Segmenting supplies and suppliers
bringing together the purchasing portfolio matrix and the supplier potential matrix
Rezaei, Jafar; Fallah Lajimi, Hamidreza DOI
10.1080/13675567.2018.1535649 Publication date
2018
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Rezaei, J., & Fallah Lajimi, H. (2018). Segmenting supplies and suppliers: bringing together the purchasing portfolio matrix and the supplier potential matrix. International Journal of Logistics Research and
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Segmenting supplies and suppliers: bringing
together the purchasing portfolio matrix and the
supplier potential matrix
Jafar Rezaei & Hamidreza Fallah Lajimi
To cite this article: Jafar Rezaei & Hamidreza Fallah Lajimi (2018): Segmenting
supplies and suppliers: bringing together the purchasing portfolio matrix and the supplier potential matrix, International Journal of Logistics Research and Applications, DOI: 10.1080/13675567.2018.1535649
To link to this article: https://doi.org/10.1080/13675567.2018.1535649
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Segmenting supplies and suppliers: bringing together the
purchasing portfolio matrix and the supplier potential matrix
Jafar Rezaeiaand Hamidreza Fallah Lajimib a
Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands;bFaculty of Management, University of Mazandaran, Mazandaran, Iran
ABSTRACT
Supplier segmentation is one of the most important supply chain-related activities for most firms working with multiple suppliers. Purchasing portfolio matrix (PPM) is a segmentation method that considers two dimensions (profit impact and supply risk) against which the materials purchased by the company are classified. Despite its popularity, PPM has been the subject of serious criticism. A new approach to supplier segmentation, called supplier potential matrix (SPM), aims to fulfil the need for a unifying framework that includes all the important variables under two overarching dimensions: supplier capabilities and supplier willingness. While the focus of PPM is onsupply, SPM mainly focuses on relationship. However, it is important to include both the supplies and therelationship with those who supply, the suppliers. The main purpose of this study is to bring these two approaches together through a hybrid matrix called PPM-SPM. Data is collected from a company working with 70 suppliers. Best worst method (BWM), is used to determine the weights of the criteria we need for the two segmentation approaches. The suppliers are segmented based on the two approaches. A combined PPM-SPM segmentation is then proposed and discussed. The results show that the combined approach improves supplier management.
ARTICLE HISTORY
Received 29 October 2016 Accepted 6 October 2018
KEYWORDS
Purchasing portfolio matrix; supplier potential matrix; supplier segmentation; best worst method (BWM)
1. Introduction
In recent decades, purchasing and supply chain management have evolved from a traditional oper-ational function into a strategic function, and are increasingly recognised by organisations as key business drivers (Van Weele2014). This means that, these days, purchasing and supply managers are more involved in strategic activities and decisions. One of these strategic activities is supplier relationship management, which can be defined as the way relationships with suppliers are estab-lished, developed and sustained. Because suppliers vary with respect to many different features, the quality of the components of the relationship with suppliers are also different. While an organ-isation tries to develop and maintain a high level of trust and commitment with its key suppliers, it may prefer a more arm’s length relationship with other suppliers (Lambert2008). While some sup-pliers play a very critical role by providing a substantial share of an organisation’s supplies, others may play a more marginal role. As a result, most purchasing and supply managers have to formulate different relationship strategies for different suppliers. Given the fact that many organisations have a
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CONTACT Jafar Rezaei j.rezaei@tudelft.nl
This article has been republished with minor changes. These changes do not impact the academic content of the article. https://doi.org/10.1080/13675567.2018.1535649
long list of suppliers, it is very difficult to formulate different relationship strategies for individual suppliers.
It appears that the key solution to this challenge is to create supplier categories. One of the ear-liest studies in this area is the classic work by Kraljic (1983), which is known in purchasing and supply management literature as the ‘purchasing portfolio matrix’ (PPM). According to PPM, there are two dimensions, profit impact and supply risk, that can be used to create four supplier segments, rather than handling individual suppliers differently. Over the years, PPM has become the standard in thefield of purchasing portfolio models, and has been used by many companies. PPM is easy to understand by managers and a very powerful tool in terms of discriminating sup-pliers according to the differences in the products/materials they supply, which is why it is still popular. On the other hand, many aspects of PPM have been criticised. What we consider impor-tant for this study is the fact that, despite the evolution of the purchasing and supply management function from an operational level towards a strategic level, PPM functions at an operational level. In fact, the PPM was proposed more than three decades ago, when the purchasing function was still at an operational level, which is reflected by the fact that PPM focuses on supply and not on the supplier. Both dimensions (profit impact and supply risk) are related to the products/ materials (supply).
As mentioned before, these days, the purchasing and supply management play a more strategic role. To manage supplier relationships, it is necessary to include the characteristics of the suppliers and the relationships. More recently, a new approach to supplier segmentation, called supplier potential matrix (SPM), was proposed by Rezaei and Ortt (2012), which focuses on these relationship management aspects by including two principal dimensions, ‘suppliers capabilities’ and ‘supplier willingness’, proposing different strategies for handling different supplier segments based on these two dimensions. While PPM focuses on supply characteristics, SPM focuses on supplier relationship characteristics. In our opinion, both elements need to be considered.
The main aim of this study is to bring these two approaches (PPM, and SPM) together, proposing a much more powerful segmentation tool. The new model, which we call PPM-SPM, allows decision-makers to segment suppliers not only by looking at what it is that they supply, but also based on their characteristics and their relationship with the buying company. It has been shown that supplier seg-mentation is a multi-criteria decision-making (MCDM) problem, which is why we formulate the problem as an MCDM problem and solve it using an MCDM method called best worst method (BWM). The proposed model is applied and discussed in a real-world situation.
In the next section, we review supplier segmentation literature, followed by a discussion of the proposed PPM-SPM framework in Section 3. Section 4 presents the methodology used in this study. In Section 5 the model is illustrated on the basis of a real-world problem. Strategies to handle different segments of PPM-SPM are presented in Section 6. In Section 7, finally, we provide the con-clusion and suggestions for future research.
2. Literature review
Today, manufacturing companies work with hundreds of suppliers to manufacture their products. These suppliers provide materials with different values, qualities and volumes, and are characterised by different features. While some suppliers may be willing to share some critical information, others may not. While some may be concerned about environmental issues, others may focus more on mak-ing a profit. These are just some examples of the differences between suppliers, which demand differ-ent strategies in terms of supplier relationship managemdiffer-ent. However, it is almost impossible for a manufacturing company to develop hundreds of different strategies, so more efficient approach to supplier management is needed. One of the most efficient ways to handle this problem is through supplier segmentation. Although the segmentation approach has been used in marketing (market segmentation) for several decades as a very popular and well-researched approach, much less atten-tion has been paid to supplier segmentaatten-tion (Rezaei and Ortt2013a).
Generally speaking, the aim of supplier segmentation is to create a manageable number of sup-plier segments, reducing the number of strategies a company needs to develop. Supsup-plier segmenta-tion maintains and enhances the posisegmenta-tion of the buying company in the marketplace (Svensson
2004). Although the task seems to be simple, the problem is how to identify the segments. One may think about features like purchasing volume, geographical distance, price, trust and so on, as a basis for the segmentation. Among thefirst researchers to propose a systematic approach to sup-plier segmentation is Kraljic (1983). The two dimensions he proposed are supply risk and profit impact. Using these two dimensions, four segments are made and strategies are suggested to manage the segments in different ways. His work has gained a lot of attention among researchers as well as companies. Based on his work, several extensions have been proposed by Olsen and Ellram (1997), Wynstra and Ten Pierick (2000), Caniëls and Gelderman (2007), Drake, Myung Lee, and Hussain (2013), Bartezzaghi and Ronchi (2004), and others. Rezaei and Ortt (2012), after reviewing supplier segmentation literature and classifying existing approaches into process, portfolio and involvement approaches, concluded that, despite the dominance of the PPM initially suggested by Kraljic (1983), subsequently extended by others, more comprehensive models are needed. They proposed a new approach called the supplier potential matrix. Several MCDM methods have been applied to solve the problem, which is an effort to solve the measurement and operationalisation issues of earlier seg-mentation approaches (Rezaei and Ortt 2013a, 2013b; Osiro, Lima-Junior, and Carpinetti 2014; Akman 2015; Lo and Sudjatmika 2015; Rezaei, Wang, and Tavasszy 2015; Hudnurkar, Rathod, and Jakhar 2016; Ross, Kuzu, and Li 2016). In the following section, we briefly discuss the two approaches mentioned above (purchasing portfolio matrix and supplier potential matrix).
Purchasing portfolio matrix: the portfolio matrix is based on the two dimensions of supply risk and profit impact.
Supply risk is defined as the probability of an incident associated with inbound supply from individual supplier failures or the supply market occurring, in which its outcomes result in the inability of the purchasingfirm to meet customer demand or cause threats to customer life and safety. (Zsidisin2003)
Profit impact is defined ‘in terms of the volume purchased, the percentage of the total cost of pur-chases and the impact on product quality or competitive strategy’ (Lee and Drake2010). Based on the values (low and high) of each dimension, supplies are divided into four segments: bottleneck, non-critical, leverage and strategic commodities. Different strategies are then formulated to manage these segments. Despite its popularity, it is not clear which criteria or factors should be included when measuring the dimensions involved. It is also not clear how the criteria could be integrated to arrive at two scores per dimension. We review existing literature to identify the criteria to measure each dimension of the Kraljic model. The results are presented inTable 1.
Supplier Potential Matrix: Rezaei and Ortt (2012) define supplier segmentation as
the identification of the capabilities and willingness of suppliers by a particular buyer in order for the buyer to engage in a strategic and effective partnership with the suppliers with regard to a set of evolving business func-tions and activities in the supply chain management.
They include the two dimensions‘supplier willingness’ and ‘supplier capabilities’ to segment suppli-ers, and define them as follows:
Supplier’s capabilities are complex bundles of skills and accumulated knowledge, exercised through organiz-ational processes that enablefirms to co-ordinate activities and make use of their assets in different business functions that are important for a buyer.
‘Supplier’s willingness is confidence, commitment and motivation to engage in a (long-term) relationship with a buyer.’ Each buyer may consider different capabilities and willingness criteria to evaluate and segment its suppliers. For a comprehensive list of criteria for capabilities and will-ingness, seeTable 2.
3. A combined segmentation approach
In the previous section, we described two important supplier segmentation approaches. As mentioned earlier, while the PPM focusses on the items being supplied, the SPM looks at two overarching supplier dimensions– capabilities and willingness. Therefore, when using the PPM, we can properly segment the purchased items, and formulate strategies to manage suppliers supplying different items. However, when using PPM, we ignore the characteristics of the suppliers and the relationship between the buyer and suppliers, making the formulated strategies somewhat inefficient. On the other hand, SPM focuses mainly on supplier characteristics and the relationship between buyer and suppliers. In this study, we combine the two supplier segmentation approaches, simultaneously including (i) the characteristics of the items, (ii) the characteristics of the suppliers and (iii) the characteristics of the relationship (the former based mainly on the PPM approach, and the latter two based mainly on the SPM approach). The combined conceptual framework is shown inFigure 1.
While, according to PPM, supply managers should formulate strategies, for instance for all lever-age items, the combined PPM-SPM approach allows manlever-agers to deal with the suppliers of leverlever-age items in four different ways, depending on their capabilities and willingness. It appears logical that a supplier with low capabilities and low willingness supplying a leverage item should be managed differently than a supplier with high capabilities and high willingness supplying the same item. In Section 6, we use a real-world case study to show how these suppliers should be treated differently.
4. Methodology
As mentioned earlier, PPM and SPM each have two dimensions. Each dimension covers a set of cri-teria. In order to arrive at two overall scores for the two dimensions of each approach, we need a scientific aggregation method. One of the most promising ways is to use multi-criteria decision-making (MCDM) methods, which are used to identify the weights of the criteria involved such that we can aggregate all the criteria under each dimension. There are several different MCDM methods in existing literature (see, for instance, Figueira, Greco, and Ehrgott2005, among others).
Table 1.Criteria used to measure the two dimensions of the purchasing portfolio matrix (PPM). Supply risk criteria Reference Suppliers available in the construction
site local market
Ferreira, Arantes, and Kharlamov (2015), Fenson (2008), Zsidisin (2003) Product availability Ferreira, Arantes, and Kharlamov (2015)
Delivery time Fenson (2008), Das and Handfield (1997), Sjöberg (2010), Zsidisin (2003) Substitution possibilities Kraljic (1983), Ferreira, Arantes, and Kharlamov (2015)
Product storage costs Kraljic (1983), Ferreira, Arantes, and Kharlamov (2015) Legal requirements Ferreira, Arantes, and Kharlamov (2015)
Ease of supplier substitution in case of failure
Ferreira, Arantes, and Kharlamov (2015) Logistical proximity of supplier market Ferreira, Arantes, and Kharlamov (2015)
Number of available suppliers Kraljic (1983), Ferreira, Arantes, and Kharlamov (2015)
Quality Lin et al. (2005), Pi and Low (2006), Parthiban, Zubar, and Garge (2012), Ho, Xu, and Dey (2010), Choy, Bun Lee, and Lo (2004), Lee et al. (2009)
Guarantee Fenson (2008) Profit impact criteria
Total amount purchased Kraljic (1983), Ferreira, Arantes, and Kharlamov (2015), Olsen and Ellram (1997), Large and Thomsen (2011)
Expected growth in company’s demand Kraljic (1983), Ferreira, Arantes, and Kharlamov (2015) Perceived bargaining power of the
buyer
Ferreira, Arantes, and Kharlamov (2015), Parthiban, Zubar, and Garge (2012) Product price Kraljic (1983), Sjöberg(2010), Padhi, Wagner, and Aggarwal (2012), Grisi, Guerra, and
Naviglio (2010) The importance of the product in the
project sequence
In this study, we use best worst method (BWM) (Rezaei2015,2016), which has been shown to be an efficient method that needs fewer data and yields more reliable results. The BWM has been already applied in several real-world studies including port performance measurement (Rezaei, van Wulfften Palthe, et al., 2018), partner selection (Bonyani and Alimohammadlou 2018; Garg and Sharma
2018), standard dominance (van de Kaa, Janssen, and Rezaei2018), firm’s performance measure-ment (Gupta2018), water security sustainability evaluation (Nie et al.2018), measuring sustainabil-ity in packaging design (Rezaei, Papakonstantinou, et al.,2018), measuring logistics performance of countries (Rezaei, van Roekel, and Tavasszy2018),firm’s R&D evaluation (Salimi and Rezaei2018), measuring quality of transit nodes in a transport system (Groenendijk, Rezaei, and Correia2018), measuring quality of baggage handling system in an airport (Rezaei, Kothadiya, et al., 2018), to name a few most recent application studies.
The buying company shouldfirst identify a set of criteria for each segmentation dimension. This is usually done by interviewing the decision-makers at the company in question. For this purpose, we show the criteria we found in existing literature (Tables 1and 2), and ask the decision-makers to select a handful of relevant criteria. We then evaluate each supplier with respect to the various cri-teria, after which we shouldfind the weight of each criterion using the best worst method (BWM). By multiplying the supplier’s scores by their weights, and adding them up for each dimension, we end
Table 2.Criteria used to measure two dimensions of supplier potential matrix (SPM) (Rezaei and Ortt2012). Capabilities criteria Willingness criteria Price/cost Commitment to quality
Delivery Honest and frequent communications Quality Communication openness
Reserve capacity Attitude
Industry knowledge Relationship closeness Supplier process capability Open to site evaluation
Geographic location/proximity Commitment to continuous improvement in product and process
Design capability Bidding procedural compliance Technical capability Reciprocal arrangements Technology monitoring Prior experience with supplier Management and organisation Impression
Production, manufacturing/transformation facilities and capacity
Ethical standards Reputation and position in the industry Willingness to co-design
Financial position Willingness to participate in new product development Performance awards Willingness to integrate supply chain management relationship Performance history Mutual respect and honesty
Cost control Willingness to share information Technology development Willingness to share ideas Repair service Willingness to share technology After-sales support Willingness to share cost savings Packaging ability Consistency and follow-through Reliability of product Willingness to eliminate waste Operational controls Willingness to promote JIT principles Training aids Dependency
Labor relations record Willingness to invest in specific equipment Impact on energy utilisation Long term relationship
Ease of maintenance design Communication system Desire for business
Human resource management Amount of past business Warranties and claims Market sensing Customer linking
Environmental health and safety Innovation
Order entry
up with an aggregated score for each supplier with respect to the various dimensions. Plotting the suppliers and using two levels (low and high) for each dimension, we can divide the suppliers into four segments. This process is implemented for the two approaches (PPM and SPM) separately. Thefinal results are then combined to create the PPM-SPM segmentation. To identify the weights of the criteria we use BWM (Rezaei2015,2016), which is described as follows.
Step 1. Determine a set of decision criteria.
In this step, the decision-maker identifies n criteria {c1, c2, . . . , cn} that are used to make a
decision.
Step 2. From the set selected in Step 1, and considering the ultimate goal of the decision problem, identify the best (e.g. the most desirable, the most important) and the worst (e.g. the least desirable, the least important) criteria.
Step 3. Express the preference of the best criterion over all the other criteria, using a number between 1 and 9 (1: i is equally important to j; 9: i is extremely more important than j). The resulting best-to-others (BO) vector would be:
AB= (aB1, aB2, . . . , aBn),
where aBjindicates the preference of the best criterion B over criterion j.
Step 4. Express the preference of all the criteria over the worst criterion, using a number between 1 and 9 (1: i is equally important to j; 9: i is extremely more important than j). The resulting others-to-worst (OW) vector would be:
AW= (a1W, a2W, . . . , anW)T,
where ajWindicates the preference of the criterion j over the worst criterion W.
Step 5. Find the optimal weights (w∗1, w∗2, . . . , w∗n).
The aim is to determine the optimal weights of the criteria, such that the maximum absolute differences{|wB− aBjwj|, |wj− ajWwW|}, for all j is minimised, which is translated to the following
minmax model: min max j {|wB− aBjwj|, |wj− ajWwW|} s.t. j wj= 1 wj≥ 0, for all j (1)
Problem (1) is converted to the following linear programming problem: minjL s.t. |wB− aBjwj| ≤jL, for all j |wj− ajWwW| ≤jL, for all j j wj= 1 wj≥ 0, for all j (2)
Solving problem (2), wefind the optimal weights (w∗1, w∗2, . . . , w∗n) andjL
∗
which is considered as an indicator of the consistency of the comparisons. That is to say, the lower thejL∗, the more consistent the comparison system.
5. Application 5.1. Data collection
To illustrate the proposed combined PPM-SPM approach, we collected data from 70 suppliers of a computer hardware company. Our data collection has two phases. In the first phase, we need to identify the most relevant criteria to measure the two dimensions of PPM and SPM, respectively. To this end, we held several meetings with IT-experts, and procurement, purchasing and commercial managers of the company.
After careful consideration and using collective agreement, the managers selected the criteria shown inTable 3.
In the second phase, two questionnaires (one for PPM and one for SPM) were designed. based on the BWM structure (Rezaei2015), to collect pairwise comparison data for the criteria identified in thefirst phase. It is worth mentioning that, before asking the decision-makers to conduct the pair-wise comparison, the objective of the research was explained to the respondents, together with the supplier segmentation concepts and how the data would be used.
5.2. BWM results
The decision-makers were asked to conduct pairwise comparisons between the best criterion and the other criteria, and between the other criteria and the worst criterion for the two segmentation approaches (PPM and SPM). By solving the programming problem (2) for each pair of vectors, the weights of criteria could be determined. Table 4 shows the results for PPM while Table 5
As shown inTable 4,‘quality’ is by far the most important criterion with regard to supply risk, followed by‘guarantee’, ‘delivery time’ and ‘geographical location’. ‘Product availability’ and ‘after sales support’ were considered to be the least important criteria for this dimension. For the dimen-sion‘profit impact’, ‘product price’ is the most important criterion, accounting for more than half of the importance of this dimension.‘Expected growth in company’s demand’ and ‘total amount pur-chased’ are the next important criteria. ‘Prior experience with supplier’ was considered the least important. The consistency ratios are close to zero, which indicates a high consistency.
As shown inTable 5,‘quality’ and ‘delivery time’ are the most important suppliers’ capabilities, followed by‘price’, ‘geographical location’ and ‘financial position’. ‘Willingness to share information’ is assigned the highest weight of all the willingness criteria.‘Long term relationship’, and ‘commit-ment to quality’ are the next important criteria, while ‘communication openness’ and ‘reciprocal arrangement’ were seen as the least important criteria.
5.3. Aggregated results
To determine the overall score for each supplier for each dimension of the two approaches, we need the criteria weights wj(Section 5.2), and the score of each supplier with respect to each criterion, xij.
Thefinal aggregate scores of each dimension for supplier i is then calculated as follows: Si=
n j=1
wjxij,∀i (3)
Table 3.The criteria selected to measure the two dimensions of PPM and SPM.
PPM SPM
Criteria to measure supply risk: Geographical location Product availability Delivery time After sales support Guarantee Quality
Criteria to measure capabilities: Price Delivery Quality Reserve capacity Geographical location Financial position Criteria to measure profit impact:
Total amount purchased
Expected growth in company’s demand Product price
Prior experience with supplier
Criteria to measure willingness: Commitment to quality Communication openness Reciprocal arrangement Willingness to share information Long term relationship
Table 5.Capabilities and willingness criteria weights. Capabilities criteria
(jL∗= 0.103)
Price Delivery time
Quality Reserve capacity Geographical location Financial position Weight 0.129 0.258 0.414 0.039 0.086 0.074 Willingness criteria (jL∗= 0.095) Commitment to quality Communication openness Reciprocal arrangement Willingness to share information Long term relationship Weight 0.190 0.095 0.048 0.476 0.190
Table 4.Supply risk and profit impact criteria weights. Supply risk criteria
(jL∗= 0.076) Geographical location Product availability Delivery time After sales support Guarantee Quality Weight 0.114 0.091 0.152 0.038 0.227 0.379 Profit impact criteria
(jL∗= 0.111)
Total amount purchased
Expected growth in company’s demand
Product price Prior experience with supplier
We then normalise the values of Sias follows.
ˆSp=
Sp− min {Si}
max {Si}− min {Si}
(4)
Table 6shows the normalised scores for each supplier for the two dimensions of the two approaches (PPM and SMP).
Based on the normalised scores, we create four segments.Table 7shows the supplier segmenta-tion based on the PPM model, as follows:
As can be seen fromTable 7, most suppliers are segmented as PPM1 (low supply risk and low profit impact). The next segments with respect to the number of suppliers are segments PPM3 and PPM4. Segment PPM2 contains the fewest suppliers.
Based on the normalised scores inTable 6, we create four segments for the SPM model, as follows (Table 8):
As can be seen fromTable 8, most suppliers are assigned to segments SPM1 (low capabilities and low willingness) and SPM4 (high capabilities and high willingness).
Figure 2shows the result of the proposed hybrid PPM-SPM model, combing results of the two approaches.
5.4. Discussion
In this section, we discuss the weights (for both models), and then address strategies to handle di ffer-ent supplier segmffer-ents for different items.
Table 4shows that the company’s decision-makers identified ‘quality’ as the most important criterion with regard to supply risk. In fact, several studies have found that quality is the most important supplier selection criterion (Kannan and Tan 2002; Agarwal, Shankar, and Tiwari
2006, 2007; Lee et al.2009; Büyüközkan and Çifçi2011).‘Guarantee’ and ‘delivery time’ are the next important criteria. The buyer wants to make sure that the selected supplier has safety stocks at levels that can guarantee product availability whenever needed. The supplier should be able to maintain the company’s delivery schedule. In many studies, these two indicators have been ident-ified as important supplier selection indicators (Weber and Current1993; Prahinski and Benton
2004; Kreng and Wang2005; Chang, Wang, and Wang2007). The two criteria of quality and guar-anteed availability together account for more than 60% of the total weight of the supply risk dimension.‘After-sales support’ is the least important criterion. Although, in the hardware indus-try,‘after-sales services’ is an important factor for customers, in light of the high speed of changes to products in this industry, companies are less concerned about after-sales services.
For the‘profit impact’ dimension, ‘product price’ is the most important criterion. This is consist-ent with empirical evidence suggesting that the price of materials and services is the most important criterion when it comes to supplier selection (Kannan and Tan2002; Grisi, Guerra, and Naviglio
2010). The next criterion is‘expected growth in company’s demand’, which has been identified as a key criterion in several studies (Kraljic1983; Olsen and Ellram1997).‘Prior experience with sup-plier’ has the lowest weight among the profit impact criteria. Although it has been argued that the purchaser’s prior experience with the situation should be taken into consideration when determining the level of risk in a supply chain (Giunipero and Aly Eltantawy2004), perhaps this is no longer that important when the supplier has been selected and the relationship is ongoing.
Table 5shows that, based on the decision-makers comparisons,‘quality’ is the most important and‘reserve capacity’ is the least important criteria with regard to supplier capabilities. We discussed the importance of‘quality’ in the previous paragraph. The second important capabilities criterion is delivery. Thanaraksakul and Phruksaphanrat (2009) surveyed 76 papers on supplier selection in pur-chasing literature and found that price, quality and delivery were the most commonly listed supplier evaluation criteria, which closely matches the results of our research. Reserve capacity was identified
Table 6.Supplier segmentation results for the two methods PPM and SPM. Supplier Normalised Supply risk Normalised Profit impact Segment (PPM) Normalised capabilities Normalised willingness Segment (SPM) 1 0.399 0.466 PPM1 0.315 0.506 SPM2 2 0.279 0.320 PPM1 0.248 0.354 SPM1 3 0.447 0.409 PPM1 0.421 0.388 SPM1 4 1.000 0.985 PPM4 0.987 1.000 SPM4 5 0.175 0.472 PPM1 0.254 0.283 SPM1 6 0.525 0.372 PPM3 0.758 0.708 SPM4 7 0.000 0.045 PPM1 0.751 0.691 SPM4 8 0.512 0.195 PPM3 0.782 0.704 SPM4 9 0.268 0.442 PPM1 0.258 0.218 SPM1 10 0.408 0.299 PPM1 0.363 0.218 SPM1 11 0.359 0.405 PPM1 0.365 0.282 SPM1 12 0.292 0.311 PPM1 0.335 0.271 SPM1 13 0.039 0.081 PPM1 0.923 0.766 SPM4 14 0.373 0.427 PPM1 0.904 0.899 SPM4 15 0.528 0.382 PPM3 0.916 0.784 SPM4 16 0.024 0.000 PPM1 0.877 0.849 SPM4 17 0.304 0.202 PPM1 0.914 0.832 SPM4 18 0.361 0.316 PPM1 0.800 0.827 SPM4 19 0.592 0.424 PPM3 0.510 0.409 SPM3 20 0.140 0.929 PPM2 0.963 0.904 SPM4 21 0.459 0.495 PPM1 0.443 0.243 SPM1 22 0.378 0.387 PPM1 0.330 0.301 SPM1 23 0.306 0.487 PPM1 0.290 0.390 SPM1 24 0.523 0.540 PPM4 0.515 0.407 SPM3 25 0.548 0.568 PPM4 0.904 0.842 SPM4 26 0.564 0.579 PPM4 0.317 0.808 SPM2 27 0.555 0.553 PPM4 0.199 0.818 SPM2 28 0.584 0.498 PPM3 0.258 0.821 SPM2 29 0.523 0.580 PPM4 0.257 0.785 SPM2 30 0.563 0.479 PPM3 0.334 0.747 SPM2 31 0.533 0.554 PPM4 0.376 0.751 SPM2 32 0.488 0.302 PPM1 0.449 0.294 SPM1 33 0.750 0.736 PPM4 0.309 0.376 SPM1 34 0.778 0.777 PPM4 0.293 0.424 SPM1 35 0.740 0.776 PPM4 0.230 0.274 SPM1 36 0.783 0.771 PPM4 0.573 0.279 SPM3 37 0.782 0.735 PPM4 0.000 0.000 SPM1 38 0.790 0.813 PPM4 0.242 0.386 SPM1 39 0.339 0.415 PPM1 0.365 0.317 SPM1 40 0.688 0.867 PPM4 0.423 0.317 SPM1 41 0.662 0.859 PPM4 0.413 0.301 SPM1 42 0.657 0.822 PPM4 0.363 0.393 SPM1 43 0.680 0.837 PPM4 0.445 0.408 SPM1 44 0.999 1.000 PPM4 1.000 0.954 SPM4 45 0.458 0.384 PPM1 0.674 0.314 SPM3 46 0.453 0.477 PPM1 0.661 0.229 SPM3 47 0.416 0.284 PPM1 0.611 0.170 SPM3 48 0.415 0.286 PPM1 0.700 0.437 SPM3 49 0.411 0.492 PPM1 0.742 0.259 SPM3 50 0.932 0.417 PPM3 0.642 0.220 SPM3 51 0.887 0.156 PPM3 0.654 0.173 SPM3 52 0.895 0.266 PPM3 0.246 0.357 SPM1 53 0.888 0.254 PPM3 0.274 0.313 SPM1 54 0.915 0.295 PPM3 0.388 0.487 SPM1 55 0.354 0.691 PPM2 0.370 0.372 SPM1 56 0.402 0.751 PPM2 0.361 0.287 SPM1 57 0.940 0.935 PPM4 0.920 0.932 SPM4 58 0.328 0.298 PPM1 0.263 0.368 SPM1 59 0.488 0.240 PPM1 0.527 0.460 SPM3 60 0.412 0.379 PPM1 0.547 0.484 SPM3 61 0.359 0.244 PPM1 0.545 0.512 SPM4 62 0.458 0.412 PPM1 0.513 0.517 SPM4 (Continued )
as being the least important criterion, which is also supported by Kannan and Tan (2006). Because, in today’s economy stock is considered to be a waste, reserve capacity is not considered to be a critical factor.
Table 5also shows that ‘willingness to share information’ is the most important criterion with regard to supplier willingness. Kuo and Lin (2012), Humphreys, McIvor, and Chan (2003), and Kan-nan and Tan (2002) found information sharing to be one of the most important criteria for supplier selection. Long-term relationship and commitment to quality, which are equally important after information sharing, have been identified as important criteria in existing literature (Humphreys, McIvor, and Chan 2003; Rezaei, Ortt, and Trott 2018). Perhaps reciprocal arrangement was found to be the least important criterion because it does not play a strategic role for the purchasing company.
6. Strategies to handle different segments of PPM-SPM
In existing literature, we canfind strategies to handle different segments of PPM as well as individual segments of SPM. What we discuss here are the strategies designed to handle different segments of PPM-SPM, which should consider both supply and the relationship simultaneously.
6.1. Managing suppliers that supply non-critical items (N = 35)
According to the data analysis, 35 suppliers from 70 suppliers can be assigned to segment PPM1. The items in this segment are of low value, and they are provided by many suppliers. For these items, bundling purchasing requirements is a general strategy (Kraljic 1983, Caniels and Gelderman
Table 6.Continued. Supplier Normalised Supply risk Normalised Profit impact Segment (PPM) Normalised capabilities Normalised willingness Segment (SPM) 63 0.481 0.387 PPM1 0.499 0.514 SPM2 64 0.999 0.926 PPM4 0.532 0.494 SPM3 65 0.320 0.342 PPM1 0.503 0.484 SPM3 66 0.415 0.442 PPM1 0.465 0.311 SPM1 67 0.334 0.382 PPM1 0.235 0.451 SPM1 68 0.404 0.432 PPM1 0.397 0.187 SPM1 69 0.964 0.986 PPM4 0.951 0.836 SPM4 70 0.317 0.257 PPM1 0.191 0.302 SPM1
Table 7.Supplier segmentation for the PPM model.
Segment Description Number Percentage PPM1 low supply risk and low profit impact 35 suppliers 50% PPM2 low supply risk and high profit impact 3 suppliers 4.3% PPM3 high supply risk and low profit impact 11 suppliers 15.7% PPM4 high supply risk and high profit impact 21 suppliers 30%
Total 70 suppliers 100%
Table 8.Supplier segmentation for the SPM model.
Segment Description Number Percentage SPM1 low capabilities and low willingness 31 suppliers 44.3% SPM2 low capabilities and high willingness 8 suppliers 11.4% SPM3 high capabilities and low willingness 3 suppliers 4.3% SPM4 high capabilities and high willingness 28 suppliers 40%
2005). With regard to the level of capabilities and willingness of the suppliers, the following strategies are suggested.
. Suppliers with low capabilities and low willingness (n = 17): if the buyer could easilyfind better alternative suppliers, the best strategy is replacement. Otherwise, it would be better to keep these suppliers to have more dispersed supplier portfolio. This allows switching between suppliers based on their price offers, which allows the buyer to realise higher profits.
. Suppliers with low capabilities and high willingness (n = 2): because a large number of suppliers are able to supply these items, we expect there to be competition among the suppliers, which means the buyer can look for more capable suppliers, which means that the best strategy may be replacement. However if it is not easy tofind more capable suppliers, the buyer could keep them and formulate strategies to develop their capabilities.
. Suppliers with high capabilities and low willingness (n = 8): since the supply market for these items is very competitive, it is not surprising to see capable suppliers with low willingness, with the nature of the market being more in favour of arm’s length relationship. However, with regard to these suppliers, the best strategy may be developing the relationship (Rezaei,
Wang, and Tavasszy2015). Considering the general strategy for PPM1, which is‘bundling of pur-chasing requirements’, one of the best ways to develop such a relationship (enhancing the level of willingness) is‘purchasing large percentage of suppliers’ annual sales’ (Krause and Ellram1997).
. Suppliers with high capabilities and high willingness (n = 8): these are the best suppliers for these items, and the best strategy here is to maintain the high quality relationship and try to expand the relationship to include other items. If these suppliers are able to supply other items, they may be good alternatives for the low-capabilities and low-willingness suppliers in PPM2, PPM3, and PPM4.
6.2. Managing suppliers that supply leverage items (N = 3)
According to the data analysis, 3 suppliers from 70 suppliers can be assigned to segment PPM2. These items are characterised by low risk and high profit impact. Usually, there are many of these suppliers in the market, and these items represent a relatively large share of end price (Kraljic
1983; Caniëls and Gelderman2005). This implies that the buyer has and could try to exploit signi fi-cant power. However, depending on the supplier’s level of capabilities and willingness, a good alternative may be to adopt development strategies.
. Suppliers with low capabilities and low willingness (n = 2): since there are many suppliers for these items in the supply market, and these items have a huge impact on the buyer’s profit, the buyer is significantly and negatively affected by these suppliers, which means that the best strategy is replacement.
. Suppliers with low capabilities and high willingness (n = 0): because, for these items, the buyer could exploit its buying power, development may not be the right strategy, and the replacement strategy may perfectly work here due to a relatively large number of suppliers for these items.
. Suppliers with high capabilities and low willingness (n = 0): the high capabilities of these suppliers may help the buyer realise the intended benefits from these items. However, the low level of will-ingness may be an indication of the attractiveness of these suppliers in the eyes of other buyers, which means that, in order to keep these valuable suppliers on board, the best strategy may be developing the relationship (Rezaei, Wang, and Tavasszy2015).‘Long-term commitment’, ‘two-way communication’ and ‘trust building’ may be the best development strategies for this segment (Coote, Forrest, and Tam2003; Krause, Handfield, and Tyler2007; Modi and Mabert2007).
. Suppliers with high capabilities and high willingness (n = 1): these are the best suppliers for these items, and the best strategy is to maintain the relationship with these suppliers.
6.3. Managing suppliers that supply bottleneck items (N = 11)
According to the data analysis, 11 suppliers from 70 suppliers can be assigned to in segment PPM3. Although these items do not have a huge impact on the buyer’s profit, the vulnerability of these items is very high, due to the supply risk. The supplier has the upper hand here, and the best strategies are to‘accept the dependence’, ‘reduce the negative effect’ and ‘move towards non-critical segment’ by looking for alternative suppliers (Kraljic1983, Caniels and Gelderman2005).
. Suppliers with low capabilities and low willingness (n = 3): the items represent a very low profit, but the risks involved are huge, which implies that a supplier with low capabilities worsens the situation with respect to profit impact, and the low willingness makes it not trustworthy, which means that the best strategy may be replacement. On the other hand, since the supply mar-ket for these items is not too competitive, these suppliers have more power, which implies that the buyer may also consider adopting developing strategies for these suppliers. Development strategies that could improve both capabilities and willingness include‘supplier assessment and feedback’,
‘financial and physical investment’, ‘knowledge transfer’, and ‘supplier incentives’ (Rezaei, Wang, and Tavasszy2015).
. Suppliers with low capabilities and high willingness (n = 2): since the risk of these suppliers is high, sometimes because there are few suppliers operating in the market, it may be useful to invest in developing the relationship (Rezaei, Wang, and Tavasszy2015) by developing the capabilities of these suppliers, as their willingness could already reduce supply risks. Because the vulnerability of these items is high, a development strategy like‘competitive pressure’ (Modi and Mabert2007) may not work. The buyer, however, could work on factors other than price, like technical and product quality capabilities (Krause and Ellram1997).
. Suppliers with high capabilities and low willingness (n = 3): as the profitability of these items is low, it is not surprising to see that some suppliers with high capabilities have a low willingness to collaborate. The high level of risk may persuade the buyer to develop the relationship with such suppliers. Strategies like ‘trust building’, ‘joint action’, ‘plants visit to suppliers’ could be among the best strategies for these suppliers (Coote, Forrest, and Tam2003; Krause, Handfield, and Tyler2007; Modi and Mabert2007; Rezaei, Wang, and Tavasszy2015).
. Suppliers with high capabilities and high willingness (n = 3): these are the best suppliers for these items, and the best strategy is to keep these suppliers, which may be more difficult than keeping suppliers with high capabilities and high willingness in the previous two segments (PPM1, PPM2), because, in this case, the suppliers have more power than the buyer. In order to keep these suppliers on board, the buyer may try to buy other items from these sup-pliers and also enhance the relationship. The buyer should also accept being dependent on these suppliers.
6.4. Managing suppliers that supply strategic items (N = 21)
According to the data analysis, 21 suppliers from 70 suppliers can be assigned to in segment PPM3. These items have a huge impact on profit and are characterised by a high level of risk. These are the most important items for the buyer and they require a much higher level of attention. The general strategies for managing these suppliers are‘maintain a strategic partnership’, ‘accept a locked-in partnership’, and ‘terminate a partnership’ (Kraljic1983, Caniels and Gelderman2005). Undoubt-edly, the level of capabilities and willingness of the supplier could help the buyer formulate supplier relationship management strategies, which are discussed below.
. Suppliers with low capabilities and low willingness (n = 9): because the impact of these suppliers is huge with respect to both profit impact and supply risk, these suppliers are the most destructive of all suppliers, which means that the best strategy is replacement. If that does not work , for instance because the number of suppliers is limited, the buyer is recommended investing in improving the capabilities and willingness of these suppliers, by adopting strategies like‘financial and physical investment’, ‘knowledge transfer’, ‘supplier assessment and feedback’, and ‘supplier incentive’ (Rezaei, Wang, and Tavasszy2015).
. Suppliers with low capabilities and high willingness (n = 4): the high level of willingness of these suppliers reduces the level of risk. Because they are willing to cooperate, the buyer could think about developing the technical and product quality of these suppliers. However, as has been suggested by Caniëls and Gelderman (2005), the low level of capabilities of these suppliers may be a reason to replace them.
. Suppliers with high capabilities and low willingness (n = 3): because of their high level of capabili-ties, these suppliers have a positive impact on the buyer’s profits, which means they are very valu-able, and the buyer could try to improve its relationship with them.‘Long-term commitment’, and ‘trust building’ are recommended as the most efficient strategies for these suppliers (Rezaei, Wang, and Tavasszy2015).
. Suppliers with high capabilities and high willingness (n = 5): these are the best suppliers, as they have a positive impact on the buyer’s profits, due to their high level of capabilities, and the buyer should be less worried about the high level of risk of the items involved, as these suppliers are willing to cooperate with the buyer. The buyer should develop strategies designed to remain and develop its relationship with these suppliers, since chances are that other buyers will also find them very attractive.
7. Conclusion and future research
In this study, two supplier segmentation approaches, called the purchasing portfolio matrix (PPM) and the supplier potential matrix (SPM), were combined to develop a hybrid supplier segmentation model, which joins the advantages of the two segmentation matrices. That is to say, using the com-bined PPM-SPM model allows buyers to incorporate several important aspects of the purchased items, as well as several important features of the suppliers providing the items. The important characteristics of the items are predominantly covered by the two dimensions of ‘profit impact’ and‘supply risk’ (PPM), while the features of the suppliers are mainly covered by the two dimensions ‘supplier’s capabilities’ and ‘supplier’s willingness to collaborate’ (SPM). By considering two levels for each dimension (low and high), each segmentation matrix results in four segments, which means that the proposed combined model contains sixteen segments. The combined model was illustrated using a real-world case study, with data being collected for 70 suppliers of a company operating in computer hardware industry. To measure each segmentation dimension, several criteria were taken into account, using a multi-criteria decision-making method. In this study, we used best worst method (BWM), a new multi-criteria decision-making method, to conduct the aggregation, which resulted in a matrix with sixteen segments, and strategies being formulated for different segments. We think that this study offers a significant contribution, as it brings together two important seg-mentation matrices that, together, provide a much more comprehensive understanding of suppliers. We think that this study can be extended in some interesting directions. Because the segmentation problem can be considered as being akin to clustering methods, future research could apply other clustering methods (e.g. C-means) to this problem. It would be also interesting to apply other multi-criteria decision-making methods with regard to the aggregation part. Finally, we think it would be interesting tofind why buyers are working with some suppliers that are characterised by low capabilities and low willingness. This is especially interesting when it involves strategic items, where we expect to see high capable high/willing suppliers. This calls for more aligned sup-plier-related activities, more specifically between supplier selection and supplier segmentation.
Disclosure statement
No potential conflict of interest was reported by the authors.
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