I
by H. Carl Bauman American Cyanamid Co.
COSTS A
W O R K B O O K
E C
F E A T U R E
Accuracy Considerations for Capital Cost Estimation These techniques are tools to be used by the seasoned cost engineer, along with his knowledge of engineering and construction economics I HE PARADOX of increasing eco nomic competition in the midst of unprecedented prosperity places a new emphasis on better capital cost predetermination. Often the speed with which a new compound is brought from laboratory to market leaves little time for accurate ap praisal of factory construction costs. Payout time has become an im portant yardstick in determining economic feasibility. It is defined as Y (years) = C/{P + D) where C is installed cost, Ρ is net annual profit after taxes, and D is depre ciation. For a given payout time net profit is penalized by inordinately high depreciation resulting from high physical asset cost. More ac curate means of estimating the cost of the capital venture are vital to the success of most competitive under takings. Large overestimates may prevent management's approval of a possibly successful facility or place in escrow funds needed for other expansion purposes. A highly op timistic estimate can lead to prohibi tive manufacturing costs and over commitment on other projects. Estimating in the traditional sense involves painstaking material takeoffs from finished drawings and spec ifications, careful evaluation from recorded experience of labor manhours necessary for installation of the material, and appraisal of "in direct" costs—engineering, field ex pense, contractors' overheads, and profits. The cost engineer must predict final capital cost within reasonably economic limits with little more than preliminary equip ment lists, flowsheets, and plot plans. Material take-offs are often nonexistent. Seldom are two proj ects in a diversified manufacturing company alike. Lacking complete
This month's feature was au thored b y H . Carl Bauman, American Cyanamid Co. As manager of Cyanamid's Cost Engineering D e p a r t m e n t , newly organized in the Engineering a n d Construction Division, a n d a professional engineer, M r . Bau man has a large reservoir of cost engineering case histories a n d can write with authority on this month's subject of Accuracy Considerations for Capital Cost Estimation. details and past similar job expe rience, today's cost engineer must explore new methods and techniques for assuring good estimates. The task is not simple. The lack of uniformity of method, complicated by a dearth of fundamental definitions of cost elements, indicates a strong need for standardization of estimate techniques. Estimating and cost ac counting functions are still adminis tered by different departments in most firms. Separated by basically different concepts, it is amazing that reasonable correlation between es timated and final costs has been achieved. The estimator's concept of labor required to install a piece of equipment may include only the cost of setting the machine on its foundation. The field superintend ent may include the foundation, as well as wiring and piping at the machine. The accountant's func tion is to feed to the ledgers such costs which could have been so loosely identified in the field. The cost report which results from such broad interpretation of code no menclature properly reflects total job labor and material, but is of little use in giving an accurate picture of piping costs relationships in local
areas of the project, and of little value in developing estimates for new projects. The cost estimation function should be part of an over all cost engineering organization which is also responsible for the methods and systems required to feed back current cost information for proper estimate and cost control. The probability of estimating exact actual cost is very small. In a random series of related events, the probability that the actual cost will be higher or lower than the estimate is 50%. If the data are extensive enough, two estimators may differ by negligible amounts in the total cost but by as much as ± 1 0 0 % in individual items. The implication is that a statistical approach to cost estimation, where limited data are available, could be a prerequisite for improved accuracies. The con ditions for establishing a basis for statistical analysis of cost data may be outlined as: Standardization of nomenclature and cost element identification Identification of basic cost variables Development of uniform cost feed-back systems The first step toward accurate estimating should be adoption of a standard cost code for all con struction projects. Table I sum marizes such a code, which has been applied to over 30 major projects in the last 3 years. The code is most effective when it is compiled on a straight-forward numerical basis with no more than three digits for cost unit identifica tion. Such a system lends itself well to punch card machine process ing. The simple numerical system can be grouped to serve the needs of plant accountants for property records, the construction superinVOL. 50, NO. 4
•
APRIL 1958
55
A
I/EC
COSTS
•
A Workbook
tendent for job control, and the cost engineer for statistical analysis. The code should separately iden tify cost variables useful in estima tion of future capital costs. It should provide the most convenient means of cost collection in the field. For instance, the lumped cost for a stripper column, including equip ment, foundation, piping, and in sulation, provides property records but cannot be used for estimating other than an equal or similar column. Collecting cost function ally permits separation of charges for individual units providing informa tion from which the installed cost of any tower may be evaluated. Ex perience with a standardized cost code has yielded gratifying results in the quantity and quality of useful statistical information fed back from the many projects to which it had been applied. Application of sta tistical sampling techniques to such uniform data provides a measure of the accuracy to be expected from information available for the prep aration of the estimate. The accumulation of much de tailed information of itself does not constitute a basis for high estimating accuracy. Analysis of contractors' Table I. Code Group 0-349
350-399 400-449 450-489 490-499 500—599 600-699 700-729 730-749 750 760-769 770-799 801 840-849 850-879 900-969 970—994 995 996 997 998 999
56 A
Standard Cost Code Summary Subdivision Direct Costs Process section (process equipment listed in flow sheet sequence 1, 2, 3, 4, S . . . ΛΓ, preceded by process identification number) Site development Process buildings Auxiliary buildings Nonprocess equipment Process accessory material (piping, insulation, instru mentation, electrical, etc.) Utilities and yard services Substructures Superstructures Painting Building services Demolition and alteration to existing structure Surplus equipment, supplies, and materials Warehouse spares Indirect Costs Home office engineering Field expenses Taxes and insurance Contractor's home office ex penses Contractor's fees Royalty payments Start-up material and labor (design modifications) Extra work authorizations
Feature
firm proposal based on completed drawings and specifications shows variations between low and high bid as high as 30%. Factors such as changes in the labor and material market, estimator's error, and con tractor's bias could account for the variations. The statistical technique is a recognition of the inherent errorproducing factors and establishes median values in price. Proper ap plication of the technique results in es timates approximating more closely the actual cost than the total of all firm bids for the project. In bidding on a large project, the average contractor must cope with the semantics of the specifications and misinterpretation of design data. The cost engineer is in better position than the contractor to evaluate the scope of the work cov ered in the proposed new facilities. Failure to encompass completely the scope in terms of equipment, struc tures, and auxiliary facilities in the es timate is the cause of most large over runs of cost. No valid estimate can be prepared for new facilities with less than a preliminary flowsheet, equip ment lists, rough plot plan, rough utility balances, and general speci fication of types of buildings and structures required. Having estab lished these requirements, methods are available for estimating costs within predictable accuracy ranges. Good correlations of piping instal lation with equipment costs have been developed. Electrical power wiring costs are related to the num bers and sizes of motor-driven equip ment. Consistent relationships within narrow limits have been found between properly segregated indirect and direct costs. The Estimating Information Guide, a variation of the Nichols' technique (3), was developed from an analysis of uniform code data collected from a representative list of completed chemical plant proj ects. It shows the range of ac curacy expected when the informa tion at the top of the chart is avail able. For all practical purposes, five kinds of estimates are useful in the evaluation of capital costs for chemical plants. The factored estimate is primarily a rule-of-thumb procedure applied only to repetitive types of plant installations for which there exists good cost history : sulfuric acid plants, nitric acid plants, am-
INDUSTRIAL AND ENGINEERING CHEMISTRY
monia plants, steam generating units, and refrigeration units. Charts (7) have been plotted for such facilities, from which capital costs of given pro duction capacities can be read with accuracies from 10 to 50%. At the other extreme is the "firm" or con tractor's estimate, defined by general usage as requiring complete drawings, specifications, and site surveys. Time seldom permits preparation of such estimates prior to approval to proceed with the project. There remain, essentially, three basic es timate types prepared most fre quently for capital evaluation. The study estimate is prepared to de termine the economic feasibility of a project before expending further funds for piloting, market studies, land surveys, and acquisition. It is defined here as having a mini mum accuracy of 30% and can be prepared at relatively low cos' with the minimum data shown in the chart. The scope estimate has a nominal accuracy of 20%, but requires more detailed information than the study. Accuracies of this type may approach that of the project control estimate as quantitative and qualitative in formation is improved. The proj ect control estimate is the most accurate—to 10% or less with the information available indicated on the chart. The accuracy limits are shown as an envelope of variability, implying variable results depending on information. The envelope de fines the limits from experience during development of the statis tical sampling techniques in the last 3 years. The most probable case is centered in the accuracy range, implying the probability of equal percentage variations over and under the most probable figure. In times of rising cost trends, however, posi tive percentage variations will prob ably be greater than the negative. The opposite can be expected in times of falling cost trends. To date, the validity of the variable envelope has been verified within the limits of a 9 5 % confidence coefficient. Statistical data have been ac cumulated for completed projects for which estimates were prepared, which progressed from study to scope to project control. Noninclusive median costs for the prepara tion of these estimates are :
A Workbook Feature
A.
Study (30%) Scope (20%) Project control (10%)
COSTS
I/EC
Estimating information guide
Up to $5 Million Median time, weeks Median cost 2 1,000 4 5,000 8 25,000
The costs include engineering, drafting, and cost engineering ex penses for projects valued up to $30,000,000. Most of the engi neering and drafting expended in the preparation of the project control estimate are applicable to the final project cost, reflecting lower net estimating costs than shown in the table. There is an obvious saving in time and money going from study to the project control es timate in this fashion. A recent check was made on the validity of the envelope of vari ability by analyzing the perform ance vs. estimates of ten capital projects varying in value from $500,000 to over $10,000,000 (Table II). T o assure consistency of data, these plants were selected among those concurrently under construc tion during the last 24 months. The standard cost code had been applied to all these projects, so that information fed back was uniform and equally defined. The effort to achieve comparison of similar and unbiased data resulted in rejecting projects whose history showed un usual premium pricing and job labor conditions or design changes during the life of the project.
•
$5 to $30 Million Median time, weeks Median cost 3 1,500 6 10,000 10 30,000
S t u d y estimates h a d been p r e p a r e d for all b u t two of these proj ects. Scope a n d project control estimates w e r e p r e p a r e d for all. Grass Roots. Complete plant, from the ground up, erected on virgin site Battery Limits. Extension to existing plant; unit within a complex Single Product. Plant manufacturing a single product—i.e., nitric acid, ammonia, sulfuric acid, aluminum sul fate Complex Chemical. Plant manufac turing more than one product or many intermediates going into one or more end products I. Chemical. Plant operated con tinuously, material fluid from raw ma terial input to final product output
II. Chemical-Mechanical. Pardy chemical operation and partly solid materials-handling mechanical opera tions III. Mechanical. Plants largely solid materials-handling IV. Civil. Plants largely civil or structural—tank farms, storage systems and warehouses, waste disposal im pounds, basin, and plants Classifications I, I I , a n d I I I a p proximate Lang's fluid, fluid-solid, a n d solid categories (2). T h e d a t a in T a b l e I I w e r e plotted to show d e v i a t i o n from' a c t u a l proj ect costs of the t h r e e estimates p r e p a r e d for e a c h project. A fairly r e p r e s e n t a t i v e spread of variation is evident for t h e project control a n d t h e scope estimates. O n l y one study h a d a n estimated cost g r e a t e r t h a n a c t u a l cost. T h e positive v a r i a t i o e p o r t i o n of t h e c u r v e b e t w e e n t h n study a n d scope is, therefore, in d e t e r m i n a t e for this s a m p l i n g . In
Table II. % Deviation from Actual Cost of Several Types of Estimates Plant Proj. No. 1 2 3 4 5 6 7 8 9 10 α A,
Capital Type Value" Study Grass roots chem.-mechanical C - 0.86 Β Grass roots chem. single product + 3.4 Β Battery limits chem. single prod. -27.4 Β Grass roots chem.-mech. single -15.7 prod. Β Grass roots chem.-mech. single -21.2 prod. D Grass roots complex chemical -14.0 Β Rehabilitation chem.-mechanical -28.6 D Grass roots chem. single product C Grass roots complex chemical -14.6 C Effluent plant, civil-mechanical less than $0.5 million. B, $0.5 to $2 million. G, $2 to $10 million
VOL. 50, NO. 4
•
Scope - 0.54 + 12.30 - 6.50 + 1.10 -
5.82
Project Control + 2.05 + 3.40 + 1.60
0+ -1.50
-10.50 -6.8 + 6.20 -2.0 - 7.40 -1.5 - 9.40 -4.1 + 0.09 + 6.3 D, over $10 million.
APRIL 1958
57
A
I/EC
COSTS
•
A Workbook
Feature
T a b l e III.
Study % dev. %of from total actual + 22.1 46.81 2.36 -44.1 0.59 ... 6.51 -24.2 2.36 -70.0 3.19 -15.6 21.75 -17.8 0.83 + 75.0 84.40 - 5.5 8.51 -61.0 7.09 -57.2 15.60 -59.6 100.0 -21.2
Code Process equipment Piping and insulation 525 Instrumentation 530-480 Electrical 350 Site development 495 Nonprocess equipment Sub- and superstructure 700-720 733 Painting Subtotal directs 850 Engineering 900 Field expense Subtotal indirects Total estimate 180
500-520
all ten plants the actual cost varied less than 10 and 2 0 % from the project control and scope estimates. The studies varied less than 3 0 % from actual cost. Five project control estimates were less and five were more than actual cost; seven scope estimates were less and three were more than actual cost. Final costs were greater than all but one of the study estimates. T h e sampling represented by these 10 cases is not conclusive, but indicative of (he skew of the envelope toward negative values as information used in the preparation of the estimate diminishes in quantity and quality. Percentage variations from actual cost of the scope and project control estimates proved to have a linear relationship and a Pearson coefficient of correlation of 0.725. This reasonably good correlation reflects the adequacy of the standard grouping of accounts comprising the estimate. A much lower correlation existed between study and scope and study and project control, largely because most of the study estimates were prepared before adoption of standard cost code groupings and did not reflect equal, unbiased data. Table III summarizes detailed cost variations from estimates of plant 5. All but two of the elements in the study were underestimated. The overestimate of painting is insignificant; the overestimate of process equipment is more relative than actual, as it is expressed as percentage of total cost. The scope estimate shows lower percentage deviation from actual in almost all accounts. T h e overestimate in sub- and superstructures 58 A
C o m p a r i s o n of Estimates with Actual Cost Scope % dev. %of from total actual 35.86 + 14.0 2.94 -16.0 0.49 6.37 -10.5 1.96 -70.0 2.65 -15.6 26.49 + 20.9 0.68 + 75.0 77.44 + 4.7 12.75 -30.6 9.81 -28.2 -29.0 22.56 100.0 - 5.82
Project Control %dev. %of from total actual 31.45 + 4.8 2.82 -16.0
...
6.82 4.16 3.05 23.15 .25
71.70 16.40 11.90 28.30 100.0
... 0
-33.0 0
+ 10.5 -40.0 + 1.3 - 6.6 - 9.1 - 7.7 - 1.5
Actual Cost, %of
Total 29.60 3.30
...
6.70 6.20 2.90 20.60 0.40 69.70 17.40 12.90 30.30 100.0
STUDY
SCOPE MEDIAN
LESS THAN MORE THAN ACTUAL COST ACTUAL COST Per cent deviation of types of estimates from actual project cost on 10 capital projects
was due to a pessimistic attitude based on local plant conditions which did not materialize; this was also reflected in the project control estimate. Plant 5 shows the largest study underestimate of indirect costs vs. actual cost. This was principally due to a higher than normal engineering and field cost, the former because of low priority given this project and the latter to unusual weather conditions in the field. Similar tables for the remaining nine projects have higher correlation ratios. It would be naive to assume that preparation of accurate estimates can be reduced to a group of charts and tables to be read with mathematical precision. Sufficient progress has been made in the techniques of capital cost estimation by these methods to promise con-
INDUSTRIAL A N D ENGINEERING CHEMISTRY
sistently good results with the continued accumulation of controlled data. However, they must be considered as tools to be used by the cost engineer, along with knowledge of engineering and construction economics. Literature Cited
(1) Bauman, H. C , Chem. Eng. Progr. 51, 45J-50J (1955). (2) Lang, H. J., Chem. Eng. 54, No. 10, (1947); 55, No. 6, 112-13 (1948). (3) Nichols, W. T., IND. ENG. CHEM. 43,
2295 (1951).
Our authors like to hear from readers. If you have questions or comments, or both, send them via The Editor, l/EC, 1155 16th Street N.W., Washington 6, D. C. Letters will be forwarded and answered promptly.
