EVALUATION OF PRODUCTION IN SEASONALITY PERIODS: ANALYSIS OF THE
CONSTRUCTION INDUSTRY IN BRAZIL
Marcos William Kaspchak Machado
Federal
Technological University of Paraná - Brazil
E-mail: wkm@marcoskaspchak.com.br
Pedro Paulo Andrade Junior
Federal
Technological University of Paraná - Brazil
E-mail: pedropaulo@utfpr.edu.br
Submission:
22/02/2013
Revisions:
08/03/2013
Accept: 30/04/2013
ABSTRACT
The present work has as an
objective to evaluate the impacts of production seasonality in seasonality periods
in the Brazilian construction industry. The adopted methodology was based on
the qualitative and quantitative approaches of the aspects inherent to the
seasonality factors in the construction industry and its possible causes.
Besides that, literature data were collected in year report books and devices
provided by institutions of the sector. The results demonstrated the importance
of production management mechanisms to optimize the use of productive factors
through cost analysis, which are fundamental to understand the operational flow
of resources used in the operational media. Obtaining this information,
connected to market indicators helped in the decision making process related to
the development of prospective scenarios which will give support to the
decision making strategy aiming to stabilize the production levels.
Keywords: Seasonality, Costs management,
Construction Industry, Performance indicators.
1. INTRODUCTION
The
ability to foresee scenarios and perform strategic changes in the corporate
world is decisive factors in companies’ growth. Each organization has,
according to its size or medium, a differentiated way of understanding the
competitive environment in which it is inserted e how it will act in a Market,
according to commercial acting patterns and management of the available
resources.
Since
the insertion of the mass production system which owes its success to the
applicability and foresee ability of the environment, besides the expansion of
the consumer market and the abundance of hand labor (HELAL, 2005), the
production management model is guided by the high output and consequent
reduction of unitary fixed costs. However, with the increasing technological
evolution and the bigger tendency to entrepreneurship, the market has become extremely
competitive and other factors have emerged for the organizations management.
Now, more than never, the management of competitive differentials has become
the basis for success. Nowadays, there is the need for companies to work
strategically with the production outputs according to demand and its scope of
the market share, defined by commercial policies. Besides producing, it is
necessary to be aware of the future production outputs, operation costs and how
to improve the performance of the supplier chain in order to make the operation
flow more stable and prospect horizons in which to act.
According
to Ilo et al (2004), the companies’ competition power and attractiveness is
connected to the capacity of innovation of productive processes, proper company
management to the organizational environment and human resources, besides
external factors such as government actions on the economy, local
attractiveness measures, amplification of credit to investors and entrepreneurs
and the globalization of information. Thus, according to the author,
competitiveness is the level of capacity of the organization to efficiently the
influence of these measures in its internal environment.
However,
this stability in the processes depends on external factors. Along an
organization’s life cycle, it experiences an influence in its production output
levels and in the adequacy of the operational and strategic decision making
process. Bittencourt (2010) says that when seasonal production scenarios are
considered, the development of an economic dimensioning systematic of the
production capacity which simultaneously encompasses the analysis capacity, the
stock management process in seasonal environments and the investment
alternative evaluation, are justified for improving and making the decision
making process more reliable (ABREU et al., 2004). Thus, the use of financial
analysis and projections tools take on the role of providers of the reliability
necessary to a strategic decision.
In
this manner, this article aims to identify the organizational and market
factors, which interfere in the management of seasonal production in the
construction industry. To achieve this objective, this article aims to
specifically describe the importance of the construction industry in the national
economy by explaining its seasonal production aspects; point out the data
strategic management tools which can provide proper managerial information and
in due time for the decision making process to be able to reduce discrepancies
found in seasonal production media; measure the interaction factors between the
commercial and production decisions in the field of construction and finally,
demonstrate the seasonal costs reduction capacity inherent to this activity
through production management.
The
segment of construction is one of the bases for direct insertion of capital in
the economy and is directly linked to macroeconomic factors of job generation,
government expense evolution and reduction of taxes and interests for the
investors.
Even
if connected to factors of the national economy, according to Leite (2004) with
inflation indexes controlled, the profits are not purely financial and are a
consequence of good management of the execution of projects. Besides, the
competition among construction companies has become harder and harder and
therefore, many companies have turned their focus to internal management
factors in order to optimize their processes by reducing costs and taking
advantage of their competitiveness towards competitors.
The
strategic management of resources, when well applied, can become a factor of
financial gain through cost reduction. Four the planning of inflation of
production factors, the construction industry uses the National Index for Civil
Construction (INCC), which is measured by the Getulio Vargas Foundation.
Through the analysis of this index composition, it is possible to observe the
role of each component in the composition of operational costs. In 2011, according to an IBGE
survey, as shown in figure 1, the construction industry participated in the
Brazilian Gross National Product with 4.93% of the total of current values and
represented 7,60% of generated jobs, acting strongly for income distribution.
The participation of the sector in the economy has been in a boosting period
which was fostered by the increase of credit lines for investors and the
general public, which has resulted in increased consume. The data obtained from
the Investment Report of BNDES in 2011 shows a credit line of R$ 7,6 billion,
being this value 76% greater than the one of the previous year.
Figure 1 - Share of Construction in GDP Source: IBGE – National Accounts |
Besides
an increasing participation, the sector has presented an evolution in the
volume invested in infrastructure projects. There has been an evolution of 262%
(Figure 2). This is due to, besides the natural growth of the Brazilian
economy, to the interest of investors and entrepreneurs to join great returns
attached to gain over production factors and low risk, since with the evolution
of participation and the volume comprehended, a demand is generated in a sector
lacking qualified technology and hand labor.
Figure 2 - GDP Construction – Current values (R$
billion) Source :: IBGE – National Accounts |
As
Ilo et al. (2004) reports, “the construction industry, for being an industry
permeated by high levels of manual work and standardization of some procedures,
ended up at the margin of the automation and flexibilization process”. In a
scenario of technological deficiencies and low levels of advanced management
processes, companies must focus in their differential because any advantage
factor in the market will make them to be positioned favorably, thus optimizing
their market share.
The
standardization, even if inefficient, can bring an accommodation of the
production mechanism management, once in the view of many business men,
innovation has dubious return in the long run. Therefore, the aid of internal
and external indicators shows fundamentally the importance of flexibilization
of commercial processes and the insertion of new technologies to perfect the
productive cycle.
According
to Muñoz and Quitella (2000) there is an incongruity between the importance of
the construction industry in the national economy and the importance managers
of such companies give to the long term strategic process of productive and
management means, making such processes out-dated, not competitive and
generators of much loss and waste.
Furthermore,
the author also states that planning is not used much in the sector, allowing
immediate decision making and only considers the situational factors available
to management. This is due to the disarticulation between the Project and the
execution and to limited planning of the productive process.
Part
of this disarticulation is due to the little knowledge of management in all
hierarchic levels, which encompasses the project execution. Besides that, the
communication process becomes inefficient in these levels, once there is no
compatibility with the instruction level of the people involved. Therefore,
productivity, which is defined as the acquisition of more expressive results in
a shorter period of time, will always be in a dissatisfactory level in relation
to organizational needs in part, due to time loss with corrections and
adaptations.
For
it is a basic sector for infra-structure projects for governmental insertion as
well as for the investment in building projects, this area of the economy is
attached to macroeconomic indicators which demonstrate the economy growth
variations and inflation indexes. Besides that, Silva (1999) show that
"each organization, faced with the need to define action strategies,
orients itself by the environmental context at a level best suited to with its
trajectory”. Therefore, if the sector presents dependence on macroeconomic
factors, these must be evaluated by managers during the decision making
process.
According
to Valentim (2002), organizations use, besides internal indicators, “data,
information and knowledge produced externally to them which foster a better
performance in the market in which they play”. Among others, the author
mentions strategic are used by the high management and facilitate the
definition of strategies through directives, social policies, action lines,
institutional plans and projects; market: enable the high management as well as
the commercial area to perceive business opportunities in the internal as well
as in the international market; financial: make it possible to the financial
area professional to process cost, profit, risk and control studies;
commercial: supports the commercial area in import and/or export materials,
services and products, as well as supports the legal area in relation to
legislation in the country in which the commercial transaction is established;
statistics: support the strategic, financial, commercial and P&D, by
identifying in percentage and/or numeric terms issues connected to the
organization business, such as export indexes, import, market demand and
restriction, economic indexes, purchase power, GNP, unemployment rates, balance
of trade and internal investment indexes.
In
order to make the cost system more foreseeable, companies can adopt a cost
accumulation forecast system. The participation of each of its production cost
factors in the cost of its final product, must be measured. Once with those
data in hand, managers can apply inflation prospection in their factors, thus
creating post adjustment cost scenarios. In so doing, it is possible to work
with price policies and production volume, which will reduce the impact of
production, costs in the short term, or by smoothing through the optimization
of the production volume the unitary costs, through the unitary fixed cost and
maintaining the same sale price.
It is
also possible to observe that despite the fact that the macroeconomic
indicators follow patterns and tendencies, according to Assunção (1996)
"considering the resemblance between building, built with the same
building process" indicator such as average building costs (R$/m2 of built
area), hand- labor global productivity (Hh/m2 of built area), costs and consume
of raw material per service broadly used by the company in this sector, must
also be subjected to analysis. Thus, organizations can evaluate their
indicators by taking the sector general indicators as a reference, which are
obtained through surveys performed by representative organisms institutions.
Besides that, companies can provide parameters or project prototypes, thus
defining indicators which can, according to the author, to be used to
"compose scenarios for analysis of production behavior" through the
standard indicators developed.
With
the communication process suited to the company’s positioning and with the
support of efficient data transmission, it is the managers’ duty to
strategically identify and evaluate the process of aggregation of costs to
products and services.
Silva
(1999) reports the need organizations have to finance all the value chain to
understand in which sectors there are possibilities for cuts or better use of
productive factors, thus turning this into possible competitive gains. For that
to be done, Nakagawa (1991) claims that the root for operational boosting
through cost is intimately connected to the establishment of a “company
excellence philosophy” whose objective is to show every collaborator the importance
of resource management in the manufacture process and service rendered.
There
are several formats of cost evaluation and allocation. However, organizations
have been using adjusted methods to their managerial systems, leaving behind
all the known traditional systems, because according to Nakagawa (1991), they
distort product costs and proper management is subjected to allocation errors
which can end up in competitive loss or low return.
In
vascularized sectors that encompass a great variety of resources and services,
as is the case of the construction industry, it must be observed in a planned
manner the whole process, from the signing of execution contracts to the final
delivery of the enterprise. For this to happen, it is imperative the proper
allocation of resources according to the activities executed in each stage of
the productive process by triggering the consumption of resources among these
activities. Many times costs amplify in a cascade effect in a productive cycle
because they are interdependent. However, interdependent processes can bring
deadline competitive advantage and optimization of resources, when totally
executed according to the initial planning of the execution cycle.
Another
important concept in strategic cost management is the learning curve that is
the continuous efficiency gains in the execution of the stages of the
productive cycle, which reduces time, consequently the cost of the enterprise.
This is essentially due to the specialized hand labor, which continuously
adjusts itself in the activities it executes. According to Leite (2004):
The use of the learning curve allows
a better dimension of financial resources and greater precision in determining
deadlines for execution of the projects. The determination of service prices
becomes precise by knowing how much the productivity of this service will
increase. The comparison of productivity absolute values between similar works
or the simple determination of parameters for productivity enhancement are not
sufficient to aid coherent planning. Thus, the possibility to determine a
calculation systematic of the services productivity enhancement, will allow
their more realistic planning.
Nowadays,
companies must focus on cost management, because according to Ilo (2004),
“management of all the interfering factors in a product final cost, especially
in this new competitive model, with reduced profit margins, in which the
production cost defines the result of the company" brings the
differentiation companies need to compete strategically.
According
to Círico (2006), in management, the capacity to prospect scenarios is a skill
which must be used to manage future demand and production. The process must
create limits that indicate the objective in a practical way, towards which the
organization must go in search for results.
As in
the case of mining which uses previous knowledge to prospect new ores, it is
also important to make use in the business world, an organized and standardized
set of past information which will help in the current decision making process
in order to influence the future. According to Securato (1993) "there is
something connecting past and future which helps us in the decision making
process and gives us the capacity for such. We will call that, forecast
sensor". As Ferreira (2009) claims, future forecast and the results the
decisions can trigger are made all the time.
According
to the author, another aspect to be approached is the scientific and technological
level of development of the society which contributes in reducing distortions
in prospection, that is, reduce risk factors that today’s decisions have in
relation to the expected future. Ferreira (2009) points out that factors like
variable social and economic policies in the short term, government budget
disorder, problems with suppliers of raw material to infra-structure suppliers,
lack of information about the market and the demand, merely political decisions
not related to technical knowledge and little openness to the international
market, are determining to increase the uncertainty level about future
projects. These measures, besides directly influencing organizations, also
affect the whole productive chain and client portfolio, which also depend on
these factors to invest or not their reserve investments in infrastructure
construction.
Correa
et al. (1999) demonstrates that organizations must act according to certain
abilities concentrated in the internal demand management. They are the following:
a)
Ability to foresee the demand –
it involves the use of proper tools the company has to anticipate demand. They
must be used from the sales database, as well as information that explain the
behavior of these indexes and how the internal and external variables influence
the productive medium. Another appropriate tool is the market information
sampling of the sector to foresee the company participation and try to expand
it.
b)
Power of influence on the
demand - besides understanding the demand, a company must find ways to
influence it positively in order to absorb a bigger market share through the
negotiation of deadlines, price reduction or simply by encouraging sales
representatives to offer a new product mixes which will bring the maximum
utilization of the productivity capacity.
c)
Ability to fulfill deadlines –
this ability is very important to maintain a planned and continuous production
process, because promising delivery deadlines to clients makes the whole
productive medium to concentrate in the chronologic flow of the production to
achieve it. Besides, it enlarges the confidence of buyers, a fact that will
bring benefits with new sales, thus incrementing the level of future
production.
d)
Ability to priorize and
allocate – due to the absorption of new businesses, at a given point in time,
the company will have to prioritize one client or another. This decision is
important because then, the company will be able to optimize its processes by
allocating the resource sources in a way that will reduce idleness.
Figure 3 – Projection level
production Source: Author |
Thus,
the decisions to evaluate the future must be systematic and objective because
they will always influence the economic and financial order of the
organization.
Such
evaluations about the future scenario can be classified in three ways,
according to Correa et al. (1999), depending on the expected future:
a)
Planning – where the future
scenario will be designed through the insertion of new tools in the
organizational control. For example, the planning for the assembling of a new
plant, in which the company has the power to interrupt planning at any time,
even if it will cost something in the future.
b)
Prediction – future scenario in
which something out of control of the company can jeopardize its planning, like
climate or another unexpected reason (VANKATRAMAN, 1994).
c)
Projection – these are
evaluations in which it is expected that the future will be a mirror of the
past following tendencies and seasonal periods, as shown in Figure 3.
For
the forecast to be admissible, it is not possible to use one technique only.
However, it is important to simulate scenarios in different ways in order to
observe the action range the organization will find in the future.
According
to Moritz et al. (2009), there is a convergence of surveys which approach
strategic planning about strategic scenarios and the competitive intelligence,
once it is possible to make decisions attached and based on the data related to
future uncertainties. On the other hand, it is becomes harder and harder for
companies to compete in the current economic context.
Porter
(1992) claims that companies must create different scenarios that use all the
information about possible market changes or in its current production and cost
structure, through communication on information networks that at the same time
distribute and collect important data, which can be used as reference for
decisions to be made.
According
to Marcial (1999), the simulation of scenarios helps the discussion of some key
questions related to the future of companies, besides granting managers a
clearer decision-making and of lesser risk. The author still reports that these
scenarios foster the identification of opportunities and threats to the
business; promote de development and the analysis of new future options for the
company when facing changes in the external environment. They supply a view of
future which can be shared by the members of the organization". That is,
besides being simulated, the scenarios must be object of joint communication
and evaluation.
According
to Ferreira (2009) "all the variables obtained quantitatively, through
historic series or indicators, serve as base to simulate future scenarios for
the alternatives to be analyzed. However, as in obtaining results in an
uncertain future, there can be or not, probabilities of success or failure as
for the results". In order to minimize these risks, the elaboration of
scenarios must encompass technical and qualitative matters. The information
sampling process for the simulation of scenarios can happen, according to
Securato (1993) in the following ways:
a)
Brainstorming – it consists of
presenting one objective to a group of people. The variables of influence are
initially listed and posteriorly discussed and selected one by one. After that
parameters that compose the different scenarios are fixed.
b)
Kinetics – similar to brainstorming
but with less people involved, normally specialists in the problem to be
discussed.
c)
Specialist - individual
analysis by a specialist who determines the parameters and groups them in
different scenarios.
d)
Delphi – tries to subject the
objective and the variables of influence to a detailed constructive criticism.
Once the variables are determined, the work with the scenarios obtained is
repeated. In this context, participants do not communicate, that is, there is
no influence among parts.
As
can be observed, there are several formats to create and evaluate scenarios.
The applicability in each organization will be conditioned to its structure and
to the objective to be reached, but obtaining these scenarios is important to
serve as a reference for the decision making in reducing risks.
3.
TOOLS USED
IN STRATEGIC MANAGEMENT PRODUCTION SEASONAL
According to Estrela (1998) “the
indicators consist of quantitative expressions which represent an information
originated from the measurement and evaluation of a production structure of the
processes which compose it and/or of the resulting products. The measurement
and evaluation refer to the identification of the data and information and to
the establishment of criteria; specifications or values for comparison between
the results obtained and defined standards or goals.”
In order to create indicators in a
company, it is necessary to point out the processes where the measurements will
be performed and the retrieval of the database for analysis. Besides that, it
is essential to evaluate how the organizational structure treats the data of
the process to be evaluated within the managerial or production hierarchy.
According to Estrela (1998) the
processes to be evaluated are those that are priorized by the company. Based on
these processes, indicators can be classified as managerial indicators, those
that are created to evaluate the implementation of strategies introduced by the
company’s board of directors. These indicators evaluate several hierarchic
levels and processes that permeate goals from the action plan to be reached.
Another group of indicators are the operational indicators, created on the
processes or operations executed at the operational level. In order to create
the indexes, it is necessary to create a flow chart of the process by
identifying the medium applied to the product which will evaluate one by one
and observe in which processes the company presents a low productivity level.
According to a PBQP-H(1991) report,
indicators must fulfill the following pre-requisites:
a) Selectivity – must be specifically related to the stages of the process
or to the product.
b) Simplicity – easy to understand, use of simple percentage, average and
absolute number variability.
c) Low cost – the cost of its processing, sampling and evaluation must not
be higher than its benefit.
d) Accessibility – data has to be easily accessed.
e) Representativeness – must satisfactorily represent the process.
f) Stability – must last with time, based on routine procedures
incorporated to the company’s activities.
g) Tractability – must be easily accessed and the information must be
properly documented.
h) Experimental approach - indicators must be tested. In case of no being
really important, they must be altered.
So, it can be seen that the
strategic planning of information is not the strategic plan itself, but it is
the result expected through the use of tools in the future of the organization
and must take into account the organizational mission. The concept of
indicators revolves around a strategic management intended to build the route
for a desirable future for the organization, be it private or public. However
these indicators must be flexible in case it is necessary according to the
changes of the operational environment (MOTTA, 2003).
Performance indicators are one of
the most important tools used to understand processes and how they can be
improved. They show the company’s current scenario in a quantitative fashion.
Several data resources from different areas of the company are necessary in
order to create performance indicators. According to Pontes (2007), data
sampling can be done in three different ways:
a) Continuous – when data are sampled along the process. Many times they
are information restricted to one single event without many variables of
influence.
b) Periodic – sampling demands time for preparation or ending of a cycle,
be it for productive or time dependence.
c) Occasional – are performed by sampling or infrequently from an isolated
random operation.
In order to manipulate a great
volume of data, database tools can be applied to make visualization and
selection of the obtained data easier.
Since in the construction industry
projects involve many resources, from human, financial, material and
technological in large volumes, however in short periods of time, it is
necessary to have an analysis structure, human as well as technological,
directed to the project.
Data originated from the different
sectors of the company, must be stored separated by areas or departments and by
activity or process, because according to Miranda (1999), data are a “known
qualitative or quantitative set of registers, organized, grouped, categorized
and standardized properly and which become information".
According to Miranda (1999),
information is “data organized in a significant fashion, being used as basis
for decision making. For such, in order to transform data into information,
human analysis of the results obtained from the evaluation of the set of data
is necessary. Such analysis can be either quantitative or qualitative.
According to Alencar (1998),
information from the conversion process must be: precise – must not contain
errors; complete – contain all the important and necessary facts; economic –
must not be costly to the organization; flexible – can be used for several
purposes; reliable – must have a methodological basis; relevant – is important
for decision making; simple – cannot be either exaggerated or complex; fast –
is available when necessary; and verifiable – can be checked.
For data to be object of strategic
decision, data mining is a tool that has been used to evaluate it. This
methodology aims to create occurrence patterns for data and its inter-relations
between the observed values and is normally inserted in specific software for
the decision maker.
According to Navega (2002), data
mining is located between data (figure 4) and the decision making process. It
is a data conversion tool that uses statistical analysis through software
evaluation.
Figure 4 - data mining in the context of decision Source: NAVEGA, 2002. |
The system aims to search for
patterns which are sequences of data regularly presented, by using the
induction method, the same used by the human brain to understand the daily
facts and happenings. Therefore, data mining is not only a data analysis
system, but it is also a fast method for information processing with logic
order of data, which transforms sequences in prime information for risk
assessment in future scenarios.
Besides planning and evaluating
data, data mining creates several rules to understand the set of data.
According to Navega (2002), they are as follows: a) Characterizing –
characterize the occurrence of data and summarize events; b) Discriminating –
separate other data from the characterizing data; c) Associative – look for
older rules which connect one concept to another; d) Time evolution – try to
identify associations or sequences between data along time.
4. RESULTS AND DISCUSSION
The relations between information
based on data sampling, constitute indicators which not only represent the
present enterprise scenario, but which will aid the future strategic planning
by limiting the rational use of resources or establishing new goals. For this
to happen it is necessary to evaluate not only data, but also variables not
pertaining to the company’s routine, but which affect the market in which they
are inserted. One example are the macroeconomic factors which strongly
influence the way investors think and which could generate demand, but because
of economic risk, end up reducing investments, which creates a vicious cycle of
caution with the retracted economic scenario. Some of these factors can be
perceived as discrepancies in indicators, but are approached not with
quantitative questions, but with qualitative ones that can work against the company.
Therefore, besides data, a holistic evaluation of external information is
necessary to fundament and delimit the company’s decision making.
The managerial use of indicators
represents the evolution level of the reliability of the decision-making, be it
of long or short term. Much of the information obtained in the studies are easy
to understand and always shoe the essential relations for good management, like
average, relation between magnitudes, percentage variation and division by
projects, which makes it easier for the direction board to make choices.
One example of evaluating parameter
is the Balance Point shown in Figure 5, which shows how much the company must
produce at a given cost and a specified value necessary to obtain zero net
profit. In this same graphic it is possible to evaluate how much profit is
possible to make with current output, or even prospect differentiated sales
values and reduced manufacturing costs to reach an ideal point of income and
profit for the organization as shows the formula below:
Where:
p=
sale cost;
q=
amount produced and sold;
cf=
production total fixed cost (variable per plant unit)
cv=
variable cost (fixed per plant unit)
At this point we find the total
income equal to the total production cost, that is, zero profit, also called
Operational Balance Point as shown in figure 5.
Besides PEE there are other two
kinds of PE that originate from the first. They are the Cash Balance Point, in
which the depreciation costs which fall upon the company’s structure are added
and the Economic Balance Points which besides depreciation are added to the
economic (opportunity cost, externality, inflation) and fixed costs. Both raise
the total cost line. When that happens, the company must produce more or reduce
costs in order to maintain the expected margin.
Figure
5 – Breakeven point Source: Author |
When the output volume is ascending,
fixed costs tend to decline because they are exponentially connected to the
volume produced. By following this reasoning it is possible to visualize the
importance of maintaining output volumes that use the plant’s full productive
capacity or services offer.
Another approach to the Balance
Point is the creation of a table in which it is possible to observe how the
several output volumes influenced the expected profit margin by practicing an
“x” sale price which can be re-evaluated and prospected at any time, up to the
maximum operational capacity at that moment. This mechanism is based on the
triad Cost – Volume – Profit which supports the strategic decision-making
process in financial, production and commercial areas. Its evaluation brings a
greater quantitative understanding what decisions can bring to organizations.
This relation that is presented,
even simple as it is, is partly unknown by some managers, leaves behind
knowledge of the real value that can be generated by the available resources.
Cost evaluation is essential because
according to Ilo (2004) "costs are originated from activities necessary to
the materialization of the Project” and to the success of strategic management,
because it is through this stage of defrayal that the project starts to be
dimensioned in regard to its Market role of obtaining income, that is, these
are the first important characteristics for the commercial bargain power of the
product. However, for a proper cost analysis, the process must be preceded by
information that captures data to the foundation of the strategy to be adopted.
Cost information is no longer only a matter of accountancy and establish a
connection with the evolution of the production future scenario. Therefore,
these data must be evaluated with a different view from the accountancy aspect.
Some accountancy variable costs become fixed costs in a managerial perspective,
as is the case of hand labor in the civil construction industry that is
directly attached to the productive process and is variable according to
production. However, if companies ended their processes today, one of the first
objects of liquidation, and in the case of the construction industry, the
costliest object would be hand labor. This productive resource represents 51%
of productive costs, according to the Brazilian Chamber of Civil Construction
Industries CBIC (2012) and thus, its analysis must be properly dimensioned in
the decision-making process and strategic planning in what concerns the
operation costs.
According to Leite et al. (2004) the
hand labor cost evaluation must be constant because there is an optimization in
the execution of tasks by the teams. “This is due to the continuous improvement
in performing the work and the familiarization of the construction team in the
operation environment, that is, it is the learning effect”. But this is only
possible when there is stability in the operation level of these teams, not
allowing idleness, situation that is common in environments of seasonal
operations.
According to Kiyan (2001), financial
information must be generated with pre-established periodicity, every two weeks
or monthly, so that data can be compared. This analysis reveals the behavior of
all productive factors, shows its participation and its mobility within the
period. With the help of a table that presents the level of variability of
indexes, the manager can verify and work with scenarios admitted between the
worst and the best stage of utilization of the productive period and the cost
dilution. Thus, the decision-making process and future evaluation of the
organization becomes less straining and with a much lower level of risk.
5. CONCLUSION
The
study pointed out that through the use of tools that join information from the
productive process and the strategic decision-making, the organization is able
to align its objectives and develop the total use of available resources.
Instruments which were until recently used merely in accounting, become more
and more important for the development of analytical management and concerned
with the continuous and stable level of production. It is a fact that there must
be an interaction between commercial decisions and production in the sector
studied and that the flow of information must be reconsidered. Besides that,
the feedback time between the sale process and process of reevaluation of the
productive capacity and operational costs must be reduced, thus serving as a
competitive advantage in new businesses.
Internal
or intrinsic factors must be evaluated and managed strategically and always
focused on the company’s competitive advantage which can be quality, leadership
in cost, from the optimized use or human resources. Once aware of this
differential, the sales department can better manage the negotiation by
offering clients a cheaper product and of better quality. Such factors can be
evaluated with the use of performance indicators, not only financial but also
operational, whose role is to show how each process is consolidated in the
production chain and what its participation in the cost of the final product.
Therefore, it is possible to show the manager which factors can be relocated
with the aim of reducing costs in seasonal periods.
In
what the external environment is concerned, it must be evaluated how the market
behaves, its costs and demand, but never take it as the only reference, because
organizations are groups that differentiate among each other by many intrinsic
factors which must also be analyzed with priority.
One
of the results obtained was to show that the sector has its demand linked to
the direct investment flow in a national economy and therefore it is paramount
that the manager always analyze the market based on information that present
general market tendencies of the sector. Thus, the manager will be able to
prospect the organizational growth according to an expected economic scenario.
Besides that, this evaluation must serve as a company goal, having everyone to
have in a combined fashion the same measured objective.
In
this way, by maintaining the production level stable and the operational costs
within the prospected parameters, already added with the inter-related
variables to the external environment, the company can reduce costs or keep
them stable, even in historically times known for suffering a reduction in the
production level, Thus, organizations become aware of their actual value flow,
being able to transmit them as a commercial policy through the competitive
advantage, maximizing their results and increasing their market share.
REFERENCES
AGENCIA
BRASILEIRA DE DESENVOLVIMENTO INDUSTRIAL. (2009) Estudo Prospectivo Setorial: Construção Civil. Brasília. 64 p.
Available in:
http://www.abdi.com.br/Estudo/Estudo%20prospectivo%20de%20Constru%C3%A7%C3%A3o%20Civil.pdf
ABREU
FILHO, J. C. et al. (2005) Finanças Corporativas. 5º ed. Rio de
Janeiro:FGV. 152 p.
ALENCAR,
M. S.(1998) Telefonia Digital. 3.
ed.São Paulo: Érica.
ASSUMPÇÃO,
J. F. P.(1996) Gerenciamento de
empreendimentos na construção civil- modelo para planejamento estratégico da
produção de edifícios. São Paulo:EPUSP. 37 p. ISSN 0103-9830
BITTENCOURT,
S. F.(2010) Sistemática para apoiar o dimensionamento econômico da capacidade de
produção de empresas com demanda sazonal: o caso de uma empresa fabricante de
máquinas agrícolas. Porto Alegre: PPGEP-UFRGS.
CIRICO, J. C. N.(2006) Prospectando
mercados: Cenários futuros para as
exportações da Empresa JR-Adamver (Mormaii Eyewear).Florianópolis: UFSC. 88 p.
CORRÊA, H. L.; GIANESI, I. G. N.; CAON, M.
(1999) Planejamento, programação e
controle da produção - MRP II/ ERP: conceitos,
uso e implantação. 2. ed., rev. E ampl. São Paulo. 411 p. ISBN 85-224-2103-X.
ESTRELA,
G. Q.(1998) Medição e gestão da qualidade através de indicadores de desempenho.
Rev. Elet. Cuero America. Available in:
http://www.cueroamerica.com/tecnologia_calzado/tecnologia_calzado_08.htm
Accessed in: 23 de novembro de 2012.
FERREIRA,
R. G. (2009) Engenharia econômica e
avaliação de projetos de investimentos:
critérios de avaliação financiamentos e benefícios fiscais análise de
sensibilidade e risco. São Paulo: Atlas. 273 p. ISBN 9788522456680.
ILO
, J. et al.(2004) Planejamento e controle da produção na Construção Civil para
gerenciamento de custos, Encontro
Nacional de Engenharia de Produção. 643-650 p. Available
in: http://www.abepro.org.br/biblioteca/ENEGEP2004_Enegep0110_0473.pdf
HELAL,
D. H. (2005) Processo de trabalho e produção na construção civil: um estudo de
caso. In: XXV Encontro Nacional de
Engenharia de Produção, Porto Alegre. XXV Encontro Nacional de Engenharia
de Produção, 2005.
KIYAN,
F. M.(2001) Proposta para
desenvolvimento de indicadores de desempenho como suporte estratégico.
Dissertação (Mestrado em Engenharia de Produção) - Escola de Engenharia de São
Carlos, Universidade de São Paulo, São Carlos, 2001. Available in:
<http://www.teses.usp.br/teses/disponiveis/18/18140/tde-02082002-075900/>.
Accessed in: 2012-12-11.
LEITE,
M. O.et al.(2004) A utilização das
curvas de aprendizagem no planejamento da construção civil. In: XXIV Encontro Nacional de Engenharia de
Produção, 2004, Florianópolis.
XXIV Encontro Nacional de Engenharia de Produção.
MARCIAL,
E. C. (1999) Aplicação de metodologia de
cenários no Banco do Brasil no contexto da inteligência competitiva.Trabalho
para obtenção do Diplôme d’Études Approfondies. Université de droite et des
sciences d'aix : Marseille.
MIRANDA,
R. C. R.(1999) Informações estratégicas:
estudo de caso aplicado à ECT. Dissertação de mestrado. Brasília: UnB.
MORITZ,
G. O. et al. (2009) Aplicabilidade da prospecção de cenários
como ferramenta de auxílio na tomada de decisão em gerenciamento de eventos.V
Congresso Nacional de Excelência em Gestão. 14 p. ISSN 1984-9354
MORITZ,
G. O. (2001) Análise de cenários para
tomada de decisão. Apostila Mimo. Florianópolis: UFSC.
MOTTA,
P. R.(2003) Gestão Contemporânea: A
Ciência e a Arte de ser Dirigente. Rio de Janeiro: Record. 256 p. ISBN:
8501037869
MUÑOZ,
R.; QUINTELLA, R. H.(2000) A inovação
tecnológica e o sistema de franquia na construção civil de Salvador. In -
EnANPAD, 24°., Florianópolis. Anais.
NAKAGAWA,
M. (1991) Gestão estratégica de
custos: conceitos, sistemas e implementação - JIT/TQC. São Paulo: Atlas.
111 p. ISBN 85-224-0731-2
NAVEGA,
S.(2002) Princípios essenciais do data mining. Infoimagem. São
Paulo: Intelliwis. Available in: http://www.intelliwise.com/reports/i2002.pdf
Accessed in: 2012-07-05.
PBQP.(1991)
Programa Brasileiro de Qualidade e
Produtividade. BSI. Available in:
http://www.bsibrasil.com.br/certificacao/sistemas_gestao/normas/pbqph/.
PONTES,
B. R.(2007) Avaliação de desempenho: nova abordagem. 8. ed. São Paulo:LTr.
PORTER,
M. E. (2004) Estratégia Competitiva:
técnicas para análise de industrias e da
concorrência. 2ª ed. 12ª imp. Rio de Janeiro: Elsevier.ISBN 85-352-1526-3
SECURATO,
J. R.(1993) Decisões financeiras em
condições de risco. São Paulo: Atlas.
SILVA,
C. L.(1999) Gestão estratégica de custos: o custo meta na cadeia de valor.
Revista FAE.Curitiba, v.2, n.2. Available in:
http://www.fae.edu/publicacoes/pdf/revista_da_fae/fae_v2_n2/gestao_estrategica_de.pdf Accessed in: 2012-11-23.
VALENTIM,
M. L. P.(2002) Inteligência Competitiva em Organizações: dado, informação e
conhecimento .Revista de Ciência da Informação.v.3 .
VANKATRAMAN, N.(1994) IT-Enabled Business Transformation: From Automation to Business Scope
Redefinition. Sloan Management
Review. Winter.