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NATIONAL COOPERATIVE HIGHWAY RESEARCH PROGRAM December 2015 Responsible Senior Program Officer: Gwen Chisholm Smith C o n t e n t s Chapter 1 Introduction, 2 Chapter 2 Literature Review, 4 Chapter 3 Research Methodology, 10 Chapter 4 telephone Interviews, 13 Chapter 5 online survey, 15 Chapter 6 Development of the Cost estimating Database and Prototype tool for Rural and small Urban Area transit Facilities, 25 Chapter 7 Guidelines for Reviewing Cost estimates, 42 Chapter 8 Conclusions, 46 References, 47 Appendices, 48 InDePenDent Cost estIMAtes FoR DesIGn AnD ConstRUCtIon oF tRAnsIt FACILItIes In RURAL AnD sMALL URbAn AReAs This digest presents the results of NCHRP Project 20-65, Task 53, âIndependent Cost Estimates for Design and Construction of Rural and Small Urban Transit Facilities.â The research was conducted by ICF International, Fairfax, Virginia, in association with Stuart Anderson, Texas A&M University, principal investigator, and Keith Molenaar, University of Colorado, and Clifford Schexnayder, Arizona State University, co-principal investigators. Research Results Digest 397 sUMMARY Most organizations that develop and deliver capital projects have a continuÂ ing program of projects. While large projÂ ects tend to have more visibility in these programs, small projects, when combined, often result in a substantial percentage of the total construction budget within a proÂ gram. Overruns in many small projects can lead to program overruns and hence be just as problematic as overruns on a few large projects. Estimating design and construction costs in a consistent, reliable, and accuÂ rate way is critical for an organization since the information generated is the basis for projecting program funds, priÂ oritizing projects by financial analysis, determining required funds, and providÂ ing a baseline for project control. This research focused on cost estimating methÂ ods and database development for design and construction of rural and small urban area transit facilities, which are usually small, numerous, and geographically dispersed. In order to address these problems, NCHRP funded the research to provide guidance to state transit agencies in assistÂ ing their subÂrecipients with preparing accurate design and construction cost estiÂ mates. The products of the study include a cost estimating database and an estiÂ mating prototype tool for rural and small urban area transit facilities. The protoÂ type tool is available on the TRB website (www.trb.org) by searching for âNCHRP Research Results Digest 397.â The cost estimating database and prototype tool can support conceptual estimating in the planÂ ning phase. This document is indepenÂ dent of the cost estimating database and prototype tool. Please refer to the introÂ duction and userâs guide in the prototype tool for more information before using the tool. The objectives of this study were to determine the distinct characteristics of rural and small urban area transit faciliÂ ties, collect actual historical cost data, and develop a cost estimating database and proÂ totype tool to assist agencies with preparÂ ing conceptual estimates. The limitations of this research and recommendations for future research are described at the end of this digest.
2small urban area transit facilities. Many factors cause this situation. First, few research projects have been conducted on collection of cost data for these types of facilities. Second, the functions and scopes of these facilities vary. For example, some facilities in rural and small urban areas serve as operations and maintenance buildings, while some are conÂ structed in order to facilitate passengers, but these can be combined with operations facilities. The garage space can be relatively larger if the fleet size is large. Depending on the number of passenÂ gers served, the passenger facilities may vary from unsheltered bus stops to transit terminals to transit centers. Third, the project can involve new facilities, but correspondingly the project may involve renoÂ vation and improvement works. Last, rural transit projects can receive funding from different sources and be administered by different agencies that may require that funding receivers follow different cost management procedures. Section 5311, the FTAâs formula assistance program for rural providers, is administered by the state departments of transportaÂ tion (DOTs), while tribal transit providers receive funding from grant programs directly, including Section 5307, urbanized area funds; Section 5309, bus and bus facilities discretionary program funds; and Section 5311 (c), tribal transit program funds. These funding programs are directly administered and managed by the FTA. Without a good cost estimating database of rural and small urban area transit facility project costs, it is difficult to prepare consistent, reliable, and accurate cost estimates. Therefore, there is a need to study the unique characteristics of rural and small urban area transit facility projects, establish a sound and structured historical cost estimating database for design and construction, and develop a correÂ sponding tool to facilitate the estimating process. The scope of this digest covers these three issues. Problem statement The FTA requires all state agencies receiving federal funding for the design and construction of rural and small urban area transit facilities submit independent cost estimates from their subÂrecipients for both design and construction as part of the application and grant implementation process. There appears to be no local or national stanÂ dard methodology or criteria for developing indeÂ pendent cost estimates associated with the design CHAPteR 1 IntRoDUCtIon background Rural and small urban area transit facility projÂ ects are relatively small in scope and dollar value, numerous, and geographically dispersed in small communities. It is difficult to estimate the design and construction costs for such projects because of: â¢ Variations in functions and project size, â¢ Different amenities associated with the facilities, â¢ Possible renovation of existing facilities, â¢ Lack of historical cost data, â¢ Unique risk factors affecting cost (e.g., remote location or lack of competition), and â¢ Absence of structured estimating processes. Extensive research has been performed and proÂ vides many technical and managerial references for estimating the cost of large urban construction projects. Selected research provides both a strateÂ gic focus and a howÂto focus. NCHRP Report 574: Guidance for Cost Estimation and Management for Highway Projects During Planning, Program- ming, and Preconstruction (Anderson et al. 2007) is a guidebook that identifies internal and external cost escalation factors and recommends appropriate global estimation strategies. Applications of methÂ ods for relevant strategies and tools to implement methods are also provided for each phase of project development: planning, programming and prelimiÂ nary design, final design, and implementation. The guidebook also describes the cost estimating and cost management processes in terms of nine general steps. The Minnesota Department of Transportation Cost Estimation and Cost Management: Technical Reference Manual (Minnesota Department of Transportation 2008) describes the estimating proÂ cedures in detail. Recent research specific to rural projects includes NCHRP Research Results Digest 381: Guidebook for Construction Management Practices for Rural Proj- ects (Hallowell et al. 2012). The digest addresses issues such as construction administration, engineerÂ ing, operation, and safety; cost estimation; scheduling; quality control and assurance; and claims and disputes based on proven management strategies. It does not cover cost estimating processes and methodologies for rural transit projects. There is a lack of compiled cost information or databases to support cost estimation of rural and
3Research objectives The main research objectives were to define the characteristics of rural and small urban area tranÂ sit faci lities, develop an appropriate cost estimating data base of relevant historical cost elements, and create a prototype tool to support a conceptual estiÂ mating process for these facilities. This research had the following three subÂobjectives: â¢ Identify the current estimating practice in the transit facility industry. â¢ Study the characteristics of available dataÂ bases and create regression models for preÂ dicting project design and construction costs. â¢ Incorporate the cost estimating prototype tool to facilitate cost estimation. Research tasks In order to achieve the objectives stated previÂ ously, this research included the following five tasks: Task 1: Conduct a Review of Recently Designed and Constructed Rural and Small Urban Area Transit Facilities Throughout the United States The objective of Task 1 was to determine the characteristics of rural and small urban area transit facilities and to understand the extent of the state of practice. A literature review and telephone interÂ views were conducted to collect key information related to typical types and sizes of facilities, locaÂ tion characteristics, and the availability of historical cost data for design and construction. The interview results confirmed or made corrections for findings from the literature review. Task 2: Scan of Rural and Small Urban Area Transit Facilities The objective of Task 2 was to collect data and inÂ formation concerning rural transit facilities to identify, at a minimum, (1) size and type of facility designed and constructed, (2) amenities provided, (3) location of facility, (4) any unusual conditions, and (5) actual costs of design and construction. An online survey was used to collect this information on a project level. Task 3: Develop a Database of Actual Costs The objective of Task 3 was to develop a dataÂ base of design and construction costs of rural and or construction of these types of transit facilities at the application stage. The objective of this research is to produce guidance for use by state transit agenÂ cies in assisting their subÂrecipients with preparing and reviewing accurate design and construction cost estimates. Research Questions The research questions of the project are disÂ cussed in the following. â¢ Characteristics and classification of rural and small urban area transit facilities â Based on functional types, how are the rural and small urban area transit facilities classified? What are the prevalent funcÂ tional types? â How do locations of rural and small urban area projects affect the design and conÂ struction of these facilities? What are the differences between rural and small urban area transit facilities? â For each functional type, what is the typiÂ cal project size in square feet (sf), as either an average or a range? What is the typical project cost, as either an average or a range? â¢ Cost estimating database and tool â What historical cost data does a state agency capture from bids or construction to support estimation of design and construcÂ tion costs of future projects? If cost data are captured, does the agency have a dataÂ base of these costs available? Where does the database reside, field offices or a central location? â What are the practical cost estimating methÂ ods and tools that have a history of success within the transit facility industry, such as scoping documents and summarized estiÂ mating steps? â How is the historical cost estimating dataÂ base developed in this research used to support estimating design and construction costs of rural and small urban area transit facilities? â¢ Risk assessment â What are the typical risks for these projÂ ects, considering functional type? â How can these risks be accounted in the project cost estimates and schedule?
4transit facilities. Limitations of the prototype tool are also addressed at the end of the chapter. Chapter 7 provides guidelines of reviewing cost estimates for rural and small urban area transit facility projects. Finally, Chapter 8 states study conclusions and disÂ cusses the recommendations for future research. CHAPteR 2 LIteRAtURe ReVIeW A literature review was conducted to acquire knowledge about the types of transit facilities in rural and small urban areas and to determine current cost estimating practices of the agencies responsible for these facilities. The literature review was necesÂ sary to support the design of interview and survey protocols and to provide insights into the developÂ ment of the cost estimating prototype tool. Searches were conducted for definitions of rural and small urban areas, transit facility functions and characterÂ istics, cost estimating methodologies, and risk idenÂ tification tools and measurement methods. The following databases were surveyed as part of the literature review: â¢ The Transportation Research Boardâs TransporÂ tation Research Information Services (TRIS). â¢ Academic engineering databases, such as Engineering Village 2. â¢ Academic business databases, such as EBSCO Business Source Complete and Management and Organizational Studies. â¢ ASCE Civil Engineering database. â¢ General Internet search engineâGoogle Scholar. â¢ Selected transportation agency websites. â¢ The Metropolitan Transportation CommisÂ sionâs online library. Review of the transit Facility Industry in Rural and small Urban Areas According to the definition given by the FTA, a rural area is defined in two ways by the U.S. DepartÂ ment of Transportation (Dye Management Group 2001). The first definition is an area with fewer than 5,000 people. The second definition is that rural is an area outside of a metropolitan area and having a population of fewer than 50,000 people. ResearchÂ ers interested in the transit facility industry can choose either definition according to their research needs. Hallowell et al. (2012) considered rural as an area with a population of fewer than 50,000 people. Their research identified cost estimating challenges, small urban area transit facilities. The historical cost data collected were input into an MS Excel database and normalized to the national average in year 2014 by using the city cost index and historical cost index in the 2014 version of the RS Means Building Con- struction Cost Data manual. Task 4: Develop a Cost Estimating Methodology to Support Conceptual Estimating The objective of Task 4 was to develop a cost estimating prototype tool using Excel based on statistical analysis of the cost estimating database developed in the previous task. A regression analyÂ sis was conducted to determine the relationship between cost and project size. Thus the regression function was built into the created prototype tool to predict project cost. The research background, instructions, and estimate report and details were also provided in this tool. Task 5: Develop Cost Estimating Reviewing Guidelines and Prepare a Research Report The objective of Task 5 was to develop guideÂ lines to support a cost estimating reviewing process for rural and small urban area transit facilities and complete the research report following the NCHRP guidelines. The guidelines of the cost estimating reviewing process are provided in Chapter 7. organization of the study This digest contains eight chapters. Chapter 1 sets the context of the research background along with the problem statement, research questions, research objectives, and research tasks. Chapter 2 focuses on the literature review concerning characÂ teristics of transit facility projects in rural and small urban areas, cost estimating databases and tools, and risk management practices. Chapter 3 describes the research methods, including the telephone interÂ views, online survey, survey data analysis, developÂ ment of the cost estimating database and prototype tool, and review of the prototype tool. Chapter 4 proÂ vides information on the telephone interview protoÂ col preparation, interview processes, and interview results. Chapter 5 discusses the survey protocolâs development, the survey process, and the results of the data analysis. Chapter 6 presents the developÂ ment of the cost estimating database, prototype tool, and estimating steps for rural and small urban area
5performed in the facilities include fueling, washing, fare collection, lightÂbulb replaceÂ ment, and fuelÂlevel checks. â¢ Level II: A secondary maintenance facility is often called an inspection garage. ActiviÂ ties conducted in this type of facility include light maintenance, engine tuneÂups, lubricaÂ tions, inspections, tire changes, brake repair, minor body work, and activities performed in Level I. â¢ Level III: A thirdÂlevel maintenance facility provides all kinds of vehicle maintenance, including engine and transmission rebuildÂ ing, testing, major body repairs, painting, and activities that can be conducted in Level I and Level II. Intercity bus transportation also plays an imporÂ tant role in smaller communities and rural areas due to its accessibility and affordable price for the local residents (KFH Group, Inc. 2002). The intercity transit industry is a private forÂprofit industry that offers scheduled passenger service and a number of other services, including package express, charter, and tour services. Intermodal and multimodal terÂ minals facilitate the coordination of the intercity bus services in both rural and urban areas (Fravel 2003). Regarding intercity transit facilities, the capital projÂ ects can be new intercity bus stations, inter modal facilities, administrative offices, and passenger ameÂ nities. The scope of facility projects can vary greatly, from lowÂcost repairs, ramps, or signs to major intermodal facilities in urban locations (Fravel and Barboza Jr. 2011). The Rural Transit Program Manual [Ohio Department of Transportation (ODOT), Office of Transit 2012] was developed to assist rural transit services in complying with all applicable federal and ODOT requirements. The manual discusses the determination of the need for rural transit and the implementation, use, maintenance, and operation of rural transit facilities. A series of documents were prepared by ODOT to support a facility feasibility study, scoping process, acquisition, and construction process. The manual recommends four steps for facility construction, which are shown in Appendix A. The Rural Transit Program Manual also states that design costs are normally limited to 6% of the estiÂ mated construction cost. Based on the evaluation of existing rural transit facilities in Ohio, a report concerning rural transit facility prototypes was developed by Brown & Bills including the lack of historical data, remote locaÂ tions, and less competition. To overcome these chalÂ lenges, the researchers suggested many strategies and resources, such as state agency cost catalogues and detailed cycleÂtime spreadsheets for equipment, material, and labor. In addition, contractors are a resource for gathering historical data and bid histories. Although Hallowell et al. pointed to examples of transit facilities that could include bus stations, administrative buildings, and storage faciliÂ ties, there were no classifications according to faciliÂ tiesâ functions. According to the Texas Rural Transportation Plan (Texas Department of Transportation 2012), transit facilities are categorized into the following groups: 1. Operations and maintenance â Administration â General purpose â Maintenance â Vehicle storage 2. Large passenger facilities â Park and ride â Terminal or garage â Transit center 3. Small passenger facilities â Sheltered bus stop â Unsheltered bus stop â SignÂonly bus stop Both new and renovated facilities are considÂ ered in the capital investment of rural transit projÂ ects. The cost of renovating a facility is 75% of that for building a new facility of the same type. For the bus stops listed, Texas A&M Transportation InstiÂ tute developed a cost per bus stop. For other types of facilities, the estimated cost per square foot is based on the Texas Department of Transportation Public Transportation Divisionâs database of historical capital cost per square foot. The recommended practice Architectural and Engineering Design for a Transit Operating and Maintenance Facility (American Public TransportaÂ tion Association 2010) includes the steps necessary to implement a new bus transit facility project, basic scope information required as part of a request for proposal procurement, and an example of a scope of services procurement document. In this recommended practice, facility types are classified as: â¢ Level I: A primary service facility providing running maintenance and storage; activities
6As project definition levels evolve and more inform ation becomes known, the expected estimate accuracy increases and accuracy range decreases. Besides project definition, there are systemic risks affecting estimate accuracy, such as project comÂ plexity, quality of reference cost estimating data, quality of assumptions used when preparing the estimate, and estimating techniques used. Cost Estimating Databases The RS Means Building Construction Cost Data manual is a primary and authoritative reference source of building cost information. RS Means tracks cost records from more than 900 cities in the United States and selected locations in Canada. A wide range of other key information is provided in the manual, including productivity rates, crew composiÂ tion, and contractor overhead and profit rates. The manual facilitates estimation of either commercial and industrial projects or large multiÂfamily housing projects from the planning stage to bid preparation. For the purpose of preliminary and intermediate budget preparation and feasibility determinations, data in the squareÂfoot cost section of the manual can be used. Project data from locations across the Architects. This report addressed guidelines for designing rural transit facilities from three aspects: general design guidelines, site guidelines, and buildÂ ing guidelines. Considering limited funding and lower operation and maintenance costs after conÂ struction, the building guidelines suggest that rural transit facilities should be constructed in a simple and elegant but economic manner (Brown & Bills Architects 2012). In order to build sustainable faciliÂ ties, the report suggests that general design and site selection of rural transit facilities meet a Leadership in Energy and Environmental Design (LEED) rating of silver or higher. Cost estimating According to the recommended practice of the Association for the Advancement of Cost EngineerÂ ing International (AACEI), cost estimates for buildÂ ing construction can be categorized into five classes (Christensen 2011). The classes are determined by the level of project definition maturity, which is usuÂ ally defined as a percentage of complete definition. The classification, maturity level, end usage of each class, methodology, and expected accuracy ranges are shown in Table 1. table 1 AACEI cost estimate classification. Estimate Class Maturity Level of Project Definition (expressed as % of complete definition) End Usage (typical purpose of estimate) Methodology (typical estimating method) Expected Accuracy Range (typical variation in low and high ranges,1 Lâlow range Hâhigh range) Class 5 0% to 2% Functional area or concept screening SquareÂfoot (squareÂ meter) factoring, parametric models, judgment, or analogy L: -20% to -30% H: +30% to +50% Class 4 1% to 15% Schematic design or concept study Parametric models, assemblyÂdriven models L: -10% to -20% H: +20% to +30% Class 3 10% to 40% Design development, budget authorization, feasibility SemiÂdetailed unit costs with assemblyÂlevel line items L: -5% to -15% H: +10% to +20% Class 2 30% to 70% Control or bid/tender, semiÂdetailed Detailed unit cost with forced detailed takeÂoff L: -5% to -10% H: +5% to +15% Class 1 50% to 100% Check estimate or preÂbid/tender, change order Detailed unit cost with detailed takeÂoff L: -3% to -5% H: +3% to +10% Notes: Adapted from the AACEIâs Recommended Practice No. 56RÂ08: Cost Estimate Classification System, 2012. (1) The +/- value represents a typical percentage variation of actual cost from the cost estimate after application of a contingency for a given scope. The typical confidence level is a 50/50 chance of falling within the accuracy ranges.
7(2013) compared different methods of estimating city indexes. First, they conducted a Moranâs test within the Geographic Information System. The test showed significant autoÂcorrelation between proxÂ imity and city cost index values in RS Means, which confirmed the method suggested by RS Means. Regarding methods to estimate cost indexes of citÂ ies not sampled by RS Means, the researchers comÂ pared the method suggested by RS Means with two alternative methods. One is called the âconditional nearest neighborâ (CNN) method and entails selectÂ ing the cost index of the nearest location listed in the city cost indexes within the same state as the location not included in the city cost indexes. This method considers the impacts of regulations and policies on construction costs. The other is called âstate averageâ method and entails taking the average of city indexes within a state and using that average as a location adjustment factor for cities not samÂ pled. For each city in the city cost index, assuming a cityâs index was not available, the researchers used those three methods to estimate the index. ConductÂ ing analysis on the difference between the estimates and actual cost indexes, the researchers found the estimate error of CNN had the smallest range and the lowest mean, median, standard deviation, and variance, which indicates the CNN method proÂ duces better estimates. The CNN method was used in this study. Cost Estimating Tools Early in the project life cycle, when there are many unknowns about a projectâs definition, paraÂ metric estimating models are usually used for the purpose of concept screening or schematic design. A parametric cost estimating model consists of one or more cost estimating relationships that are usuÂ ally developed from regression analysis of historical cost data. The cost estimating relationships convert technical or project parameters into estimates. HowÂ ever, the accuracy and validity of these estimates are limited since the cost estimating relationships are built on many assumptions. The estimate results are often prepared following UniFormat II, which allows the design team to evaluate alternatives with ease (Manfredonia et al. 2010). AACEI developed a parametric model for cost and value assessments (Association for the AdvanceÂ ment of Cost Engineering International 2014). This model supports estimation of building construction United States are collected to develop the squareÂfoot cost at the national average level, so the estimatorâs judgment and caution should be exercised when the squareÂfoot data are used. If more precision is needed, the latest edition of the RS Means Square Foot Costs manual would be a better reference. However, the squareÂfoot cost data in the manuals do not reflect characteristics of rural and small urban area transit facilities of small size and in remote locations. When more design details are available, the cost data in the unit price section of the manual can be used to prepare the estimate. The unit price section gives average prices for thousands of items. The unit cost data are divided into the 50 divisions based on the Construction Specification Institute (CSI) MasterFormat system. In the reference section, additional information is provided about construcÂ tion equipment rental costs, crew listings, historical cost indexes, city cost indexes, location factors, and a change order process. City cost indexes and historical cost indexes are important references when comparing projects located in different areas and constructed at differÂ ent times. According to RS Means, âa city cost index number is a percentage ratio of a specific cityâs cost to the national average cost of the same item at a stated time periodâ (RS Means 2014). Therefore, cost in one city can be adjusted to cost in another city and national average cost by using the followÂ ing two equations: Ã = Index for City A Index for City B Cost in City B Cost in City A, and Ã = Specific City Cost City Index Number 100 National Average Cost. Cost can be adjusted by using historical cost indexes and the following: Ã = Index for Year A Index for Year B Cost in Year B Cost in Year A. City cost indexes provide data for a number of cities in the United States and Canada. For those citÂ ies and locations that were not sampled, the manual suggests the cost index for a nearby city with similar economic characteristics be used. However, this sugÂ gestion lacks statistical validation. Migliaccio et al.
8Risk Management Many uncertainties are associated with project development. Project participants may fail to idenÂ tify the uncertainties and make appropriate adjustÂ ments to an estimate, which gives rise to project cost overruns. In order to address this problem, NCHRP Report 658: Guidebook on Risk Analysis Tools and Management Practices to Control Transportation Project Costs (Molenaar et al. 2010) discusses a series of systematic tools and management practices for use in risk identification, assessment/analysis, mitigation and planning, allocation, and monitoring and control. The guidebook explains risk priority ranking processes through risk analysis workshops. Once the prioritization of risks is completed, availÂ able resources for analysis, planning, and mitigaÂ tion can be best allocated. One of the best tools to facilitate the risk ranking is a probability Ã impact matrix used for qualitative risk evaluation. Each risk factorâs frequency and impact on project impleÂ mentation are combined in a matrix. Combinations can be categorized as (1) high risk, (2) moderate risk, and (3) low risk. Risks are prioritized based on the results of matrixes, and therefore, the project team can assign resources to the risks having the highest potential adverse impact on the project. An example of a probability Ã impact matrix is shown in Figure 1. Molenaar and Wilson (2009) developed a threeÂ tier approach process to estimate contingency based on risk analysis for highway projects. Their threeÂ tier process is shown in Figure 2. Project complexity is categorized as (1) nonÂ complex projects, (2) moderately complex projects, or (3) most complex projects. Based on the deterÂ mination of project complexity, one of three tiers of risk analysis and contingency estimating methods is selected. The three tiers are: Type Iârisk identification and percentage continÂ gency: for noncomplex projects, a list of risks needs to be developed, and contingency is estiÂ mated as a percentage of project cost. Type IIâqualitative risk analysis and identified contingency items: for moderately complex projects, a probability Ã impact matrix analysis tool is recommended to rank project risks. Then, expected values of risks (the product of probabilÂ ity of occurrence of risks and cost impact on the project) with high ranking will complement the contingency calculated in the Type I analysis. and design for offices, warehouses, industrial buildÂ ings, and labs that are steel or concrete structures with up to seven stories. The user needs to input parameters, such as floor area, floor height, number of floors, and percent of area as office. Then, once the âcalculateâ button is clicked, an approximate buildÂ ing cost estimate is shown in a browser window havÂ ing two major sections. The costs include all labor, material, and contractor overhead and profits, excluding site improvements, furnishings, producÂ tion equipment, and contingency. DProfiler, developed by Beck Technology, integrates a conceptual threeÂdimensional model with the process of cost estimating during planning and conceptual design phases. This has been widely used by architectural, engineering, and construction firms (Khemlani 2008). DProfiler uses RS Means cost database information that can be updated quarÂ terly in order to capture the most current cost data if the user pays a maintenance and support program fee. When a user starts a project in DProfiler, there are two important variables besides the project details. The first of these is the zip code for the projÂ ect location, which is needed so the estimated cost can be adjusted to an appropriate local cost from the national average. The second is the building type. Using the building type, the application automatiÂ cally enables corresponding cost data to be applied to the components of the model. The user can creÂ ate, modify, and remove components based on the requirements of design. When estimating the cost of each component, the user can either use the default RS Means cost data or input adjusted unit costs. The calculation formulas can also be modified based on the userâs specific needs. The estimates report can be generated in the format of CSI MasterFormat or UniÂ Format II. The model information can be exported into multiple formats, such as PDF, DPC, and XLS. At later stages of design, a more precise estimate can be performed based on the actual quantities of the building components specified by the project drawÂ ings. A quantity takeÂoff program is usually used at this stage. Programs such as OnÂScreen Takeoff, Paydirt, Constructware, and iSqFt, are commonly used in the construction industry. These programs translate and export dimension and quantity data directly from the project plans into an estimating system such as in Excel. Then, detailed calculations can be performed in the estimating system. The quantity takeÂoff software enables the estimator to prepare an accurate estimate in an efficient way.
9definition becomes clear and information for cost elements becomes available, the baseline estimates increase while the contingency portion should decrease. Regarding the contingency estimating method, Olumide et al. (2010) used a Delphi study to collect a group of expertsâ opinions in contingency estimating for highway projects, and a topÂdown slidingÂscale contingency estimating technique was developed. The method considers project complexÂ ity and the impact of different project development phases on project cost estimates. The method proÂ duces a range of contingency values. According to project complexity, project type is classified into three categories: most complex, moderately complex, and noncomplex. For each type of project, percent continÂ gency decreases across the phases of project developÂ ment with low, most likely, and high values provided for each phase. For example, for noncomplex projects, the slidingÂscale contingency is shown in Figure 3. AACEIâs recommended general principles on contingency estimating include the following methÂ ods (Hollmann 2008): Expert judgmentâContingency should be estiÂ mated based on the estimatorsâ experience and Type IIIâquantitative risk analysis and continÂ gency management: for the most complex projÂ ects, a risk analysis workshop to identify project risks is conducted, and project cost and appropriÂ ate contingency are estimated by the workshop team members. It is important to keep project risk factors and estimated contingency updated across the project development process. Baseline estimates and contingency are two major components of project estimates. Baseline estimates cover the development of estimated costs for all components of a project, exclusive of project contingency. This might be thought of as the bricks and mortar part of the estimate. Contingency is set to address project uncertainties and risks. The sum of the baseline estimate and the contingency proÂ vides the total estimate of project cost. As project Figure 1 Example of probability Ã impact matrix. Source: NCHRP Report 658: Guidebook on Risk Analysis Tools and Management Practices to Control Transportation Project Costs (Molenaar et al. 2010). Figure 2 The threeÂtier approach process to estimate project contingency. Risk Analysis Type ContingencyComplexity Source: âA Risk-Based Approach to Contingency Estimation in Highway Project Developmentâ (Molenaar and Wilson 2009).
10 quantified risk factors against cost escalation of historical projects. Once a risk factor is quanÂ tified by the project team, estimates, such as a most likely value and a range of costs, can be derived from the parametric model. Since each method has both advantages and disadvantages, the report pointed out that the best approach is to use more than two methods to estimate cost of risk factors. Expert judgment is a fundaÂ mental estimating method and should be combined with any methods. Analysis results of a parametric model may provide reference on developing a preÂ determined estimating method. Chapter summary Through the literature review, classifications of rural and small urban area transit facilities are defined. Project development processes, estimating practices, and prototypes of those facilities used by ODOT were reviewed. These resources provided insight for developing interview and survey proÂ tocols. Cost estimating techniques, databases, and cost estimating tools used in the construction indusÂ try were reviewed. Finally, risk analysis and continÂ gency estimating were studied. CHAPteR 3 ReseARCH MetHoDoLoGY A clear research methodology ensured that the research objectives of this study were achieved in a systematic, logical, and effective way. The research methodology of this study included a literature review, telephone interviews, a survey, and survey data analyÂ sis. Based on the analysis, a cost estimating protoÂ type tool was developed and tested. judgment on risk management and qualitative and quantitative analysis results. Predetermined methodâFor each AACEI estiÂ mate class stated in Table 1, contingency should be estimated as a single value or a range. Simulation analysisâThe simulation analysis method determines projectÂspecific risks and generates probabilistic output. Both expert judgÂ ment and the Monte Carlo simulation process are required. Monte Carlo simulation is compuÂ tational probabilistic calculations that use randomÂ number generators to draw samples from probÂ ability distributions (Anderson et al. 2007). In this case, Monte Carlo simulation is used to identify the effect of multiple uncertainties on the total project cost. One common method is called ârange estimating.â A range estimate repÂ resents a statement of project cost variability and conveys uncertainties in earlier stages of project development. First, a cost model that defines a total estimate at a certain level of detail should be determined. The model should consider all cost elements that have a significant impact on total cost estimates. Then, the project team assigns a range and distribution for each cost element and determines the correlations between cost elements. Finally, a Monte Carlo or similar simulation should be run based on ranges and distributions of the cost elements. The simulation results support the estiÂ mates by providing a total estimateâs distribution and related data, such as mean, median, and stanÂ dard deviation of the estimate. Parametric modelingâA parametric model is generated from a multiÂvariable regression rela tionship that is found through analysis of Figure 3 SlidingÂscale contingency for noncomplex projects. Source: âSliding-Scale Contingency for Project Development Processâ (Olumide et al. 2010). Note: MLE = most likely estimate. Pe rc en t C on tin ge n cy Phase of Project Development
11 area transit facilities suggested by the interviewees. For example, the descriptions of risk factors were aggregated based on all intervieweesâ inputs. In addition, typical unit prices for different facility types provided by the interviewees were normalized to the 2014 national average. The results of the interviews assisted in the design of the survey questions. Online Survey Based on the literature review and telephone interview results, survey questions were developed to collect specific historical design and construction cost data from transit agencies. The survey provided the initial input to the cost estimating database and was designed to capture data from the following key information: â¢ Size and type of facilities, â¢ Different facilities features, â¢ Locations of facilities, â¢ Actual design costs, â¢ Actual construction costs, â¢ Design schedule (start and finish), â¢ Construction schedule (start and finish), â¢ Unusual conditions surrounding the projects, and â¢ Major facilitiesâ component costs of conÂ struction. The pilot survey protocols were sent in PDF format to three transit managers, two DOT personÂ nel, and two consultants. The feedback from this preÂtest was important for revising the survey. After the survey protocol was finalized, the online survey was developed via the Texas A&M Transportation Instituteâs online survey tool. Potential particiÂ pants included state DOT Section 5311 program managers, transit managers, and consultants. Email addresses were provided by RTAP. With the help of personnel from RTAP, survey invitations explainÂ ing the background and objectives of the research as well as the online survey link were sent to potential survey participants. Several methods were used to improve the survey response rate, including sendÂ ing followÂup emails, shortening the length of the survey, and phone calls to transit managers. Emails asking for clarifications concerning survey results were also sent to participants. Survey Data Analysis With the help of the online survey software, all survey results were exported to Excel, where data Methodology The logic of development of this research is shown in Figure 4. The problem identification and literature review discussed in the previous chapters were fundamental to the development of the teleÂ phone interviews, survey protocols, and estimating prototype tool. Telephone Interviews A telephone interview protocol was developed to better understand the characteristics of rural and small urban area transit facilities. Interviewees included personnel at state DOTs, transit managers, and consultants involved in design and construction of rural and small urban area transit facilities. Their contact information was obtained from the Rural Transit Assistance Program (RTAP). Before the interview, a research project memorandum and a list of questions were sent to the interviewees so that they could be prepared for the discussions. Telephone Interview Summarization The summarization of interview results reflects the typical characteristics of rural and small urban Figure 4 The research process. Problem Identification Literature Review Telephone Interview Online Survey Survey Data Analysis Cost Database Development Cost Estimating Tool Development Conclusion Review of Cost Estimating Tool Cost Estimating Reviewing Guidelines Development
12 (10%), then the null hypothesis should be rejected. That is, a regression model is needed. In order to evaluate fit of the regression model, the value of RÂsquare should be checked. RÂsquare is calculated as a ratio of a modelâs sum of squares and total sum of squares. A large RÂsquare value (close to 1.00) indicates a close fit of the data to the estimated line. In the database, different combinations of adminÂ istration, operations, maintenance facility, and vehiÂ cle storage were categorized. For each combination of facilities, the percentage of construction cost for each construction system was calculated by taking the average of the survey responses. For example, for projects that were combinations of four types of facilities (administration, operations, maintenance, and vehicle storage), seven people provided gross percentages for building site work. The average value of the percentages was taken. The results of average percentages provided a reference for estimating a percentage breakdown for each construction system in the cost estimating proto type tool. Cost Estimating Database Development The survey data for parkÂandÂride facilities, shelÂ tered bus stops, unsheltered bus stops, and signÂonly bus stops were incomplete or limited. Therefore, the historical cost data collected to develop this dataÂ base cover only those facilities in administration, operations, maintenance, and vehicle storage. GenÂ erally speaking, administration, operations, mainteÂ nance facilities, and vehicle storage were combined in most of the projects included in the database. In the cost estimating database, the classification of building elements is the same as in the standards of the UniFormat II. Acting as a checklist for the cost estimating process, the standardized classificaÂ tion can facilitate communications among project participants (e.g., transit operators, state DOT staff, and consultants). The database includes project locaÂ tion, project type, midpoint of design time, midpoint of construction time, design cost (estimated and actual), construction cost (estimated and actual), perÂ centage of construction cost for each construction system, and contingency percentage. Cost Estimating Prototype Tool Development Two experts in the field of cost estimating were consulted and assisted in the development of the cost estimating prototype tool. The prototype tool was were normalized to the 2014 national average before further data analysis. The RS Means Building Con- struction Cost Data manual has a city cost index that includes many cities in all the states. The index of each city represents a percentage ratio of a buildÂ ing componentâs cost at any stated time to the national average of that same component at the same time. The cost index of the national average is 100. A national average cost can be calculated with the equation: Specific city cost City index number 100.Ã For cities that are not listed in the city cost index, the CNN method (the value of the nearest city included in the city cost index within the same state as the city not included in the city cost index) was used in this study as suggested by the research of Migliaccio et al. (2013). For example, a project was constructed in Fresno, California, in 2009 with an actual construction cost of $1,170,000. The city cost index is 107.9. Thus, the national average cost in 2009 of this project is Ã =$1,170,000 107.9 100 $1,084,337. The manual also has a historical cost index that can be used to convert national average building costs in a particular year to approximate building costs for some other time. The equation is: Ã = Index for Year A Index for Year B Cost in Year B Cost in Year A. For the project in the previous example, since the cost indexes of 2009 and 2014 are 180.1 and 202.7, respectively, the national average construction cost in 2014 is $1,084,337 Ã =202.7 180.1 $1,220,406. In Johnâs Macintosh Program (a statistical analyÂ sis system known as JMP), regression analysis was performed at a 90% confidence level (10% signifiÂ cance level) to determine the relationship between design cost and project size, and the relationship beÂ tween construction cost and project size. In order to prove the necessity of a regression model, a hypothÂ esis test should be conducted. The null hypothesis (H0) was that no regression model was needed, and the alternative hypothesis (H1) was that a straightÂ line regression model was required. Therefore, if the pÂvalue of the test is less than the significance level
13 and small urban area transit facilities. A structured interview protocol was developed based on the findÂ ings obtained from the literature review. It included 13 questions covering seven aspects of rural and small urban area transit facilities: â¢ Differences between rural and small urban area transit facilities, â¢ Typical project size, â¢ Typical design and construction costs, â¢ Availability of historical cost databases, â¢ Availability of checklists of critical estimate items, â¢ Typical risk factors, and â¢ Contingency estimation. The duration of each interview was about 1 hour. Interview Process Thirteen potential interviewees (five DOT perÂ sonnel, two consultants, and six transit managers) were selected. These professionals were located in different regions in the United States. Sending out interview invitations via email was the first step in the interview process. Six people (three DOT perÂ sonnel, two consultants, and one transit manager) expressed their willingness to participate in the interviews. The project memorandum and interview protocol were sent via email to these individuals several days prior to the scheduled interview. This enabled the participants to review the protocol and prepare for the interview questions. The memoranÂ dum included the research background, expectaÂ tions, and instructions, and confirmed the date and time of the interview. The research background covÂ ered the purpose and products of this research. The expectations and instructions outlined the key inforÂ mation sought from the interview. The team sought to develop a clear understanding the characteristics of different types of rural and small urban area tranÂ sit facilities. The estimated interview duration was provided to the interview participants at the end of the memorandum. Interview Results The interview results cover seven aspects, which are summarized in this section. Inputs from DOT personnel, transit managers, and consultants were aggregated to reflect the typical characteristics of rural and small urban area transit facilities. developed in Excel based on the surveyed cost data analysis results. Once the user inputs basic project information, such as project location, size, and the midpoint of design and construction year, the tool will provide the user with the estimated design and construction costs and contingency values. Based on the research of Olumide et al. (2010), continÂ gency percentage is estimated with low, most likely, and high values. The ranges of contingency percentÂ age of survey and interview results were used to estiÂ mate low, most likely, and high values of contingency percentages. Review of the Cost Estimating Prototype Tool A review of the cost estimating prototype tool was conducted. The cost estimating experts first reviewed and tested the prototype tool. Then, both an evaluation questionnaire and the cost estimating prototype tool were sent to people who participated in the telephone interviews or online survey. The results of the review helped to improve the clarity of the instruction and the friendliness of the operaÂ tional setting. Cost Estimating Reviewing Guidelines Development The basis of the cost estimating review guideÂ lines for rural and small urban area transit facilities was derived from previous cost estimating research. The guidelines cover cost estimating processes and a checklist of questions for each step of the cost estiÂ mating process. The review guidelines aim at ensurÂ ing that the process is performed in a systematic and consistent manner. Chapter summary This chapter discussed the research process and research methods used in the study. Details conÂ cerning telephone interviews and online surveys are presented in Chapters 4 and 5. The process of develÂ oping the cost estimating database and prototype is discussed in Chapter 6. The cost estimating review guidelines are provided in Chapter 7. CHAPteR 4 teLePHone InteRVIeWs Interview Protocol Telephone interviews were used to conduct a review of recently designed and constructed rural
14 Availability of Historical Cost Databases Few state DOTs or transit agencies maintain their own historical cost databases. They tend to hire consulting firms to perform certain tasks on their behalf, such as preparing and reviewing estimates and checking change orders for projects. However, consulting firms have separate cost databases for building construction, mechanical work, electrical work, plumbing, landscaping, and equipment. Both the RS Means Building Construction Cost Data manual and their own cost databases are used by the cost engineers of the consultants. Cost analysis is also conducted by cost engineers to identify reasons for cost overruns or underruns. Availability of Checklists of Critical Estimate Items Cost engineers in consulting firms maintain checklists of critical estimate items updated to be as current as possible. Design engineers help estiÂ mators maintain and update cost data. ODOT has a guidance report to support the design and estimation process for rural and small urban area transit faciliÂ ties. Although state DOTs do not have checklists of critical estimate items, they hire consulting firms to perform an independent estimating review and track reasons behind delays and cost overruns. Typical Risk Factors According to the interviewees, the typical risk factors associated with rural and small urban area transit facilities are: â¢ Higher transportation expenses: construcÂ tion in remote areas increases transportation expenses and the need to pay travel time. â¢ Soil conditions: contaminated soil or unÂ expected soil conditions. Differences Between Rural and Small Urban Area Transit Facilities In small urban areas, transit facilities, such as maintenance buildings and indoor garages, are usuÂ ally larger due to high volume of passengers that use the agencyâs transit services. Further, land is usuÂ ally difficult to acquire to construct a transit facilÂ ity. Small facilities, such as passenger shelters, are mainly located in urban areas. Although FTAâs funding is often split 80/20, where 80% goes to urban transit facility projects and 20% goes to rural projects, lack of funding for rural transit facilities is one of the major causes of project delays. Typical Project Size Various factors have an impact on the size of a transit facility project, including employee ratio, fleet size, types of maintenance work performed, fleet mileage, the availability of funding, location, and the projectâs complexity. The size range of an administration office was found to be from 2,500 to 3,000 ft2. The size of a bus shelter can vary from 50 to 150 ft2. The typical range of operation and maintenance facilities is about 8,000 to 13,000 ft2. The size range of a vehi cle storÂ age building is from 8,000 to 12,000 ft2. The size of a transit complex (including administration, storage, and garage) can range from 12,000 to 20,000 ft2. Typical Design and Construction Costs The cost of rural and small urban area transit facilities varies based on project location, the feaÂ tures of facilities, change orders, soil conditions, geological conditions, weather conditions, environÂ mental mitigation requirements, the application of the LEED rating system, the involvement of expanÂ sion and transformation of existing buildings, and legislative rules (e.g., the Buy America Act). Generally speaking, the total cost of a rural or small urban transit facility is between $2 and $4 milÂ lion. The cost can range from $8 to $24 million if a project is located in a West Coast area. The cost range of a paratransit facility is $12 to $16 million. (Paratransit is an alternative mode of flexible pasÂ senger transportation that does not follow fixed routes or schedules.) Table 2 shows unit costs of difÂ ferent types of facilities. With more features added, the unit cost would be higher. table 2 Unit costs of transit facilities. Facility Type Unit Cost Administration $150â$200/ft2 Maintenance $300/ft2 (The cost depends on what kind of maintenance service is performed.) Open bus storage $125â$250/ft2
15 â¢ In order to address project risks, contingency is estimated as a percentage of construction cost; however, risks are seldom tied directly to the amount of contingency. â¢ Lack of funding for rural facilities often gives rise to project delays. â¢ DOTs and transit agencies often lack experÂ tise in estimating design and construction costs, and they therefore depend on estimates provided by consulting firms. Chapter summary This chapter discussed the interview protocol development and interview process. Then, results of the interviews were summarized. The collected qualitative data obtained from telephone interviews were used for developing the survey protocol, which is discussed in the next chapter. CHAPteR 5 onLIne sURVeY survey Protocol The main objective of the survey was to colÂ lect historical projectÂspecific cost data from state DOTs, transit agencies, and consulting firms. The data were collected on rural and small urban area transit facilities. The cost data served the purpose of developing a cost estimating database and a tool to support estimatesâ preparation. The survey protocol included 11 main sections: â¢ Background, â¢ Survey instruction, â¢ Survey declaration, â¢ Respondent information, â¢ General project information, â¢ Characteristics of the project, â¢ Cost estimating, â¢ Schedule, â¢ Risk, â¢ Change orders, and â¢ Other. The background section served as a memoranÂ dum to explain the research objectives, provide conÂ tact information of the research team, and give the deadline for completion of the online survey. The survey instruction section described certain types of transit facilities that were designed and constructed â¢ Buy America Act compliance: materials made in the United States must be used. â¢ Weather conditions: extreme weather, such as icy winters, heavy rains, and hurricanes. â¢ Unexpected underground conditions: buried debris and unexpected utilities. â¢ Funding availability: construction of rural transit facilities is often delayed because of funding constraints. â¢ Increased scope: continuous incremental changes in project scope. â¢ Environmental risk: new information required for permits or changes of environmental reguÂ lations. â¢ Neighborhood complaints: major complaints concerning noise and dust control can cause a lengthy construction delay. â¢ Archaeological impact: if relics are found on the site, construction is often suspended until relics are protected or removed. â¢ Lack of competition: lack of competition (i.e., the number of bidders per project) will increase bid prices, which gives rise to higher project cost. Contingency Estimation Contingency is set according to project type, size, location, and project characteristics. HowÂ ever, sometimes the contingency is not sufficient to cover all the unknown factors, such as weather conditions, soil conditions, site location, or needed change orders. According to the interviewees from state DOTs, 10% to 15% of construction cost is often suggested as an appropriate contingency. Design firms usually work with contractors to set a feasible contingency (percentage of construction cost) for design and construction. Interview Results summary The interview results reveal the following charÂ acteristics of rural and small urban area transit facilities: â¢ Project size and costs vary due to different facility types, location, and facility features. â¢ Project risks were identified, such as soil conÂ ditions, Buy America Act compliance, and unexpected underground conditions.
16 ground conditions, soil conditions, and environmenÂ tal issues, were mentioned by interviewees and then added as choices in a question asking for the reasons for cost overruns. Survey invitations were sent on November 6, 2013, to 52 state DOT personnel who manage pubÂ lic transit facility funding programs and 323 transit managers and consultants across the United States. The contact information of these potential particiÂ pants was provided by the RTAP. FollowÂup survey requests were sent to the same group of people on November 26, 2013. Unfortunately, there were only nine surveys submitted by respondents, which was much fewer than expected. This probably resulted from a limited number of transit facilities having been constructed in rural and small urban areas in recent years, difficulty of respondents in accessing project data, respondents having limited time to complete the survey, and respondents lacking cost estimating knowledge. In order to further reduce the difficulty of completing the survey and improve the response rate, the survey structure was changed and the size of the survey was reduced. The descriptions of the main body of the shortened survey are shown in Table 4. in the last 5 years. The survey declaration aimed at confirming that the participants had basic knowlÂ edge related to the cost estimating practices for rural and small urban area transit facility projects and voluntarily consented to participate in the surÂ vey. Participantsâ email addresses were requested in case further clarification was needed at the end of the survey declaration section. Table 3 describes the other survey sections. Before sending the survey to practitioners, the survey protocol was pretested in October of 2013. Three transit managers and one DOT employee parÂ ticipated in the pilot survey. The feedback from the pilot survey revealed that the respondents had difÂ ficulties in locating actual historical cost data and completing the openÂended questions on cost estiÂ mating, scheduling, and risks. Some transit operaÂ tors lacked cost estimating expertise, and they relied on the estimates provided by consulting firms. ThereÂ fore, the survey protocol was redesigned by changing the openÂended questions to multipleÂchoice quesÂ tions. The multipleÂchoice questions were tailored from the results of the interviews and pilot surveys. For example, risk factors, such as unexpected underÂ table 3 Descriptions of survey sections. Section Description Respondent information The name and type of agency that constructed transit facilities General project information â¢ Project location â¢ Design schedule (start and finish) â¢ Construction schedule (start and finish) â¢ Funding source(s) â¢ Project delivery method â¢ Design and construction contract type Characteristics of the project â¢ Type and size of facilities â¢ Different facilitiesâ features and elements Cost estimating â¢ The type of historical cost database used to prepare the estimates â¢ Actual/estimated design costs â¢ Actual/estimated construction costs â¢ The percentages of construction cost for major construction systems â¢ Estimating methods for design and construction â¢ Influential factors in the cost estimating process Schedule â¢ Actual/estimated design schedule â¢ Actual/estimated construction schedule â¢ Reasons for delays Risk â¢ Methods to estimate the construction contingency â¢ Unusual conditions surrounding the projects Change orders The reasons for change orders and their financial impacts on the projects Other Lessons about the estimating process learned from this project
17 actual design and construction costs and design and construction schedules (start and finish data). Only one transit manager replied and provided a design and construction schedule for a project. survey Data Analysis Table 5 shows original design and construction cost data collected through the online survey for 26 projects. Different types of facilities are comÂ bined in most of the projects. Only one project includes just one type of facility (operations). Eleven of the 26 projects consist of two or three types of facilities (e.g., administration and operations, or admin istration, operations, and vehicle storage). One project was a renovation project. Nine projects include four types of facilities (administration, operations, maintenance, and vehicle storage). Two projects concern small facilities for passengers survey Process The survey process is shown in Figure 5. When the secondÂround survey was distributed, telephone calls were made to 25 transit managers across the United States to encourage them to parÂ ticipate. In order to collect more cost data, the inviÂ tations of the shortened survey were distributed to 1,055 transit managers and consultants, excludÂ ing the 323 people contacted during the firstÂround survey. The contact information of the 1,055 people was again provided by RTAP from its database. FollowÂup invitation emails for the shortened surÂ vey were sent on February 7, 2014. Unfortunately, there were only 13 responses to the shortened surÂ vey by the end of February. Therefore, there were 26 surveys submitted by respondents, including four pilot surveys. Clarification requests were sent through emails if the respondents did not provide table 4 Descriptions of the shortened survey. Section Description Respondent information The name and type of agency that constructed transit facilities General project information â¢ Project location â¢ Funding source(s) â¢ Project delivery method â¢ Design and construction contract type Characteristics of the project â¢ Type and size of facilities â¢ Different facilitiesâ features and elements Cost estimating â¢ The type of historical cost database used to prepare the estimates â¢ Estimating methods for design and construction â¢ Actual/estimated design costs â¢ Actual/estimated construction costs â¢ Reasons for cost overruns in the project â¢ The percentages of construction cost for major construction systems Schedule â¢ Actual design schedule â¢ Actual construction schedule Risk â¢ Major risk factors â¢ Methods to estimate the construction contingency Change orders The reasons for change orders and their financial impacts on the projects Other The availability of the cost estimating database and willingness to share information 2nd Round Survey (shortened version) Survey Development Survey Revising Survey Revising Pilot Survey 1st Round Survey Follow-up Invitation Follow-up Invitation Figure 5 Survey process.
table 5 Survey design and construction cost data. # Midpoint of Design Midpoint of Construction Facility Type Project Size (sf) Estimated Design Cost ($) Actual Design Cost ($) Estimated Construction Cost ($) Actual Construction Cost ($) 1 08/2008 03/2009 Operations 6,000 130,000 130,000 1,170,000 1,170,000 2 â â Administration, operations 19,000 216,246 291,020 1,889,067 734,440 3 07/2011 04/2013 Operations, maintenance 8,300 120,000 130,000 1,200,000 1,300,000 4 08/2012 06/2013 Operations, vehicle storage 6,720 â â 277,637 277,637 5 10/2011 12/2012 Operations, vehicle storage 28,000 446,980 550,658 3,980,000 4,594,000 6 10/2011 07/2012 Administration, operations 4,078 â 129,677 1,345,760 1,371,694 7 â 10/2012 Operations, maintenance 5,000 Included in construction 468,000 242,000 8 10/2007 10/2008 Administration, vehicle storage 13,529 105,000 105,000 1,375,000 1,376,223 9 â 02/2014 Administration, maintenance (renovation) 200 â â 20,000 â 10 â â Administration, operations, vehicle storage 36,967 350,000 353,000 3,739,432 3,756,481 11 â â Administration, operations, vehicle storage 17,000 250,000 252,632 2,500,000 2,323,192 12 11/2006 08/2008 Operations, maintenance, vehicle storage 8,184 43,600 41,950 545,000 524,312 13 11/2009 02/2010 Administration, operations, maintenance, vehicle storage 29,030 482,000 482,000 4,088,000 4,800,000 14 05/2006 â Administration, operations, maintenance, vehicle storage 16,500 200,000 â 4,790,000 â 15 04/2000 03/2005 Administration, operations, maintenance, vehicle storage 30,000 129,500 154,370 2,450,000 2,329,000
16 01/2010 Not completed Administration, operations, maintenance, vehicle storage 70,000 1,500,000 2,000,000 30,000,000 â 17 01/2012 05/2012 Administration, operations, maintenance, vehicle storage 2,000 â 16,600 122,500 133,100 18 09/2012 â Administration, operations, maintenance, vehicle storage 33,295 450,000 â 6,816,772 â 19 01/2010 06/2011 Administration, operations, maintenance, vehicle storage 40,000 1,586,500 1,586,500 7,557,392 7,872,283 20 05/2011 10/2011 Administration, operations, maintenance, vehicle storage 12,500 â â â â 21 10/2009 Not completed Administration, operations, maintenance, vehicle storage 75,000 2,000,000 2,000,000 30,000,000 â 22 10/2009 07/2010 Sheltered bus stop 100 6,000 7,500 90,000 128,000 23 09/2011 Sheltered bus stop, signÂonly bus stop 30 â â 6,691 7,531 24 08/2007 03/2010 Administration, operations, maintenance, vehicle storage, park and ride 32,000 â â â â 25 08/2013 â Administration, operations, maintenance, vehicle storage, small passenger facility, sheltered bus stop, unsheltered bus stop, signÂonly bus stop 75,000 95,000 â 950,000 â 26 10/2006 06/2005 Administration, operations, maintenance, vehicle storage, small passenger facility, sheltered bus stop 45,000 70,696 81,686 1,390,762 1,364,494
20 Construction Cost Data manual. For locations not included in the city cost index, the CNN method was used to estimate cost indexes. Then, the national averÂ age costs were adjusted from any previous years to 2014 using the historical cost index in the manual. Construction Cost Estimating Table 6 shows estimated, actual, and normalized construction cost data available for conducting the analysis. Facility types are administration, operaÂ tions, maintenance, and vehicle storage. The number of projects in the construction cost analysis was 12. The range of normalized construcÂ tion costs is from $129,813 to $8,586,186, and the mean is $2,437,699. The plot of the normalized conÂ struction cost and project size is shown in Figure 6. Regression analysis was performed to identify the relationship between the normalized construction cost and project size for rural and small urban area transit facilities. The normalized data were fitted with a straightÂ line regression model at a 90% confidence level. The regression plot and statistical summary are shown in Figure 7. If construction cost and project size are Y and X respectively, then at a 90% confidence level, the straightÂline regression model is Y = 172.6989 X (X > 0). (sheltered bus stop or signÂonly bus stop). Three projects include not only administration, operations, maintenance, and vehicle storage, but also passenger facilities (e.g., parkÂandÂride facilities, sheltered bus stop, unsheltered bus stop, and signÂonly bus stop). Thus, the data were incomplete concerning parkÂandÂ ride facilities, sheltered bus stops, unsheltered bus stops, and signÂonly bus stops. The cost data that can be used to conduct the analysis only cover those new facilitiesâ construction in the areas of admin istration, operations, maintenance, and vehicle storage. However, years for design and construction for eight projects were not provided by responÂ dents. Construction of two projects was not comÂ pleted until the respondents submitted the surveys. Therefore, design and construction costs for these 10 projects could not be converted to the year of 2014. Eleven projectsâ estimated and/or actual design costs were missing, and eight projects lacked estimated and/or actual construction costs. Therefore, survey data analysis was conducted based on a limited amount of design and construcÂ tion cost data. Before further data analysis was performed, all design and construction cost data were normalized by performing the following two steps. First, all actual design and construction cost data were adjusted from various locations to national average costs by using the city cost index in the RS Means Building table 6 Construction cost data. # Midpoint of Construction Facility Type Project Size (sf) Estimated Construction Cost ($) Actual Construction Cost ($) Normalized Construction Cost ($) 1 03/2009 Operations 6,000 1,170,000 1,170,000 1,220,406 2 04/2013 Operations, maintenance 8,300 1,200,000 1,300,000 1,635,071 3 06/2013 Operations, vehicle storage 6,720 277,637 277,637 311,131 4 12/2012 Operations, vehicle storage 28,000 3,980,000 4,594,000 4,201,247 5 07/2012 Administration, operations 4,078 1,345,760 1,371,694 1,444,681 6 10/2012 Operations, maintenance 5,000 468,000 242,000 286,447 7 10/2008 Administration, vehicle storage 13,529 1,375,000 1,376,223 1,627,730 8 08/2008 Operations, maintenance, vehicle 8,184 545,000 524,312 593,875 9 02/2010 Administration, operations, maintenance, vehicle storage 29,030 4,088,000 4,800,000 5,517,413 10 03/2005 Administration, operations, maintenance, vehicle storage 30,000 2,450,000 2,329,000 3,698,384 11 05/2012 Administration, operations, maintenance, vehicle storage 2,000 122,500 133,100 129,813 12 06/2011 Administration, operations, maintenance, vehicle storage 40,000 7,557,392 7,872,283 8,586,186
21 group elements: (1) substructure, (2) shell, (3) interÂ iors, (4) services, (5) equipment and furnishings, and (6) special construction and demolition. According to survey results, administration, operations, mainteÂ nance facilities, and vehicle storage were combined in most of the rural and small urban area transit projÂ ects. Assuming that various combinations of facility types give rise to a different percentage of construcÂ tion costs for each construction system, projects were categorized into the following two groups: projects including four types of facilities (adminisÂ tration, operations, maintenance, and vehicle storage), and projects including two or three of those facility types (e.g., administration and operations). Figure 8 shows the percentage breakdown for each construction system for projects with a comÂ bination of four types of facilities (administration, operations, maintenance, and vehicle storage). FigÂ ure 9 shows the percentage breakdown for each conÂ struction system for projects with only two or three types of these facilities. In order to prove the necessity of the model, a hypothesis test was conducted at a 90% confidence level. The hypotheses are as follows: H0: There is no linear relationship between project size and construction cost. H1: There is a positive linear relationship between project size and construction cost. Accordingly, the pÂvalue is <0.0001 < a = 0.1. The null hypothesis should be rejected. That is, a straightÂline regression model is needed. The RÂsquare = = + + = SS SS 1.3637e 14 1.4494e 14 0.940872085, total model which indicates that the straightÂline regression model is a good fit for the normalized construction cost data. Percentage of Construction Cost for Each Construction System In this study, the classification of building eleÂ ments followed UniFormat II. There are six major Figure 7 Construction cost analysis: regression plot and statistical report of straightÂline regression. * = statistically insignificant. Figure 6 Plot of the normalized construction cost and project size.
22 â¢ The larger percentages of shell and services construction costs for the second combinaÂ tion might be due to the fact that projects including operations, maintenance, or vehicle storage might require more heating, ventilaÂ tion, and air conditioning (HVAC), plumbÂ ing, and electrical construction to ensure that services or activities can be performed safely and efficiently. Design Cost Estimating Table 7 shows the design costÂestimating methods used by respondents to the survey. Most of the design costs of those projects were estimated by using similar projects. Therefore, using regression analysis to find the relationship between design cost and project size should be appropriate in this case. Table 8 shows estimated, actual, and normalized design cost data available to perform a data analyÂ sis. For projects that lacked actual design costs, their Compared with the first combination, the secÂ ond combination has similar percentages only for substructures and special construction and demoÂ lition. Possible reasons for the differences are as follows: â¢ The larger percentage of building siteÂwork construction cost for the first combination might be due to the necessity of more site meÂ chanical utilities (e.g., water supply and fueling distribution) and more site electrical utilities (e.g., electrical distribution and site lighting) if there were more types of facilities involved in a project. â¢ The larger percentages of interior and equipÂ ment and furnishings construction costs for the first combination might be due to the need for more wall, floor, and ceiling finishes, interior doors, partitions, and furnishings conÂ struction if more facility types were included in a project. 20.02% 12.85% 29.21% 13.27% 17.97% 5.67% 1.00% Building Sitework (20.02%) Substructure (12.85%) Shell (29.21%) Interior (13.27%) Services (17.97%) Equipment (5.67%) Special Construction & Demolition (1.00%) Figure 8 Percentage of construction cost for each construction system (four types of facilities). 13.67% 12.58% 34.83% 9.70% 26.72% 2.00% 0.50% Building Sitework (13.67%) Substructure (12.58%) Shell (34.83%) Interior (9.70%) Services (26.72%) Equipment (2.00%) Special Construction & Demolition (0.50%) Figure 9 Percentage of construction cost for each construction system (two to three types of facilities).
23 If design cost and project size are Z and X respecÂ tively, then at a 90% confidence level, the straightÂ line regression model is Z = 31.635567 X (X > 0). In order to prove the necessity of this model, hypothesis test was conducted at a 90% confidence level. The hypotheses are shown as follows: H0: There is no linear relationship between project size and design cost. H1: There is a positive linear relationship between project size and design cost. estimated design costs were assumed to be the same as the actual design costs. The number of projects in the design cost analysis was 14. The normalized design costs range from $16,190 to $2,632,715, and the mean is $706,533. The plot of design cost versus project size is shown in Figure 10. The normalized design cost data were fitted with a straightÂline regression model with a 90% confidence level. The regression plot and statistical summary are shown in Figure 11. table 7 Summary of design costÂestimating methods. Design Cost-Estimating Method Number of Projects Similar projects 11 Hours to design 5 Similar project and hours to design 2 Similar project and historical percentage of construction cost 1 Contractorâs estimates 1 Architectsâ estimates 1 Historical percentage of construction cost 1 Bid 1 table 8 Design cost data. # Midpoint of Design Facility Type Project Size (sf) Estimated Design Cost ($) Actual Design Cost ($) Normalized Design Cost ($) 1 08/2008 Operations 6,000 130,000 130,000 135,375 2 07/2011 Operations, maintenance 8,300 120,000 130,000 172,059 3 10/2011 Operations, vehicle storage 28,000 446,980 550,658 512,536 4 10/2011 Administration, operations 4,078 â 129,677 139,006 5 10/2007 Administration, vehicle storage 13,529 105,000 105,000 132,253 6 11/2006 Operations, maintenance, vehicle storage 8,184 43,600 41,950 52,913 7 11/2009 Administration, operations, maintenance, vehicle storage 29,030 482,000 482,000 564,500 8 05/2006 Administration, operations, maintenance, vehicle storage 16,500 200,000 â 258,787 9 04/2000 Administration, operations, maintenance, vehicle storage 30,000 129,500 154,370 307,382 10 01/2010 Administration, operations, maintenance, vehicle storage 70,000 1,500,000 2,000,000 2,583,935 11 01/2012 Administration, operations, maintenance, vehicle storage 2,000 â 16,600 16,190 12 09/2012 Administration, operations, maintenance, vehicle storage 33,295 450,000 â 580,831 13 01/2010 Administration, operations, maintenance, vehicle storage 40,000 1,586,500 1,586,500 1,802,982 14 10/2009 Administration, operations, maintenance, vehicle storage 75,000 2,000,000 2,000,000 2,632,715
24 of construction materials. Not recognizing a projÂ ectâs high complexity will cause some criteria for a project not to be met during the decision process, and contingency will not be estimated at a proper level. Design omissions and errors and shortage of construction materials can cause cost overruns and construction delays. However, the survey responÂ dents did not think of the archaeological requireÂ ments of local government as a risk. Although some respondents suggested risk factors in the survey, their projects did not expeÂ rience cost overruns. The reasons could be that there was sufficient contingency in the estimated construction cost or that project control plans were carried out effectively by the project management teams. Contingency Estimating Although 21 out of 26 respondents stated that a percentage of construction cost was used to estiÂ Accordingly, the pÂvalue is 0.0001 < a = 0.1. The null hypothesis should be rejected. That is, a straightÂline regression model is needed. The RÂsquare = = + + = SS SS 1.6421e 13 1.8027e 13 0.910911411, total model which indicates that the straightÂline regression model is a good fit for the normalized design cost data. Risk Analysis The frequency of the risk factors stated by survey participants is shown in Figure 12. Soil conditions and unexpected underground conditions are two of the most frequent risk factors, and most interviewees also suggested these two risks. Contaminated soil, buried debris, and unexpected utilities can increase project costs and also cause unanticipated delays during construction. Compared with the interview results concerning risks, the survey respondents also considered risk factors, including high project comÂ plexity, omissions and errors in design, and shortage Figure 11 Design cost analysis: regression plot and statistical report of straightÂline regression. * = statistically insignificant. Figure 10 Design cost versus project size.
25 manual. The database is limited by the amount of cost data collected through the online survey. The facility types covered in this database include administration, operations, maintenance, and vehicle storage, but the types exclude passenger facilities (small and large), parkÂandÂride facilities, bus stops (sheltered and unsheltered), and signÂonly bus stops. Most projects in the database are combinations of administration, operations, maintenance, and vehicle storage. The cost estimating database was conÂ structed excluding land acquisition and had the following features: â¢ Basic project information: city, state, the midÂ point of design time (month/year), the midpoint of construction time (month/year), location (rural/small urban), and facility type. â¢ Project duration: design duration (month) and construction duration (month). â¢ Cost information: project size (sf), estimated design cost ($), estimated construction cost ($), actual design cost ($), and actual construction cost ($). â¢ Percentage of construction cost for each construction system: building site work (%), substructure (%), shell (%), interiors (%), equipÂ ment and furnishings (%), and special construcÂ tion and demolition (%). Screen captures of the database are shown in Figure 13, Figure 14, and Figure 15. mate contingency, only eight of them provided the percentages they used. Contingency percentage proÂ vided by the respondents ranges from 4% to 15%. The average contingency is 9.5%, and the median of contingency is 10%. Chapter summary This chapter first described the survey protocol development and survey process. Then, regression functions to predict design and construction costs were identified and verified. Risk factors and conÂ tingency estimating for rural and small urban area transit facility projects were discussed. The analyÂ sis results supported the development of the cost estimating database and prototype tool, which is the subject of the next chapter. CHAPteR 6 DeVeLoPMent oF tHe Cost estIMAtInG DAtAbAse AnD PRototYPe tooL FoR RURAL AnD sMALL URbAn AReA tRAnsIt FACILItIes Cost estimating Database Development After gathering and classifying actual historical cost data through surveys, all data were input into an Excel spreadsheet and were adjusted to national average costs for 2014 by using the 2014 version of the RS Means Building Construction Cost Data Figure 12 Frequency of the risk factors.
26 Figure 13 Cost estimating databaseâbasic project information and project duration. Figure 14 Cost estimating databaseâproject cost information.
27 Introduction The cost estimating prototype tool is an Excel file. Once the user opens the tool, the Introduction tab will be shown. In order to ensure that the tool works propÂ erly, the user is asked to read the introduction with care before starting the userâs cost estimating process. The screen captures of the introduction section are shown in Figure 16. As the first section of the estimating tool, the introÂ duction section introduces the research background, the objectives of the cost estimating prototype tool, types of facilities considered, tips for navigation and document saving, and copyright information. Userâs Guide The Userâs Guide tab explains how to use the tool and contains tips for using the tool. The section includes five aspects: how to navigate the tool, how to save and print the results of the estimate, how to input project information, how to set variables (e.g., inflaÂ tion rate, contingency percentage, and location adjustÂ ment factor), and how to interpret the estimate report. The tool supports cost estimating from year 2015 to year 2025. The tool suggests that the user should Cost estimating Prototype tool Development The types of rural and small urban area transit facilities include administration, operations, mainÂ tenance, vehicle storage, park and ride, sheltered bus stops, unsheltered bus stops, and signÂonly bus stops. The historical cost data collected to develop the database in support of this prototype tool cover only those facilities in the administration, operaÂ tions, maintenance, and vehicle storage types due to incomplete data concerning the last four types. Generally speaking, administration, operations, mainÂ tenance, and vehicle storage were combined in most of the projects included in the database. Thus, the prototype tool was developed based on project size and costs for the combination of these facility types. The tool is considered a prototype due to this lack of historical cost data collected and used to develop the cost estimating database (only 12 to 14 projects with complete historical data). The dataÂ base was developed in Excel and consists of five tabs: Introduction, Userâs Guide, Project InformaÂ tion, Estimates Report, and Estimates Details. Each tab is described in detail with its screen capture. Figure 15 Cost estimating databaseâpercent of construction cost for each construction system.
28 Figure 16 (A) Screen capture of the Cost Estimating Prototype ToolâIntroduction. Figure 16 (b) Screen capture of the Cost Estimating Prototype ToolâIntroduction (continued).
29 is 100. The prototype tool uses the following equaÂ tion to adjust design and construction costs from the national average to any particular region. Ã Cost at national average 100 Regionâs index number The screen captures of this section are shown in Figure 17. After reading the section, the user can go to the Project Information tab by clicking the ConÂ tinue button. Project Information The Project Information tab enables the user to input the project information necessary to generate an estimate report: agency name/type, project name/ owner, project construction location, estimated midÂ point of the design and construction duration, order of magnitude of project size (sf), inflation rate, conÂ tingency percent, and date. The screen captures of this tab are shown in Figure 18. For the userâs referÂ ence, the tool provides the user default values for the inflation rate and contingency percentage (lower boundary, most likely, and upper boundary). HowÂ ever, users can also input the values of those variÂ ables based on their knowledge of the project. To help the user estimate a proper range of contingency percentages, suggestions are provided. Figure 18 B and C show the screen captures of the suggestions. After completing the project information, the user can go to the Estimates Report tab to review the estiÂ mate results by clicking the Calculate and Continue button. carefully evaluate any estimates made using this tool after the 5Âyear mark (after 2020). Users can either choose the default inflation rate (2.5%) or input a value based on their knowledge of local economic conditions. The default inflation rate was set after consulting two experts in cost estimating. In this prototype tool, contingency is estimated as a percentage of construction cost. Users can either choose the default percentage range or input a conÂ tingency percentage based on their knowledge of the project scope, uncertainties such as site conditions, and other project characteristics that may influence a projectâs costs. The default range of contingency is 10% to 25%, and the most likely contingency perÂ centage is 15%. The default contingency percentages were set by the experts in cost estimating based on the results of interviews and online surveys and their estimating experience. Before setting contingency, the tool recommends that the user assess the risk facÂ tors listed in the tool to ensure that a sufficient amount of contingency is estimated. As for the location adjustment factor, the estimatÂ ing prototype tool has 10 regions within the United States, based on the 10 standard federal regions estab lished by the Office of Management and Budget (1974). For each region, 20 cities, including large and small cities, were selected, and cost indexes of those cities from the 2014 version of the RS Means Building Construction Cost Data manual were used to calculate the location factor. The chosen cities, popuÂ lation, and citiesâ indexes are located in Appendix F. The location adjustment factor for each region is listed in Table 9. The index of the national average table 9 Regions and location adjustment factors. Region Location Adjustment Factor Region I: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont 103.1 Region II: New Jersey, New York, Puerto Rico, Virgin Islands 107.6 Region III: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia 96.0 Region IV: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee 80.3 Region V: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin 99.5 Region VI: Arkansas, Louisiana, New Mexico, Oklahoma, Texas 83.3 Region VII: Iowa, Kansas, Missouri, Nebraska 91.6 Region VIII: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming 86.7 Region IX: Arizona, California, Hawaii, Nevada 102.0 Region X: Alaska, Idaho, Oregon, Washington 102.1
Figure 17 (A) Screen capture of the Cost Estimating Prototype ToolâUserâs Guide. Figure 17 (b) Screen capture of the Cost Estimating Prototype ToolâUserâs Guide (continued).
Figure 17 (C) Screen capture of the Cost Estimating Prototype ToolâUserâs Guide (continued). Figure 18 (A) Screen capture of the Cost Estimating Prototype ToolâProject Information.
Figure 18 (b) Screen capture of the Cost Estimating Prototype ToolâProject Information (continued). Figure 18 (C) Screen capture of the Cost Estimating Prototype ToolâProject Information (continued).
33 Estimates Details The Estimates Details tab provides the user with the detailed calculations of the estimate and the hisÂ torical index information. The user can also review the location factor for each region, risk factors, and any comments the user input in the Project InformaÂ tion tab. The screen captures of this tab are shown in Figure 20. The user can print information in this tab by clicking the Print button. Review of the Cost estimating tool The purpose of the review was to ensure the selfÂ explanation, functionality, and userÂfriendliness of the prototype tool. The prototype tool was not tested for the accuracy of its estimates due to the limited Estimates Report The Estimates Report tab generates the estiÂ mates based on the userâs input. Estimate information includes base construction cost ($), range of continÂ gency ($), range of total construction cost ($), design cost ($), and construction cost for each construction system. The construction base estimate and design costs, exclusive of project contingency, are estimated by using the regression functions described in ChapÂ ter 5. The base construction cost and contingency add up to the total construction cost. The screen captures of this tab are shown in FigÂ ure 19. The user can print the report by clicking the Print button at the top of the screen. To review estiÂ mate details, the user should click âContinueâ to go to the Estimates Details tab. Figure 19 (A) Screen capture of the Cost Estimating Prototype ToolâEstimates Report.
Figure 19 (b) Screen capture of the Cost Estimating Prototype ToolâEstimates Report (continued). Figure 19 (C) Screen capture of the Cost Estimating Prototype ToolâEstimates Report (continued).
35 Figure 20 (A) Screen capture of the Cost Estimating Prototype ToolâEstimates Details. database. Throughout the cost estimating prototype toolâs development, two cost estimating experts provided consistent help and reviewed and tested the prototype tool. They recommended that the conÂ tingency be estimated as a range, with high, most likely, and low values rather than as a specific value during the conceptual estimating phase. Therefore, the contingency estimating method suggested by Olumide et al. (2010) was used in this estimating prototype tool. The default range of contingency in the tool was set based on their estimating expertise and the interview and survey results. The default inflation rate was determined based on the expertsâ judgment of the economic conditions and prediction of labor and material costs of the building construcÂ tion industry. After consultation, the projects were classified into two categories. The reasons behind this classification were that administration, operaÂ tions, maintenance, and vehicle storage are comÂ bined in most of the projects for which informaÂ tion was collected through the online survey, and different combinations have a different percentage
36 breakdown for each construction system. In this way, the difference of percentage breakdown of difÂ ferent combinations can be reflected to some degree. The Introduction and Userâs Guide tabs were also revised based on the expertsâ comments. The protocol, including a research memoranÂ dum and a list of questions, was sent to reviewÂ ers for comments and suggestions. The protocol is provided in Appendix G. Both the protocol and prototype tool were sent to two DOT personnel and three transit managers through emails on May 16, 2014. FollowÂup emails were sent on May 28, 2014. One response from a transit manÂ ager was received. The respondent did not experiÂ ence any difficulty in navigating through the tool, understanding the userâs guide, and completing the project information section. The estimate details section was helpful for the respondent to underÂ stand adjustment factors and calculations of design and construction costs. Figure 20 (b) Screen capture of the Cost Estimating Prototype ToolâEstimates Details (continued).
37 Figure 20 (C) Screen capture of the Cost Estimating Prototype ToolâEstimates Details (continued). Moreover, an Excel file including a list of rural transit facility projects constructed in Texas was provided by the Texas Transportation Institute (TTI). Project size, year of construction, location, and cost were included in the file. However, this file did not explicitly explain what the costs represented (e.g., total construction cost, design costs, or estimated total construction costs). Assuming that the costs listed in the file were total construction costs, the projects were used to evaluate the appropriateness of the construction cost estimates produced by the prototype tool. Default inflation rate and range of contingency percentage were used in the evaluation test. Although some construction cost estimates calÂ culated by the prototype tool were similar to the costs provided in the TTI file, other estimates had great difÂ ferences. The differences might be due to the fact that the costs in the file were not exact total construction costs, or there might have been some mistakes made when the project cost data were documented.
38 Figure 20 (D) Screen capture of the Cost Estimating Prototype ToolâEstimates Details (continued). steps of Cost estimation Practice and Cost estimation Management The steps of cost estimation practice and manÂ agement were developed based on guidance from NCHRP Report 574: Guidance for Cost Estimation and Management for Highway Projects During Plan- ning, Programming, and Preconstruction (Anderson et al. 2007) and the Minnesota Department of TransÂ portation Cost Estimation and Cost Management: Technical Reference Manual (Minnesota DepartÂ ment of Transportation 2008). Although both guideÂ books are focused on highway cost estimation and cost estimation management, the descriptions for each step are generic and applicable to facilitating the development of rural and small urban area transit facility estimates. The fiveÂstep estimating process developed by Anderson et al. (2007) is provided as follows: 1. Determine estimate basis (e.g., project scope, location, unique characteristics),
39 contingency as follows: lower boundary (e.g., 10%), most likely contingency percentage (e.g., 15%), and upper boundary (e.g., 20%). Clicking the Calculate and Continue button, the estimate report will be proÂ vided. The screen captures of the Project InformaÂ tion section are shown in Figure 21. Fourth, the appropriateness and completeness of the estimate should be reviewed and verified. In this instance, the transit manager should review and check the Estimates Report and calculation details presented by the prototype tool. Screen captures of the Estimates Report and Estimates Details are shown in Figure 22 and Figure 23. Last, in order to help communicate information about the estimates, transit managers can print the estimate report and estimate details, which convey estimate basis, assumptions, and project risks. Limitations of the Research The cost estimating database and prototype tool only support conceptual estimating during the scheÂ matic development phase since this is the level of historical cost data collected. Both the cost estimatÂ ing database and prototype tool were constructed based on the actual historical cost data available for rural and small urban area transit facilities. The folÂ lowing factors may be related to the lack of data: â¢ A limited number of transit facilities were constructed in the rural and small urban areas in the last 5 years. â¢ The majority of potential survey participants in the contacts database provided by the RTAP are state DOT personnel and transit managers. Some may lack the cost estimating knowledge to complete the survey, or the data simply are not kept. â¢ Respondents have difficulty in accessing projÂ ectsâ design and construction cost data. â¢ The public transit programs of state DOTs and transit agencies have experienced staff shortages, and therefore DOT personnel and transit managers did not have time to comÂ plete the online survey. However, the database of relevant cost elements and the estimating prototype tool can be improved by performing further data collection on a larger scale and with an extended amount of time. Design consultants and contractors could be another source of historical cost data. 2. Prepare base estimate (techniques and tools, historical database, adjustment factors), 3. Determine risk and set contingency (uncerÂ tainty in estimate basis and base estimate to determine the dollar amount of cost conÂ tingency), 4. Review and approve estimate (structured approach to verify completeness, estimate data used, documentation, accountability for estimate), and 5. Determine estimate communication approach (convey basis, assumptions, uncertainty). Appendix H contains descriptions of each cost estimation step. The cost estimating prototype tool in the research can facilitate all these estimating steps. For example, a transit agency, referred to as âABCâ in this research, needs to construct a transit complex, including administration and maintenance facilities. A conceptual estimate of this project could be preÂ pared by following this fiveÂstep estimating process. First, when determining the estimate basis of this project, the transit manager should determine and docÂ ument the project concept definition (e.g., project size, location, and descriptions of key works) and site charÂ acteristics. After determining the estimate basis, the transit manager should input the following key inforÂ mation into the estimating prototype tool: project size (e.g., 6000 ft2), location (e.g., Butler, Pennsylvania), facilities function and features (e.g., administration and maintenance), and site characteristics (e.g., the site used to be an old depot, and therefore the underÂ ground conditions could increase construction cost). Second, in order to prepare the base estimate, the transit manager should select an appropriate esti mating approach and a tool supporting concepÂ tual cost estimating. Assumptions, such as for the inflation rate, should be made in this step. In this case, the transit manager selects the cost estimatÂ ing prototype tool developed in this research and inputs assumptions into the prototype tool, such as the estimated midpoint of design year (e.g., 2015), the estimated midpoint of construction year (e.g., 2016), and the inflation rate (e.g., 3.0%). Third, project risks should be determined in order to set contingency. The transit manager should identify potential risks, such as unexpected underÂ ground and weather conditions, and document these in the prototype tool. For a lowÂcomplexity project, percentages of construction cost are used to estimate the range of contingency. The transit manager defines
Figure 21 (A) Screen capture of ABC ProjectâProject Information. Figure 21 (b) Screen capture of ABC ProjectâProject Information (continued).
Figure 21 (C) Screen capture of ABC ProjectâProject Information (continued). Figure 22 (A) Screen capture of ABC ProjectâEstimates Report (continued).
42 ment of Transportationâs Cost Estimation and Cost Management: Technical Reference Manual (MinneÂ sota Department of Transportation 2008). The cost estimating processes developed in these research projects have a history of success in preparing conÂ sistent, reliable, and accurate estimates at any phase in the project development process. Since the proÂ cess is generic, it is applicable to development of rural and small urban area transit facilities as well. Moreover, reviewing estimates by following guidelines provided in this chapter will ensure the quality of estimates. The review guidance follows the generic cost estimate development process in Figure 24. CHAPteR 7 GUIDeLInes FoR ReVIeWInG Cost estIMAtes This chapter covers guidelines for reviewing cost estimates from an ownerâs perspective. The basis of the guidelines for rural and small urban area transit facilities was tailored from previous research: NCHRP Project 20Â07/Task 278, âProduction of the New AASHTO Guide to Estimatingâ and Task 308, âCompletion of the New AASHTO A Practical Guide to Estimatingâ; NCHRP Report 574: Guidance for Cost Estimation and Management for Highway Projects During Planning, Programming, and Preconstruction; and the Minnesota DepartÂ Figure 22 (b) Screen capture of ABC ProjectâEstimates Report (continued).
43 2. Did the estimator clearly follow a structured cost estimating process, such as that depicted in terms of the flowchart in Figure 24? 3. Were all key inputs taken into consideration and clearly documented by the estimator (e.g., historical data, market conditions, cost estimating techniques and tools, the macro environment, and information from third parties)? 4. Were assumptions determined and docuÂ mented clearly by the estimator? Process of Reviewing Cost estimates A cost estimating reviewer should answer the following five general questions: 1. Did the project meet all regulations of the FTA? For additional information and regulaÂ tions of the FTA, refer to Circular C 4220.1F: Third Party Contracting Guidance (Federal Transit Administration 2013) and Project and Construction Management Guidelines (Federal Transit Administration 2011) Figure 23 Screen capture of ABC ProjectâEstimates Details.
44 Figure 24 Cost estimating process derived from the Practical Guide to Cost Estimating (American Association of State Highway and Transportation Officials 2013). Approved Cost Estimate Package Project Definition (Major Parameters, Schematics, Preliminary Plans, Final Plans) Project Characteristics (Location, Type, and Complexity) Financial Groups Inputs/Requirements Historical Data Determine Estimate Basis Cost Estimating Technique and Tools Input from 3rd Party Macro Environment Market Conditions Prepare Base Estimate Determine Risk/Contingency Review and Approve Estimate Determine Estimate Communication Approach Cost Estimate Communication Package Input Step Database Document Legend
45 Determine Risk and Contingency In order to review risks and contingency deterÂ mined by the estimator, the reviewer should consider the following: â¢ What is the contract type for the project? According to the FTA, typical contract types include firm fixedÂprice and cost reimburseÂ ment contracts. However, cost plus a perÂ centage of cost and percentage of construction cost contracts are prohibited. Time and materiÂ als contracts can be used only when no other contract type is suitable and a ceiling price is confirmed. â¢ Does the estimate explicitly identify a conÂ tingency amount? â¢ Does the estimate file (or report) clearly justify the basis of the contingency estimate? â¢ Is there a list of key assumptions, clarificaÂ tions, and exclusions that address project unknowns and project risks (see also DeterÂ mine Estimate Basis)? â¢ Has the estimate been reviewed for any conÂ tingency buried in line items or not explicitly identified? â¢ Has the final contingency estimate been comÂ pared to other contingency estimates for simiÂ lar projects? â¢ Is lack of bidding competition a potential risk factor in the project? For example, when a single proposal is received, which is considÂ ered as one without price competition, the estimated contingency is recommended to be increased. Review and Approve estimate Before an estimate is released to both internal and external project stakeholders, it should be reviewed and approved. This step includes the following considerations: â¢ Does the estimate cover the entire project scope, as known at the time of the estimate? â¢ Are cost estimating methods and historical cost data applications consistent with the scope definition? â¢ Are the estimate basis, assumptions, allowÂ ances, unknowns, contingencies, and changes from previous estimates documented in the final esti mate package in a clear and concise manner? 5. Is there a project cost estimate file available that contains all the information relevant to preparÂ ing a project cost estimate (questions 1 to 3)? Determine estimate basis Reviewing the estimate basis serves the purpose of ensuring that all information required to prepare a cost estimate is collected and clearly documented. This step includes the following aspects: â¢ Is the scope of the project clearly defined, including what is included in the scope and what is not included in the scope? â¢ Has the estimator visited the future construcÂ tion site to determine the existing conditions and any potential site access issues? â¢ Is the technical scope for the estimate consisÂ tent with the regulatory requirements and conÂ straints (e.g., permit conditions, regulations)? â¢ Has the estimator asked for, and been provided with, clarifications from the design team, local stakeholders, or appropriate permitting agenÂ cies, where necessary? â¢ Has an estimate file (or report) been prepared to document the estimate basis (e.g., drawing numbers and dates, specifications, quotes)? â¢ Has a list of key assumptions, clarifications, and exclusions been prepared to document what is not yet designed or known about the project? Prepare base estimate When reviewing the most likely cost estimate (base estimate) without a contingency, the followÂ ing should be considered: â¢ Were appropriate estimating methods used in relation to the available scope information, hisÂ torical cost data, and other references used by the estimator (e.g., conceptual, bidÂbased, costÂ based, and riskÂbased estimating methods)? â¢ Were assumptions and calculations documented clearly? â¢ Were estimate components identified, meaÂ sured, and quantified correctly by the estimator? â¢ Are the categories summarized in an estimatÂ ing tool (e.g., spreadsheets) consistent with the components of the total project cost estimate? Are the calculations in the backup correct? â¢ Were the estimating assumptions and base cost estimate summary and details clearly documented?
46 â¢ Both design and construction costs are estimated based on similar projects. Regression functions of design and construction costs were obtained through regression analysis, and the functions were used in the cost estimating prototype tool to predict future design and construction costs at the conceptual estimating phase. â¢ Risk factors were identified through telephone interviews, and the frequency of the risk facÂ tors was obtained from the online survey. â¢ In order to address project risks, contingency is estimated as a percentage of construcÂ tion cost. The ranges of contingency percentÂ age given by the interviewees and survey results provided a reference for determining the default contingency range for the cost estimating protoÂ type tool. Recommendations for Future Research A cost estimating database and a prototype tool were developed based on actual historical cost data collected via the online surveys. Further research should be conducted in order to capture additional data through the following approaches. First, it is necessary to target a greater number of practitioners with cost estimating expertise who are involved in rural and small urban area transit facility projects, especially design consultants and contracÂ tors that may provide historical data. Second, as an alternative to collecting cost data through a survey, a Delphi process can be performed. The candidates of the Delphi study can be personnel at state DOTs who are in charge of funding distriÂ bution of rural capital programs, transit managers having knowledge of cost estimating, and consulÂ tants having experience in design and construction of transit facilities in rural and small urban areas. In order to ensure consistency in sample size, it is betÂ ter that all the experts can respond to each round of the Delphi surveys. Third, through the online survey, it was found that most rural and small urban area transit projects were combinations of many types of facilities, such as those for administration, operations, mainteÂ nance, and vehicle storage. Therefore, in the future data collection process, it may be better to ask the survey participants to provide size and cost for each type of facilities in one project so that an estimating tool can be developed to support estimates for each type of facilities. â¢ Were the estimating documents in the project estimate file reviewed? â¢ Has the cost estimate been approved by the appropriate level of management? Determine estimate Communication Approach This step ensures that the cost estimates are a vehicle for succinctly and clearly conveying key project information to both internal and exterÂ nal project stakeholders. The following questions should be considered: â¢ Does the estimating package include major features of the project, specialty features, and features that have been considered? â¢ Were key assumptions, allowances, unknowns, and contingencies identified and documented? â¢ Are the estimating spreadsheets and diagrams in the estimating package comprehensive and clearly depicting the cost estimate for the project? CHAPteR 8 ConCLUsIons This chapter summarizes the conclusions that were drawn from this study and provides recomÂ mendations for future research. Conclusions This research included a literature review, teleÂ phone interviews, and an online survey. A cost estiÂ mating database was constructed based on historical cost data collected through the survey. Analysis of historical cost data was the basis for development of the cost estimating prototype tool. The general conclusions are: â¢ Project design and construction costs depend on various factors, such as facility types, projÂ ect size, location, and facility features. â¢ Many construction projects for rural and small urban area transit facilities were suspended or delayed due to lack of funding. â¢ Most transit projects in rural and small urban areas include more than one type of facility. â¢ State DOTs and transit agencies rely on estiÂ mates prepared by consultants. State DOTs hire consultants to perform independent cost estimate reviews.
47 2003. Transportation Research Board of the National Academies, Washington, D.C., 24â29. Fravel, F.D., and Barboza, R. Jr. 2011. NCHRP Research Results Digest 356: Analysis of State Rural Intercity Bus Strategies: Requirements for Utilization of S.5311(f) Funding. TransportaÂ tion Research Board of the National Academies, Washington, D.C. Hallowell, M., Tran, D., and Molenaar, K. 2012. NCHRP Research Results Digest 381: Guidebook for Con- struction Management Practices for Rural Proj- ects. Transportation Research Board of the National Academies, Washington, D.C. Hollmann, J.K. 2008. âContingency EstimatingâGeneral Principles TCM Framework: 7.6âRisk Management.â AACEI Recommended Practice No. 40RÂ08, AACEI, Morgantown, WV. KFH Group, Inc. 2002. TCRP Report 79: Effective Approaches to Meeting Rural Intercity Bus Trans- portation Needs. Transportation Research Board of the National Academies, Washington, D.C. Khemlani, L. 2008. âDProfiler: A âMacroâ BIM Solution.â http://www.aecbytes.com/review/2008/DProfiler .html (Oct. 20, 2014, 2013). Manfredonia, B., Majewski, J.P., and Perryman, J.J. 2010. âCost Estimating.â http://www.wbdg.org/ design/dd_costest.php (April 25, 2014). Minnesota Department of Transportation. 2008. Cost Estimation and Cost Management: Technical Refer- ence Manual, http://dotapp7.dot.state.mn.us/edms/ download?docId=670233. Migliaccio, G., Zandbergen, P., and Martinez, A. 2013. âEmpirical Comparison of Methods for Estimating Location Cost Adjustments Factors.â J. Manage. Eng., 10.1061/(ASCE)ME.1943Â5479.0000240, 04014037. Molenaar, K.R., Anderson, S.D., and Schexnayder, C.J. 2010. NCHRP Report 658: Guidebook on Risk Analysis Tools and Management Practices to Control Transportation Project Costs. TransportaÂ tion Research Board of the National Academies, Washington, D.C. Molenaar, K.R., and Wilson, C.R. 2009. âA RiskÂBased Approach to Contingency Estimation in Highway Project Development.â Proc., 2009 Construction Research CongressâBuilding a Sustainable Future, 786â795. Office of Management and Budget. 1974. Circular AÂ105, Standard Federal Regions. Executive Office of the President, Office of Management and Budget, Washington, D.C. Ohio Department of Transportation, Office of Transit. 2012. Rural Transit Program Manual. http://www. dot.state.oh.us/Divisions/Planning/Transit/Docu ments/Forms/Rural%20Transit%20Manual.aspx? RootFolder=%2FDivisions%2FPlanning%2FTransit Fourth, the survey data were incomplete conÂ cerning parkÂandÂride facilities, sheltered bus stops, unsheltered bus stops, and signÂonly bus stops. Efforts in collecting data on the costs of those types of facilities should be made in the future. Last, the cost and schedule impacts of each risk factor should be requested in the survey so that risk factors can be quantified; risk analysis and manageÂ ment for rural and small urban area transit facilities can thereby be better structured. ReFeRenCes American Association of State Highway and TransportaÂ tion Officials. 2013. Practical Guide to Cost EstimatÂ ing. Washington, D.C. American Public Transportation Association. 2010. Architectural and Engineering Design for a Transit Operating and Maintenance Facility. APTA BTSÂ BMFÂRPÂ001Â11, American Public Transportation Association, Washington, D.C. Anderson, S.D., Molenaar, K.R., and Schexnayder, C.J. 2007. NCHRP Report 574: Guidance for Cost Estimation and Management for Highway Projects During Planning, Programming, and Preconstruc- tion. Transportation Research Board of the National Academies, Washington, D.C. Association for the Advancement of Cost Engineering International. 2014. âCost Estimating Model for Buildings.â http://www.aacei.org/resources/Building Model.shtml#AboutTheModel (May 20, 2014). Brown & Bills Architects. 2012. âRural Transit FacilÂ ity Prototype for Ohio Department of Transportation Office of Transportation.â http://www.dot.state.oh.us/ Divisions/Planning/Transit/Documents/Rural%20 Trans i t%20Manua l /Rura l%20Trans i t%20 Manual%20Revised%202012/Rural%20Facility %20Prototype%20Report.pdf (Jan. 10, 2014). Christensen, P. 2011. âAACE International Recommended Practice No. 17RÂ97.â Dye Management Group, Inc. 2001. âPlanning for Transportation in Rural Areas.â Federal Highway Administration in Cooperation with the Federal Transit Admin istration, Bellevue, WA. Federal Transit Administration. 2011. âProject and ConÂ struction Management Guidelines.â http://www. fta.dot.gov/FTA_Project_and_CM_Guidelines_Â_ July_2011_Update_12Â01Â26.pdf (Oct. 13, 2014). Federal Transit Administration. 2013. âCircular C 4220. 1F: Third Party Contracting Guidance.â http://www. fta.dot.gov/legislation_law/12349_8641.html (Oct. 13, 2014). Fravel, F. D. 2003. âIntercity Bus Links: Moving into New Territory.â TR News, No. 225, MarchâApril
48 struction projects, proceed with Phase 1 work outlined in the following a. Phase 1: architectural and engineering services (1) Conduct qualificationsÂbased selecÂ tion (QBS) process (in accordance with Brooks Act) (2) Develop QBS and obtain ODOT concurrence (3) Select an architecture/engineering (A/E) firm (4) Negotiate contract (5) Conduct A/E work: (a) Preliminary design (b) Site selection and environmenÂ tal work 5ÂbÂ1. Submit environmental package to ODOT for subÂ mission to FTA 5ÂbÂ2. Following FTA concurÂ rence, proceed with site development. If FTA does not concur, additional enÂ vironmental work will need to be conducted or alternaÂ tive site selected. (6) Site development (construction only) (7) Prepare construction bid documents (8) Submit periodic invoices to ODOT B. Construction management oversight (opÂ tional in Phase 1âcan be done as part of the overall construction bid if desired) 1. Conduct selection process 2. Development bid/proposal for project oversight services and obtain ODOT concurrence a. Select project manager b. Negotiate contract Step 3 A. Apply for funding for Phase 2: construction 1. Submit application 2. Following approval and contract execuÂ tion with ODOT, proceed with next steps B. Bid construction project 1. Negotiate contract 2. Monitor construction (construction manager) %2FDocuments%2FRural%20Transit%20Manual (August 8, 2015). Olumide, A.O., Anderson, S.D., and Molenaar, K.R. 2010. âSlidingÂScale Contingency for Project DevelÂ opment Process.â Transportation Research Record: Journal of the Transportation Research Board, No. 2151, Transportation Research Board of the National Academies, Washington, D.C., 21â27. RS Means. 2014. RS Means Building Construction Cost Data, 72nd Ed., Norwell, MA. Texas Department of Transportation. 2012. âThe Texas Rural Transportation Plan.â Transportation Planning and Programming Division, Texas Department of Transportation, Austin, TX. APPenDIX A PRoCess FoR FACILItY ConstRUCtIon (oDot, RURAL tRAnsIt PRoGRAM) Planning Phase: Review Rural Transit Facility Prototype 1. Develop conceptual plans 2. Prepare square footage cost estimate 3. Site decisionsâsite needs 4. Environmental considerations Step 1 A. Program project on a 4Âyear capital and operating (C&O) plan: 1. Phase 1: architectural and engineering services, and 2. Phase 2: construction Costs at this time will be from tentative estimates based on similar projects and consultation with city/ county engineering staff, and so forth. B. Complete a feasibility study to document the need for the facility and to conduct site selection, and include preliminary drawings and environmental work. To the extent feaÂ sible, prepare preliminary design sketches and provide pictures or schematics of existÂ ing facilities with estimated costs. Step 2 A. Apply for funding 1. Submit application 2. Complete the scoping process 3. Following scoping process, application approval, and contract approval, for conÂ
49 As part of NCHRP Project 20Â65, Task 53, this research focuses on the development of independent cost estimates for the design and construction of rural and small urban area transit facilities. The work is being conducted by the Texas A&M Transportation Institute (TTI). The research products include a database of historical cost elements and a cost estimating tool. The purpose of the cost estimating tool is to assist state transportation agencies (STAs) with the distribution and management of funding for rural and small urban area facilities. It should also assist transit operators when they apply for funds from the Rural Transit Assistance Program. This cost estimating prototype tool was developed based on the limited amount of valid historical cost data currently available. The research team thanks you for your previous participation in the interview and/or online survey. Now the research team is inviting you to review the prototype tool by estimating a project and provide your suggestions on revising the tool by answering the following questions. 1. Is it easy to navigate the tool by following the instructions provided? If you have any difÂ ficulty, please explain the issue and provide your suggestions for improvement. 2. Do you think the Userâs Guide is selfÂ explanatory and comprehensive? Did you have any difficulty in understanding how to set the following variables? â¢ Inflation factor â¢ Location adjustment factor â¢ Contingency (%) Do you think the default values are appropriÂ ate? Please list any difficulties you experienced. 3. Did you have any difficulty in completing the project information section? Do you think the suggestions and instructions concerning the contingency setting are helpful? 4. Do you think the estimates report clearly shows the base construction estimates, conÂ tingency range, total construction cost, design cost, and construction cost for each construcÂ tion system? If you have any suggestions, please list them here. 5. Do you think the Estimates Details section is helpful for understanding the adjustment factors and calculations of the construction and design costs? If there was any cause for C. Perform project oversight (construction manager) 1. Perform regular site visits 2. Oversee general contractor (if separate from construction manager) and subÂ contractors 3. Check site work with specifications 4. Negotiate any necessary change order 5. Report progress and any problems to grantee 6. Approve and/or submit invoices to ODOT Step 4 Continue to monitor the project. Although ODOT will also monitor the project, it is the granteeâs responsibility to provide project oversight and ongoing monitoring. Notes â¢ Section 5311 grantees can choose to conduct the A/E portion locally without Section 5311 funding. They must still follow the Brooks Act requirements as well as FTA requirements for conducting the environmental assessment and so forth, and ODOT must still review and approve the selection process and contracts. â¢ As noted previously, construction oversight can be bid separately after the A/E work is performed and either prior to or concurrent with the construction bid process or as part of the overall construction bid. [Note: Appendices B through E are unpublished.] APPenDIX F LoCAtIon ADJUstMent FACtoR The RS Means city index has a base value of 100.0, representing a 30ÂU.S. city average. The location adjustment factor is determined by dividÂ ing the âCity Indexâ column value (Column 4 in Table 10) by 100.0. For example, the location factor for Bridgeport, Connecticut, would be 111.3/100.0, or 1.113. APPenDIX G tooL ReVIeW PRotoCoL Following is the text of the tool review protocol for NCHRP Project 20Â65/Task 53. (continued on page 55)
50 table 10 Location adjustment factor. City Name Population* City Index Region I Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont Connecticut Bridgeport 144,229 111.3 New London 27,620 108.9 Waterbury 110,366 111 Norwalk 85,603 114.5 Maine Portland 66,194 97.1 Rockland 7,297 91.8 Waterville 15,722 89.7 Massachusetts Boston 617,594 118.9 Fall River 88,857 114 Springfield 153,060 106.8 Framingham 68,318 114.2 New Hampshire Manchester 109,565 98.8 Nashua 86,494 98.1 Concord 42,695 97.7 Littleton 5,928 88.9 Rhode Island Newport 24,672 108.1 Providence 182,911 109.5 Vermont Burlington 42,417 95.1 Rutland 16,495 93.8 Montpelier 7,855 93.5 Number of cities 20 Average of city indices 103.085 Region II New Jersey, New York, Puerto Rico, Virgin Islands New Jersey Newark 277,140 114.7 Atlantic City 39,558 110.9 Elizabeth 124,969 112.7 Trenton 124,969 112.7 New Brunswick 55,181 113.1 Jersey City 247,597 112.6 Paterson 146,199 113.3 Vineland 60,724 110.5 Hackensack 43,010 112.5 Summit 21,457 112.3 New York Albany 97,660 102 New York 8,244,910 133.1 Jamestown 31,020 93.1 Elmira 29,204 97.2 Mount Vernon 67,780 117.8 Glens Falls 14,728 94.4 Syracuse 145,151 98.8 Watertown 27,423 96.2 Poughkeepsie 32,790 113 Puerto Rico Puerto Rico 3,725,789 80.4 Number of cities 20 Average of city indices 107.565
51 table 10 (Continued) City Name Population* City Index Region III Delaware, District of Columbia, MaryÂ land, Pennsylvania, Virginia, West Virginia Delaware Wilmington 71,305 104.5 Newark 31,618 104.2 Dover 36,560 104.6 District of Columbia N/A Maryland Baltimore 619,493 93.2 Cumberland 20,739 90.9 Salisbury 30,484 83.4 Elkton 15,443 90 Pennsylvania Philadelphia 1,526,006 115.4 Pittsburgh 305,704 102.9 Reading 88,082 100.1 York 43,718 97.9 Virginia Norfolk 245,782 87.4 Portsmouth 96,470 85.3 Richmond 210,309 87.7 Winchester 26,881 92.3 Fairfax 23,461 93.7 West Virginia Charleston 51,400 97.9 Huntington 49,138 99.2 Martinsburg 17,227 93.9 Romney 1,848 95.7 Number of cities 20 Average of city indices 96.01 Region IV Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee Alabama Anniston 23,106 82.5 Mobile 195,111 84.8 Selma 20,756 77.2 Florida Jacksonville 823,316 85 Pensacola 51,923 84.8 Tampa 335,709 91.1 Georgia Atlanta 443,775 88.2 Columbus 197,872 84.6 Statesboro 29,779 80 Kentucky Louisville 597,337 92.5 Somerset 11,196 88.5 Mississippi Columbus 23,640 79.6 Jackson 173,514 84.4 North Carolina Charlotte 731,424 82.3 Rocky Mount 57,477 78.4 South Carolina Columbia 130,591 80.8 Aiken 29,627 86 Tennessee Memphis 655,155 87.8 (continued on next page)
table 10 (Continued) City Name Population* City Index Chattanooga 171,279 86.5 Cookeville 31,010 81.5 Number of cities 20 Average of city indices 84.325 Region V Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin Illinois Bloomington 76,610 103.8 Kankakee 27,537 111.2 Chicago 2,695,598 118.4 Indiana Columbus 787,033 90.5 Fort Wayne 253,691 89.9 Washington 11,739 90.7 Michigan Detroit 713,777 103.7 Muskegon 38,401 92 Jackson 33,534 96.6 Minnesota Minneapolis 382,578 109.7 St. Cloud 65,842 106.6 Windom 4,646 95.2 Mankato 39,309 99.9 Ohio Columbus 787,033 95.6 Lima 38,771 95 Marion 36,837 90.9 Wisconsin Madison 233,209 100.6 Green Bay 104,057 98.9 Lancaster 3,868 96.2 Milwaukee 594,833 104.5 Number of cities 20 Average of city indices 99.495 Region VI Arkansas, Louisiana, New Mexico, Oklahoma, Texas Arkansas Little Rock 193,524 83.7 Fayetteville 76,899 75.7 Hot Springs 35,193 77.1 Harrison 12,943 76.2 Louisiana New Orleans 343,829 88.3 Lafayette 120,623 83.8 Monroe 48,815 81 Thibodaux 14,566 85 New Mexico Albuquerque 555,417 88.5 Farmington 45,854 88.7 Socorro 9,051 87.4 Tucumcari 5,363 88.6 Oklahoma Oklahoma City 599,476 84.9 Tulsa 391,906 82.9 Woodward 12,051 83.1 Ponca City 25,387 81.3 Texas Houston 2,160,821 87.5 Dallas 1,241,162 85.7 Bryan 78,061 81.5 Victoria 64,376 75 Number of cities 20 Average of city indices 83.295
53 table 10 (Continued) City Name Population* City Index Region VII Iowa, Kansas, Missouri, Nebraska Iowa Des Moines 203,433 93.7 Cedar Rapids 126,326 93.6 Burlington 25,663 88.7 Creston 7,834 89.4 Sibley 2,798 80.9 Kansas Wichita 385,577 86.4 Kansas City 147,268 98.7 Topeka 127,939 86.3 Salina 48,045 87.2 Hays 20,993 85.5 Missouri St. Louis 319,294 103.7 Kansas City 459,787 104.8 Rolla 19,559 96.9 Sikeston 16,318 95.1 Joplin 50,150 92.3 Nebraska Omaha 421,570 91.3 Alliance 8,499 88.6 Grand Island 49,989 90.7 McCook 7,652 87.5 Norfolk 24,332 90.3 Number of cities 20 Average of city indices 91.58 Region VIII Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming Colorado Alamosa 8,780 90.6 Denver 600,158 94 Greeley 92,889 90.1 Montana Great Falls 58,505 92.6 Wolf Point 2,621 90.5 Billings 106,954 92.2 Helena 28,190 90.7 North Dakota Fargo 105,549 88 Jamestown 15,427 77.5 Williston 14,716 82.6 South Dakota Sioux Falls 153,888 82.9 Watertown 21,482 78.4 Mitchell 15,254 77.5 Utah Salt Lake City 186,440 88 Price 8,715 85.4 Logan 48,174 87.6 Wyoming Cheyenne 59,466 86.3 Rawlins 9,259 87.2 Wheatland 3,627 85 Rock Springs 23,036 87.5 (continued on next page)
54 table 10 (Continued) City Name Population* City Index Number of cities 20 Average of city indices 86.73 Region IX Arizona, California, Hawaii, Nevada Arizona Phoenix 1,445,632 89.5 Show Low 10,660 88.8 Tucson 520,116 88 Kingman 28,068 87.4 Flagstaff 65,870 89.4 California Berkeley 112,580 117.2 Stockton 291,707 108.6 Los Angeles 3,792,621 108 Oxnard 197,899 106.8 Redding 89,861 110 Salinas 150,441 110.5 San Luis Obispo 45,119 105.5 Hawaii Hilo 43,263 116.6 Honolulu 390,738 119.1 States & Poss. Guam 159,358 100.8 Nevada Las Vegas 589,317 104.9 Reno 227,511 97.3 Carson City 55,439 97.3 Elko 18,546 93.1 Ely 4,288 101.3 Number of cities 20 Average of city indices 102.005 Region X Alaska, Idaho, Oregon, Washington Alaska Anchorage 291,826 119.8 Fairbanks 31,535 119.9 Juneau 31,275 120.1 Ketchikan 8,050 126.1 Idaho Boise 205,671 91.5 Coeur dâAlene 44,137 97.7 Idaho Falls 56,813 89.6 Lewiston 31,894 99.3 Pocatello 54,255 91.7 Oregon Bend 76,639 99.8 Eugene 156,185 99.6 Portland 583,776 100.1 Vale 1,874 91.7 Medford 74,907 99.4 Washington Clarkston 7,229 92.8 Olympia 46,478 101.1 Seattle 608,660 104.3 Tacoma 198,397 102 Yakima 91,067 99.9 Wenatchee 31,925 96.1 Number of cities 20 Average of city indices 102.125 * Population statistics (2010) were obtained from the list of cities in the United States at Wikipedia.com.
55 o Yes o No Please explain the reasons. APPenDIX H Cost estIMAtInG PRoCess Table 11 shows the five steps of the cost estimatÂ ing process and their descriptions. confusion, please list your suggestions for correcting the situation. 6. If more actual cost data are captured and there is a more refined differentiation of types of facilities with the appropriate cost data, would the cost estimating tool be helpÂ ful for your agency? table 11 Steps of the cost estimating process. Cost Estimation Step Description Determine estimate basis Document project type and scope, including: â¢ Scope documents, â¢ Drawings that are available (defining percent engineering and design completion), â¢ Project design parameters, â¢ Project complexity, â¢ Unique project location characteristics, and â¢ Disciplines required to prepare the cost estimate. Prepare base estimate Prepare estimate, including: â¢ Documentation of estimate assumptions, types of cost data, and adjustments to cost data; â¢ Application of appropriate estimation techniques, parameters, and cost data consistent with levelÂofÂscope definition; â¢ Coverage of all known project elements; â¢ Coverage of all known project conditions; and â¢ Checking of key ratios to ensure that estimates are consistent with past experience. Determine risk and set contingency Identify and quantify areas of uncertainty related to: â¢ Project knowns and unknowns, â¢ Potential risks associated with these uncertainties, and â¢ Appropriate level of contingency congruent with project risks. Review and approve estimate Review estimate basis and assumptions, including: â¢ Methods used to develop estimate parameters (e.g., quantities) and associated costs, â¢ Completeness of estimate relative to the project scope, â¢ Application of cost data, including projectÂspecific adjustments, â¢ Reconciliation of current estimates with the baseline estimate (explain differences), and â¢ Preparation of an estimation file that compiles information and data used to prepare the project estimate. Approving estimates includes: â¢ Review of current project scope and estimate basis, â¢ Securing of approvals from appropriate management levels, â¢ Approval of current estimates, including any changes from previous estimates, and â¢ Release of estimate for its intended purpose and use. Determine estimate communication approach Communication approach is dependent upon the stakeholder who is receiving the information, but should take into consideration: â¢ Mechanism for communicating the cost estimate for its intended purpose, â¢ Level of uncertainty to be communicated in the estimate given the information upon which it is based, and â¢ Mechanism to communicate estimate to external parties. (continued from page 49)
Transportation Research Board 500 Fifth Street, NW Washington, DC 20001 These digests are issued in order to increase awareness of research results emanating from projects in the Cooperative Research Programs (CRP). Persons wanting to pursue the project subject matter in greater depth should contact the CRP Staff, Transportation Research Board, National Academies of Sciences, Engineering, and Medicine, 500 Fifth Street, NW, Washington, DC 20001. COPYRIGHT INFORMATION Authors herein are responsible for the authenticity of their materials and for obtaining written permissions from publishers or persons who own the copyright to any previously published or copyrighted material used herein. Cooperative Research Programs (CRP) grants permission to reproduce material in this publication for classroom and not-for-profit purposes. Permission is given with the understanding that none of the material will be used to imply TRB, AASHTO, FAA, FHWA, FMCSA, FRA, FTA, Office of the Assistant Secretary for Research and Technology, PHMSA, or TDC endorsement of a particular product, method, or practice. It is expected that those reproducing the material in this document for educational and not-for-profit uses will give appropriate acknowledgment of the source of any reprinted or reproduced material. For other uses of the material, request permission from CRP. ISBN 978-0-309-37491-0 9 7 8 0 3 0 9 3 7 4 9 1 0 9 0 0 0 0 Subscriber Categories: Highways â¢ Administration and Management â¢ Construction