A fuzzy QFD approach to achieve agility
Introduction
The concept of “agility” was introduced by researchers of the Iacocca Institute (1991), and, since the first introduction, it has been receiving an increasing attention by both researchers and industrial communities. From 1990s until recently, many publications on the subject have appeared, which, due to its newness, attempt to provide a definition of agility. Currently accepted definitions relate agility to the ability of companies to respond quickly and effectively to (unexpected) changes in market demand (Brown and Bessant, 2003; Sharifi and Zhang, 2001; Fliedner and Vokurka, 1997), with the aim to meet varied customer requirements, in terms of price, specification, quality, quantity, and delivery (Prince and Kay, 2003). Agile enterprises react quickly and effectively to changing markets, driven by customised products and services. Moreover, agility directly affects company's capability to produce and deliver new products in a cost-efficient way (Swafford et al., 2006). Decrease in manufacturing costs, increased customer satisfaction, removal of non-value added activities and increased competitiveness (Lin et al., 2006) are among benefits that can be achieved through agile strategies. Accordingly, agility, encompassing both companies and the supply chain as a whole (Ren et al., 2001), is recognised as fundamental for survival in turbulent and volatile markets and to help companies to deliver the right product at the right time to the customers (Agarwal et al., 2007; Lin et al., 2006; Yusuf et al., 1999).
It is recognised in literature that agile enterprises are characterised by proper “attributes” (or “capabilities”) which allow companies to promptly respond to changes in business environment. Among others, agile attributes include integration of information systems or technologies, people, business processes and facilities (Ren et al., 2001; Christopher and Towill, 2001). However, as suggested by Ren et al. (2003), different agile attributes would lead to different levels of competitive priorities. Specifically, companies typically compete along several dimensions, such as, for instance, costs or responsiveness (see Yusuf et al., 1999, for a viable list of them), whose relative importance in achieving competitive advantage depends upon the specific market field. In addition, trade-off exists between competitive priorities, being recognised that companies cannot excel in all them simultaneously (Burgess et al., 1998). Consequently, agile attributes to be enhanced may vary depending on the competitive bases the companies are willing to excel in (Ren et al., 2003). Moreover, according to several conceptual models of agile enterprises available in literature (e.g., Lin et al., 2006), companies can exploit several leverages (i.e., agile “enablers”) to achieve the agile capabilities. Enablers include, among others, concurrent engineering practices or rapid prototyping tools (Gunasekaran, 1998).
The above considerations suggest a 3-step conceptual model to achieve agility, whose structure is accepted by several authors, as detailed in the next section. Specifically, the model consists of the following steps:
- 1.
according to the characteristics of the market field, companies should first define the competitive bases they are willing to excel in to achieve competitive advantage;
- 2.
agile attributes enhancing the selected competitive bases should be identified;
- 3.
finally, agile enablers to be exploited in order to achieve the required agile attributes should be identified and implemented by companies.
The remainder of the paper is organised as follows. In the next paragraph, we review previous studies related to agility, with a specific focus on (i) agile attributes; (ii) agile enablers; and (iii) methodologies to achieve agility. By discussing agile attributes and enablers available in literature, we strive to provide practitioners with the required fundamentals to apply the methodology developed to real cases. Moreover, methodologies to achieve agility are presented to show how the present paper goes beyond the existing literature. In particular, based on the findings from the literature, the contribution of the present work is detailed in Section 3. Then, the QFD approach is detailed. A numerical example is presented in Section 5 to illustrate the application of the methodology and to discuss the results provided. Limitations of the study and future research directions are finally sketched.
Section snippets
Agile attributes
The concept of agility introduced by the Iacocca Institute (1991) mainly refers to agile manufacturing. More recently, agility concepts have been extended to the entire supply chain, based on the assumption that companies cannot be truly agile by themselves (Christopher, 2000; Van Hoek et al., 2001). A comprehensive review of agile manufacturing literature was performed by Sanchez and Nagi (2001). The authors examined 73 papers focusing on nine main research topics of the subject, such as
Contribution of the study
A first outcome of the literature analysis is that none of the approach proposed in literature grounds on the QFD methodology. This latter, and specifically the HOQ, represents a practical tool, which allows directly assessing the impact of agile attributes on competitive bases and of agile enablers on agile attributes, through the relationships matrixes. Clearly, in practical cases, it would also be possible that a company directly identifies a set of suitable agile enablers to be implemented,
The proposed approach
In the approach proposed, QFD and HOQ principles are translated from the new products development field to the agility context. Specifically, we propose to exploit HOQ to first relate competitive bases to agile attributes, then agile attributes, in turn, to agility enablers. Accordingly, the basic structure of the approach proposed, as well as the conceptual model it follows, are shown in Fig. 1.
As can be seen from the figure, the approach proposed requires building two HOQs, whose specific
A numerical example
In this section, we provide a numerical example to illustrate the application of the methodology. The example aims at assessing the usefulness and ease of application of the tool, as well as at considering practical implications and limitations of the methodology proposed. Moreover, the example provides an illustration of the steps required to apply the methodology in practice; they can be summarised as follows:
- Step 1:
identifying the competitive bases a company is willing to excel in to achieve
Future research directions and conclusions
In this study, an original approach has been proposed which shows the applicability of the quality function deployment (QFD) methodology, and particularly of the house of quality (HOQ), to enhance agility of enterprises. As input, the approach requires defining the characteristics of the market where a company operates, expressed as competitive bases with a given importance weight; as output, it provides a set of agile enablers to be implemented by the company to achieve competitive advantage.
References (68)
- et al.
Modeling agility of supply chain, Industrial Marketing Management
(2007) - et al.
A self-assessment tool for implementing concurrent engineering through change management
International Journal of Project Management
(2003) - et al.
Strategic management of logistics service: a fuzzy QFD approach
International Journal of Production Economics
(2006) - et al.
Enabling technologies of agile manufacturing and its related activities in Korea
Computers & Industrial Engineering
(1996) The agile supply chain-competing in volatile markets
Industrial Marketing Management
(2000)- et al.
The effects of internal versus external integration practices on time-based performance and overall firm performance
Journal of Operations Management
(2004) - et al.
Information technology, organizational form, and transition to the market
Journal of Economic Behavior & Organization
(2006) - et al.
The fuzzy weighted average within a generalized means function
Computers & Mathematics with Applications
(2008) Agile manufacturing: a framework for research and development
International Journal of Production Economics
(1999)Preparing industrial suppliers for customer integration
Industrial Marketing Management
(2006)
Relationship between total quality management (TQM) and continuous improvement of international project management (CIIPM)
Technovation
Quality and work force management: from manufacturing managers’ perspective
Journal of Quality Management
Co-locating NPD? The need for combining project focus and organizational integration
Technovation
Agility index in the supply chain
International Journal of Production Economics
Total cycle time compression and the agile supply chain
International Journal of Production Economics
Achieving cost savings with innovative welding and examination techniques
International Journal of Pressure Vessels and Piping
Disentangling leanness and agility: an empirical investigation
Journal of Operations Management
Combining lean and agile characteristics: creation of virtual groups by enhanced production flow analysis
International Journal of Production Economics
The antecedents of supply chain agility of a firm: scale development and model testing
Journal of Operations Management
A new approach to quality function deployment planning with financial consideration
Computers & Operations Research
Designing supply chains: towards theory development
International Journal of Production Economics
A procedure for ordering fuzzy subsets of the unit interval
Information Science
Agile manufacturing: the drivers, concepts and attributes
International Journal of Production Economics
Fuzzy sets
Information and Control
Quality function deployment: the unused tool
Engineering Management Journal
The manufacturing strategy-capabilities links in mass customization and agile manufacturing-an exploratory study
International Journal of Operations and Production Management
Making the leap to agility—defining and achieving agile manufacturing through business process redesign and business network redesign
International Journal of Operations & Production Management
Competitive priorities, process innovations and time-based competition in the manufacturing sectors of industrialising economies: the case of Turkey
Benchmarking for Quality Management & Technology
Supply chain migration from lean and functional to agile and customized
Supply Chain Management: An International Journal
An integrated model for the design of agile supply chains
International Journal of Physical Distribution & Logistics Management
ERP adoption: a technological evolution approach
International Journal of Agile Management Systems
Linking of manufacturing strategy, market requirements and manufacturing attributes in technology choice: an expert system approach
The Engineering Economist
Quality performance and organizational culture: a New Zealand study
International Journal of Quality & Reliability Management
Cited by (138)
Decision-making on the selection of lean tools using fuzzy QFD and FMEA approach in the manufacturing industry
2022, Expert Systems with ApplicationsMatching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based method
2021, Computers and Industrial EngineeringCitation Excerpt :Most of these studies employ fuzzy methods to optimize QFD matrices. A few studies offer conceptual models based on QFD matrices (Bottani, 2009; Vinodh et al., 2011; Prasad et al., 2012; Tidwell and Sutterfield, 2012; de Fátima Cardoso et al., 2015). The scope of QFD-SCM studies focus on key attributes of supply chains (i.e., agility, resilience and flexibility, efficiency and effectiveness, leanness, reliability and security, and quality).
A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties
2020, International Journal of Production EconomicsPerformance Measurement with Lean, Agile and Green Considerations: An Interval-Valued Fuzzy TOPSIS Approach in Healthcare Industry
2024, International Journal of Supply and Operations ManagementDeploying Industry 5.0 drivers to enhance sustainable supply chain risk resilience
2024, International Journal of Sustainable Engineering