knowledge and shows how the model was used to develop an assessment system. Through theuse of expert knowledge, it is possible to get an appropriate initial assessment of the expected accuracy and reliability of an estimate which should be later complemented with historical and empirical information.Keywords:  conceptual estimating, costs, estimating methodology, knowledge-based models, project costing, uncertaintyLes estimations des cou ˆ ts sont des informations importantes pour les proprie´taires amene´s a`  prendre des de´cisions de`s lede´but de la planification des projets de construction. Or, un proble`me re´current lie´ a` l’estimation conceptuelle est celuid’e´valuer la qualite´ des estimations, c’est-a`-dire la pre´cision et la fiabilite´ escompte´es des chiffres, compte tenu del’incertitude et des risques que tout projet rencontre pendant son de´veloppement. L’une des me´thodes utilise´es poure´valuer la qualite´ d’une estimation est de s’appuyer sur les compe´tences et l’expe´rience. Dans cet article, l’auteur examinele proble`me de la qualite´ de l’estimation conceptuelle, propose un mode` le de ce proble`me reposant sur les connaissancesexistantes et montre comment il a e´te´ utilise´ pour e´laborer un syste`me d’e´valuation. En ayant recours aux connaissancesd’experts, il est possible d’obtenir une premie`re e´valuation approprie´e de la pre´cision et de la fiabilite´ escompte´es d’uneestimation; elle devra eˆtre comple´te´e ulte´rieurement par des informations historiques et empiriques. Mots cle´s:  estimation conceptuelle, cou ˆ ts, me´thodologie de l’estimation, mode`les base´s sur la connaissance,e´tablissement du prix d’un projet, incertitude Introduction Conceptual estimates are critical inputs for owners’decision-making in the early planning stages of a con-struction project. Owners or clients have to make plan-ning decisions based on cost figures that are estimatedunder a high level of uncertainty about the project’sfuture. An assessment of the expected quality of thisinput is as important as knowing the expected cost of a new project. This can be considered as a way of mea-suring the cost risk of the project.For the decision-maker (i.e. owner), quality means theexpected accuracy and reliability of the estimate figure.Figure 1 shows a model of the conceptual estimatingproblem, where the estimator has to determine anapproximate cost to accomplish the new project basedonly on a set of predictors about what the projectwould be when finished.The quality and quantity of these predictors willimpact on the capability of the estimator to estimatethe future project cost accurately. Conceptual estimat-ing requires extensive knowledge and expertise(Shen  et al. , 2001) and requires extensive use of judge-ment to produce a meaningful result (Rush and Roy,2001). B UILDING  R  ESEARCH  & I NFORMATION  (2004)  32 (2), March–April, 157–164 Building Research & Information   ISSN 0961-3218 print⁄ISSN 1466-4321 online # 2004 Taylor & Francis Ltdhttp:⁄⁄⁄journalsDOI: 10.1080⁄0961321032000172373  Using information generated from previous (Serpell,1990) and ongoing research, the present paper exam-ines the problem of accuracy and reliability as mea-sures of the quality of a conceptual estimate,proposes a model of this problem based on existingknowledge and shows how the model was used todevelop an assessment system. Conceptualcost estimatingaccuracyandreliability Accuracy can be defined as nearness to truth(Rebata, 1978). Something is accurate if it is exact andfree of errors and mistakes. In the case of constructionconceptual estimates, accuracy reflects the closeness of estimates to the actual reference cost of a project. Thedifference between the estimate and reference values isthe estimating error. For an owner, this reference costis normally the lowest bid received for a project.Accuracy can be defined as the per cent differencebetween the estimated value of the product or workwhen compared with the price for which the productor work is contracted (True, 1988).Reliability is a very general concept that is applied toseveral different domains. The concept is more com-mon in fields such as materials and structural engineer-ing, equipment performance and test measurement,where precise experimental and actual data are easyto obtain (O’Connor, 1985). The application of thisconcept to ‘softer’ areas has been much more limitedbecause of the difficulty to obtain data. According toBabbie (1983), reliability is a matter of whether a par-ticular technique, applied repeatedly to the sameobject, would yield the same result each time.Nachmias and Nachmias (1987) defined it as theextent to which a measuring instrument contains vari-able errors, i.e. errors that differed from observation toobservation during any measuring instance. Accordingto Evans and Lindsay (2002), the reliability of a mea-surement refers to knowing how well the measuringinstrument consistently measures the true value of the characteristic. Rebata (1978) gives a definition of reliability as the degree of variance shown by a statisticin repeated sampling, adding that reliability is also ameasure of the degree of consistency with experience.As described by Ahuja  et al.  (1994), the success or fail-ure of a project is in great part dependent on the accu-racy of several estimates. Unfortunately, in many cases,estimates are used as deterministic figures and toomuch confidence is assigned to them (O’Connor,1985). The expected accuracy range and its associatedreliability enable the decision-maker to analyse differ-ent possible scenarios according to different cost fig-ures. This information helps planners establishcontingency levels on a sounder basis and manageuncertainty better. In addition, it assists managementin predicting the cash flow for the life of a project morerealistically and develops confidence in the estimatingfunction (Clark and Lorenzoni, 1985). Factorsa¡ectingtheaccuracyofconceptualestimates Factors were identified through the analysis of threesources of data:   Comprehensive analysis of the factors that affectthe accuracy of conceptual estimates was per-formed (Serpell, 1990). A number of factors wereidentified during the conceptual estimating litera-ture review.   In addition, data were gathered from a group of estimators that answered a survey on conceptualestimating practices (Ashley and Serpell, 1988).The structure of this survey is shown inAppendix A.   Direct interviews with experienced estimatorsallowed for the discussion of additional accuracyfactors. Modelling theproblem An accuracy causal model was created based on thefactors identified as explained above. Each major cate-gory was expanded to more detailed levels as explainedbelow. Scope quality This category was subdivided into two factors thatattempted to measure the potential of variation of scope: completeness and stability of the scope. Thecompleteness of scope reflects the potential of variationof the scope due to the lack of inclusion of unidentifiedscope items at the conceptual stage. It includes twosubfactors:   design/estimating experience of the company’steam; the more experienced this team, the morecomplete the scope Figure 1  Estimate’s accuracy problem (adapted from Hogarth,1980) Serpell 158    consistency of scope with project demands; the bet-ter the scope represents the project stated needs, themore complete it is going to beThe factors that assess the expected stability of scopetry to represent the potential for the scope to changedue to changes in owner’s project needs or changestriggered by characteristics of the project. Three sub-factors are considered critical in this respect:   owner’s commitment: the more committed theowner organization is to the stated scope, the lowerthe number of expected changes  project complexity: the more complex the projectin term of size, work space and other parameters,the higher the possibility of scope changes  project technology: the higher the technology levelof the project, the higher the possibility thatchanges will be necessary in the future Informationquality Two types of information were considered: historicaland current. Two aspects of historical informationhave been included in the model. The applicability of this information attempts to measure how valid theexisting historical data are for estimating the currentproject. The reliability of historical information mea-sures the confidence that can be assigned to it as aresult of the previous collection efforts, possible errorsand inaccuracies. The quality of current information isdependent on its availability from vendors, designersand other sources. The same properties are consideredin the case of historical information. Uncertaintylevel Two basic uncertainty sources were included in themodel: environmental and project. Environmentaluncertainty covers unknowns related to changes inmarket conditions such as a reduction of supply, finan-cial uncertainty and other effects. On the other hand,project uncertainty is related to sources of uncertaintypresent during the project’s management and construc-tion. Labour productivity is considered an importantand uncertain factor. Project technology and complex-ity are also determinants of this uncertainty. Estimator performance The estimator’s performance is dependent upon threefactors: the estimator’s experience, the effort appliedand the estimator’s personal characteristics. The esti-mator’s experience includes that related to field con-struction and to estimating. The effort applied isdetermined to a great degree by the perception the esti-matorhasabouttheimportanceoftheestimate,forhimand for his company (Adams and Swanson, 1976).Finally, the most important personal characteristics arethe estimator’s common sense and self-confidence(Skitmore, 1985). Qualityof the estimating procedure The most important factors that affect the quality of the estimating procedure are the expected level of errors and omissions, and the time available to performthe estimate.The complete estimating accuracy model is presentedin Figure 2. This model is the basis of the measuringapproach proposed below. Developinganaccuracyandreliabilityassessment methodology There are two basic categories of predicting methodsthat can be considered for assessing estimates quality:   data-based methods: forecasts are made using his-torical data and quantitative models   judgmental-based methods: individual opinions areacquired and processed to derive predicted valuesThe databased methods require the availability of mea-surements of accuracy based on historical data and theuse of these data to predict future outcomes(Stevenson, 1982). Using the databased approach,extrapolative or causal models can be used to predictthe future. However, the assessment of estimates’ qual-ity presents several limitations that preclude theirapplication in this case:   prediction procedures require that information isalready available; however, in practice, most firmsdo not keep adequate estimating records   information must be collected over a number of years (Fildes, 1987)   collecting and processing the data necessary forassessing the quality of estimates is a costly process   even the most accurate methods leave a high levelof residual uncertainty, especially with very com-plex problems (Fildes, 1987)The judgement-based approach relies on the acquisi-tion and processing of individual or group opinionsnormally from experts in the field of interest. In thiscase, experts assess critical variables by considering thevalue of the factors that affect them. This is performedwith qualitative models. However, prediction methodsusing judgement also have some disadvantages for theassessment of estimates’ quality:   difficult to validate  subject to experts’ biases Towardsa knowledge-basedassessment ofconceptual cost estimates 159    performance can be worse than the performance of quantitative methods in many cases (Hogarth,1978)Mahmoud (1987) asserts that only when the condi-tions are similar in practice can more accurate predic-tions using quantitative techniques be expected.When the estimator deals with a limited number of observations, qualitative methods might be moreappropriate. Lawrence  et al.  (1986) show that, onaverage, judgmental and quantitative predictions areequally accurate, while in certain circumstances, judg-mental predictions are significantly better.In the present study, the proposed methodology is pri-marily based on experts’ experience and judgementthat can be complemented and expanded with feed-back information generated after each project. Thegoal is to validate experts’ assessments, to correctbiases of experts’ assessments and to generate moreobjective assessment models.Using the accuracy causal model as the core of theaccuracy assessment, a computer-based methodologywas devised (Serpell and Ashley, 1999). This metho-dology was based on the application of expertise andknowledge through a knowledge-based expert systemapproach. Assessmentreasoningprocedure The assessment procedure has been designed to evalu-ate the quality of an estimate by providing a qualitativereasoning approach. The first step in this procedure isto determine the conditions of the new project. Theseconditions correspond to the values of the mostdetailed level factors or raw factors of the modelshown in Figure 2. They are determined by the useras he appraises the different factors for the project/esti-mate under study. The set containing all these valuesestablishes the scenario under which the cost of theproject is estimated. This scenario will affect the cap-ability of the estimating system for forecasting the real Figure 2  Proposed estimating accuracy model Serpell 160
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