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1991 AACE TBlWBM3103S

H.5Practical Cost, Estimation in aCompetitive Environmentby Osama Moselhi, Tarek Hegazy, and Paul Fazio

'IBIEBDwIcpIa3Construction estimating forms the basis forvarious strategic decisions regarding preparation ofbid proposals, procurement plans, various levels ofschedules, and job cost control. As opposed to manu-facturing, construction estimating is a crude processdue to the absence of standardization of conditionsfrom one job to the other [a]. In addition, theinherently complex factors of weather, labor, materialand locality make the computation of exact construc-tion costs a matter of accident than of design. Yet,these estimating difficulties are exacerbated in thecompetitive environment so prevalent in the construc-tion industry. In order to win a job and maintain afair profit under such environment, a contractor needsto provide a competitive bid value in terms of realis-tic unit prices assigned to the different contract

items. To compile the bid proposal, contractorsgenerally have to perform, in a timely and efficientmanner, three main functionsz (1) estimate direct andindirect costs; (2) decide on an optimummarkup value;and (3) decide on an optimum bid unbalancing method.Although several estimating tools are available (eg,software systems and published cost data), they havenot been able to provide a structured estimating pro-cedure or an effective decision aid that adequatelyconsiders the realities of the competitive bidding en-vironment.This paper presents an integrated methodology forcost estimation and bid preparation under the riskyand uncertain environment so prevalent in the indus-try. The methodology minimizes redundancy and aidsthe various decisions necessary to compile a bid.

Based on the methodology adopted, a prototype micro-computer system (Em B) is developed. An exampleapplication is presented to illustrate the essentialfeatures of the system. The prototype operation andnecessary future enhancements are also discussed.~ICIBECY OF EXISTIIR; xxs

With the advent of affordable, reliable, and moreefficient computer systems in the 1980'6, intensiveresearch work has been conducted in the area of costestimation, aiming at the development of effectivetools f?r contractors to compile competitive bids ina timely and practical manner. On one hand, a largenumber of commercial computer software systems [3]have been developed to assist contractors organize

their direct and indirect cost estimates. Equalllarge number of books and publications have providedample cost data and/or demonstrated methodologies acustom-designed computerized systems that aid cotractors in cost estimation and/or job coat contro(See [7, 15, 19, 21, 22, and 261 for examples).the other hand, various research efforts have beconducted to develop decision aids regarding testimation of an optimum markup value and the determination of a bid unbalancing method. Several probability-based bidding strategy models have been prposed since the mid-1950'6, providing differentassessments to the optimum markup problem, mainly account of job profitability and expected competition(eg, the bidding strategy models of Friedman [SGates [9], and Carr [4 ]. Other research efforts habeen directed towards the development of optimum bunbalancing methods that improve the contractor'scashflow, using mathematical programming (eg, [24]).

Despite the proliferation of available estimatingtools and their underlying methodologies, estimatorsdevelop procedures of their own to compile the cost construction, based mainly on their experience and an intuitive manner that suits their work environmen[201. This has been attributed to the lack of generally accepted estimating guidelines [4]), and also the inability of existing tools to provide integrationamong the different efforts necessary for an overalestimating methodology. The main deficiencies available tools and procedures could be summar xed follows:Lack of inteqrationr the cost and time of costruction are highly dependent on the quantity work, cost of resources, date of execution, aproductivity of working crews, pertaining to tmethod of construction adopted. Thus, coestimation, planning and scheduling and controoperations are highly interrelated managemefunctions, although usually treated as thredistinct and isolated ones [25]. Most availabletools are designed to perform one of the threfunctions, leading to high redundancy, timeconsuming processing operations, and higheprobability of introducing errors.Lack of structured methodolosv8 two basic aproaches have evolved to orqanise work items festimating. One approach -ia to identify wocategories contained in the project's writtenspecifications, such as those of the Construction

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1991 Aiuz Y!@AEmmIoBB

databases for estimation purposes. In general, howev-er, researchers have reported that databases contarn-ing historical productivity data, in' terms of work-hours needed to perform a certain work, are morepractical than those containing unit costs [I, 211.This is because historical productivity data are notas sensitive to change over time as unit cost dataare. Currently in construction, several publishedcost data describe combination of crews, averageproductivity data, different construction activities,and work packages (eg, Means [15]. These data couldreadily be utilized in developing an integrated costestimation methodology.

articles. The linear programming model developed

Qualitative A6sessmantThe first aspect to be considered in the qualita-tive assessment of bid preparation, as shown in Figure1, is the utilization of a simple and practicalprocedure for optimum markup estimation. Such aprocedure should consider many of the qualitativefactors that represent the risk environment which thecontractor has to assess (eg, contractor need for the

job, market conditions, and owner attitude) andprovide an estimate of the contractor's probability ofwinning the job associated with the optimum markupvalue estimated. Although most of the existingbidding strategy models provide such estimates, inpractice, they have been very limited in use due tothe limitations described earlier.In recent literature, research work'was pursuedin an effort to simplify the optimum markup estimationprocedure and include the qualitative factors. Someof these efforts have not been successful since theyincluded some 'of the qualitative factors into themodel formulation, and thus, add more.complexity tosuch models. Some of those efforts include the ea&yworks of Goodman and Burmeister [lo], Knode andSwanson [14], and Grinyer and Whittaker [ll] where

factors such as contractors managerial judgement andlimited capacity were introduced into the models.l4oselhi and Hegasy [17, 181 have presented acomputer program (BID) incorporating the three common-ly used probability-based models of Friedman (81,Gates [9], and Carr [4 ]. In an effort to'extract thecommonalities and markup trends among those models,the program was used to conduct a parametric study andsensitivity analysis over a wide range of statisticalparameters that characterize bid situations (mean andstandard deviation-of bid/cost ratio and number oftypical competitors). The study revealed that thethree bidding models used represent a pessimistic

(Friedmans), an optimistic (Gates'), and a mostlikely (Cart's) estimators for optimum markup. Atrade-off among these three strategies could be s&nplydone by the contractor, in view of the anticipatedrisk environment. As such, program (BID) is perceiveda simple and satisfactory decision aid, for theinitial prototyping of the integrated estimationmethodology.

The second aspect to be considered in the quali-tative assessment of bid preparation, as shown inFigure 1, is the utilization of a simple procedure forbid unbalancing. Bid preparation frequently consti-tutes the compilation of all the project costs intounit Prices assigned to the different contract items,to be submitted to the owner as the contractor8s bidfor the project. This bid unbalancing technique isused to enhance the. contractor's cashflow, whilemaintaining his/her competitiveness. The total ofdirect cost, indirect cost, and profit (markup) areoPtimallY distributed over the different contract

Stark and Mayer [24], minimize the contractor's cout-of flow as an objective, under a set of cstraints: limited cashflow, expected differences bid quantities, and estimated upper and lower limitfor the unit prices. As such, this cashflow analysrequires data pertaining to the expected expense cur(S-curve) and the expected income profile, which.couldbe obtained based on the project cost qd scheduestimates.Prooedura

Based on the previous discussion, the, cestimation methodology that effectively includequantitative and qualitative assessments could outlined as shown in the flow diagram o f Figure 2. the first step, bid documents are received and contr,act.items form transformed into a computerizedatabase, with the ,following fields: contract itnumber, item description, unit of measure,. and quantity. In the next step, work breakdown structure(WBS) is performed, based on study of the projecdrawings and specifications. Interactive WBShighly desired, and WBS templates can be of greassistance. Bach element in the W SS is automaticallyassigned a unique code of accounts. The elements the lowest level of the WBS are interactively assigna task or a group of tasks (ie, activity) from appropriate database(s),'and the user is prompted the quantity of work estimated and the appropriate'contract item to which this task or activity linked. Once the logic-driven WBS is performeddirect costs associated with.all the elements of WBS are automatically calculated by means of a suable algorithm that reads the a,ctivitiea and tasks the WBS elements and retrievesftheir resource typcost and average productivity data from the apppriate databases. The,algorithm calculates the labcosts, equipment hours and costs, material quantitiesand costs1 'subs costs, and total workhours used, addition to the total of direct costs, for the different WSS levels and contract items,

RECEIVE RID DOCUMENTS& LL CONTRACT FORM.4t WORKBREAKDOWN 1 PROkEREPORTS.

ESTIMATION.

Figare - Flow Diagram of an IntegratedMethodology for Cost Estimation and Bid PreparationIn the integrated environment, the..tasks activities identified in the cost estimation step

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to be scheduled, and the cost implications of such aschedule addressed. In the scheduling step, activ-ities are assigned planned start and finish times, andCritical activities are determined. Practical produc-tivity factors should then be assigned to the activi-ties to account for expected weather conditions at thescheduled times, trade congestion, overtime, and otherproductivity-related factors, Workload of ownedresources has to be considered to adjust the cost ofresources. Based on these considerations, a cycle ofschedule updates may become necessary, and resourcesmay have to be real-located, impacting the direct costand the schedule. According ly, reports pertaining tothe project activities, direct costs, schedule, andresource use, can be generated at the differentmanagement levels. Some of these reports, particular-ly those pertaining to accumulated resource use,provide a guide for indirect cost estimation.Indirect costs are generally estimated to includethe project overhead and a part of the firm generaloverhead, and the total costs cannot readily be

attributed to a certain contrac t item. A list ofpossible indirect cost items could be utilized andestimated costs are assigned to those applicable tothe project.The step to follow is to identify the projectexpected competition and collect available informatiqnabout the competitors and any other factors thatcontribute to a better classification of the projectdegree of risk. Accordingly, optimum markup andprobability of winning the job are estimated, utilix-ing a suitable bidding strategy that provides anadequate decision aid. Once this is done, the bid canbe prepared for submission to the owner. A suitablebid unbalancing procedure is utilized, such as that ofStark and Mayer, to provide the final unit prices forthe differen t contract items. A possible strategy to

be used with the linear programming algorithm is tospecify as a constra int that the unit price of acertain contract item is greater than or equal to thedirect cost of this item/item quantity. A simplerprocedure for bid unbalancing would be to allow userinteractive distribution of the indirect costs andprofit among the different contract items.

Eased on the methodology described earlier, amicrocomputer system (ESTICZQTSIR) s being designed andimplemented in an effor t to illustrate the practicali-ty of the methodo logy. The computerized system isdesigned in a modular architecture, incorporating fourmain modules, as shown in Figure 3: a cost estimation

module, a planning and scheduling module, a markupestimation module, and a bid preparation module .These modules are linked through a core of databasesdesigned based on input from Wontreal area contractorsin building and civil engineering works.The system contains basic resource data indifferent databases8 labor database, equipmentdatabase, constru ction material database, permanentmaterial database, crews database, and subs database.Another database includes data regarding various worktasks and a reference to the resource used to performthat task and the productivity of those resources*Several tasks can be grouped to form an activity thatcan be stored in a separate database for efficiency ofprocessing. The last database contains data regardingthe competitors and their performance in past bids.With its database, spreadsheet, and graphics capabili-ties, Lotus l-2-3 is used as an implementation envi-ronment for the present system databases. The recordstructure of the various databases is described inFigure 4 (see page H.5.5). Bach of the system's nine

databases is a separate Lotus file, and the databasemanager is a macro-driven program that customizes theuser interface, allowing user-interactive maintenanceof the databases and simultaneous data viewing asneeded. The decentralized design adopted allows eachdatabase file to have as many records as the usermight want without much effect on the processing time.When a database is saved, a standard ASCII version ofthe database is produced and can be read by an inter-facing program, designed to link the databases to thedifferent system modules.A work breakdown structure is also implemented ina user friendly, menu-driven lotus environment.Currently, the WSS allows the user to specify threelevels: area level (1 to 7 elements), major-activitylevel (1 to 7 elements), sub-activity level (1 to 7

elements). The total number of elements permitted atthe lowest WBS level is therefore 7 * 7 * 7 = 343.However, if these elements are selected from theactivities database, then the total number of tasksincluded in the project could be unlimited. In Figure5, WSS for the example project is shown, with a uniquecode of accounts assigned for each WSS element. Thecode is designed to be a sequential number from 1 to4008 7 elements at the area level, 45 elements at thesecond level, and 343 elements at the third level, inaddition to one code for the entire project. As such,the code allows the processing of the WSS data in

j-.-I

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1991 AWB !PmnSAc!i!IoIvS

..,:.,:_: Fields: ,;.ljj rate ($).i,cjijli: Fringe Benefit,,:;li.:$ Weekly,zj:i:I oveflime.,.>::..j.::..,.:.:

-# of resources.

tional costs-External rent

($/hour). costs ($/hour). .,( .:::......:.: .:,.:..\I..,......,:,c....,-Fuel Consump. a..v,s,x.ya,....::, ... :::. ..:..:. .::,,. ,.::.-Fuel cost.-Engine oil

consumption.-Engine oil cost.-Gear oil consumption.-Gear oil cost.-Hydraulic oil consumption.-Hydraulic oil cost. ;:::. -Price ($)/ Unit.::j;:::::3:.: I.,, ., , . .( ,. ,, .,( ,. , .,i:iilii~ii~~.~~~........,,....,....,........ ~ .,.,jl..,.,.:,.,...,. .. .. .. ,, ,. ..>:.:.:.~..,:.,:.;:. Tnnnt Pnln.

-Depreciation period( year) .

TASKS /;ASEATABP InputFieldsCOMPETITORSACTIVITIESDATABASE DATAL InPutFieldsInput rFields

-Code.-Description.-Activity code.-Relation to

predecessor.-Relation to

Notes:

Calculated Fields

NON

Mean (p) of Bidto Cost ratio.St. Deviation(o) of Bid toCost ratio.

Code.Description.Unit of Measure(U.O.M.).Resource code(Labor, Equip.,

Material, orCrew).

# ot resources.Daily U.O.M.output.

NON

Code.Competitor.

OptionslMean (p) of Bidto Cost ratio.

St. Deviation(a) of Bid toCost ratio.

#atabases are designed based on input from Montreal area contractors - Databases data could be saved with the project data files1 heavy civil and buildings. - All the data bases allow user specification of the date when last modified .Figure 4 -&xordStructnreo f ContractorDatabase

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arrays of 400 maximum size,avoiding PC memory limitatio-t-S. at any WBS level, theelements' codes are functionof their parent elements atupper levels (as shown in ~~~~~~~ ~Figure S), and as such the 1aggregation and/or detailingof the WBS data is facilitat- mm fl.Nm@l ffB!B Morn LWed. The WDS is performed in Ian interactive manner, withinput templates and menusthat dynamically incorporatethe selected WDS elementsinto the user interface, hid- 11-B-S Level 3 : SUBJWTIUITIES I :ing the internally calculated IIcode (see Figure 4a). LEUEL 1: EAST-IBEA IITheWBS elements' data are stored LEML 2: SUB-STBUC. I Iin a database of 400 records, Sub. Act. t)BT. I) QlhWTITY iIwith the following fields: a -----reference indicating the po-sition of this element on the=s, the contract articlenumber that is linked to theelement, the quantity ofwork, the unit of measure,the number of work repeti-tions, and the task or activ-ity code that links that ele-ment to the tasks database orthe activities database (see +92==fr=Zlll=ll==fllI-II-ILIE--llllrlrll=========~+Figure 6b). Fig. 4 @I).

The prototype developedincorporates an interfacing pllanxT :NosA.wBs WBSalgorithm that integrates the --_--^-^-----^------------------------------------------------------------databases and all the system REF. DEXRIFTION ART. #modules, except for the plan- QUANTITY U.O.M. Repeat. CfJDE____________-_---__--------------------------------------------------ning and scheduling modulewhich is currently being im-plemented. The system menuoptions shown in Figure 7should be followed in se- Al-Ml-S1 DENXTERING 1 1000 sfca 2.22quence, and the user is prom- Al-Ml-S2 Excavation 1 4800 cuyd 2.1pted if they are not. The Al-Ml-S3 Piling 2.1 50 eacil 2.355first option is to start the Al+ll-S4 Concrete Footing 2.2estimation by filling the 510 cuyd 3.1Al-XL-S5 Sand Fill @ Slab 2.2contract articles and per- 160 cuyd 2.223forming the WDS. The second Al-Nl-s6is to generate reports con- Al-Ml-s7cerning the different WBS Al-M&S1 Form Work 3 1200 sft 3.751elements and the resources Al-G-S2 Rebars 3 1200 sqft 3.5used. Samples of these re- Al-&?-S3 Concrete Walls 3 150 cuyd 3.12ports for the example project Al-K?-S4 Structrl Framing 3 1200 sqft 6.1are shown in Figure Ba and b. Al*-s5These reports provide elabo- Al-&!-S6rate data on the cost ele-ments, workhours, and the Al-&?-s7resources used, for each Al-M3-Sl Brickwork 4 2600 sqft 4.1task. These reports could A1+3-S2 Interior Panelng 7 1300 sqft 6.43then be utilized in formulat- . . .. 0. .ing a strategy for allocating 0_----------^--------__________^_________---------------------------------individual indirect cost com- lig. 6@p,ponents. A Lotus spreadsheetis prepared with differentindirect cost items, and thecontractor is expected to I?igum 6 -a) WBS tk'exiplate madc2smm; b) Szmpls~S Dztmbazmfill the costs pertaining tothe project applicable categories. The next option as shown in Figure 9. The user is prompted to confirmcould then be activated and the interfacing program the markup selection, and accordingly proceed to theprompts program (MUD) to calculate an optimum markup bid summary option. A bid summary report is shown inutilizing the competitors' data residing in the Figure 10, where detailed direct costs associatedwithdatabase. During optimum markup calculation, the user each contract item are provided. The total of thecan interact with BID to visualize the impact of a indirect cost and the profit (markup *- direct cost) isselected markup on the probability of winning the job, interactively distributed among the different contract

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Total Directs ts)= 2054516Total Indirects( 135450. . . . . . . . t!aarjQl.p(F -,)= 3.5Project: KEA.prj - Bid Sunmary Report.

Total to Distribute(S) = 207358 - Assigned: 182358 - Remaining: 25000----------^________^^___________^_______-----------------------------------------------------------------------------Art. Description UNt Quantity Labor Equivt Platehal slh other lbtd Indirect Unitrt cost cost cost cost cost direct cost prxe-----------_____________________^______^--------------------------------------------------------------------------1.00 Excavation wft 1000 7461 738 0 200000 0 208198 +O 208.22.10 Plled foundations each 20 0 0 0 45000 0 -15000 *100000 7250.02.20 Isolated Footings each 25 35622 6559 59582 0 0 101763 +25000 5070.53.00 Supsstructure flaer 20:: 194292 752 201125 25000 0 421170 +O 21058.54.00 Brick work rn2 232266 0 158400 0 0 390666 +O 195.35.00 Electrical work hnn 1 23803 0 0 0 0 23803 *107358 131161.26.00 ?-kha~Cal work lsum 210 106222 0 9040 400000 0 515262 +O 515261.87.00 Interior Decorati flaer 167550 0 65640 0 0 233190 -50000 9159.58.00 landscaping lslno 1 422 42 0 115000 0 115464 *O 115464.1-----------____1-1__------------------------------------------------------------------ -^-^-------------^ra?bNDmm 767638 8091 493707 785000 0 2054516 +182358--------a--- I___-__----_____-^-----------------------------------------------------------------total Bid: 2236874.0a... UseDp&DDwnAr-toVieslallArticles.... F2-DIZ?IRIBUl'E>CF3-%?Gl?S>

items * Bach time a contract item is assigned anindirect cost, the unit price of that item is modifiedand so is the total bid value. The user is alwaysprovided with the total assigned and the remainingportion yet to be (see Figure 10).Based on the prototype operation, the system hasseveral interesting features2

0 highly structured, modular architecture allowingfuture expansions and enhancements;0 efficient, user interactive and fast processingon IBM AT machines and compatibles;0 transparent, changes in the databases are simplyreflected on the estimate;0 practical, databases are saved and downloadedwith the project files for records;0 flexible, all project files could be renamed andused as templates.

The planning and scheduling module is currentlybeing developed to permit bid unbalancing usingoptimization methodology.

A structured methodology for cost estimation andbid preparation is developed to improve the efficiencyand facilitate the process o f preparing a bid estimatein a competitive bidding environment. The methodologyemploys the work breakdown structure (WSS) concept, aunified code of accounts, and resource productivitydatabases, to provide an efficient quantitativeassessment of direct and indirect costs, incorporatingthe impact of the project schedule. The procedureintegrates two existing techniques: bidding strate-gies and linear programming, to consider the qualita-tive aspects of bid preparation. Bidding strategiesare used to maximize the markup value, and hence the

contractor*s profit. Linear programming is used tooptimally distribute the total of indirect costs andprofit among the different contract items (bid unbal-ancing or front-end loading), to improve the contrac-tor's cashflow. A prototype PC-based software system(Is-) is developed to automate the bid estima-tion process and provide a user friendly interfacewith minimum devel6pment cost and programming skills.The system is designed to work as a front-end to othermanagement software systems pertaining to scheduling,quantity takeoff, procurement, and job cost control.?UI example application is presented in an effort toillustrate the essential features of the system anddemonstrate the operations of the prototype developed.

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Dr. Osama EioselhiCentre for Building StudiesConcordia University1455 de Maisonnevue Blvd. WRontrreal, QuebecCanada H3G lM8

Tarek HegazyCentre for Building StudiesConcordia University1455 de Yaisonnevue Blvd. WMontreal, QuebecCanada H3G lH8

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Dr. Paul FazioCentre for Building StudiesConcordia University1455 de Maisonnevue Blvd. WMontreal, QuebecCanada H3G lW8