DECISION SUPPORT SYSTEM BASED IN AHP METHOD TO SELECTION
VENDORS OF CLINICAL LABORATORYS INPUTS
André Andrade Longaray
Federal University of Rio Grande -
Brazil, Brazil
E-mail: longaray@yahoo.com.br
Anderson Picua Gonçalves
Federal University of Rio Grande -
Brazil, Brazil
E-mail: anderpigo@gmail.com
Vilmar Gonçalves Tondolo
Federal University of Pelotas - UFPEL, Brazil
E-mail: vtondolo@gmail.com
Rosana Tondolo
Federal University of Pelotas - UFPEL, Brazil
E-mail: rosanatondolo@gmail.com
Catia Maria dos Santos Machado
Federal University of Rio Grande -
FURG, Brazil
E-mail: catiamachado.furg@gmail.com
Submission: 11/01/2018
Revision: 11/06/2018
Accept: 12/14/2018
ABSTRACT
In a
competitive marketing scenario, the purchasing area contributes significantly
to the achievement of organizational goals. Its mission is to identify the
competitive needs of products and services, becoming responsible for the timely
delivery, costs optimization and quality. Within shopping, a correct selection
of vendors is important for this to happen. From this perspective, the present
study aims to develop a model that assists in the vendors’ selection process.
In order to achieve this goal, we conduct case study in a clinical analysis
laboratory located in the city of Rio Grande, where the AHP (Analytic Hierarchy Process) was used
as an intervention tool. The development process consisted in three stages. The
first one aimed at structuring the model, in which the hierarchy of criteria
was defined. In the second step, the judgments were carried out and the
relative weights for each criterion and subcriterion
were calculated. Finally, the third step aimed at applying the model developed
in a purchasing process. The model was tested in a selection process that
involved the evaluation of three vendors of a laboratorial input, in order to
identify which one met the demands of the organization. The result obtained
with its use was considered satisfactory, this way, the model was approved by
the manager who participated in the structuring process of the AHP hierarchy.
Keywords: AHP, vendors selection, clinical
laboratory
1. INTRODUCTION
Supply logistics aims to make available, in a dynamic
and integrated way, the material resources, equipment and information that
contribute to the attainment of the goals of an organization (BALLOU, 2001).
Insert in this scenario, the purchasing area plays a fundamental role in
achieving the company's objectives, as its mission is to understand the
competitive needs of products and services, becoming responsible for the timely
delivery, costs, quality and other elements in the operations strategy
(COLETTI; CASTALLANELLI; DIDONET, 2002). Alignment between strategy and
purchasing management function is central to company’s performance
(RODRÍGUEZ-ESCOBAR; GONZÁLEZ-BENITO, 2017).
In order to ensure that business processes occur
efficiently, the tasks of identifying the best vendors for a new product or
service are essential (GUARANIERI, 2015). The proper choice of a vendor can
produce positive results in the supply system, while an inappropriate choice
will certainly bring problems not only to a particular area of the company
but also to other functions involved in this decision, directly impacting the
company's profitability. The inappropriate selection of vendors may result to
the strategic purposes of the organizations in the future need of replacement,
which implies costs for the organization (BUSTAMENTE,;UARTE; ALMEIDA, 2010).
Regarding supply chain as a role, vendors are one of the critical keys aspects
of company’s performance (PARK; OK; HA, 2018).
In this sense, the search for tools that facilitate
the decision making process has become frequent. Considering the nature that
involves multiple criteria in the selection of vendors, it is necessary to
include an approach to aggregate them adequately, and it is important to
emphasize that there are several methods used for this purpose. Their choice
basically depends on the decision objectives, the types of criteria to be used
and the decision maker's rationality (GUARANIERI, 2015).
The problem of vendors selection has been widely
discussed in the Brazilian scientific literature (TRAMARICO et al., 2012),
because the supplier evaluation and selection process depends on several
factors. The existing studies on the subject present several methodologies and
decision support criteria that can be considered in the evaluation and
selection of companies that supply the most varied products and services.
In this context, a systematic literature review was
carried out using the bibliometry technique, with
which a sample of 85 articles were collected, from the online databases
, Scielo and Academic Google. With the analysis of
these 85 articles, it was possible to identify what has been published
regarding vendors selection, as well as on multicriteria
decision support methods. This study also made it possible to identify research
gaps regarding the application of the multicriteria
decision support model in several areas, such as selection of vendors of
butchery equipment, uniforms, construction materials, and clinical laboratory
inputs. Base on that preliminary study emerged the following research question:
How to develop a model that assists in the vendors’ selection process to the
Clinical Analysis context?
From this perspective, the present study aims to
develop a model that assists in the vendors’ selection process. In order to
achieve this goal, we conducted a qualitative and quantitative case study using
interviews and questionnaires as data collection instruments. The multicriteria AHP method was the main procedure of data
analysis. Our study was conducted in a
laboratory located in the city of Rio Grande, which is small in size, with 17
employees and serves about 3000 clients per month.
This article is divided into six sections. Having
established the introduction, section 2 presents an overview of the problem of
vendor’s selection. Section 3 discusses the AHP, which is the multicriteria method used in the study. Section 4 presents
the methodology adopted in the study. Section 5 details the steps proceeded in
the case study. Finally, section 6 presents the concluding remarks,
highlighting some research opportunities on the topic.
2. SELECTION OF VENDORS
According to Gonçalo and Alencar (2011), vendors selection is a process in which
vendors are inspected, evaluated, and chosen to eventually become part of an
organization's supply chain .The purpose of this selection is to identify the
vendors with the greatest potential to meet the needs of the organization,
being this vendor adapted to the company's strategy. The growing impact of the
vendor on the performance of organizations has reinforced the need to hire
well-qualified companies who are committed with the contractor's goals. As a
consequence, organizations have become increasingly selective, incorporating
new criteria into the selection process and intensifying vendor's monitoring
(VIANA; ALENCAR, 2010).
According to Aires, Silveira
Neto, Salgado, Araujo and Colombo (2013), the current marketing environment is
competitive, characterized by low profit margins, high expectations for quality
products and services, and short deadlines. They also point out that for these
objectives to be achieved it is necessary for companies to consider all the
dimensions that involve their supply chain, from product delivery, quality and
flexibility, to response time, as they are forced to obtain advantage of every
opportunity to optimize their business processes.
The steady increase in vendor participation in the
overall performance of the organization is largely a consequence of the recent
emphasis on building partnership relationships. By focusing on their business
purpose, passing on all other non-core business activities to third parties,
organizations become more and more dependent on their vendors' performance. In this
context, it is important to promote the coordination of operations between
organizations, which requires the construction of close, reliable and
long-lasting relationships (VIANA; ALENCAR, 2012).
Gonçalo and Alencar (2011) point out that there is a trend in
maintaining long-term partnerships between companies and their vendors and the
use of less vendors and more reliable ones. The authors also show that the
criteria most considered by decision-makers to evaluate and select vendors no
longer have the price factor as the main criterion, according to the authors'
search, in order of occurrence: quality, delivery, price cost, manufacturing
capacity, service, management, technology, research and development, finance,
flexibility, reputation, relationship, risk and safety, and the environment.
Denicol and
Cassel (2013) argue that the buyer-vendor relationship based solely on cost is
no longer acceptable. They also say that increasing the importance of decisions
for vendor’s selection has led organizations to rethink their procurement and
evaluation strategies in order to reach the most appropriate vendor to meet
their demands. In this context, it is understood that the task of evaluating
and selecting vendors involves multiple criteria, which makes it necessary to
use methods to aggregate them adequately.
3. AHP MULTI-CRITERIA METHOD
Multicriteria
Decision Support (MCDS) approach to operational research is characterized as a
set of methods used to support organizations to make fitting decisions even
under the influence of numerous criteria (SOUZA; CARMO, 2015). According to Alencar, Almeida and Mota (2007),
multicriteria decision support modeling does not aim
to find a solution that is a single truth represented by the selected action,
but to support the decision process so that the satisfactory decision is made
according to the criteria of the decision-makers.
Analyzing the existing literature on the subject, we
observe the use of several multicriteria
methodologies. Among the methods cited in the analyzed articles are those of
the ELECTRE family (Elimination and Choice Translating Reality), as well
as those of the PROMETHEE family (Preference Ranking Method for Enrichment
Evaluation), as well as methods such as AHP (Analytic Hierarchy Process),
ANP (Analytic Network Process), and TOPSIS (Technique for Order Preference
by Similarity to Ideal Solution) (LONGARAY; BUCCO, 2014).
Among these methods, AHP stands out because it has wide applicability, robustness and flexibility (LONGARAY;
BUCCO, 2014; LONGARAY; ENSSLIN, 2014). Thus, the use of this method is justified, since the
vendors selection process, which is the subject of this study, is an example of
a complex decision, since it takes into account several criteria, which makes
up the relationship between customers and their vendors.
The Analytic
Hierarchy Process (AHP), proposed by Saaty
(2008), is a comparison of pairs, methodology that results in the breaking of a
complex problem and then combining the solutions. It has been widely recognized
that AHP analysis is one of the best methodologies to prioritize various
indicators. In addition, the AHP approach needs only a small number of
respondents with experience and knowledge (COSTA; RAMOS, 2015).
The basic principle of the AHP method lies in the
analysis of several alternatives of different criteria (COSTA; RAMOS, 2015).
Thus, the AHP model is constructed in the form of a descending hierarchical
structure, from a global objective to criteria, subcriteria
and alternatives, at successive levels (SAATY, 2008 ). As can be seen in figure
1, the overall objective is put on the first level, which is decomposed into
secondary objectives, and these are succeeded by decision alternatives, in a
number of levels and criteria that represent the problem as completely as
possible without which, however, implies the loss of sensitivity to changes in
the elements of the model (LONGARAY; BUCCO, 2014).
Figure 1: AHP Hierarch
Source: Adapted from Major and Belderrain
(2007)
From the construction of the hierarchical structure,
the stages of judgment and synthesis of the priorities of each criterion and subcritera are followed. The criteria judged is made by
means of the peer-to-peer comparison, using a scale developed by Saaty (2008). Such a scale is shown in Table 1.
Table 1: Saaty fundamental scale
|
Intensity of importance on an absolute scale |
Definition |
|
1 |
Equal importance |
|
3 |
Moderate importance of one over another |
|
5 |
Essential or strong importance |
|
7 |
Very strong importance |
|
9 |
Extreme Importance |
|
2, 4, 6, 8 |
Intermediate values between two adjacent judgments |
|
Reciprocal |
If activity i has one of the numbers
above when compared to activity j , then activity j has the
reciprocal value when compared to i |
Source: Adapted from Saaty (2008)
Based on comparative judgments, a positive array of
options is derived from these criteria. A structure is obtained later, with a
vector of priorities. The same procedure is applied for the alternatives
considered for each criterion. Then, the weights of the criteria are applied
for the considered alternatives and, finally, the corresponding totals for each
alternative are calculated (COSTA; RAMOS, 2015).
4. METHODOLOGY
This section describes the methodological procedures
adopted in the development of this work as to its purpose, its nature, the
source of data collection, the research logic, the methodological approach and
the intervention instrument used. In general, this research has a nature
practical driven.
As to its purpose, the present work is characterized
as an exploratory study. According to Triviños
(1995), the exploratory studies allow the researcher to increase his experience
around certain problems. Based on a hypothesis, the researcher deepens his
study within the limits of a specific reality, seeking antecedents and greater
knowledge. This perspective is in line with the general and specific objectives
of this research, aimed at the construction of a customized vendor selection
model for a clinical analysis laboratory, in order to identify, operationalize
and measure actions that meet the needs of the organization.
As far as its nature is concerned, this research can
be classified as a case study. According to Yin (2001), the application of the
case study enables the transformation of goals into actions that are feasible
and consistent with the reality in which the analyzed organization is inserted
.It takes into consideration, mainly the comprehension, as a whole, of the
investigated subject, leading to the emergence and discovery of relations that
otherwise would not be established.
The case described in this study was developed in a
laboratory of clinical analyzes, located in the city of Rio Grande - RS. In
this laboratory work 17 employees, distributed in the areas of management, billing,
reception, collection and analysis of samples. The company watches monthly on
average 3000 clients, those coming from the private service and from agreements
that the company maintains with public and private agencies.
The data source is characterized as being of primary
nature. The necessary information for the development of the study was obtained
from the laboratory manager, who participated in all stages of the process. In
this process, the data were obtained through semi-structured interviews and a
questionnaire.
As for the research logic, it can be inferred that it
is mixed. In the structuring phase, logic is inductive, because at this stage
in which the elements of evaluation are determined, it is not based on
principles but on facts resulting from observations and insertion in reality (ROESCH,
2010). Already in the evaluation stage, the logic is deductive, because, from
the constructed model, we seek to establish particular conclusions (TRIVIÑOS,
1995). In the recommendations phase, the logic is predominantly inductive,
since the analyzes are made from the understanding acquired throughout the
development of the model.
The methodological approach used in this research is
characterized as qualitative-quantitative (ROESCH, 2010). The study assumes the
qualitative profile in the structuring phase, based on an intervention process
that promotes reflection in search of identification, representation and
determination of the primary evaluation elements and their interrelationships
in the construction of ordinal scales. It can be characterized as quantitative
in the evaluation phase, when the construction of the multicriteria
mathematical model occurs, through the transformation of the ordinal scales
into cardinal scales, the determination of the compensation rates between
criteria and the identification of the performance profile of the actions.
The intervention instrument selected for the
development of the vendor’s selection model, and main procedure of analysis is
the multicriteria AHP method. The choice of this
methodology of support to the decision is due to its ability to provide
conditions for identification, operationalization and measurement of the
actions that represent the perception of the laboratory manager, as well as the
possibility of selecting a vendor that meets the demands of the company.
5. DEVELOPMENT OF THE MODEL
The AHP method is applied in three steps: structuring
the model, realizing the judgments and summarizing the priorities, and finally,
a purchasing process using the developed model.
5.1.
Structuring
the model
The unit of analysis of this research is a clinical
analysis laboratory, where varieties of products, such as chemical solutions,
laboratory glassware, plastic materials, stationery, etc
are purchased throughout a financial year.
Due to the amount of resources spent in the industry
and the great variation in the quality of the products supplied, it is
important that these vendors can be selected in an efficient manner, thus
enabling the supplied inputs to have quality, competitive prices, as well as
delivery guaranteed within the specified period and under the conditions
promised.
At the Company, decisions about vendor selection are
based on buyers' experience rather than on formally discussed and
pre-established criteria. It is proposed, therefore , the construction of the
AHP method, a rational and structured tool, capable of assisting the decision
maker in choosing the company that meets the needs of the laboratory.
To do so, initially, information was collected for the
process of structuring the AHP hierarchy, these were obtained through
interviews with the manager responsible for decision making in the
organization. Having in hand the necessary data, the hierarchy was constructed,
this one is presented in figure 2.
Figure 2: AHP Hierarchy
It is identified in Figure 2 that the first level is
intended for the general purpose of the model, in this case the selection of a
vendor. In the next level (Level 2), the criteria "Budget",
"Price", "Quality", "Delivery" and
"Post-sale" are located, which aim to contribute, each with its
relative weight, to its achievement. Finally, located at the third level, are
the quantifiable criteria, defined here as subcriteria,
that serve as a reference for directly evaluating decision alternatives.
With regard to the "Budget" criterion, the subcriterion "Quotation", which corresponds to
the effort required to obtain the information necessary to evaluate the vendor,
and the "Proposal Validity", which is intended to define a validity
period for the information obtained with the quotation.
In order to evaluate the "Price" criterion,
the subcriteria "Price" - unit price of the
product, "Discount on payment sighted" - discount percentage offered
by the vendor, if payment is made on the same day of delivery, "Discount
on large quantities " - percentage of discount offered by the supplier
when a significant quantity of products are purchased, and "Interest free
installments" - maximum number of monthly installments, without occurrence
of additional collection.
Next, it was selected, in order to evaluate the
"Quality" criterion, "Reliability" takes into account the
history of the product, if it has already presented a problem, the
"Brand" of the product, since certain brands imply loss of the
equipment warranty, and the "Product Validity" that determines the
time the laboratory will have to use the product, and is also decisive in the
case of a large amount of purchases.
As for the "Delivery" criterion, if
"Delivery time" has been defined - the time that the vendor took to
deliver the product after the order has been made, the "Conformity between
order and delivery" - what was delivered is in accordance with the
combined, and "Product Integrity", which evaluates whether any
product has been damaged or lost during delivery.
Lastly, there is the "After-Sale" criterion,
which was quantified by means of "Problem Solving Readiness", in
order to evaluate the vendor's response time in the event of an invoice or
ticket problem and product integrity during the delivery of the same.
Defining the criteria and subcriteria
in a hierarchical structure, the next step of the AHP method is started: the
execution of judgments and the calculation of relative weights.
5.2.
Carrying
out the judgments and calculating the relative weights
The execution of the judgments occurs through paired
comparisons between the criteria of the same level, thus allowing to evaluate
the relative preferences between each element of decision. The comparison is
made using the AHP Pair Comparison Scale, shown in Table 1.
In order to facilitate the process of judgment, a
questionnaire[i] was
constructed and presented to the interviewee. The following is an example of
the peer questionnaire for Level 2 and Level 3 components. In the first, all
the pairs of criteria are compared, and in the second, all pairs of subcriteria are compared, which in the case of the
following example is the “Budget”.
Level 2: Criteria
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How important is “budget” when compared to “price”? |
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Q1 |
9 |
8 |
7 |
6 |
5 |
4 |
3 |
2 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
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How important is “budget” when compared to “quality”? |
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Q2 |
9 |
8 |
7 |
6 |
5 |
4 |
3 |
2 |
1 |
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3 |
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9 |
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How important is the “budget” when compared
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Q3 |
9 |
8 |
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How important is the “budget” when
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Q4 |
9 |
8 |
7 |
6 |
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1 |
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How important is “price” when compared to “quality”? |
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Q5 |
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How important is “price” when compared to “delivery”? |
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Q6 |
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How important is “price” when compared to “after-sale”? |
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Q7 |
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How important is “quality” when compared to “delivery”? |
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Q8 |
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Q9 |
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Q10 |
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Level 3: Budget Components
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How important is “quotation” when compared to
“proposal validity”? |
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Q11 |
9 |
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To respond to the questionnaire the respondent received
the following guidelines: and the first attribute is more important than the
second, tick your answer in one of the boxes to the left of the option
"1", depending on your preference. If the second attribute is more
important than the first, choose your answer in the boxes to the right of
option "1".
After the comparisons were made and the preferences
defined, the values of this scale were introduced into an array, which has as
reference the generic reciprocal matrix shown in Figure 3.Thus, the results of
the paired comparisons of level 2 are described in Table 1.
A =
Figure 3: Generic reciprocal matrix
Source: Longaray and Bucco (2014)
Table 1: Results of paired comparisons of
level 2
|
CRITERION |
Budget |
Price |
Quality |
Delivery |
After-sales |
|
Budget |
1.00 |
0.13 |
0.13 |
0.50 |
1.00 |
|
Price |
8.00 |
1.00 |
1.00 |
5.00 |
6.00 |
|
Quality |
8.00 |
1.00 |
1.00 |
6.00 |
6.00 |
|
Delivery |
2.00 |
0.20 |
0.17 |
1.00 |
2.00 |
|
After-sales |
1.00 |
0.17 |
0.17 |
0.50 |
1.00 |
Source: Prepared
by the authors
As can
be seen in Table 2, the "Price" and "Quality" criteria have
strong or extremely preferential importance over the "Budget"
criterion, and so on. Following this line of reasoning, matched comparison
matrices for level 3 were constructed .These
are presented in Tables 2, 3, 4 and 5.
Table 2: Result of the
paired comparisons of the sub-criteria of the "Budget"
|
Subcriteria
of the Budget |
price |
Validity of the proposal |
|
price |
1.00 |
1.00 |
|
Validity
of the proposal |
1.00 |
1.00 |
Table 3: Results of the
paired comparisons of the sub-criteria of the "Price"
|
Subcriteria
of the Price |
Price |
Discount
on cash payment |
Discount
on large quantities |
Interest
free parcelling |
|
Price |
1.00 |
4.00 |
4.00 |
5.00 |
|
Discount
on cash payment |
0.25 |
1.00 |
1.00 |
6.00 |
|
Discount
on large quantities |
0.25 |
1.00 |
1.00 |
6.00 |
|
Interest
free parcelling |
0.20 |
0.17 |
0.17 |
1.00 |
Table 4: Results of the
paired comparisons of the sub-criteria of "Quality"
|
Subcriteria
of Quality |
Reliability |
Brand |
Product
validity |
|
Reliability |
1.00 |
3.00 |
4.00 |
|
Brand |
0.33 |
1.00 |
2.00 |
|
Product
validity |
0.25 |
0.50 |
1.00 |
Table 5: Result of the
matched comparisons of the sub-criteria of the "Delivery"
|
Subcriteria
of the Delivery |
Deadline |
Order-to-delivery
compliance |
Product
Integrity |
|
Deadline |
1.00 |
1.00 |
2.00 |
|
Order-to-delivery
compliance |
1.00 |
1.00 |
2.00 |
|
Product
Integrity |
0.50 |
0.50 |
1.00 |
It is
worth mentioning that because the criterion "After-sale" has only one
sub-criterion, there is no possibility of building a matrix. In this case the
"Alertness in the solution of problems" has all representative of the
criterion.
Constructed all matrices, the calculation of relative
weights was started, which could be conducted using Microsoft Excel .For
calculation purposes, three steps are suggested (SAATY, 2008; COSTA; RAMOS, 2015).
1.
The results of the paired comparisons are presented in
Tables 1, 2, 3, 4 and 5 to insert the data in Excel, where the construction of
matrices of binary comparisons is performed for each level of the hierarchical
structure.
2.
Summary of priorities:
2.1.
Add each column of the matrix;
2.2.
Divide each element of the matrix by the sum of the
corresponding column, obtaining a new standardized matrix;
2.3.
The average of each row of the standardized matrix
(sum and division by n variables considered) is calculated, obtaining
the column vector of "W" (relative weight).The sum of the vector must
be equal to 1;
3.
Matrix consistency check (MC):
3.1.
Multiply the sum of each column of the original matrix
(step 2.1) by the vector of "W" (step 2.3), obtaining a new vector
(measure of consistency);
3.2.
If the matrix is consistent, the s vectors
calculated in step 3.1 will have preference values equal to 1.
Tables 6 and 7 below present the matrix of level 2
with the criteria and a matrix of level 3, which is represented by the subcriteria of the "Budget". In them are
contained the results regarding relative weights and the measure of consistency
(MC) of each criterion and subcriterion.
Table 6: Components of Level 2
|
CRITERION |
Budget |
Price |
Quality |
Delivery |
After-sales |
W |
MC |
|
Budget |
0.0500 |
0.0502 |
0.0508 |
0.0385 |
0.0625 |
5.04% |
1,0079 |
|
Price |
0,4000 |
0,4013 |
0,4068 |
0.3846 |
0,3750 |
39.35% |
0.9806 |
|
Quality |
0,4000 |
0,4013 |
0,4068 |
0.4615 |
0,3750 |
40.89% |
1,0053 |
|
Delivery |
0.1000 |
0.0803 |
0.0678 |
0.0769 |
0.1250 |
9.00% |
1,1700 |
|
After-sales |
0.0500 |
0.0669 |
0.0678 |
0.0385 |
0.0625 |
5.71% |
0.9141 |
|
Sum |
1 |
1 |
1 |
1 |
1 |
100% |
|
Source: Prepared
by the authors
Table 7: Components of the "Budget"
|
Budget
Criteria |
price |
Validity
of the proposal |
W |
MC |
|
Price |
0.5000 |
0.5000 |
50.00% |
1 |
|
Validity
of the proposal |
0.5000 |
0.5000 |
50.00% |
1 |
|
Sum |
1 |
1 |
100% |
|
Source: Prepared
by the authors
After applying the same process to all matrices, we
were able to illustrate the final results using the original hierarchical
structure, as shown in Figure 4.
Figure 4: Percentage of relative
weight for criteria and subcriteria
Once all the calculations have been made, the
"Price" and the "Quality" are the most important criteria
in the whole process, representing 39.35% and 40.89%, respectively. It could
also be found that among the subcriteria of quality,
which is the most important, the "Reliability" of the product
represents 62.32% of the criterion.
5.3.
Purchase
Simulation
Taking possession of the synthesis of the model and
the decision structure, the simulation of the purchase of a laboratory input
was elaborated. This simulation was made with three vendors that currently
participate in the quotation processes carried out in the laboratory. The
evaluation process was based on the assignment of a grade in the scale of 1 to
5 for each subcriterion described in the hierarchical
structure. Tables 8, 9 and 10 present the scores attributed to each subcriterion for the three vendors evaluated.
Table 8: Assignment of the note to vendor A
|
Criterion |
Note |
Note |
|
1.1 |
4 |
You had to get in contact twice to get all the information you need. |
|
1.2 |
4 |
A proposal valid for 17 days was submitted. |
|
2.1 |
4 |
The unit price was R $ 750.50. |
|
2.2 |
2 |
Offered 3% discount for the cash payment. |
|
2.3 |
2 |
Offered 2% discount for purchase of 15 units or more. |
|
2.4 |
3 |
Portion up to 2X without interest charges. |
|
3.1 |
5 |
The product offered has no history of problems. |
|
3.2 |
4 |
The brand is generic, which causes you to lose the equipment warranty. |
|
3.3 |
3 |
The product is valid for 160 days. |
|
4.1 |
4 |
Delivery was made in 6 business days. |
|
4.2 |
4 |
The price reported in the invoice was not the same as the combined
price. |
|
4.3 |
5 |
No product has been damaged or lost. |
|
5.1 |
2 |
The correction of the invoice was carried out in 4 working days. |
Source: Prepared by the authors
Table 9: Assignment of the note to vendor B
|
Criterion |
Note |
Note |
|
1.1 |
4 |
You had to get in contact twice to get all the information you need. |
|
1.2 |
3 |
A proposal valid for 12 days was submitted. |
|
2.1 |
4 |
The unit price of the product was R $ 751.00. |
|
2.2 |
2 |
Offered 3% discount for the cash payment. |
|
2.3 |
2 |
Offered 3% discount for purchase of 15 units or more. |
|
2.4 |
3 |
Portion up to 3X without additional charge. |
|
3.1 |
4 |
The product has already presented a problem once, interrupting the
operation of the equipment for a period of 2 days. |
|
3.2 |
4 |
The product is generic, which results in the loss of the equipment
warranty. |
|
3.3 |
4 |
The product delivered is still valid for 218 days. |
|
4.1 |
5 |
Delivery was made in 3 business days. |
|
4.2 |
4 |
There was an error regarding the payment deadline. |
|
4.3 |
5 |
No product has been damaged or lost. |
|
5.1 |
5 |
Correction of the ticket made on the same day. |
Source: Prepared by the authors
Table 10: Assignment of the note to the vendor
C
|
Criterion |
Note |
Note |
|
1.1 |
4 |
You had to get in contact twice to get all the information you need. |
|
1.2 |
2 |
A proposal valid for 8 days was submitted. |
|
2.1 |
3 |
The unit price was R $ 770.00. |
|
2.2 |
2 |
Offered 3% discount for cash payment. |
|
2.3 |
3 |
Offered 5% discount for purchase of 15 units or more. |
|
2.4 |
5 |
Portion up to 5X without interest. |
|
3.1 |
5 |
The product has no history of problems. |
|
3.2 |
5 |
The product is original, as indicated by the manufacturer of the
equipment. |
|
3.3 |
4 |
The validity is 230 days. |
|
4.1 |
4 |
Delivery was made in 5 business days. |
|
4.2 |
5 |
There was no error as to the conformity between the order and
delivery. |
|
4.3 |
5 |
No product has been damaged or lost. |
|
5.1 |
5 |
There were no product or delivery issues, and the company also
expressed concern about the quality of the service when it called the lab to
see if everything happened as agreed. |
Source: Prepared by the authors
After evaluating the three suppliers, we performed the
calculations to obtain the weighted grade of each subcriterion
.The weighting is done using the relative weights of the criteria and subcriteria, and the note (N) that each vendor obtained in
the evaluation.The equations used to obtain the
grades are presented in Table 11.
Table 11: Equations for the calculation of the
weighted grade
|
Relative
weight of criteria |
Relative
weight of subcriteria |
Equation for the calculation of
the weighted grade (Np) |
|
W
(1) = 0.0504 |
W
(1.1) = 0.5000 W
(1.2) = 0.5000 |
|
|
W
(2) = 0.3935 |
W
(2.1) = 0.5408 W
(2.2) = 0.12 W
(2.3) = 0.120 W
(2.4) = 0.0568 |
|
|
W
(3) = 0.4089 |
W
(3.1) = 0.6232 W
(3.2) = 0.2395 W
(3.3) = 0.1373 |
|
|
W
(4) = 0.0900 |
W
(4.1) = 0.4000 W
(4.2) = 0.4000 W
(4.3) = 0.000 |
|
|
W
(5) = 0.0571 |
W
(5.1) = 1.0000 |
|
Source : Prepared by the authors
Table 12 presents the weighted note of the subcriteria for each of the three vendors evaluated.
Table 12: Weighted note of sub-criteria for
each vendor
|
Criterion |
Vendor A |
Vendor B |
Vendor C |
|
1.1 |
0.1008 |
0.1008 |
0.1008 |
|
1.2 |
0.1008 |
0.0756 |
0.0504 |
|
2.1 |
0.8514 |
0.8514 |
0.6385 |
|
2.2 |
0,1583 |
0,1583 |
0,1583 |
|
2.3 |
0,1583 |
0,1583 |
0.2375 |
|
2.4 |
0.0671 |
0.0671 |
0.1118 |
|
3.1 |
1,2743 |
1.0194 |
1,2743 |
|
3.2 |
0.3917 |
0.3917 |
0,4897 |
|
3.3 |
0.164 |
0.2246 |
0.2246 |
|
4.1 |
0.1440 |
0.1800 |
0.1440 |
|
4.2 |
0.1440 |
0.1440 |
0.1800 |
|
4.3 |
0.0900 |
0.0900 |
0.0900 |
|
5.1 |
0,1143 |
0.286 |
0.286 |
|
TOTAL |
3,7634 |
3,7469 |
3,9855 |
Source: Prepared
by the authors
Table 13 presents the final ranking of the AHP
algorithm applied to the selection decision of the vendor of a laboratory
input, for the case under study, in descending order of punctuation.
Table 13: Final AHP Ranking
|
Provider |
Global Performance |
|
C |
3,9855 |
|
A |
3,7634 |
|
B |
3,7469 |
Source: Prepared
by the authors
In order to maximize the objective function, it is
verified that the vendor C should be the one selected, since in the evaluation
process it was the one that obtained the highest score, as it is represented by
Figure 5. In this sense, it can be concluded that it is the one that meets the
needs of the organization, when considering the criteria defined in this model.
Figure 5: Result of vendor´s selection
6. FINAL CONSIDERATIONS
The present study had as proposal the elaboration of a
decision support model for the selection of a vendor. For this process the AHP
method was chosen and it was built to meet the demands of a clinical analysis
laboratory. The process of constructing and validating the model was divided
into three main stages, with the participation of the laboratory manager,
responsible for making decisions in the organization.
The first task of the process was to define the
hierarchical structure of the criteria. In a process of constant exchange of
information with the decision maker, it was possible to identify the ordering
of aspects considered relevant to the decision situation.
In the second moment, a matching comparison between
the criteria and subcriteria was made, which allowed
to identify the relative preferences between each element considered important
in the decision making. Then the calculation was carried out referring to the
relative weights of each element of the hierarchy. This process sought to identify
the percentage of importance that each criterion represents in the process as a
whole. Still in this step, in order to know if the comparisons presented
coherence, a consistency analysis of matched comparison matrices
In the final phase of the study, having defined all
structure of the AHP model, a purchase simulation was elaborated with three
vendors (A, B and C) who participated in the quotation processes for the
purchase of a laboratory input. This simulation made it possible to interpret
that the criteria, "Price" weighing 39.35% and "Quality"
with 40.89%, are the factors that most influence the choice of vendors of the
inputs used in the laboratory.
After the simulation was performed, the results of the
model were presented to the decision maker, who considered it to be valid and
could be used to support the decision in the next purchasing processes to be
carried out by the company.
The overall objective of the work was entirely
reached, as a multicriteria model was constructed, in
order to assist the manager of a clinical analysis laboratory, in decision
making related to vendors selection.
Specific objectives were achieved during the
development of the study. At first, the criteria and subcriteria
were identified, being structured in a hierarchy. Then, through the paired
comparisons, the relative weights for each decision element were determined. In
the last stage of the work, the developed model was tested and presented to the
company manager, in order to know if the developed model is effective. This
research also contributes to the field of study of statistics, which is central
to many other fields.
Regarding the limitations of the work, there is the
high degree of commitment of the decision maker during the research and the
high demand for time due to the intervention level of the case study.
As a suggestion for future studies, the use of the AHP
method is indicated in the development of decision support models directed to
different problems, such as those of the research gaps cited in this study,
being them: selection of vendors of butchery equipment, uniforms and
Construction Materials. Another opportunity would be to develop the same model
in another laboratory of clinical analyzes, with the intention of comparing the
results, thus making it possible to identify the possible existence of
similarities between the two.
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