This is an easy way to adjust prior to Questimate’s annual pricing update. If your copy is a year old, and materials prices have increased an average of 3 percent, adjust with a single entry covering all accounts, 100-999, and an index of 103. Use EDMI (see Section 301 in this manual), or any other index you choose, for estimating materials cost changes.
Also, you can use this menu to bury tax and freight in your materials estimates to avoid entering those items separately. This menu offers the advantage of spreading these costs throughout the estimate rather than showing them as one-line entries, if that’s your preference. Just use an index that combines the two (along with any escalation).
Risk factors on a project can cover any number of project elements. It may be bene- ficial to actually prepare risk-based estimates focusing on major cost components for which risk is a significant issue. Formalized risk-estimating methods are available and may be appropriate for certain circumstances. Range estimating can be done in a rather simple fashion by selecting the 20 percent of line items in an estimate that represent 80 percent of the cost, developing a range for each of these items, and then simply adding the low and high ranges. A more advanced approach involves taking the same 20 per- cent of items, establishing the range, and then using any one of several available soft- ware packages to produce a risk profile. This approach would give a more accurate projection of the logical highs and lows involved with 20 percent factors. A sensitivity analysis can also be prepared to vary the key risk parameters.
cost, and reduce the potential for human error. In fact, a common complaint from
estimating firms is how much they hate paying estimators to simply count or quantify when they bring so much more expertise and experience to the table.
By automating the tedious task of quantifying, BIM allows estimators to use that time instead to focus on higher value project-specific factors - identifying construction assemblies, generating pricing, factoring risks, and so forth - that are essential for high- quality estimates. For example, consider a commercial project slated for construction in northern Minnesota in the winter. The estimator will realize that winter heating and dewatering will be needed for a portion of the concrete substructure. This is the sort of specialized knowledge only professional estimators can factor in to the cost estimate accurately. This construction wisdom, not "counting," is the real value professional estimators bring to the costestimating process.
The first principles (basic cost) estimating method, outlined in section 4.2.3, involves calculating the cost of all the resources needed to complete the project, including an assessment of the likely risks to be encountered and allocation of contingency amounts to accommodate these risks.
For strategic, concept and preliminary design estimates, estimators are encouraged to use updated historical information as a reality check when building up their first principles estimates. This requires districts to keep accurate information on previous project costs in the form of a date/cost table for resources such as rock, gravel, sand, cement and concrete.
End Usage: a short discussion of the possible end usage of this class of estimate.
Estimating Methods Used: a listing of the possible estimating methods that may be employed to develop an estimate of this class.
Expected Accuracy Range: typical variation in low and high ranges after the application of contingency (determined at a 50% level of confidence). Typically, this provides a 90% confidence level that the actual cost will fall within the bounds of the low and high ranges. The estimate confidence level and accuracy range is limited by the reliability of the scope information available at the time of the estimate in addition to the other variables identified above. Note: the cost estimate represents a point estimate based upon a prescriptive design, which may or may not change throughout the life cycle of the design phase. The expected accuracy range is influenced by the complexity and uncertainties of the project.
CostEstimating Handbook December 2002
The primary goal of the project is to provide national leadership and coordination to minimize the loss of mine-roosting bats during mining and mine land reclamation.
The most common bat protection measures taken at AML sites are the implementation of bat gates. Bat gates are designed to keep humans out of the abandoned mines, maintain air flow and provide access for bats. Hundreds of bat gates have been constructed and installed since the AML program began. The type of gate installed depends on the size of the opening, the location and the species of bats using the mine. Bat gates are typically designed and constructed in adits, although some have been used with vertical shafts. Rebar, manganese steel, angle iron and even wire cable can be used in the construction of bat gates. Typically the metal bar or wire cable is crisscrossed and anchored into the mine walls. The openings in between cross member bars are typically 5¾" with at least a 24" wide space between vertical supports. A popular bat gate designed by Roy Powers uses 4"x4" angle iron for structural members and cross member supports with 1½"x1½"x½" angle iron stiffeners welded inside the cross members to increase integrity and stiffness.
CostEstimating Body of Knowledge (CEBoK ® ) – ICEAA is also indebted to Technomics, Inc., for the
independent review and maintenance of CEBoK ®
• ICEAA is also indebted to the following individuals who have made significant contributions to the development, review, and maintenance of CostPROF and CEBoK ®
• Sharing lessons learned on past projects increases corporate knowledge.
2.11.5 Estimating rationale
DoT’s costestimating rationale must be exercised in the broader context of a project to provide assurance that estimate values are continually dependable. Estimating forms an integral part of a system of co-dependent core inputs, such as scope, time, cost, and quality. Projects are inherently uncertain, and therefore, irrespective of the stage of a project, there will be incomplete scope information on which to base the Project’s completed-as estimate. The aim of this manual is to establish a set of Project parameters, apply a risk assessment process to allocate contingencies to cover probable eventualities, and convey meaningful information concerning the reliability of the figures provided.
convenient attribute upon which an initial design cost may be based because it can be easily scaled and adjusted for different ship sizes, even with limited design informa- tion. Historical information from a known design and cost data for selected major systems and equipment can provide first approximations of ship cost for a series of concept designs that meet the capability requirement. Another reason that weight is such a useful indicator for cost is that weight data is also an important element of a ship design. Draft, trim, heel, stability, strength and sea keeping are just some of the ship characteristics that are affected by weight or influence weight. Weights are also easy to predict from existing ships because they will vary predictably with ship characteristics. The key is selecting the ship characteristics where strong correlation with weight exists. For example, the size and weight of a power plant and the minimum compartment length for an engine room are related to the propulsion type and the installed power. The weight of the pipes in a ship correl- ates well with ship length. The magic in predicting cost is developing the CostEstimating Relationship (CER) that links a weight to cost. Different CERs are used for different weight groups. When all the weight groups are added together, it gives the weight of a ship. The designer can then use the costs from an existing ship of one size with one group of weights to predict the cost of a new ship of a different size and different weights. When precise costs are known – such as the cost of a propulsion engine, equipment or system – that cost can be directly included. This approach to cost estimation is one of the simplest, but it is still time consuming. As well, getting good data to develop a model and the CERs is often difficult, particu- larly if current cost information is not available. More significantly, the weight-based system of cost estimation has one important limitation – weight-based cost models
Faculty of Engineering Technology, Section of Product Design, University of Twente and Philips Innovation Services, Eindhoven, The Netherlands
Digitalization provides us with increasingly sophisticated tools, such as 3D CAD and ERP, that have become drivers of innovation in many industries. Traditionally, estimating product cost requires both craftsmanship as well as elaborative calculations. Product costestimating practices are currently advancing with new digital approaches that, in this paper, are referred to as Computer Aided CostEstimating (CACE) tools. CACE skills will give new engineers entering the manufacturing industry an edge, especially those in positions in which the cost of goods is an important aspect. This paper describes a new family of engineering tools referred to as CACE, elaborates on the use of costestimating through the product lifecycle, and relates this to the educational context. The paper contemplates how CACE software might continue to develop and provides suggestions on how best to incorporate the development of CACE skills into engineering curricula.
The commonly used methods are described below. A list and brief description of several estimating tools (spreadsheets) that MOTI recognizes are provided in Section 7.4.
7.1 Parametric Estimating Method
The parametric method produces a high level estimate using various factors (parameters) developed from historical databases, engineering practices and technologies that define the cost of typical transportation infrastructure or facility segments, such as cost per lane kilometer of roadway, cost per interchange, cost per square meter of a bridge structure, and cost per intersection. The historical costs used to develop these estimates come from previous relevant projects and from relevant historical percentages. The appropriateness of this method depends largely on the extent of the project definition available, and the similarity between the new project and historical models. This approach is beneficial when little or no design information is available. This method can be refined somewhat if selection of relevant projects and assessment of the data is more tailored to the specifics of the project being estimated. Costs from similar projects in the past provide an excellent source of information, but analysis of the data requires good judgment, both to select the most appropriate past project as a source, and to assess the accuracy of the historical data.
Understanding Local Track Record
The estimating track record for the E&P segment as a whole is too high level to be a reliable guide for developing future estimates. The trends in individual SPUs, PUs or fields will be much more informative – provided that sufficient data is available. All estimators should keep track of (or at least know where to find) estimated and actual times and costs in their work area, so that they can work to eliminate any systematic cost variances which have arisen. Total estimates and total actuals are required to balance - over a large number of wells – at the local as well as at the Company level.
Estimating the public cost of student loans
all fees were to increase by £500, then the average cost per student under the two systems would be roughly equivalent.
However, it should be emphasised that these baseline estimates are highly uncertain. They are based on a large number of assumptions, changing any of which would alter the estimated cost, sometimes significantly. Quantifying these uncertainties provides some sense of the magnitude by which the long-run cost of issuing student loans may be overestimated or underestimated. This report has illustrated the extent to which our estimated cost changes as we make different assumptions about future earnings growth, student numbers, fee levels, loan take-up rates, repayment behaviour and the government’s cost of
Entity Code + Project Number + WBS Code + Code of Accounts + Estimating Commodity Code
Entity Code + Project Number + WBS Code + Code of Accounts + Activity Detail Code
Entity Code + Project Number + WBS Code + Code of Accounts + Cost Type
7.08 A Review to “validate whether the estimate represents the projects scope, verify the completeness of the engineering deliverables used for the estimate and confirm whether the take offs (MTOs) reflect those deliverables” is called:
Construction Engineering (CE) – The project management effort (budget/cost) applied to the contract execution and construction phases of the project. Refer to the Plans Preparation Manual, Section 800.03, for guidance on estimating the CE cost.
Cost Estimate – A prediction of quantities, cost, and/or price of resources required by the scope of an asset investment option, activity, or project. As a prediction, an estimate must address risks and uncertainties. Estimates are used primarily as inputs for budgeting; cost or value analysis; decision making in business; asset and project planning; or for project cost and schedule control processes. Cost estimates are determined using experience and calculating and forecasting the future cost of resources, methods, and management within a scheduled time frame. (Source:
Estimating is an important process in order to prepare costestimating for a proposed project. Cost estimate will give client an overview towards the total cost needed to be spent based on design. Due to the importance of the cost estimate for a proposed project, the utilization of computer to prepare cost estimate should therefore be practiced. The entry of computer technology in the estimating practice is a major event in the improvement of the traditional estimating method by reducing estimate preparation time, reducing the amount of paperwork required for the conventional data storage, and improving the quality of documentation. However, the actual use of the computer varies. Some companies use the computer for all projects and others do not use at all. The software are under-utilized due to its inefficiency in terms of difficulty, cost and because the program does not match with the company’s style of estimate This study is intended to identify estimating techniques used by contractors for cost estimate, to identify problem causes using that techniques and to develop a computerized costestimating system for contractors. The study has found out that most of the contractors were using approximate quantity estimating technique for their cost estimations using computers. However, some of them still prefer to use manual technique as it is easier to apply. Microsoft Excel is the popular software used by contractors to prepare estimate.
LCLS Contingency Estimating Guidelines, Design Maturity and Judgment Factors (Section 5.3)
The costestimating methodology used on the LCLS project is a bottom up process based on the foundation of a logically networked schedule that is resource loaded at the lowest activity level. The schedule used for the cost estimate must reflect the scope of work as defined in the LCLS WBS and support all key event milestones. Standard estimating guidelines and methodologies are used as part of the process.
Since most of the biases arise in estimatingcost of equity, the paper is largely focused on that part. Our recommendation on estimating beta can be summarized as follows: we suggest using Sum-Beta for obtaining raw beta from the regression. It is superior to OLS beta as it takes into account autocorrelations of a stock over 2 successive periods and reduces the downward bias arising from delay under which the market news are incorporated in the stock price. Consistent with the results of our research on Kraft Foods, we suggest using 104 weekly returns to populate the data sample. The sample should exclude non-recurring events influencing both the individual stock prices and the overall market prices. A larger adjusted sample size of 104 weekly returns (2 years) should lead to a lower standard error than 60 monthly returns (5 years) and reflect a more forward looking view of company’s systematic risks. One should consider, however, if using weekly frequency would not impede consistency with other inputs estimated on monthly basis. Furthermore, though ultra-high frequency betas provide promising methods of excluding market inefficiencies in beta estimates, we believe these betas still have a long way to go until they will gain credibility in corporate finance. Finally, if one is ready to dedicate more time to obtain higher beta precision, we recommend bottom-up /peer group approach.