Application of the Kraljic Matrix in the Purchasing
Area of an Hospital Centre
Centro Hospitalar Universitário Lisboa Central Case Study
Andreia Sofia Frias Alhais
Department of Engineering and Management, Instituto Superior Técnico
Abstract
Over the years, the purchasing area has been assuming an important role in companies’ management
from all sectors of activity. In the specific case of the health sector, medicines purchasing area is
highly relevant considering the amounts involved, the impact on services’ quality and the huge variety
of products that are purchased. Thus, considering the complexity associated to the purchasing
processes, the main goal of this master’s dissertation is to develop a support model for the formulation
of differentiated purchasing strategies for different classes of medicines. For this, it was used the
Kraljic Portfolio Matrix (KPM), which classifies item classes according to two dimensions: the profit
impact and the supply risk, namely. In order to evaluate these dimensions, a set of independent
criteria was established which have been weighted in their respective dimension, using the AHP tool
(Analytic Hierarchy Process). As a case study, it was applied the methodology developed to medicines
in Centro Hospitalar Universitário Lisboa Central (CHULC).
Finally, the application of KPM to a Portuguese hospital centre contributed to increase the number of
applications of this matrix. The results of its application confirmed the KPM value in defining strategies
in the health sector, particularly of medicines and it allowed the elaboration of a set of
recommendations so that CHULC can improve the way they acquire medicines.
Keywords: Purchasing Portfolio, Kraljic Portfolio Matrix, Analytic Hierarchy Process, Health Sector
1. Introduction
In recent years, health sector has evolved, in
both public and private sectors, through the
implementation of a set of structural reforms,
the strengthening of the care network and a
process of modernization and digital
transformation (Ministério da Saúde, 2018). In
2018, total health expenditure (public and
private) represented about 9,1% of the Gross
Domestic Product (GDP) and the state spent
about 4,4% of GDP. These values show the
high economic importance of health sector in
Portugal.
Health care services are provided specially by
hospitals, which are organizations that offer a
wide range of patient care that require a wide
range of products and services from different
categories (Medeiros and Ferreira, 2013). Thus,
hospital procurement involves a large set of
financial resources and time, and carries risk,
especially in terms of storage, since most
handled products are fragile and may not be
defective when used. Additionally, given the high
quantity and variety of products and services
required to be purchased, not all should be
managed and purchased in the same way. For
Medeiros and Ferreira (2013), purchasing
portfolios could be an excellent tool to manage
hospital purchases strategically.
The most recognized and used purchasing
portfolio model was introduced by Kraljic (1983).
1
This model is considered an important
advance in purchasing area development and
consider a matrix that classifies product item
classes into four different categories,
noncritical, bottleneck, leverage and strategic,
according to two dimensions, profit impact and
supply risk. This matrix allows to define
purchasing strategies according to the
characteristics of each product item class
(Gelderman and Van Weele, 2003). To rate the
Kraljic Purchasing Matrix (KPM) dimensions, a
set of criteria must be defined for each one and
weighted using the Analytic Hierarchy Process
(AHP) tool. The Kraljic matrix has already been
applied in several areas, however, it has not
yet been applied to the health sector in
Portugal. In this way, the aim of this paper is to
increase the scope of the KPM applicability
through the development of this study in
Centro Hospitalar Universitário Lisboa Central.
This paper is organised into six different steps:
on the first step, the company and the problem
statement are characterized; in the second
step, is presented the theoretical background
about the health sector and the Kraljic
purchasing matrix; in the third step, is
described the research approach to apply to
the problem defined; on the fourth step, the
results and their discussion are reported and,
finally, in the last step, the case study is
concluded.
an organization’s total revenues. However,
among the most representative products and
services, medicines have the highest weight in
the total value purchases, with a percentage of
46%. This value is in line with Medeiros and
Ferreira (2013) values, who stated that,
generally, drug represent about 45% of total
hospital costs.
The list of CHULC’s medicines contains over
2000 items, all of them with different
characteristics, what makes the purchasing
process complex. Additionally, they have many
problems associated with purchasing processes
and that could be related to the misalignment that
exists between purchasing strategies and
product characteristics, because, nowadays,
experts consider only the purchase volume into
their purchasers. Thus, was did a product
analysis to define purchase strategies and were
created groups of products, called item classes.
The first principle selection used was consider
medicines that account for 80,09% of total
expenditure on medicines, although they only
account for 5,3% of total spending. After that,
medicines were grouped according to their
characteristics, the number of suppliers and their
risk in patients’ lives. This approach resulted in
22 medicines item classes (Table 1).
Table 1 – Medicines item classes and respective purchase
volume
2. Hospital Centre
Centro Hospitalar Universitário Lisboa Central
(CHULC) is a hospital centre that assemble six
hospital units. The procurement of their
products and services is ensured by the
Purchasing,
Logistics
and
Distribution
Management Area (PLDMA). In a hospital,
purchase is considered a complexity activity
because purchasers have to deal with a set of
limitations and to look constantly for solutions
(Serrou
and
Abouabdellah,
2016).
Furthermore, their supply policy must meet not
only the organization but also the patient
himself (Almeida and Lourenço, 2009).
In 2017, purchases in CHULC exceeded 144
million euros. The products and services
purchases volume represent approximately
52% of total revenues per year, a figure that
highlights the strategic importance of CHULC
procurement area. This value is in line with the
idea of Lee and Drake (2010), who claim that
purchases represent between 50% and 70% of
3. Literature review
Health supply chain is considered complex and
highly responsible, as it must ensure that the
right products reach the right person at the right
time and in perfect condition. Moreover, it is a
chain with a great sensitivity due to the high
2
importance of the customer service level and
the impact it has on their health and safety
(Uthayakumar and Priyan, 2013). Hospitals
have lots of different departments that aim to
provide healthcare services, which requires a
wide range of products. The procurement area
aims to provide to hospital staff materials that
they need to perform their services, i.e.
consumables such as medicines, and
permanent material, such as the example of
equipment (Almeida and Lourenço, 2009).
Medicines involve the highest costs of a
hospital, usually with a weight between 40%
and 60% of the public sector budget (Medeiros
and Ferreira, 2013). The management of this
products is critical because they must be
transported and stored under specific
conditions, there can be no stockout and they
cannot be consumed after the expiration date.
Thus, the purchasing specialists must carefully
decide which products to order and their
quantities and also, the ideal time to place their
order to serve patients in timely and efficiently
(Uthayakumar and Priyan, 2013). Furthermore,
considering the different characteristics of all
products, is required to organize and
categorize them. For this, purchasing portfolio
models are important tools that manage
hospital purchases strategically according to
the specific characteristics of each product
(Medeiros and Ferreira, 2013).
The most used and recognized purchasing
portfolio model was created by Kraljic (1983).
The recognition of this model is based on the
simplicity of its application, what allows it to be
understood by all entities that must know which
purchasing
strategy
should
prevail
(Uthayakumar and Priyan, 2013). The main
goal of this portfolio is to minimize the
companies’ vulnerabilities taking advantage of
their strengths and then define suitable supply
strategies (Gelderman and Van Weele, 2003).
In his model, Kraljic (1983) highlights a matrix
that classifies purchased products (or group of
products) of a company in four different
categories: noncritical, bottleneck, leverage
and strategic, according to two dimensions, the
supply risk and the profit impact. However,
during the years, some authors have
introduced some changes in the matrix
dimensions, in order to adjust them to their
studies (Gelderman and Van Weele, 2003).
Thus, some of these dimensions were
presented to CHULC experts to select the ones
that could best fit organisation interests. They
have decided to evaluate medicines classes
according to the strategic impact and the supply
risk (Figure 1).
Strategic
impact
Supply Risk
Low
High
Low
Noncritical
Bottleneck
High
Leverage
Strategic
Figure 1 – Kraljic matrix (adapted from Kraljic, 1983)
In this matrix, noncritical items represent products
that are purchased daily and products that are low
in value, however take up 80% of purchasing
department time and account for less 20% of
purchasing volume. Bottleneck items represent
products whose suppliers have a dominant
position due to the supply shortage (Caniëls and
Gelderman, 2005). Leverage items represent
products that are used regularly and in large
quantities and, finally, strategic items represent
products who have a small quantity of suppliers
in the market and a high strategic impact
(Gelderman and Van Weele, 2003). Each
category has a set of recommended strategies
that can be found in the literature (Kraljic, 1983;
Caniëls and Gelderman, 2005). To allow
purchasers to better know the bargaining power
and to identify an appropriate strategy to reduce
companies risk, Kraljic (1983) defined a set of
criteria to each matrix dimension he chose
(Kraljic, 1983; Ferreira, Arantes and Kharlamov,
2015). To assess profit impact, Kraljic considered
the purchase volume or total costs, while to
assess supply risk, he considered the supply
market complexity that includes supply shortage,
technological advance, substitute products, entry
barriers, logistics costs and monopoly and
oligopoly conditions.
The professionals opinions about this matrix are
divergent. Montgomery, Ogden and Boehmke
(2018) assert that the Kraljic approach is the most
important diagnostic and prescriptive tool in
purchasing management and Gelderman and
Van Weele (2003) consider KPM a huge
innovation in professional procurement area.
However, for Caniëls and Gelderman (2005)
manage purchases only based in two factors, it’s
not a precise evaluation because there is no way
to measure dimensions and there are conflict of
3
interests in buyer-supplier relationships, since
both entities claim to have a dominant position
that takes into account the benefits associated
with it.
Kraljic matrix was already used in many
contexts and areas. Gelderman and Mac
Donald (2008) studied the application of KPM
to a logistics infrastructure developed in an oil
company, while Arabzad et al. (2012) used the
same model with the Failure Mode and Effect
Analysis (FMEA) technique to find an integrated
approach to select suppliers and to allocate
orders. Ferreira et al. (2015) applied KPM in a
multinational construction company, in two
branches located in markets with different
characteristics. The results obtained were
aligned with the expected behaviour of the
company in emergent markets and they
confirmed that KPM is a valuable tool to support
the development of purchasing strategies in the
construction industry. Botes, Niemann, and
Kotzé (2017) investigated mechanisms
whereby buyer-supplier relationship enables
resilience in the petrochemical industry. For
this, they resorted to KPM, to underly risks of
supply disruptions inherent to the resilience.
The results suggested that collaboration
between buyers and suppliers doesn’t lead
directly to supply chain resilience but allows
antecedents to provide chain resilience.
Possamai (2018) used KPM to show how
indirect purchases can be manage in a strategic
way in a cosmetic industry. This study
addressed different situations of indirect
spending, identifying the flaws and existing
opportunities that could be exploited.
Finally, regarding to the heath care sector,
Medeiros and Ferreira (2013) developed an
approach to manage a hospital’s purchasing
portfolio in Brazil, using the Kraljic model and
the Fuzzy-TOPSIS method. The results
showed that the combination of MCDM and
Fuzzy-TOPSIS is an effective way to deal with
the difficulties that purchasing portfolio models
face and it’s a flexible and efficient tool for
solving classification problems. However, they
faced some limitations such as the fact that
criteria, weights and language terms are related
to decision-maker preferences and that they
used only data from one hospital and a sample
of twelve products. They concluded that the two
dimensions and the four categories of KPM are
appropriate to manage hospital purchases.
The examples presented above show the breadth
of the Kraljic matrix, as it can be applied to a wide
range of areas, some of them very distinct.
Furthermore, this matrix was already applied to a
hospital unit in Brazil, therefore, it can be
concluded that if the application of this matrix was
adequate and efficient in other areas, it may also
be applied to a Portuguese hospital in a certain
way. Then, this paper contributes to expand the
applicability of the Kraljic matrix.
4. Research Approach
The approach used for this case study involved
an action research (AR) of eight months in
CHULC. This method was inspired by the model
created by Kurt Lewin (1946) to solve problems
that require group decision making in
organizations. The AR method is compared with
a spiral of steps, each one represented by a
planning, action and verification cycle on the
outcome of the action. This process is circular
because at the end of each stage is given
feedback about the results obtained, allowing
that research acts on reality. Thus, for this case
study were defined five steps in order to obtain a
valid KPM with all medicines item classes
identified (Figure 2).
Figure 2 – AR method to apply to KPM
The first step of the AR method is to define the
set of criteria for both KPM dimensions,
according to the studies developed by some
authors. In the second step, the CHULC experts
were asked to build rating scales for each
criterion and then priorate them, by calculating
their weights. In the third step, the 22 medicines
classes defined are rating according to the
parameters calculated on step two, which gives
a score for each class according to the strategic
impact and the supply risk. Finally, the Kraljic
4
purchasing matrix is built and it must be
validated by the purchasing experts. To assure
consistent results, the team of experts consists
of three people who must be agree.
5. Development of Kraljic Matrix
In order to apply the Kraljic matrix, it’s required
the use of a multiple criteria decision-making
tool, which are important in problem solving,
characterized by multiple actors, criteria and
objectives (Kumar et al., 2017). The main goal
of these tools is to support decision-makers as,
there is usually not only one optimal solution for
problem solving and it’s required to differentiate
existing solutions (Saaty, 1980).
In this paper, the development of the Kraljic
matrix is based on Analytic Hierarchy Process
(AHP) method, introduced by Saaty (1980) with
the main objective of simplify the decision
making problem through pairwise comparisons,
reducing the complexity of calculate weights
(Fatih Tüysüz, 2018). This method is applied in
a hierarchy of four levels to evaluate both KPM
dimensions (Figure 3). The dimensions chosen
for the hospital centre specialists for the
development of this study was the strategic
impact and the supply risk. The first level of the
hierarchy refers to the goal, which correspond
to the overall score of each medicine item class
in both dimensions. The second level contains
the set of criteria selected by the specialists to
evaluate each dimension. The third level consists
into rate and prioritize each criterion by calculate
its relative weight in the specific dimension. The
fourth and last level contains all the alternatives
of medicines item classes. To calculate the
weights of the criteria, in the second level, is used
a comparison scale recommended by Saaty
(1994) . This scale compares criteria based on
values from one to nine, that each value
corresponds to the importance of a criterion
regarding another (Table 2). However, to
determine the values in third and fourth levels is
used direct measurement, which corresponds to
value assignment according to the knowledge
and experience of purchasing specialists.
According to Saaty (1994), AHP is a flexible and
powerful tool because values are calculated
through pair-wise comparisons, which minimize
the
number
of
comparisons
needed.
Furthermore, is an objective and simple method
because decompose the decision-making
problem in several levels, which contributes to the
rationalization of the whole decision process. This
method was already applied to both Kraljic
dimensions by Ferreira et al. (2015) to position
construction item classes in KPM also according
to the strategic impact and the supply risk. After
that, similar methods were applied to prioritize
criteria, as Lee and Drake (2010). In this paper,
authors have used AHP method to consolidate
qualitative measures of the competitive priorities
Figure 3 – AHP model for each KPM dimension (adapted from Ferreira, Arantes e Kharlamov, 2015)
Table 2 – Comparison Scale (Saaty,1994)
5
in the positioning of
‘component value’ scale.
purchase
on
the
5.1. Criteria selection and rating
To choose a set of criteria for each KPM
dimension, was considered the criteria defined
by Kraljic (1983). To assess the profit impact
dimension, Kraljic considered the percentage
of purchase volume in billing volume and the
amount created by each line of the final
product, while to assess the supply risk
dimension, he considered the supply market
complexity, which includes supply shortages,
technology advances, product substitution,
entry barriers, logistics cost and monopoly and
oligopoly conditions. However, despite the
relevance of each one of these criteria, not all
can be applied to the purchase area of a
hospital centre. Thus, a research was made to
several articles where KPM was already been
applied. From the research, the purchase
specialists selected criteria that best fit CHULC
and, moreover, some of criteria have been
adjusted and new criteria have been defined,
considering that they must be comprehensive,
non-redundant, operational, thrifty and
independent (Saaty, 1980).
After selecting the criteria, they were rated.
Qualitative criteria were rated according to a
scale from one to five, which each value was
assigned by the purchasing specialists
according to their knowledge, allowing classes
to be qualitatively distinguished in each
criterion. In this range, one is the worst
scenario and five is the best scenario (Saaty,
1994). Quantitative criteria were defined
according to a value function that must to
represent the performance of the specific
criteria in CHULC.
volume’ as the most important of this dimension.
This criterion besides being selected by Kraljic
(1983), is also the most used by the authors as
Gelderman and Donald (2008) and Ferreira,
Arantes and Kharlamov (2015). Finally, the last
criterion selected was ‘expected growth in
demand’ that it isn’t consider as relevant as the
previous but allows experts to evaluate the longterm performance of product purchases and
make predictions about medicines demand.
Table 3 - Criteria rating scales of the strategic impact
dimension
In this dimension, one criterion is qualitative, and
two are quantitative. Thus, for the ‘importance of
the product in the patient’s life’ criterion was
established a scale between one and five. For
the ‘purchase volume’ criterion was defined this
value function: 𝑦 = 𝑘𝑥 2 , because specialists
consider that this is the performance of the
CHULC purchase volume. In this function, 𝑦
correspond to a scale from zero to one, 𝑥 denote
the purchase volume of each medicine in 2018
and 𝑘 is equal to (
1
𝑀𝑎𝑥𝑖𝑚𝑢𝑚 𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒𝑑 𝑉𝑜𝑙𝑢𝑚𝑒
)2 .
Finally, for the ‘expected growth in demand’
criterion was defined a function that considers
the demand of each medicine and the respective
unit cost that enables to know the impact of each
item class in medicines total cost.
5.1.1. Strategic Impact
5.1.2. Supply Risk
Three criteria were selected to evaluate the
strategic impact dimension (Table 3). The first
criterion selected was the ‘importance of the
product in the patient’s life’, since the essence
of a hospital unit is to restore the health of its
patients with a positive reflection on the image
it builds. When certain medicines are missing
can endanger patients’ lives or even end it.
This criterion was also selected by authors
who based their studies on the health sector,
although with another name, as Medeiros and
Ferreira (2013) and Singh and Prasher (2019).
Second, was selected the criterion ‘purchase
For supply risk dimension were defined four
criteria (Table 4). In the first place, experts
agreed that the ‘number of suppliers’ is a key
criterion for assessing this dimension, since in
hospitals, the trade-off between price and
quality depends on the number of potential
suppliers available on the market (Medeiros
and Ferreira, 2013). The second criterion
defined was ‘substitute products’ because
alternative products help to solve some of the
problems that managers face daily, such as
delays in delivery, arrival of damaged products,
suppliers’ stockouts and lack of attendance of
6
some suppliers. Therefore, it is relevant to
consider the criterion ‘logistic proximity’,
given that CHULC cannot store a large
quantity of medicines, and the knowledge
about medicines delivery time from the
supplier to the hospital can help specialists to
manage stock more efficiently. Moreover, the
importance of this criterion is highlighted by
the fact that medicines purchased come not
only from Portugal but also from other
European and American countries. Thus, it is
indispensable to consider the ‘transport
requirements’ criterion. To choose these
criteria, the experts were always in
agreement, what made the study easier.
Table 4 - Criteria rating scales of the supply risk
dimension
To evaluate this dimension were chosen two
qualitative criteria and two quantitative
criteria. For ‘logistic proximity’ and ‘transport
requirements’ criteria were established a
scale between one and five. For the ‘number
of suppliers’ and the ‘substitute products’
criteria were defined value functions. In the
first case, experts chose the same function as
Ferreira, Arantes and Kharlamov (2015) that
is: 𝑦 = 𝑥 −𝑁 , which 𝑦 corresponds to the rate
scale between zero and one, 𝑥 is the number
of suppliers available in each class and 𝑁
represents the behaviour of supply risk when
the number of suppliers increase. Experts
assigned the value 1.1 to the exponent 𝑁. In
the second case, experts defined a function
who represent the supply risk when the
number of substitute products of a medicine
increase. And they concluded that the more
appropriate function is: 𝑣𝑎𝑙𝑢𝑒 =
1
𝑥+1
, where
𝑥 is the number of substitute products
available. However, to obtain the value of a
class is considered the average of the results
of each item class.
5.2. Criteria Prioritization
After defined all criteria, the relative weights
were calculated, according to their importance
in the dimension to which they belong. For that,
the AHP tool was applied, starting by the pairwise comparisons. These comparisons were
done by the experts, that have assigned a value
of the comparison scale (Table 2), according to
their experience and their knowledge.
First, they started to compare the three criteria
of the strategic impact dimension (Table 5).
Table 5 – Relative weights of the strategic impact criteria
According to the results, the most important
criterion in the strategic impact dimension is the
‘purchase volume’, with a relative weight of
63,5%. This value was expected, since in the
acquisition process this is the main parameter
considered. In addition, generally, when this
criterion is considered by organisations, it
always has a value above 50% (Ferreira,
Arantes and Kharlamov, 2015). Next, the
criterion considered as the second important
was the ‘importance of the product in the
patient’s life’ with a relative weight of 28,7%
because the main goal of a hospital is to ensure
an efficient treatment to all their patients by
providing services with quality (Medeiros and
Ferreira, 2013). Finally, the criterion ‘expected
growth in the demand’ was defined as the least
important. This criterion is considered
ambiguous because it refers to the medicines
growing demand. However, when purchasers
make predictions about the demand, they
expect the total amount of products purchased
be consumed by patients. The comparisons
made by the purchasing experts to calculate
the relative weights were made with some
redundancy, so the results obtained presented
some inconsistency. In the strategic impact
dimension, the comparisons made led to a
consistency ratio of 9,8% which, according to
7
Saaty (1980) can be tolerated, since it is a
value less than 10%.
criteria between one and five were converted
Next, were compared the four criteria of the
supply risk dimension (Table 6).
value assigned by experts. Quantitative criteria
didn’t require to be converted because the
results of the value functions were directly
between zero and one. Thus, it was obtained a
classification for the 22 medicines item classes
according to strategic impact and supply risk
(Table 7 and Figure 4).
Table 6 – Relative weights of the supply risk criteria
through this function: 𝑦 =
𝑥−1
4
, where 𝑥 is the
Table 7 – Classification of medicines item classes
according to both matrix dimensions
According to the results, the ‘number of
suppliers’ criterion’ is the most important, with
a relative weight of 54,6%. This value can be
explained by the high impact that the number
of suppliers has on the hospital service, since
they are responsible for supplying the
required products for health care activities
and for the patients’ treatment. Next, experts
considered important the ‘substitute products’
criterion, with 29,5% relative weight, because
medicines often arrive damaged or don’t
meet the desired characteristics. Thus, it’s
important to have alternative products so that
the necessary medicines never miss. In third
place, was considered the ‘proximity logistic’
criterion with 11,3%. This criterion is not
considered very important, as the main
concern of the hospital is to make medicines
available to its users, regardless of where
they come from. However, this criterion is
associated with the waiting time which should
be short as possible. Finally, the criterion
‘transport requirements’ was considered the
least important, as the transport is not the
responsibility of the hospital centre. However,
medicines must be transported under proper
conditions so that they don’t arrive damaged.
In the supply risk dimension, comparisons
made let to a consistency ratio of 8,8%, which
it’s also a value less than 10%.
6. Results and discussion
According to AR method, the next step is to
rate the 22 medicines item classes, according
to the rate scales defined to each criterion
(Table 3 and Table 4). All values must be
between zero and one, which corresponds to
the matrix scale. Thus, values of qualitative
However, the boundaries of each quadrant are
not known so Padhi, Wagner and Aggarwal
(2012) suggested the Multidimensional Scaling
(MDS) principles, which compares the
characteristics of the 22 medicines item
classes and group them according to their level
of similarity. This is calculated through
Euclidean
distances
considering
their
classifications in supply risk and strategic
impact dimensions (Table 7). This approach
allowed to adjust the different item classes and
position them in a product category (Figure 5).
Noncritical category has the largest number of
classes that correspond to 50,1% of the total
purchasing volume. These classes have low
supply risk, due to the large number of
suppliers and substitute products, and a low
strategic impact, due to the small purchase
volumes in each class. Thus, for these item
classes is recommended the reduction of the
logistical and administrative complexity and the
standardization and aggregation of the
transaction costs of purchase orders (Caniëls
and Gelderman, 2005). The bottleneck
category, despite being the second with the
largest number of classes, has the lowest
8
Table 8 – Number of classes and respective purchase volume in each category
Figure 4 – Visual representation of medicines item classes
purchase volume (3%). These classes have
high supply risk due to the reduced number of
suppliers and the fact there is no substitute
product in case of need. They also have low
strategic impact because of the low purchase
volumes and the low impact that demand
growth has on the organization. Therefore, it is
recommended to ensure medicines availability
through larger stocks or contracts with current
suppliers (Caniëls and Gelderman, 2005).
However, according to experts this is not
possible, as they cannot afford to maintain high
medicine stocks.
Furthermore, their high importance to CHULC
is due to the high impact they have on patients’
lives when there is a break on stocks. It is
recommended to applied purchasing strategies
that exploit the CHULC purchasing power,
through price negotiation. This can be done by
competitive bidding (Lee and Drake, 2010).
Experts stated that they are already using this
strategy, but they recognize they may not be
applying to the right medicines. Finally, the
strategy category has only one item class but
with a high relative weight (29,5%). Antivirals
has high strategic impact and high supply risk.,
since it has high impact on organization
amounts when there is a growth in demand,
and high risk in patients’ lives when they are
missing. Furthermore, it hasn’t a significant
number of suppliers and of substitute products.
Then, experts recommend establishing a longterm strategic partnership with the supplier, so
that he has updated knowledge about the
CHULC medicines demand.
7. Conclusion
Figure 5 – KPM applied to CHULC purchasing area
Leverage category comprises three classes
with a relative weight of 17,4%. These classes
are characterized by low supply risk because
they have several substitute products and
many suppliers located in Portugal.
This paper highlights the complexity associated
with the medicines purchasing process from
hospital centres, particularly from CHULC.
Thus, its purchase process was studied and
analysed, and it was concluded that most of the
problems identified are related to the
misalignment
between
each
medicine
characteristics and its purchase strategy.
Furthermore, currently, CHULC’s medicines
purchasing strategy is only a function of
purchasing volume. In this sense, KPM was a
9
fundamental tool because consider more
parameters that are defined according to
CHULC interests, which allows to position the
22 item classes in the most appropriate
quadrant. Regarding the results obtained, the
large number of routine classes was
expected. However, classes identified as
lever or strategic not. When results based on
MDS principles were presented to experts,
those validated them, which proved the great
efficiency of MDS in KPM.
The AR approach was useful to organize the
study, as well as to obtain valid and
consistent results. This was possible due to
the collaboration of CHULC professionals
and the application of AHP tool. This tool was
considered exhaustive and redundant,
however, in the end, experts agreed that it’s
a very useful, efficient and simple tool as it is
not required to be applied by workers with
very in-depth.
The biggest limitation faced was the lack of
purchasing managers availability, which led
to long periods of stagnation. Furthermore,
the existence of only one case study applied
to the hospital purchasing are it was also a
limitation (Medeiros and Ferreira, 2013).
Finally, as future work, it is suggested to
apply KPM to other product/services
headings, so that buyers can manage their
acquisition effectively and economically. In
addition, it is suggested to implement
advanced technological tools to develop
information systems to centralize and update
all stock daily.
8. References
Almeida, A. and Lourenço, L. (2009) ‘As diferenças
regionais ao nível das práticas de aprovisionamento
nos hospitais públicos portugueses’, Revista
Portuguesa De Saúde Pública, pp. 81–94.
Arabzad, S. M. et al. (2012) ‘Proposing a New
Approach for Supplier Selection Based on Kraljic’s
Model Using FMEA and Integer Linear Programming’,
Journal of Production and Operations Management,
Vol 3, Iss 1, Pp 19-40 (2012), 3(1), pp. 19–40.
Botes, A., Niemann, W. and Kotzé, T. (2017) ‘BuyerSupplier Collaboration and Supply Chain Resilience:
A Case Study in the Petrochemical Industry’, South
African Journal of Industrial Engineering. South
African Journal of Industrial Engineering (University of
Pretoria), 28(4), pp. 183–199. Available at:
http://10.0.27.254/28-4-1736.
Caniëls, M. C. J. and Gelderman, C. J. (2005)
‘Purchasing strategies in the Kraljic matrix—A power
and dependence perspective’, Journal of Purchasing
and Supply Management, 11(2), pp. 141–155. doi:
https://doi.org/10.1016/j.pursup.2005.10.004.
Caniëls, M. C. J. and Gelderman, C. J. (2007) ‘Power
and interdependence in buyer supplier relationships:
A purchasing portfolio approach’, Industrial Marketing
Management, 36(2), pp. 219–229. doi:
10.1016/j.indmarman.2005.08.012.
Centro Hospitalar Lisboa Central: Relatório e Contas 2017
(2018). Lisboa.
Fatih Tüysüz (2018) ‘Simulated Hesitant Fuzzy Linguistic
Term Sets-Based Approach for Modeling Uncertainty in
AHP Method’, International Journal of Information
Technology & Decision Making, 7(3), pp. 801–817.
Ferreira, L. M. D. F., Arantes, A. and Kharlamov, A. A.
(2015) ‘Development of a purchasing portfolio model for
the construction industry: An empirical study’,
Production Planning and Control, 26(5), pp. 377–392.
doi: 10.1080/09537287.2014.906679.
Gelderman, C. J. and Mac Donald, D. R. (2008)
‘Application of Kraljic’s purchasing portfolio matrix in an
undeveloped logistics infrastructure: The staatsolie
suriname case’, Journal of Transnational Management,
13(1), pp. 77–92. doi: 10.1080/15475770802059610.
Gelderman, C. J. and Van Weele, A. J. (2003) ‘Handling
measurement issues and strategic directions in Kraljic’s
purchasing portfolio model’, Journal of Purchasing and
Supply Management, 9(5–6), pp. 207–216. doi:
10.1016/j.pursup.2003.07.001.
INFARMED (2015) Regulamento relativo às boas práticas
de distribuição de medicamentos para uso humano.
Lisboa.
Kraljic, P. (1983) ‘Purchasing Must Become Supply
Management’, Harward Business Review Boston, 61(5),
pp. 109–117. doi: 10.1225/83509.
Kumar, A. et al. (2017) ‘A review of multi criteria decision
making (MCDM) towards sustainable renewable energy
development’, Renewable and Sustainable Energy
Reviews. Elsevier, 69(August 2018), pp. 596–609. doi:
10.1016/j.rser.2016.11.191.
Kurt Lewin (1946) ‘Action research and Minority
Problems’, Journal of Social Issues, 2, pp. 34–46.
Lee, D. M. and Drake, P. R. (2010) ‘A portfolio model for
component purchasing strategy and the case study of
two South Korean elevator manufacturers’, International
Journal of Production Research, 48(22), pp. 6651–6682.
doi: 10.1080/00207540902897780.
Medeiros, M. and Ferreira, L. (2013) ‘The Management of
Operations Development of a purchasing portfolio model :
an empirical study in a Brazilian hospital’, Production
Planning & Control. Taylor & Francis, 7287, pp. 1–15. doi:
10.1080/09537287.2018.1434912.
Ministério da Saúde (2018) Retrato da Saúde 2018. Edited
by Ministério da Saúde. Lisboa.
Montgomery, R. T., Ogden, J. A. and Boehmke, B. C. (2018)
‘A quantified Kraljic Portfolio Matrix: Using decision
analysis for strategic purchasing’, Journal of Purchasing
and Supply Management. Pergamon, 24(3), pp. 192–203.
doi: 10.1016/J.PURSUP.2017.10.002.
Saaty, L. T. (1980) The analytic hierarchy process, McGrawHill, New York. New York. doi: 10.1002/jqs.593.
Saaty, T. L. (1994) ‘How To Make A Decision : The Analytic
Hierarchy Process’, pp. 75–105.
Serrou, D. and Abouabdellah, A. (2016) ‘Logistics in the
Hospital: Methodology for Measuring Performance’,
Journal of Engineering and Applied Sciences, 11(5), pp.
2950–2956.
Singh, A. and Prasher, A. (2019) ‘Total Quality Management
& Business Excellence Measuring healthcare service
quality from patients ’ perspective : using Fuzzy AHP
application’, Total Quality Management. Taylor & Francis,
30(3), pp. 284–300. doi:
10.1080/14783363.2017.1302794.
Uthayakumar, R. and Priyan, S. (2013) ‘Pharmaceutical
supply chain and inventory management strategies :
Optimization for a pharmaceutical company and a
hospital’, Operations Research for Health Care, 2, pp. 52–
64. doi: 10.1016/j.orhc.2013.08.001.
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