COST MANAGEMENT IN AGRIBUSINESS: STUDY PROFITABILITY
SCENARIOS OF INTEGRATED SYSTEM VS. INDEPENDENT
SYSTEM FOR A POULTRY PRODUCER
Laura
Maria Leite Ferreira
Fundação
Getulio Vargas, Brazil
E-mail: laurinhaf@hotmail.com
Maritiza
dos Santos Wanzeler
CIABA,
Brazil
E-mail: maritizawanzeler@hotmail.com
Renata
Melo e Silva de Oliveira
University
of Porto, Portugal
Universidade
do Estado do Pará, Brazil
E-mail: renata_ep@yahoo.com.br
Alef
Berg de Oliveira
Universidade
do Estado do Pará, Brazil
E-mail: alefberg@hotmail.com
Submission:
19/11/2013
Revision:
19/11/2013
Accept:
06/12/2013
ABSTRACT
Addressing the theme of the
cost management in agribusiness poultry industry, this study aims to analyze
from the perspective of variable costing indicators the possibility of a
poultry producer who works under the scheme of integration migrate to a system
of independent production. Through an applied, quantitative case of study, the
cost were raised, the contribution margin, break-even point and margin of
safety and income statement were calculated in both production systems to
enable a comparative analysis between the independent and integrated system of
production. Finally, a sensitivity analysis of the contribution margin in
relation to the variable cost in the independent system was performed, so a
more accurate comparative analysis was possible. Based on the results obtained
it was possible to address the pre-established problem of the research and
discuss the results found.
Keywords: Variable costing; Sensitivity Analysis; Decision.
Contributors and Supporting Agencies: Thanks are due to CAPES for funding this work though Program
Science without Borders. (BEX 19131127).
1.
INTRODUCTION
Agribusiness
is considered one of the most important economic activities
Brazil (MIELE, et al., 2010), every year thousands of tons are exported abroad
Brazil. Inserted into this context, Poultry Industry
is one of the most expressive activities of Agribusiness in the Amazonian State
of Para, where the agro industry has exceeded both geographic and technologic
boundaries for becoming an international business activity.
Beside
the fact that Brazil leads Poultry exportation, this industry weighs on other
important economics activities, e.g.: production of soya, corn, rations. The
Brazilian Association of Producers Cutting Poultry (APINCO) has published that
this country produced 6.006 thousands of birds in 2012. This production volume
raised 4% since 2011 and it is an upward trend.
Thus, it is clear that this industry shows high relevance to the
country's economy.
In
order to analyze the manner of operation at Poultry industry and also to
identify opportunities to raze the low margins of profitability, which are
considered fairly modest (FERREIRA; WANZELER, 2011), this work aims to study the
case of a Poultry Industry located at the State of Para. This company works
under the integrated system of Poultry production, which has shown very little
improvement in profit margin during the last 20 years. As this company
possesses the resources to migrate to the independent system of production, it
created the opportunity to conduct a comparative study of scenarios in both
systems for production. Thus, it became possible to analyze if the change in
modus operandi was advantageous from the financial point of view.
To
accomplish that, the variable costing method was applied in combination with a
sensitivity analysis, so advantages and disadvantages could be discussed in
order to subsidize decision making. Consequently, it was necessary to identify
all the exposedness involved in this process in order to measure efficiency
indicators (e.g. margin contribution, break-even point, safety margin) – which
was performed all long 13 months.
It
is important to point out that the analysis of scenarios for enhancing
profitability is not only important for measure gains but also it is
fundamental to guarantee enterprises survival in long term. Under this perspective of regarding the
economic sustainability of Poultry farms companies, Araujo et Al. (2008) emphasize that all economic agents involved in the
production chain should be properly paid, to stay on and they must make the
necessary investments in order to continue at this activity.
Therefore,
this study aims to examine the financial advantages for a Poultry farmer to
migrate from integrated system to independent system of production. The
analysis performed in this work follows the perspective of the indicators of
variable costing, which has been proved as an efficient tool to support both
medium and short term at operational planning.
1.1. Conceptual framework
This
section presents the theoretical framework of Variable Cost Method and
Sensitivity Analysis. Both themes are aligned with concepts and peculiarities
of Poultry Industry agribusiness and its main challenges related to
competitiveness. Concepts related to Cost Management here presented are based
on Variable Costing and its short term indicators, as Even Break Point,
Contribution Margin and the report named Incoming Statement. Sensitivity Analysis Approach is the method
used to analyze profit scenarios of rather Independent System and Integrated
System.
As in Brazilian Poultry agribusiness
competiveness almost every link of the chain is totality restricted to the
integrated system the producers need to compete basically for offering the best
price. This fact is explained cause the chickens are commodities, so the market
share defines the price of this kind of product, the producers aim to reduces
the cost can competes in market share.
1.2.
A variable costing method review
According to this Cost Management
System, the costs faced by companies can be categorized into two main
categories: fixed costs and variable costs.
The first group, fixed costs, comprehends the costs which are independent
of production output. Fixed Costs often include among other items: rent,
buildings, machinery. The second group is composed by the Variable Costs which
consist to vary with production output. Often, variable costs increase at a
constant rate relative to labor and capital applied.
Variable costs category may include
wages, utilities, materials used in production, among other items. Cost
management is defined by Martins (2010) as the field of accounting which focus
on strategic cost issues which are driven by both financial and non-financial
information. It possess great affinity to Industrial engineering approaches to
Manage both Strategic and Operational management. Therefore, the purpose of
cost management is to provide assessment to enterprises take decisions that
ultimately increase the organization’s competitiveness.
Colauto et al. (2004) argue that the
increasing use of variable costing method has proved that it became an
essential tool for Business planning, control and decision making that involves
minimizing costs and optimizing results. Then,
much of the knowledge established on this field can ultimately increase
decision taking in short term as argued by Bruni and Fama (2009) or to enhance
the effectiveness of Strategic Planning while supporting Financial Perspectives
indicators as the ones defined by Kaplan and Norton (1996). Variable costing
also brings about advantages to business management, as this method arose from
the need to solve the problems, which were caused by the difficulty of
appropriation of indirect fixed costs to products and useful knowledge variable
cost (BACKES et al., 2007).
To provide input for decision-making
is one of the main functions of cost accounting, which involves estimates of
prices, quantities demanded and costs of products and / or services that
provide the contribution of each of the venture. In this context, the analysis
of costs, volumes and profits aims to establish a table showing the relative
importance of products / services offered by the enterprise. Horngren et al.
(2003) cite the Cost Analysis / Volume / Profit is one of the most basic
assessment tools used at managerial level since it examines the behavior of
total revenue and costs, results of operations resulting from changes in the
levels of outputs (sales), selling price, unit variable costs or fixed
costs. For the same author this is the
kind of analysis that all managers ought to do, because understanding the
patterns of behavior of costs brings information necessary for planning and
control activities in the short and long term.
|
Figure 1: shows indicators which helps
management assessment of Cost-volume-profit analysis. Source: Adapted from Martins (2010) |
Indicators
of Cost-Volume-Analysis can be observed in details at table 1, below.
Table 1: Variable Costs indicators
|
Indicator |
Components |
|
Contribution margin |
CM ($) =
Price per unity – Variable Costs per unit |
|
Even Break Point |
EBP(q) =
[total Fixed costs]÷CM per unit |
|
Margin of safety |
MS(q) =
Sales(q) –Even break Point(q) |
Source: Martins (2010)
Wernke,
et al. (2002) define that the
assessment of cost-volume-profit agribusiness can provide information about
impacts caused by changes in production costs, sale prices and volume produced
in profitability. These authors also emphasize that this information is
strategic, considering that are constant fluctuations in the prices of
production inputs employed in agribusiness.
In
the agribusiness sector, it is essential that managers consider the assessment
of cost-volume- profit as a methodology for planning, since it provides useful
management tools as short-term operational planning; quantitative estimates
derived from various expected economic scenarios; anticipation of difficulties
arising from unfavorable seasonal disruptions to the company.
1.3.
Sensitivity Analysis Concepts
While
studying scenarios for Decision Aiding, it is likely that values and
constraints incur into errors. Therefore, to increase the reliability of
Decision Aiding tools, especially when financial investments are at stake, the
Sensitivity Analysis (S.A.) can be a valuable resource for the investigation of
potential changes and errors in artificial scenarios. S.A. can aid managers and
decision makers to further understand the impacts of each available choice.
Thus, Horngren, et al. (2004); Carneiro, et al. (2004) define the Sensitivity Analysis as a
simulation technique that examines how much results will change if the initial
forecast data are not obtained or if any fundamental assumption is changed. Complementarily, Sensitivity Analysis
consists into a range of exploratory steps that aim to observe the behavior of
variables by the alterations of a model. For example, Pannell (1997) defines
that there are various possible ways to explore changes by varying:
i)
The contribution of an activity to the objective;
ii)
The objective (e.g. minimize risk of failure instead
of maximizing profit);
iii)
A constraint limit (e.g. the maximum availability of a
resource);
iv)
The number of constraints (e.g. add or remove a
constraint designed to express;
v)
Personal preferences of the decision maker for or
against a particular activity),
vi)
The number of activities (e.g. add or remove an
activity), or
vii)
Technical parameters of a model.
Additionally,
the sensitivity analysis studies the effects of a certain variation of a given
input on income results. It can reflect on the increase or decrease in revenues
or expenses (MATSUHITA, et al., 2006).
For the same authors, the sensitivity analysis can be successful used on
various situations and planning practices such as: i) Manufacturing of new products, since it can represent changes on
the set of variables of a problem; ii)
Impact Assessment related to the use of new technologies or new manufacturing
processes; iii) Estimation of
changes caused by the use of new resources or new production systems.
The chosen approach in
this study was to vary the value of the numerical parameter of variable costs
through several levels in order to verify if the independent production system
would be more profitable than the integrated system even if the costs were
higher.
2.
METHODOLOGY GUIDELINES
This
section aims to present the methods and approaches applied on this research.
According to the criteria used by Silva and Menezes (2005) and Kumar (2010),
this work is based on the applied research settings, which focus on using
practical solutions for the problem case of one specific poultry producer. Then, the design for this research aims to
investigate the profitability in a different scenario, where the independent modus operandi at poultry farms could be
explored in comparison to the integrated system of production. Thus, this work is also based on
quantitative models in order to subsidize information analysis under the optics
of rational knowledge.
Likewise,
this research addresses the idealization of a model capable of maximize the
profit on poultry supply chain. Wherefore, according to Miguel, et al. (2010),
aligns to the axiomatic type of research. In addition, this work sets a Case
Study which is defined by Richardson (1999); Yin (2009) and Miguel, et al.
(2010) as an empirical work that investigates a certain phenomenon within the
context of the current reality, through detailed analysis of one or more
cases.
In
this article, the phenomenon investigated is the profitability in two decision
scenarios for poultry business: i) the integrated system of production; ii) the
independent system of production. The conceptual model of this research is
presented at Figure 1: Case
Study Conceptual model.
|
Figure 2: Case Study Conceptual model. Source: Adapted from George and Bennett
(2005) and Yin (2003) |
The
stages and proceedings to collect data and analyze results were performed
according to the Variable Cost Management approach of Leone (2000), Martins
(2010) and Bruni and Fama (2009). Thereby, for rather real scenario and
simulated scenario, there were calculated:
i)
Income Statements;
ii)
Total contribution margins;
iii)
Contribution margin per unit;
iv)
Even Break Point;
v)
Sensitivity analysis.
On
section 3,
the obtained results are presented and discussed
3.
RESEARCH RESULTS
After
presenting the theoretical framework used on this research, there are presented
in this sections the Case Study of integrated system and independent, which
contains in addition to the enterprise contextualization: i)
Application of variable costing the integrated system; ii) application of variable costing system independent system
(simulated scenario); iii)
calculation of contribution margin, even break point balance and margin of
safety; iv) sensitivity analysis v) recommendations.
3.1. Company’s Framework
Since 1986, the
studied company works with fattening and sale of live chickens, which
configures its fitting to the segment of the poultry industry. The farms plant
is located in the municipality of Benfica (State of Para, Brazil), where this
company commercializes mostly live chicken. Beyond chicken sales, the farmer
also sells organic manure, a byproduct of poultry production.
It stands about 30 kilometers from the state capital which represents an
advantage to the company and yet to the client because, cause it is close to
major retail outlets and abattoirs – which implies into economic advantages
during products distribution.
The company operates according to
integrated production system, with an integrative company that provides the
one-day-born birds, food and technical support during the fattening period.
The
integrative company also pays expenses related outbound logistics, as delivery
of one-day old chicks and delivery of feed on farms, the integrator is also
responsible for logistics distribution the final product (chicken with an
average weight of 2.5 kg). This context is important because, as the focus of
this study is the poultry production itself (fattening and sale), the main
variable costs considered into this case are related to electricity, manpower.
The other costs, like feed, poultry vaccine and young birds, were considered as
fixed costs.
At
the beginning, the company counts with seven employees. During its early years
during the decade of 1980, this enterprise possessed a shed of 132 m2
and capacity for fatting one thousand birds per batch. From 2011, this company
started to work with five aviaries, with a capacity for 27,000 birds per each
batch. Its production plant is divided
into two units: a) farm 1 consisting of three aviaries with a total capacity of
171,000 birds per batch, and b) farm 2, which has two aviaries and total
capacity to 114,000.
After
more than 2 decades operating under the integrated system, this poultry company
started to question of the independent system would represent a more profitable
business scenario in a short term horizon.
In order to answer to that question, indicators of variable costing
method were measured for both situations so that the real context could be
compared to a different scenario simulated. As a way to acquire the results of
interest to this study, there were taken the steps illustrated at Figure 3:
Research Application.
|
Figure 3: Research
Application. Source:
Adapted from Ferreira and Wanzeler (2011) |
In
the next sections, there will be presented details of the research applications
as well as preliminary results will be discussed.
3.2.
Application of variable costing on integrated system
In
order to apply the variable costing method appropriately it was necessary to
perform data collecting during 13 months. After that, classification (Table 2) of
expenses was conducted based on the criteria of EMBRAPA Methodology for the
Calculation of Cost of Production of Broiler - Version 2, Miele, et al. (2010).
Table 2:
expenses classification
|
Expenses |
Classification |
Comments |
|
Electricity |
Variable Cost |
These expenditures have changed their
total value in the quantity produced. |
|
Manpower |
Variable Cost |
|
|
Firewood |
Variable Cost |
|
|
Sawdust |
Variable Cost |
|
|
General Accommodations |
Variable Cost |
|
|
Maintenance |
Variable Cost |
|
|
Depreciation on plant and machinery |
Fixed Cost |
There are no changes to the amount
produced. |
After
classification of the expenses it became possible to calculate the variable
costs per unit. First, it was obtained the sum of total spending on each item
during the period from July 2010 to July/2011.
Next, this sum was divided by the total number of birds produced in the
same period and then the result per bird was obtained (R$ / bird). Finally,
this last result was divided by total kg produced during the same period,
obtaining the variable cost per kilo at each farm.
As
it was necessary to know the production volumes and weight per month at each
farm, this information is presented at table 3.
Table 3: Production volumes and production weight
|
Lots |
Birds Production (Birds) |
Production weight (Kg) |
||
|
Farm 1 |
Farm 2 |
Farm 1 |
Farm 2 |
|
|
Lot 1 |
66.445 |
43.400 |
174.086 |
120.348 |
|
Lot 2 |
67.763 |
43.869 |
169.950 |
109.014 |
|
Lot 3 |
65.914 |
43.144 |
177.770 |
114.245 |
|
Lot 4 |
60.043 |
42.700 |
148.066 |
103.889 |
|
Lot 5 |
73.839 |
48.248 |
177.657 |
108.654 |
|
Lot 6 |
73.829 |
49.398 |
187.009 |
134.511 |
|
Subtotal |
407.833 |
270.759 |
1.034.537 |
690.662 |
|
TOTAL |
678.592 |
1.725.199 |
||
If
studied separately, there could found differences in consumption of inputs
between the studied farms, which permitted to observe that each farm generated
different costs to produce 1 kg of chicken, although the amount produced in
quantity and number of birds remained constant.
However, for this study, the target information is the average Costs/kg.
Results of the Costs calculations are presented on the next table.
Table 4: Costs Calculation for Integrated System
|
Costs Calculation |
Amount |
Per Birds |
Per Kg |
|
Variable
Costs (VC) |
R$
170.943,45 |
R$
0,25 |
R$
0,10 |
|
(+)
Direct Manpower |
R$
49.209,14 |
R$
0,07 |
R$
0,03 |
|
(+)
Electricity |
R$
59.016,28 |
R$
0,09 |
R$
0,03 |
|
(+)General Accommodations |
R$
3.771,82 |
R$
0,01 |
R$
0,00 |
|
(+)Maintenance |
R$
11.246,21 |
R$
0,02 |
R$
0,01 |
|
(+)Firewood |
R$
5.700,00 |
R$
0,01 |
R$
0,00 |
|
(+)
Sawdust |
R$
42.000,00 |
R$
0,06 |
R$
0,02 |
|
FIXED
COST (FC) |
R$
83.414,32 |
- |
- |
|
(+)Depreciation on plant |
R$
45.106,62 |
- |
- |
|
(+)
Depreciation on machinery |
R$
18.043,74 |
- |
- |
|
(+)
Indirect Manpower |
R$
20.263,96 |
- |
- |
|
TOTAL
COST (VC +FC) |
R$
254.357,76 |
R$
0,48 |
R$ 0,19 |
The
next step was to build the Income Statement through which it could be
concluded that on the integrated
system gross profit R$ 0,22/bird or R$ 0,09/kg. Net profits are R$ 0,10/bird R$ 0,04/kg. Income Statement calculation for
this production system is present on the table 5.
Table 5: Income Statement for Integrated System
|
Income
calculation |
AMOUNT |
PER
BIRD |
PER
KG |
|
GROSS
INCOME |
R$
323.155,26 |
- |
- |
|
(
- ) TAXES |
R$
12,00 |
- |
- |
|
NET
INCOME |
R$
323.143,26 |
R$
0,48 |
R$
0,19 |
|
(
- ) VARIABLE COSTS |
R$
170.943,45 |
R$
0,25 |
R$
0,10 |
|
GROSS
PROFIT (CONTRIBUTION MARGIN) |
R$
152.199,81 |
R$
0,22 |
R$
0,09 |
|
(
- ) FIXED COSTS + EXPENSES |
R$
83.414,32 |
- |
- |
|
NET
PROFIT |
R$
68.785,50 |
R$
0,10 |
R$
0,04 |
Once
calculated the incomes of the enterprise on integrated system, the next step
was to construct a simulated scenario of Independent system in order to not
only to analyze possibilities, but also to make possible a further incomes
comparison for subsidizing decision.
There
are presented on section 3.3 the calculations for the simulated profitability at Independent
system, according to variable costing procedures.
3.3.
Application of variable costing on Independent System
For
the application of variable costing method into the independent system of
poultry production first it was necessary to identify the new expenses which
that naturally incur to the independent producer. For example, the independent producer would
produce bird feed, besides to operate the logistics to buy one-day old birds
for fattening.
The
operational management of machinery maintenance and its depreciation would be
an additional responsibility for the farmer, as well as the additional expenses
related to the depreciation at new ration fabric plant – this would also incur
into new expense on electricity to guarantee the operation of this new plant.
Note that this study did not consider financial disbursements for the
construction of the ration factory, as this configures not a production cost
but a long term investment.
As
the calculation of results at independent system was performed on the same
temporal series used for section 1.2, another point to be remarked it that the
total expenses with sawdust, firewood and various accommodations were the same
calculated to the integrated system. Yet, since to perform the comparison
between the two systems, the quantity produced (table 3 – section 4.2) were the
same for both cases.
Although
much information to simulate this independent scenario was available from the
previously presented on section 1.1 and
3.2; it
was necessary to define new expenses which were innate from Independent System.
For example, to illustrate one of the many procedures taken to perform this
stage of the study, calculate new costs which would generated to produce birds
ration at the farms an auxiliary study was performed in order to better
understand Birds ration formulation which had to consider the animal nutrition
needs during all the different stages of fatting (13 months). Only after that,
it would be possible to precede the costs rising.
According
to FAEPA - North Unity (2011), there are 4 stages on the fatting process and
for each stage there must be used a different ration composition, aiming to
maximize the gain of weight. The table 6
presents the fatting stages and the ration quantities per bird to gain the
appropriated weight.
Table 6: Required amount of feed per bird.
|
Stage |
Pre-initial |
Initial |
Growth |
Finishing |
Total |
|
Amount (Kg) |
0,3 |
1 |
2,2 |
2,5 |
5 |
|
Source:
FAEPA S.A (2011) |
|||||
After
that, the feed formulations were calculated for 723.100 broiled birds at the
company farms during the realization of this study. The next step was to
perform ingredients average quotation for each ingredient of the ration. Summary
results can be observed table 7.
Table 7- quotation of ingredients per feed type
|
Ingredients |
Total |
Pre-Initial |
Initial |
Growth |
Finishing |
|
Corn
(R$) |
1.269.770,69 |
61.499,66 |
237.408,19 |
557.175,16 |
413.687,68 |
|
Soybean
meal (R$) |
835.809,60 |
75.556,72 |
198.490,95 |
366.524,93 |
195.237,00 |
|
Soybean
oil (R$) |
205.533,94 |
9.892,01 |
32.973,36 |
96.721,86 |
65.946,72 |
|
Meat and bone meal (R$) |
98.095,75 |
6.074,04 |
19.740,63 |
43.429,39 |
28.851,69 |
|
Limestone
(R$) |
9.596,98 |
585,71 |
1.887,29 |
4.390,66 |
2.733,32 |
|
Salt
(R$) |
3.771,33 |
292,86 |
976,19 |
1.574,91 |
927,38 |
|
Sodium
bicarbonate (R$) |
21.114,52 |
867,72 |
3.326,26 |
9.544,92 |
7.375,62 |
|
Premix
(pre-starter) (R$) |
25.380,81 |
25.380,81 |
- |
- |
- |
|
Premix
(initial) (R$) |
79.541,00 |
- |
79.541,00 |
- |
- |
|
Premix
(growth) (R$) |
164.331,71 |
- |
- |
164.331,71 |
- |
|
Premix
(finishing) (R$) |
101.197,85 |
- |
- |
- |
101.197,85 |
|
Total (R$) |
2.814.144,17 |
180.149,52 |
574.343,87 |
1.243.693,53 |
815.957,25 |
Source: Ferreira and Wanzeler (2011)
After
that, calculation of unitary costs of feed was possible to be performed. Therefore,
results obtained were: R$ 4,15 /bird R$ 1,63/bird-kg. Similar proceedings were adopted to calculate
other costs that were not contemplated at section 3.2.
Thus, first results obtained through variable costing method on the simulated
independent system of production can be observed on table 8 – Variable Costs
for Independent System.
Table 8- Costs Calculation for independent System
|
Costs Calculation |
Amount |
Per
Bird |
Per
Kg |
||
|
Variable
Costs (VC) |
R$
3.871.571,40 |
R$
5,71 |
R$
2,24 |
||
|
(+)
Ration (bird feed) |
R$
2.814.144,17 |
R$
4,15 |
R$
1,63 |
||
|
(+)
one-day old bird |
R$
686.945,00 |
R$
1,01 |
R$
0,40 |
||
|
(+)
Direct Manpower |
R$
69.473,10 |
R$
0,10 |
R$
0,04 |
||
|
(+)
Electricity |
R$
73.612,17 |
R$
0,11 |
R$
0,04 |
||
|
(+)General Accommodations |
R$
3.771,82 |
R$
0,01 |
R$
0,00 |
||
|
(+)Maintenance |
R$
175.925,14 |
R$
0,26 |
R$
0,10 |
||
|
(+)Firewood |
R$
5.700,00 |
R$
0,01 |
R$
0,00 |
||
|
(+)
Sawdust |
R$
42.000,00 |
R$
0,06 |
R$
0,02 |
||
|
FIXED
COST (FC) |
R$
72.339,36 |
- |
- |
||
|
(+)Depreciation on plant |
R$
54.295,62 |
- |
- |
||
|
(+)
Depreciation on machinery |
R$
18.043,74 |
- |
- |
||
|
TOTAL
COST (VC +FC) |
R$
3.943.910,76 |
R$
5,81 |
R$
2,29 |
||
Source: Ferreira and
Wanzeler (2011)
From
Table 8 it is possible to observe that unitary operational costs both per bird
and per produced kg are much greater than the costs observed for integrated
system (section 3.2). While the former costs $0, 48 per bird the latter costs 12 times more
($5,81). As costs have increased so
much, for the independent scenario to be interesting to the farmer, it is
necessary that the net profit be much higher than the one obtained on the
integrated model, which is tested below (Table
9).
Table 9- Income Statement for Integrated System
|
Income
calculation |
AMOUNT |
PER
BIRD |
PER
KG |
|
Gross
income |
R$
4.398.128,53 |
- |
- |
|
(
- ) Taxes |
R$
12,00 |
- |
- |
|
Net
income |
R$
4.398.116,53 |
R$
6,48 |
R$
2,55 |
|
(
- ) Variable costs |
R$
3.871.571,40 |
R$
5,71 |
R$
2,24 |
|
Gross
profit (contribution margin) |
R$
526.545,13 |
R$
0,78 |
R$
0,31 |
|
(
- ) Fixed costs + expenses |
R$
72.339,36 |
- |
- |
|
Net
profit |
R$
454.205,77 |
R$
0,67 |
R$
0,26 |
After the formation of
Income Statement, there were estimated a gross profit per bird of R$ 0.78 and
R$ 0.31/kg. Estimated net income is $ 0.67/bird and R$0.26/kg. Thus, it was
verified that the net profit per bird at the independent system is 6,7 times
greater than in the integrated system.
As
a preliminary conclusion for this particular study, it can be inferred that
although the expenses increases at independent system, net profit at this
system is more attractive than the net profit of integrated system.
3.4. Calculation of
variable costing indicators
Variable
Costing indicators provide a broader view on results of each production system,
as it allows extending the analysis beyond the net profit earned at each
production system.
Table 10-Indicator Calculation
|
Indicator |
Integrated Production System |
Independent Production System |
||
|
Amount |
Per bird |
Amount |
Per bird |
|
|
Contribution Margin (R$) |
152.199,81 |
0,22 |
526.545,13 |
0,78 |
|
Even Break Point (unit) |
371.908 |
- |
93.228 |
- |
|
Even Break Point (R$) |
177.107,81 |
- |
604.236,52 |
- |
|
Safety Margin
(unit) |
306.684 |
- |
585.364 |
- |
|
Safety Margin
(R$) |
146.047,45 |
- |
3.793.892,01 |
- |
|
Safety Margin
(%) |
45,19% |
- |
86,26% |
- |
Results were
surprising, as according to these indicators, independent production system has
shown more attractive rates, although majority of scientific and technical
studies abroad Brazil has proven the opposite. For this reason, a further
analysis must be performed: the sensitivity analysis.
3.5. Sensitivity Analysis
As
effective decision depends on the accuracy of results calculation, sensitivity
analysis was used to measure the sensitivity to the variation of the most
representative Variable costs of the Company, which had great impact on both
gross and net profit. For example, at
Independent system, one of the most impacting costs are the ones related to birds
feed production and new birds
acquisition (e.g. Ration Corn represents 72,69% of variable costs, and one-day
old birds represents 17,74% of them). Final results calculation of sensitivity
analysis can be observed on table 11.
Table 11- Sensitivity Analysis Scenarios
|
Costs Calculation |
Initial |
5% Variation |
10% Variation |
15% Variation |
20% Variation |
|
Variable Costs (R$) |
3.871.571,40 |
3.935.059,93 |
3.998.548,47 |
4.062.037,00 |
4.125.525,54 |
|
Bird Feed (R$) |
2.814.144,17 |
2.877.632,70 |
2.941.121,23 |
3.004.609,77 |
3.068.098,30 |
|
Corn Cost R$/Kg |
0,54 |
0,57 |
0,59 |
0,62 |
0,65 |
|
Corn Cost (R$) |
1.269.770,69 |
1.333.259,22 |
1.396.747,76 |
1.460.236,29 |
1.523.724,82 |
|
Contribution Margin (R$) |
526.557,13 |
463.068,60 |
399.580,06 |
336.091,53 |
272.603,00 |
|
Contribution Margin (R$/Kg) |
0,31 |
0,27 |
0,23 |
0,19 |
0,16 |
|
Contribution Margin (R$/bird) |
0,78 |
0,68 |
0,59 |
0,50 |
0,40 |
After these results, it
was observed that contribution margin remains positive even with the simulated
increases on the price of corn. That means that for this particular case, the
independent system presents superior profits than the integrated system even if
the cost with corn raises 20%.
4.
CONCLUSIONS AND RECOMMENDATIONS
A
critical observation of the dynamics of integrated system shows that it is
advantageous in many ways as the integrator company stands responsible for
providing all necessary inputs and also for the supplements to the Poultry
Production, but as in counterpart the producer will be unable to reach
different options of suppliers as well as it will be forbidden to freely pursue
new buyers. The results obtained through this study show that the net profit
per bird (R$0, 10) and per produced Kg(R$ 0, 04) is not as much attractive as
the net profits simulated for the Independent System (R$ 0, 67/ bird and R$ 0,
26/kg). In fact, after performing the sensitivity analysis this second system
remains more profitable even of if variable costs increase 20%.
Therefore,
if the decision to considered only criteria of minimizing costs and maximizing
of profits per bird, the production system recommended would be the independent
one. However, there are other aspects to be considered on this study.
This
work accomplished its objective to make a comparative study of profitability,
between two different systems of poultry production. However, it is important
to point out that it is necessary to conduct a further study on investment
analysis to support the decision of expanding the farms and migrating to the
independent systems.
Although
the accuracy of results they can only partially support decision of this
magnitude. Furthermore there are qualitative management aspects to be
considered beyond financial indicators which are the willingness of the
producer to assume the management of supplies and if this farmer possesses the
required expertise to operate his under the rules of an independent strategy of
cost leadership.
REFERENCES
APINCO.
Associação Brasileira de Produtores de Pinto de corte. (2013). Estatísticas 2013: em foco. Campinas:
São Paulo.
ARAUJO,
G. C.; et al. (2008) Cadeia produtiva da avicultura de corte : avaliação da
apropriação de valor bruto nas transações econômicas dos agentes envolvidos
production chain of poultry cutting : assessing the ownership of the gross
value of transactions of economic agents involved. Gestão &
Regionalidade, v. 24, n. 72, p. 6–16.
BRUNI,
A. L.; FAMÁ, R. (2009) Gestão de custos e formação de preços: com aplicações na calculadora HP 12C e
Excel. 5 ed. São Paulo: Atlas.
CARVALHO,
A. DE; LLANILLO, R. F. (2004) Frango de corte. Londrina, Instituto Agronômico do Paraná (IAPAR). Available: <http://www.iapar.br>
COLAUTO, R. D.; BEUREN, I. M. (2005) Cost-targeting as
support for decision making in developing new products: a study in the
furniture industry. Revista Produção Online, v.
5, n. XI, p. 1–18.
FEAPA.
Metodologia da Pesquisa e Elaboração de Dissertação. Belem: [s.n.]. Available:
<http://www.sistemafaep.org.br/Estatico/Cotacoes>.
FERREIRA, L. M. L.; WANZELER, M. S. (2011) Cost
Management in Agribusiness:
Analysis of the Possibility of Migration to the Independent Production System
in a Poultry Producer. [s.l.] Universidade do Estado do Para.
HORNGREN, C. T.; DATAR, S. M.; FOSTER, G. (2003) Cost
Accounting: A Managerial Emphasis.
11. ed. London: Pearson.
KAPLAN, R. S.; NORTON, D. P. (1996) The Balanced
Scorecard: Translating Strategy into Action. 1 ed. Boston: Harvard Business
Review Press.
KUMAR, R. (2010) Research Methodology a step by step guide for
beginners. 3 ed. Thousand Oaks: Sage Pubns Ltd.
LEONE,
G. S. G. (2000) Custos:
Planejamento, Implantação e Controle. 3rd. ed. São Paulo: Atlas.
MARTINS,
E. (2010) Contabilidade de Custos. 10 ed. São Paulo: Atlas.
MATSUSHITA1,
M. S.; HOEFLICH, V. A.; PARCHEN, C. A. P. (2006) Uso de planilha eletrônica para analise de sensibilidade das principais
atividades comerciais agropecuárias e florestais no município de Palmeira-Encontro
de Economia Paranaense. Anais. Curitiba: Universidade Federal do Paraná.
Available: <http://www.ecopar.ufpr.br/artigos/a4_076.pdf>
MIELE,
M. et al. (2010) Metodologia para o Cálculo do Custo de Produção de Frango
de Corte – Versão 2. Concordia.
Embrapa. Available: < www.cnpsa.embrapa.br>
MIGUEL,
P. A. (COORD.) (2009) Metodologia de Pesquisa em Engenharia de Produção e
Gestão de Operações. 1 ed. Rio de Janeiro:
Elsevier.
PANNELL, D. (1997) Sensitivity analysis of normative
economic models: theoretical framework and practical strategies. Agricultural
Economics, v. 16, n. 2, p. 139–152.
RICHARDSON,
R. J. (1999) Pesquisa social:
Métodos e Técnicas. 3rd. ed. São Paulo: Atlas.
SILVA,
E. L. DA; MENEZES, E. M. (2005) Metodologia
da Pesquisa e Elaboração de Dissertação, Florianópolis, UFSC.
Available: <http://tccbiblio.paginas.ufsc.br >
WERNKE,
R.; LEMBECK, M.; HEIDEMANN, J. S. (2002) Análise Custo/Volume/Lucro aplicada à suinocultura: estudo de caso em
pequena propriedade rural (A. Robles Junior, Ed.) CONGRESSO BRASILEIRO
DE CUSTOS. Anais. São Paulo: Associação Brasileira de Custos, 2002.
Available: <http://www.abcustos.org.br/congresso>
YIN, R. K. (2009) Case Study Research: Design and Methods. 4 ed. London:
Sage.