Today, outsourcing is an important strategic issue for organizations such as
private and public. Organizations expect to attain different benefits through
successful outsourcing; however there are some risks that may be realized if
outsourcing is not managed appropriate (Kremic et al.,
2006). Organizations may outsource some functions or activities they used
to perform themselves or which are new functions (or activities).
In this respect, a significant question faced to organizations that is what functions (activities) should perform in-house and which ones should buy from outside suppliers? The answers to these questions are known as make-or-buy decisions.
These decisions are very important for organizations. Although, the outsourcing
strategies of many organizations dont remain constant over time. So, make-or-buy
decisions must be reconsider in order to support the firms new strategies.
In other words, markets, demand, or governmental policies may be changed over
time and consequently, influenced business strategies of the firms. Therefore,
outsourcing strategies must be co-ordinated with these changes (Canez
et al., 2000; Fine and Whitney, 1996; Probert
et al., 2001, Perrons, 2004).
The make-or-buy decisions issue has partly long history. Based on statements
Mclvor and Humphreys (2000), the conceptual foundation
for the make or buy decision is Williamsons theory (transaction cost analysis).
Although, considering the strategic issues caused a evolution in the context
of the make-or-buy decisions (Mclvor et al., 1997;
Canez et al., 2000). Leong
et al. (1990) considered five areas as competitive priorities: quality,
delivery performance, cost, flexibility and innovativeness. They believed that
manufacturing strategies should be developed based on conditions of these priorities.
Some studies in literature of make-or-buy decision-making (mobdm), such as
Venkatesan (1992), Mclvor et al.
(1997) and Cox (1997) analysed mobdm from resource-based
view (where the decision is taken by concentrated on the firms resources).
Also, some works, like Venkatesan (1992) and Mclvor
et al. (1997) is founded on identifying strategic modules (in the
products) or core activities (in general). Therefore, the outsourcing strategy
is retaining core activities (strategic modules) and outsourcing non-strategic
modules (sub-assemblies, parts) or non-core functions (activities).
From other viewpoint, some studies like Welch and Nayak
(1992) and Probert
(1997) viewed mobdm from technological aspect. Welch and Nayak
three factors maturity level of process technology, competitorss process
technology position and importance of process technology in a decision matrix
as named strategic sourcing model.
Quinn and Hilmer (1994), proposed core competency and
strategic vulnerability as the mobdm criteria. Fine and Whitney
(1996) presented three factors consists of capability, manufacturing competitiveness
Jennings (1997) provided a framework for evaluating
the outsourcing decisions contained a set of strategic guidelines based on areas:
business environment, cost, supplier relationships, technology and capability.
Fill and Visser (2000) presented a conceptual framework
for mobdm consists of contextual factors, strategy and structure and transaction
costs and Mclvor and Humphreys (2000) discussed a computer-based
system based on case-based reasoning for make-or-buy decisions.
Insinga and Michael (2000) applied potential for an
activity for yield competitive advantage and Internal capability to perform
an activity in comparison with competitors in a two-dimensional decision matrix.
Canez et al. (2000) and Platt
et al. (2002) applied technology and manufacturing processes, cost,
supply chain management and logistics and support systems as influencing areas
in mobdm and developed the set of criteria related to each area.
Pandey and Bansal (2004) considered criticality, stability
and simplicity as the factors for selecting activities to outsource (IT Outsourcing
Henny van de and van Peet (2006) inspiration from Canez
et al. (2000) and Platt et al. (2002)
developed their studies and applied engineering and RandD, human resources,
financial, supply chain management and logistics, support systems and technology
and manufacturing as the areas for outsourcing decision-making.
Kremic et al. (2006) proposed strategy, cost,
function characteristics and environment as factors which may impact outsourcing
Mantel et al. (2006) applied criteria which
had been developed by Quinn and Hilmer (1994) by developing
Wang and Yang (2007) discussed six factors economic,
resource, strategy, risk, management and quality for information systems outsourcing
Chupra and Meindl (2007) considered demand scale, demand
uncertainty and specifity of assets as the factors influencing propency to outsource
and Hwang et al. (2007) applied manufacturing
technology, outsourcing risk and managerial, financial and operational issues
as the items for evaluation of a make-or-buy decision-making problem.
As can be seen, in make-or-buy decisions literature, various criteria are proposed
with different authors. Moreover, many models and frameworks have been developed
to this purpose; however, many of them were concentrated on identifying sourcing
strategy based on conceptual frameworks or qualitative models (Insinga
and Michael, 2000; Quinn and Hilmer, 1994; Welch and Nayak
(1992)). It would be better to say there are seldom works which were
contained the methodologies for unequivocal decision-making between in-house
performing and outsourcing alternative (Platt et al.,
In analysis of mobdms literature, can be said that generally, many managers
expect to gain more accurate and clear results (material) for their final decisions.
The important point in earlier works is that in these works, little attention
has been to mathematical modeling. In other words, in many works of literature,
two or three-dimensional matrices (Welch and Nayak
and Michael, 2000) or decision-making algorithms (Tayles
and Colin, 2001) more than mathematical models can be seen.
As also in the articles and studies of recent years has been shown, regarding
to the complexity and nature of outsourcing decision-making, this problem can
be considered as a multi-criteria problem (Canez et al.,
2000; Platt et al., 2002; Mantel
et al., 2006; Henny van de and van Peet, 2006;
Hwang et al., 2007; Wang
and Yang, 2007). So, perhaps can be expressed that using two or three-dimensional
matrices and decision-making algorithms can not be useful to solving this problem
and therefore, utilization of mathematical models (especially, multi-criteria
decision-making models) can be more helpful. Using mathematical techniques (in
particular, multi-criteria techniques) can be helpful for increasing accuracy
and speed of decision-making process.
The other point is lacking appropriate access to reliable data in real environments. So, generally refer to the viewpoints and Judgements of experts based on linguistic variables and fuzzy numbers can be a good solution to this deficit.
Moreover, because the importance of the firm`s core activities, this articles authors believe that a single-stage (single-phase) framework is not useful for decision-making outsourcing.
In this study, to resolve these shortcomings, a decision-making framework based on two-phase is proposed. the first phase is devoted to identification and screening the core activities and the second phase contains the decision-making model based on using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) as a multi-criteria technique and application of the fuzzy set theory. Also, proposed framework for real data (in a advising manufacturing firm) is performed and the gained results by the experts and cross-functional team members (that was convened to judge and make outsourcing decision in the firm) is approved.
THE DECISION-MAKING FRAMEWORK
Phase 1: In first phase of developed framework, must be identified that
the activity under consider is core or non-core? Because sustaining the competitive
advantages, the core activities must be performed in-house. Mclvor
et al. (1997) defined core activity as is central to the company
successfully serving the needs of potential customers in each market. Arnold
(2000) defined core activities such that all activities which are necessarily
linked to the firm's existence. Arnold (2000) called
these activities as the companys core.
Mclvor et al. (1997) believed that distinguishing
between core and non-core activities is a difficult task and it needs to sufficient
accuracy. The guidelines for identifying core activities (and examples of these
activities) should be developed by top management.
If the activity was core, rationally, this must be performed inside the firm
(Venkatesan, 1992; Mclvor et al.,
1997); but, the logical question is that are firms capability and
If the firms capability and capacity were not enough, the firm must be enhance them. These enhancement may be realized by research and development and other investments such as purchasing new equipments, technology acquisition from outside of the firm and so on.
Phase 2: If considered activity was not core, should be referred to second phase. In phase 2, a fuzzy multi-criteria decision-making model based on TOPSIS technique (Technique for Order Preference by Similarity to Ideal Solution) and application of the fuzzy set theory has developed.
The decision-making criteria (or factors) may be changed from a range of candidate activities to others; for example, the decision-making criteria of RandD (Research and Development) activities may be differed from manufacturing activities. In this article have been concentrated on manufacturing activities and hence, proposed decision-making criteria have been developed related to manufacturing conditions. On the other hand, the considered alternaties in this article consist of performing activity in-house or internally and outsourcing.
In this phase, the criteria have been developed in two categories:
In strategic criteria, four criteria core competency, information risk and ability and in economic criteria, only total cost have been considered.
The proposed criteria in this article based on both conditions of real production
environments and review of proposed criteria in previous works, especially Quinn
and Hilmer (1994) and Mantel et al. (2006)
and also, Fine and Whitney (1996) that was expressed two
dimensions of dependency to suppliers (knowledge and capacity) are developed.
Also Tayles and Colin (2001) hint to capability and
capacity. In this article, these factors called to gather as ability.
Although, in first phase, the core activities have been screened but it may
be exist the traces or vestiges of firms core competency in activities
which have been came to second phase. So, in phase 2, the risk of core competency
damage (lose) has been noticed. As Arnold (2000) cited,
core competencies have three characteristics:
||Differentiation between the company and its competitors
||Impossible to imitate by competitors over time
||Usable for multiple purpose
Each resources with these characteristics are core competencies and should remain within a company and should not be outsourced.
In addition to core competencies, can not be passed easily from significance of the firm`s key information. Often, because dissemination of some information like the information of firms new technologies or products in hand (under working) and disclosure them for the competitors, future of firms competitive position may be faced to serious risks. Therefore, risk of information dissemination should be consider about each nominated activity which has been acceded to phase 2.
Another important condition to perform each activity is existing of enough
capability determine whether the firm has the capability to perform the activity
(process). Also, the next question is that do it have enough capacity? Tayles
and Colin (2001) defined that capacity is about the availability of resources
include labour, capital, plant and equipment time.
||The proposed framework for outsourcing decision-making
||Criteria, sub-criteria and related measures of phase 2
In this study, sum of capability and capacity has been called ability. Beside
to strategic criteria, the total cost of activity performing has been considered
as the measure of the economic criteria which used in phase 2. Criteria and
sub-criteria are shown in Fig. 1 and the measures of (sub)criteria
are shown in Table 1.
The decision-making model based on fuzzy TOPSIS: The technique used
here is TOPSIS technique (Technique for Order Preference by Similarity to Ideal
Solution); Generally, the numerical data (related to quantitative factors) may
be not available carefully and also, data of qualitative factors should be asked
from experts in the form of linguistic variables. So, moreover TOPSIS as decision-making
technique, fuzzy sets theory were utilized. In order to attain technical principles
of fuzzy TOPSIS, the study of Bottani and Rizzi (2006)
has been used. The steps of the decision-making model are:
|To determine the relative importance (or weight) of factors by paired
|To determine the level of each factor for both two alternatives in the
form of linguistic judgements
|To transform expert opinions (linguistic judgements) to fuzzy triangular
numbers and to establish the initial numerical matrix
|To normalize the numerical data and to establish the weighted matrix.
In order to attain normalized data bottom equations (Bottani
and Rizzi, 2006) were applied:
To calculate the distances of the alternatives (in-house and outsourcing) from
ideal values by below equations (Bottani and Rizzi, 2006):
Finally, to calculate the final ratio (Eq. 5) and select (suggest) the appropriate alternative.
Whatever the final ratio of an alternative is larger, this alternative is better; because, the final ratio is the relative distance of negative ideal.
THE FRAMEWORK APPLICATION
In order to apply the framework in the real case, the data of some manufacturing activities belong to a firm that manufactures parts and subassemblies for OEMs in aviation industry were used.
For performing this framework, a cross-functional team were shaped and some workshops were implemented. During these sessions, the framework were described and considered data were collected. then, paired comparison between factors were performed (based on consensus of the team members) to determine the relative importance (or weight) of measures (as shown in Table 2).
In continuance, based on consensus of team members, Level of each factor for
each alternative were recorded (in the form of linguistic variables). These
levels consist of Very Low (VL), Low (L), Medium Low (ML), Medium (M), Medium
High (MH), High (H) and Very High (VH) (Zimmermann, 1991;
Bottani and Rizzi, 2006). This fuzzy numbers were showed
in Fig. 2. Finally, based on data collected and the decision-making
model, the appropriate alternative (in-house or outsourcing) were made.
In this case, the assembly of final products identified as one of the core activities. About other activities, for example, one of the nominated activity is manufacturing of a part as called DPC. This part is manufactured by casting technology. The activity of DPC manufacturing is not core and hence, retaining this activity is not necessary (the activity code is 22-CAS-DP_).
Technological capability for this activity is at high level internally and also, its potential suppliers have very capable in this way. From capacity viewpoint, the firm is average but the external suppliers have sufficient capacity. Also, internal total cost is less than the considered potential suppliers. 22-CAS-DP_ doesnt contain any core competency and then, its outsourcing hasnt drawback consequences for present core competencies; although, because abondoning it may be lost a little information of firm.
After execution of the decision-making model for this activity, acquired recommend is outsourcing. The steps of the model and related computations are shown in Table 3.
||Expressing the criteria levels by fuzzy numbers
||The relative importance of factors
||An example of calculations for 22-CAS-DP
||Outsourcing decision-making for five manufacturing activities
Moreover, the results of decision-making for five activities (this activity beside to other four activities) have been shown in Table 4.
The identified gaps from the literature review consisted of little attention to mathematical modeling in decision-making outsourcing problems and considering this problem as a multi-criteria problem and also, lacking appropriate access to reliable data in real environments. By developing the proposed framework, has been tried to remove these shortcomings; meanwhile, the framework in this article has been developed for manufacturing activities.
Applicability is one of the strengths of this framework. Beside to, the concentration on the core activities and retaining them inside the firm in order to protect competitive advantages is another sufficiency dimension of this framework. Although, identification of the core activities and how to enrichment of the firm`s ability is required to deeper studies.
Another strength of this framework is a decision-making model based on multi-criteria technique (TOPSIS) and linguistic judgements that were resulted to using fuzzy sets; hereby, data gathering has been facilitated and the results is more adequate; but, due to framework application has been understood that the model in second phase is sensitive to weights and hence, in future research paying attention to this issue is necessary.