Indirect Costs in Shipbuilding: a proposal for its appropriation

Indirect Costs in Shipbuilding: a proposal for its appropriation

José Augusto Dunham (UGF)

José Haim Benzecry (UGF)

Marco Antônio Almeida (UGF)

Mauro Rezende Filho (UGF/COPPE)

ABSTRACT

This article introduces some concepts of costing methods, details the development of a

settlement for the shipbuilding industry and provides an application example with its

preliminary results. Due to data sources on resources and time employed are limited, in most

cases the input parameters for the cost of building a ship are estimated. Thus a methodology for

estimating the input parameters of the system based on cost uncertainty is proposed. This

methodology incorporates knowledge about the vagueness and uncertainty of data on costing

systems. Finally, to investigate the activity of the constructive system of the ship and its potential

benefits, an analytical model was developed.

Keywords: absorption costing, cost estimation, uncertainty

1. INTRODUCTION

Traditionally, in shipbuilding, overhead and profit of the shipyard are allocated as a proportion

of the sale price proposed. This may provide distorted information costs since the building

systems of a ship are different in size, complexity, material requirements and / or configuration,

and do not allow to know the profitability of each building system.

Aiming to improve the product and the cost of information production process companies

began to plan costing systems (Drury, 2006). These systems can provide valuable information to

decision makers, investigating business activities, resource consumption and cost drivers. The

development of a costing system involves four main steps:

1) Identify the activities / pool systems and assign costs based on cost factors like, for

example, purchasing, receiving and inspection activities can be assigned to a set of

process costs;

2) Determine the cost of these activities, identifying and assigning resource consumption;

3) Select a driver of cost for each system, for example, the tonnage of steel processed can

be a driver for the appropriation of the cost structure and,

4) To determine the rate of consumption for the various cost drivers.

One of the main obstacles encountered during the development of the costing system is the

analysis of the extensive amount of data collected. Two to four steps listed above in the

development process costing system require the collection of three types of data: costs of

activities that are summed to calculate the total costs of the system, the cost drivers and the

rates of consumption of resources by driver. Collecting information to specify the activities and

assign costs of these activities in a costing system is a costly and involves time. Costing systems

using estimated costs for the collection of information to generate product costs is an expensive

process. Cooper and Kaplan argue that "managers can make good decisions based on

information approximate cost (about 10%)." (COOPER & Kaplan, 1998).

As the data in most cases are estimated, and their values have uncertainty, their estimates tend

to be imprecise. As the vessel is constructed as the actual value of each parameter data is not

known with precision, it is important to incorporate some degree of uncertainty in the system.

The incorporation of uncertainty and imprecision around the input parameters for a costing

system provides the user information for many purposes, such as building systems costing,

pricing, quotation and budget development.

System cost is defined as a method of calculating costs. There are several forms of settlement

that can be mutually used each with their advantages and disadvantages, such as absorption

costing, direct costing or variable, and costing activities (ABC).

The absorption costing makes full ownership of all costs (direct, indirect, fixed and variable)

products / services. Therefore, absorption costing is the method which consists in the

appropriation of all production costs to goods produced, ie, all expenses related to the

manufacturing effort are distributed to all products / services (Martins, 2001).

The direct costing or variable makes the separation of variable costs and fixed costs,

appropriating the goods and services costs, with the variation of its volume of production,

whereas fixed costs are expenses of the period. The direct costing is also called variable costing

or marginal costing, since variable costs, most of which are direct.

The ABC (Activity Based Costing) costing method allows better visualization of costs through the

analysis of activities performed within the company and their relations with the cost objects

(Martins, 2001). The ABC costing is suitable for complex organizations, where products consume

resources unevenly. The principle of this method is to make directly the best possible cost

proportional and non-proportional through cost drivers. The benefits of the ABC method are

many, especially the following (Bruesewitz & Talbott, 1997):

1. improvement in management decisions;

2. facilitates the determination of the relevant costs as it reduces the need for cost

allocation "arbitrary";

3. identifies actions in order to reduce the costs of overheads;

4. provides greater accuracy in product costs;

5. determines the cost of services / products to the extent that identifies the cost of each

activity in relation to the total costs of the entity;

6. supports benchmarking;

7. determines the amount of shared services;

8. can be used in various types of businesses.

Despite the benefits, the ABC method may present some disadvantages to the company, such

as:

1. High expenditure for implementation;

2. high level of internal controls to be implemented and evaluated;

3. need for constant review;

4. difficulty of involvement and commitment of the employees of the company;

5. difficulty in integrating information between departments;

2. CONCEPTS OF COSTS

One of the objectives of a business is to be profitable. As the partners or shareholders of

a company expect profits, managers have a responsibility to use resources wisely and to

generate revenues that exceed the costs of operation of the business, investment and

financing.

Costs can be classified and used in several ways depending on the purpose of analysis (Crosson

& Needles, 2011). The classification will allow managers to:

1. Control costs, determining which are traceable to a particular cost object, such as a

service or product.

2. Calculate the number of units that must be sold to achieve a certain level of profit (cost

behavior).

3. Identify the costs of activities that add value or not a product or service.

4. Classify the costs for the preparation of financial statements.

The costs may be classified as follows:

• Direct costs are those costs that can be conveniently and economically allocated to a

product and / or service. For example, the wages of workers who make cereal bars can

be assigned to a particular batch because their hours worked in manufacturing are

known. Similarly, materials such as cocoa butter, sugar, milk, etc..

• Indirect costs are costs that can not be conveniently and economically allocated to a

product and / or service. For example, quality control, equipment maintenance,

supervision spending, etc.. As a matter of accuracy, however, this overhead should be

included in the cost of a product or service.

May also present the following characteristics:

• Variable cost is a cost that changes in direct proportion with the quantity produced (or

some other measure of volume).

• Fixed cost is a cost which is constant within a defined range of activity or time period.

Table 1 shows examples of these concepts to the production of the cereal bar.

Table 1 – Examples of Costs

Item Classification Behavior Attribute Value Type

Sugar Direct Variable Add value Direct material

Labor Direct Variable Add value Direct labor

Supervision Indirect Fixed Does not add Overhead

Depreciation Indirect Fixed Add value Overhead

Sales commission Expense Variable Add value Expense

Administration Expense Fixed Does not add Expense

3. DEVELOPMENT OF THE SYSTEM

A costing system for building a vessel is of high complexity. Should consider the subdivision of

the vessel on specific systems, each having specialized subsystems performing specific tasks and

processing data sometimes imprecise or vague. A hypothetical application is shown based

costing used as the procedure for generating input parameters. The figures are illustrative. The

system was developed for the calculation of expenses and perform the analysis of profit / loss.

This analysis example of a costing system was chosen because it is an application most often

used in the analysis of costs and allows monitoring and understanding, especially in shipping,

once the price is set by the shipyard with the shipowner.

3.1. DESCRIPTION OF THE PROBLEM

The costing system shown has five different systems, shown in Table 2.

Table 2 – Direct Costs of the Building Systems

System Parameter Qty Value

Structure Direct labor 56.700 844.263,00

Material / Equipment 256.000 28.225.024,00

Machines Direct labor 24.100 343.666,00

Material / Equipment - 14.457.414,00

Accessories Direct labor 18.600 274.350,00


Nets and Pipes Direct labor 26.100 437.958,00


Treatment and Painting Direct labor 32.500 859.625,00


Total Direct Costs Direct labor 158.000 2.759.862,00


Grand Total of Direct Costs 56.642.566,00

Table 3 presents the indirect costs to be allocated as well as their drivers.

Table 3 – Indirect Costs

Type of Cost Parameter Value

Equipment hours

Total cost 1.650.000,00

Driver: machine hours 24.000,00

Rate 68,75

Procurement

Total cost 265.000,00

Driver: number of orders 2.100,00

Rate 126,19

Planning

Total cost 1.080.000,00

Driver: number of manufacturing orders 22.500,00

Rate 48,00

Quality control

Total cost 1.350.000,00

Driver: hours 8.400,00

Rate 160,71

Administration

Total cost 2.800.000,00

Driver: direct labor 158.000,00

Rate 17,72

Classifier

Total cost 245.800,00

Driver: hours 1.300,00

Rate 189,08

Profit to be appropriated will be equivalent to 10% of direct costs plus indirect, ie, $

6,378,866.00, then forming the sales price of the vessel at $ 70,167,732.00. Table 3 shows the

distribution of the drivers use of the systems:

Table 3 – Use of the Drivers

Item Structure Machines Accessories Nets Painting Total

Driver: machine hours 15.360 3.360 1.920 1.680 1.680 24.000

Direcionador: número de pedidos 504 252 462 546 336 2.100

Driver: number of manufacturing orders 14.400 900 2.700 4.050 450 22.500

Driver: hours 5.376 1.176 672 588 588 8.400

Driver: direct labor 56.700 24.100 18.600 26.100 32.500 158.000

Driver: hours 832 182 104 65 117 1.300

3.2. DEVELOPMENT OF PARAMETERS

In developing this system cost input parameters were estimated using triangular numbers. This

required the estimation of possible lower values (SP), the most probable (MP), and lower (LP) for

each input parameter. By developing a real system, these estimates are developed from a survey

of shipyard experience and analysis of historical data. After a thorough review of all available

data, the parameters are extracted for all input parameters estimated in the light of experience.

The triangular function for each parameter can be achieved by asking three questions: 1) What is

the most promising parameter value, 2) What is the parameter value most likely? and 3) What is

the largest possible value of the parameter?

This process will result in triangular parameters for all input parameters of the estimate. If the

estimator know the true value of a parameter, estimates of SP, MP and LP are equal. If there is

much uncertainty about the true value of the parameter, the parameter of cost will have a wide

triangular membership function, represented by larger ranges of values between the estimates

of the SP, MP and LP. If there is any uncertainty about the true value of the parameter, there will

be narrow lanes between the estimates of the SP, MP and LP. The triangular membership

functions are not necessarily symmetrical and can be tilted to the right or left, depending on the

judgment of the estimator.

In this analytical model, the following steps will be used to generate estimates for each

triangular input parameter in the system example, assuming the hypothesis that it is not

possible to develop these estimates by extrapolation or analysis of historical data (Harrison and

Sullivan, 1996). Thus, we have:

1) In the traditional system costs, the value is assigned as the average of its data set and

this is the most likely value which represents the number triangular this parameter in the

system.

2) It is assumed that a good estimator is able to provide estimated values which remain in

the range of plus or minus 10% of the actual value of the parameter data in constructing

the system. (Cooper and Kaplan, 1988)

3) It is assumed that the data set for each parameter has a normal distribution frequency.

This assumption enables the use of empirical rule approximation to the sample standard

deviation for each parameter. The states of empirical rule implies that almost all

measurements in the data set lying within three standard deviations averaged. Therefore,

10% of the value of the parameter can be equated to three times the standard deviation

of the sample. This will be used to calculate the sample standard deviation, sd, for each

parameter.

4) It is assumed that each parameter is a normal distribution with mean equal to the sample

value of the system parameter and the sample standard deviation is equal to 10% *

(parameter value) / 3.

5) Five hundred random numbers were generated from the resulting distribution. The result

of random numbers is ordered from smallest to largest. The lowest and highest possible

parameters are defined as the same as random numbers lowest and highest, respectively.

An example showing the values, smaller, more likely larger of the total cost of the account

"Hours of equipment," respectively Csi, Cmi, and Cli, for the first group of costs is shown below.

1) Total Cost = sample mean estimate = promising = $ 1,650,000

2) 10% * (Total Cost) = $ 165,000

Desired accuracy range = [$ 1,485,000, $ 1,815,000]

3) 3sd = 10% (Total Cost)

3sd = $ 165,000

sd = $ 55,000

4) Total Cost - parameter distribution = N ($ 1,650,000, $ 55,000)

5) The lowest and highest random numbers are 1466590 and 1792479 respectively.

Minor estimate = $ 1,466,590

Greater estimate = $ 1,792,479

The parameter for the total cost of depreciation of equipment is (CS1, Cm1, Cl1) = ($ 1,466,590, $

1,652,250, $ 1,792,479).

Figure 1 - Triangular Distribution of Depreciation

This same procedure will be done for the other drivers and costs. Table 5 shows the parameters

for each charge, and Table 6 the drivers.

Table 5 – Summary of Costs

Tipo de Custo Cs Cm Cl

Equipment hours 1.792.479 1.650.000 1.466.591

Procurement 288.001 265.000 237.951

Planning 1.196.425 1.080.000 977.618

Quality control 1.489.375 1.350.000 1.245.434

Administration 3.099.288 2.800.000 2.488.760

Classifier 270.175 245.800 216.603

Tabela 6 – Summary of Drivers

Tipo de Custo Ds Dm Dl

Equipment hours 26.638 24.000 21.625

Procurement 2.321 2.100 1.843

Planning 25.208 22.500 20.431

Quality control 9.398 8.400 7.482

Administration 171.314 158.000 142.640

Classifier 1.532 1.300 1.126

3.3. DEVELOPMENT OF RATES

Once the parameters of costs and drivers were obtained, shall be determined rates Rsi, Rmi, Rli,

calculated for each cost center i. The calculations are presented below.

si mi lisi mi li

si mi li

C C CR ,R ,R , , ,

D D D

(1)

This division operation is an approximation resulting in a triangular quotient more conservative.

Note that, by definition, the rate is most likely the same rate resulting from traditional analysis

costs.

Therefore, the development of the system will contribute to the information provided by a

traditional costing system. Using the estimated parameter in the above example, we performed

calculations for depreciation of equipment. The parameter is generated using the procedure

described in section 3.2:

s1 s2 s3

s1 s2 s3

s1 s2 s3

s1 s2 s3

C ,C ,C 1.792.479,1.650.000,1.466.591

D ,D ,D 26.638,24.000,21.625

1.792.479 1.650.000 1.466.591R ,R ,R , ,

26.638 24.000 21.625

R ,R ,R 67,29;67,75;67,82

Overall rates Rs1, Rs2 and RS3 can be used in many types of analyzes, including product costing,

pricing for profit, product development, analysis and budget development, etc.. The application

presented in this paper uses the general rates for product costing as a tool for determining the

profit / loss of each building system, and these analyzes familiar to anyone working in this area.

Table 7 – Summary of the Rates

Tipo de Custo Rs Rm Rl

Equipment hours 67,29 68,75 67,82

Procurement 126,19 124,06 129,10

Planning 48,00 47,85 47,62

Quality control 166,47 160,71 158,61

Administration 18,09 17,72 17,45

Classifier 192,32 189,08 178,30

To calculate the total cost of each production system, overhead costs are obtained by

multiplying the consumption of each system cost by the corresponding rate for each building

system and adding the resulting values. These overheads are used in the analysis of profit / loss,

to make the comparison with the total cost resulting from the sales price of the vessel. The

algorithm for the calculation is shown below:

1) Calculate the indirect cost to the alternatives, the smaller, the more likely and higher,

OHsk, OHmk, OHlk, respectively, for a system k.

m

sk sm lk si sik mi mik li liki 1

OH ,OH ,OH R CDC ,R CDC ,R CDC

(2)

Where: CDCsik = lower consumption cost driver system i to k

CDCmik = more likely consumption the cost driver system for k i

CDClik = less consumption cost driver system for k i

m = number of systems

Table 8 – Allocation of Overhead

Sistema

Structure Machines Accessories Nets Painting

Equipment hours

CDCs1k 1.033.589,30 226.097,66 129.198,66 113.048,83 113.048,83

CDCm1k 1.056.000,00 231.000,00 132.000,00 115.500,00 115.500,00

CDCl1k 1.041.702,64 227.872,45 130.212,83 113.936,23 113.936,23

Procurement

CDCs2k 63.599,76 31.799,88 58.299,78 68.899,74 42.399,84

CDCm2k 62.526,24 31.263,12 57.315,72 67.736,76 41.684,16

CDCl2k 65.063,91 32.531,95 59.641,91 70.485,90 43.375,94

Planning

CDCs3k 691.200,00 43.200,00 129.600,00 194.400,00 21.600,00

CDCm3k 689.040,00 43.065,00 129.195,00 193.792,50 21.532,50

CDCl3k 685.728,00 42.858,00 128.574,00 192.861,00 21.429,00

Quality control

CDCs4k 894.942,72 195.768,72 111.867,84 97.884,36 97.884,36

CDCm4k 864.000,00 189.000,00 108.000,00 94.500,00 94.500,00

CDCl4k 852.687,36 186.525,36 106.585,92 93.262,68 93.262,68

Administration

CDCs5k 1.025.777,90 436.000,84 336.498,57 472.183,48 587.967,93

CDCm5k 1.004.810,13 427.088,61 329.620,25 462.531,65 575.949,37

CDCl5k 989.293,97 420.493,56 324.530,30 455.389,29 567.055,63

Classifier

CDCs6k 160.010,24 35.002,24 20.001,28 12.500,80 22.501,44

CDCm6k 157.312,00 34.412,00 19.664,00 12.290,00 22.122,00

CDCl6k 148.345,60 32.450,60 18.543,20 11.589,50 20.861,10

2) Calculate the product cost to the alternatives, the smaller, the more likely and higher,

PCsk, PCmk, PClk, respectively, for a system k.

(PCsk, PCmk, PClk ) = (DLk + DMk +OHsk, DLk + DMk +OHmk, DLk + DMk +OHlk) (3)

Where: DLK = directly labor cost assumed for the system k

DMK = material cost assumed for the system k

Table 9 – Total Costs by System

Item Estutura Máquinas Acessorios Redes Pintura

PCsk 32.938.406,92 15.768.949,34 5.621.066,13 3.251.240,21 6.529.678,40

PCmk 32.902.975,37 15.756.908,73 5.611.394,97 3.238.673,91 6.515.564,03

PClk 32.852.108,49 15.743.811,93 5.603.688,16 3.229.847,60 6.504.196,57

3) Calculate the estimated profit to the alternatives, the smaller, the more likely and higher,

SPsk, SPmk, SPlk, respectively, for a system k.

(NPsk, NPmk, NPlk) = (SPk - PCsk, SPk - PCmk, SPk - PClk) (4)

Where: SPk = estimated profit for the system k

Table 10 – Profit by System

Item Structure Machines Accessories Nets Painting

NPsk 3.262.641,16 2.643.561,68 399.518,88 -392.587,72 494.229,14

NPmk 3.229.748,77 2.641.604,89 398.338,00 -390.863,66 500.038,00

NPlk 3.226.635,11 2.643.376,02 400.075,07 -386.729,83 505.825,54

3.4. ANÁLISE DOS RESULTADOS

The traditional cost analysis will give us the profit of the vessel is $ 6,378,866.00, which is the

same result obtained by the most probable hypothesis, however, does not present the results

for each system. When analyzed individually each system we can observe that the profit of the

yard is guaranteed, however, in our example, the system "Nest and Piping" presents a loss.

This fact may be related to drivers adopted, however, is an answer that was not visible in the

traditional system. It is therefore the manager to analyze data and adjust the parameters

adopted in order to be sure of the profitability of each system. It is also important to note that

the entry of uncertainty in the system, provides the shipyard the boundaries of its profitability,

since the Indirect Costs and Profit, are spending under your control.

Figure 2 – Probability distribution of Profit

4. CONCLUSION

Os sistemas de cálculo de custos devem basear-se em dados precisos, levantados

meticulosamente. Na maioria das vezes, as empresas não conseguem incorporar em seus

sistemas de custos dados mais detalhados, devido às despesas que isso acarreta, bem como, os

requisitos de tempo necessários. Os sistemas de custeio são construídos utilizando dados

estimados. Portanto, desenvolver um sistema de custeio, que permita lidar com a imprecisão de

dados, e a incerteza inerente, é uma abordagem de custo-benefício atrativa para a gestão da

empresa. Fornece ao gestor uma alternativa de geração de informações gerenciais com três

estimativas para cada parâmetro estimado, permitindo que o usuário reconheça que essas

estimativas apesar de não representarem os valores verdadeiros, incorporam uma noção sobre a

variabilidade dos dados, e a incerteza em seus processos decisórios.

Este trabalho abordou a atividade de custeio, detalhou o desenvolvimento de um modelo, e

apresentou uma aplicação hipotética. Trabalhos futuros nesta linha irão pesquisar o

detalhamento dos subsistemas e suas atividades, de forma a se obter uma visão analítica da sua

lucratividade, uma vez que em construção naval, além dos direcionadores de custos, tem-se

também os estágios de produção, atividade na qual os custos devem ser apropriados.

5. REFERENCES

BRUESEWITZ, S. and TALBOTT, J. "Implementing ABC in a Complex Organization," CMA

Magazine, Vol. 71, No. 6 (July-August, 1997), pp. 16-19.

DRURY, C. “Cost and Management Accounting”. 6a Ed. London, Thompson, 2006.

COOPER, R. and KAPLAN, R.S. “How Cost Accounting Distorts Product Costs,” Management

Accounting, Vol. 69, No. 10 (April, 1988), pp. 20-27.

COOPER, R. and KAPLAN, R.S. “The Promise and Peril of Integrated Cost Systems,” Harvard

Business Review, Vol. 76, No. 4 (July-August, 1998), pp. 109-119.

CROSSON, S.V. and NEEDLES, B. E. “Managerial Accounting”. 9a Ed. Ohio, South-Western

Cengage Learning, 2011.

HARRISON, D. S. and SULLIVAN, W.G. “Activity-based Accounting for Improved Product

Costing,” Engineering Valuation and Cost Analysis, Vol. 1, No. 1 (1996), pp. 55-64.

MARTINS, E. Contabilidade de custos. 8. ed. São Paulo: Atlas, 2001.

Indirect Costs in Shipbuilding: a proposal for its appropriation

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