Information systems outsourcing decisions using a group decision-making approach

Abstract

Outsourcing refers to a company that contracts with another company to provide services that might otherwise be performed by in-house employees. Information system (IS) outsourcing policies define the criteria that organizations utilize to decide upon the scope and degree of reliance of their IS capabilities upon external sources. IS outsourcing is an innovative organizational tool for IS management in both private and public sector organizations. In this paper, an interactive group decision-making methodology is proposed to select/rank IS providers under multiple criteria. A measure for the consensus level of the group preferences is developed to satisfy an acceptable level of group agreement and reliability. The Spearman coefficients for both the aggregated rank order and each DM's rank order have also been calculated. The group and the individual evaluations are gathered through a fuzzy TOPSIS approach. The proposed methodology is applied in the largest office furniture manufacturer in Konya-Turkey. Eight alternative IS providers are evaluated based on seven criteria by five decision makers. Sensitivity analyses are also provided to see the effects of parameter changes on the final decision.

Introduction

Outsourcing is increasingly used to refer to sub-contracting of a set of functions or processes by one firm to another, or to a group of individuals. The latter organization is often in another physical location, or another country altogether. Outsourcing can be seen as a strategic way to align technology initiatives and business goals, as a strategy for managing technology operations in today's difficult business environment, and as a way to reduce operating costs. Often, companies begin the process by outsourcing non-essential business operations, which may include applications, assets, people and other resources. Yet outsourcing carries risks: loss of control and flexibility and geopolitical uncertainty in the case of offshore outsourcing.

The outsourcing theory that was originally developed by Williamson in 1975 explains the reasons due to which firms produce certain goods or services internally or acquire them outside the firm through a transaction in the market, considering whether transaction costs exceed or not production and coordination costs using the firm's own staff (Gonzalez et al., 2005). In different industries, firms have done these activities for many years. Some examples are the industries in the manufacturing sector such as automotive, shipbuilding, aircraft, computers, mobile phones, audio/video systems, mechanical watches, air conditioning, and the other specialized manufacturers. Although the idea of outsourcing activities is not new, the practice of information system (IS) outsourcing has been around since 1954. Outsourcing became very popular in the 1990s, encouraged by success such as Eastman Kodak's externalization of ISs and outsourcing is often presented as an attractive business proposition to improve productivity reduce cost and increase competitiveness (Chou et al., 2006).

In the literature, outsourcing decisions are often based on multicriteria approaches and group decisions. Group decision making is a type of participatory process in which multiple individuals acting collectively, analyze problems or situations, consider and evaluate alternative courses of action, and select from among the alternatives a solution or solutions. The criteria taken into account for outsourcing decisions are generally economics, resource, strategy, risk, management, and quality. In recent years some papers have been concentrated on outsourcing and IS outsourcing. Chen et al. (2006) presented a fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. In the study, five criteria were considered; profitability of supplier, relationship closeness, technological capability, conformance quality, and conflict resolution. The technique for order preference by similarity to ideal solution (TOPSIS) was proposed to solve the supplier selection problem under a fuzzy environment. Shyur and Shih (2006) proposed a hybrid model for supporting the vendor selection process in new task situations. Firstly, they formulated the vendor selection problem by the use of the multicriteria decision-making approach. Second, they proposed an analytic network process and the last, they used a modified TOPSIS method. Araz et al. (2007) proposed a methodology for outsourcing management, using the information obtained from outsourcing selection process. The developed model allows the incorporation of decision maker's imprecise aspiration levels for the goals by means of interactive fuzzy goal programming approach. The application was made in a textile company. At the first phase of the study, evaluation criteria for outsourcers and the objective of the company were determined. The existing outsourcers of the company were evaluated by Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). At the second phase, the developed fuzzy goal programming model selects the most appropriate outsourcers suitable to be strategic partners with the company and simultaneously allocates the quantities to be ordered them. The results are compared with the current situation of the company. Işıklar et al. (2007) proposed an integrated intelligent decision support model for effective supplier selection problem. The proposed framework integrated case-based reasoning, rule-based reasoning and compromise programming techniques in fuzzy environment. Yang et al. (2007) identified factors affecting the business process outsourcing decision and structured a decision model using the analytic hierarchy process (AHP) method. The categorization of outsourcing decision was expectation, risk, and environment perspective. The sub-criteria of expectation were cost savings, focus on core competence, and flexibility. The sub-criteria of risk were information security, loss of management control, labour union, and morale problem and the sub criterion of environment was vendor's service quality. Olson (2006) presented a multicriteria approach for evaluating of enterprise resource planning outsourcing decisions. Almeida (2007) presented a multicriteria decision model for outsourcing vendor selection, using contributions from utility theory associated with ELECTRE method. Two different multicriteria approaches were used for the problems. These methods were multi-attribute utility theory (MAUT) and PROMETHEE. Cao and Wang (2007) proposed a two-stage vendor selection research framework in outsourcing. The first stage was a trial phase that helped the client to find the best match between the vendor and the outsourced project. In the second stage, the client employed the chosen vendor for the full implementation of the project. This selection decision was formulated under the two-stage framework as a combinatorial optimization model. Hafeez et al. (2007) presented a structured framework for identifying the competences of firms based on “uniqueness and collectiveness characteristics”. Two AHP-based methods were developed for evaluating competences and assets of a firm. Chen et al. (2007) used a fuzzy decision tree to form a search mechanism for vague knowledge in design for outsourcing with index for classifying vague knowledge. Holcomb and Hitt (2007) proposed a theoretical model for strategic outsourcing. Wang and Yang (2007) considered six factors, including economics, resource, strategy, risk, management, and quality for outsourcing decisions and proposed the AHP and PROMETHEE as aids in making IS outsourcing decisions. Wadhwa and Ravindran (2007) modeled the vendor selection problem as a multi-objective optimization problem, where one or more buyers ordered multiple products from different vendors in a multiple sourcing network. They considered three conflicting criteria such as price, lead-time and rejects (quality) to be minimized simultaneously. Yang and Huang (2000) proposed a decision model, which used AHP method to help users in structuring the outsourcing problems. The decision model was generated numeric values for users to decide whether they should adopt the outsourcing strategy for each IS under consideration. In that outsourcing decisions model, five factors; management, strategy, economics, technology, and quality were employed. The problem of how to make IS outsourcing decisions process is very important for the firms. There are many research in the field of IS outsourcing decision making. Nellore and Söderquist (2000) proposed an extension based on the role that specifications might play in outsourcing decisions. This research was based on a longitudinal study of one automotive OEM (global family), one truck OEM and four medium-sized expert suppliers, all located in Europe. Ngwenyama and Bryson (1999) proposed a model for analyzing outsourcing decisions based on transaction cost theory. The model provides managers with a framework, approach and a set of techniques for exploring some of the more subtle issues of complex outsourcing decision problems. In a later study, Bryson and Ngwenyama (2006) presented a method and some mathematical models for analyzing risks and constructing incentive contracts for information science (IS) outsourcing.

The aim of this paper is first to determine the companies needing IS outsourcing. These companies are determined by using a multiple criteria method, namely TOPSIS. Sensitivity analyses are also added to see the effects of parameter changes. This paper is organized as follows. The basics of outsourcing are given in Section 2. In Section 3, IS outsourcing is introduced. In Section 4, a fuzzy group decision making methodology based on TOPSIS is presented. And then the proposed method is illustrated with an application in Section 5. The conclusion and suggestions for further research are presented in Section 6.