Evaluating QFD's Use in US Firms as a Process for Developing Products

Quality Function Deployment (QFD) is a process that originated in Japan for managing product development. In this article, Abbie Griffin presents results of a field-based, scientific study of US firms' efforts to implement QFD methods. Her research goals were to understand the QFD process as it is used and implemented, to begin to estimate US product development improvements attributable to QFD and to identify factors linked to QFD's successful use. Based on a study of 35 projects, she found that QFD demonstrated only relatively minor, short-term, measurable impacts on product development performance. Yet, the process may have the potential to improve the development climate in the long term, possibly leading to future, measurable improvements in development performance. Successful projects differed in several ways from those projects that failed in their implementation efforts. Finally, the results suggest several characteristics of product development processes that improve the way products are developed in US companies, including structuring the decision-making processes across functional groups, building a solidly organized, highly motivated team and moving information efficiently from its origin to the ultimate user.     

A comparison of quality function deployment and conjoint analysis in new product design

In this work, we compare two product design approaches, quality function deployment (QFD) and conjoint analysis, by applying each to the design of a new all-purpose climbing harness for the beginning/intermediate ability climber that would complement a leading manufacturer's existing product line. While many of the optimal design features were the same under both approaches, the differences allow us to highlight the strengths of each approach. With conjoint analysis, it was easier to compare the most preferred features (i.e., ones that maximized sales) to profit maximizing features and also to develop designs that optimize product line sales or profits. On the other hand, QFD was able to highlight the fact that certain engineering characteristics or design features had both positive and negative aspects. This tradeoff could point the way to "out of the box" solutions. QFD also highlighted the importance of starting explicitly with customer needs, regardless of which method is used.
Rather than competing, we view them as complementary approaches that should be conducted simultaneously; each providing feedback to the other. When the two approaches differed on the optimal level or importance of a feature, it appeared that conjoint analysis better captured customers' current preferences for product features while QFD captured what product developers thought would best satisfy customer needs. Looking at the problem through these different lenses provides a useful dialogue that should not be missed. QFD's ability to generate creative or novel solutions should be combined with conjoint analysis' ability to forecast market reaction to design changes. © 2002 Elsevier Science Inc. All rights reserved.     

Ranking the strategic actions of Iran mobile cellular telecommunication using two models of fuzzy QFD

Mobile cellular telecommunication success in target markets first requires ranking the customer’s expectations and then prioritizing the engineering characteristics (ECs) to meet the expectations. In this paper, two prioritization models based on quality function deployment (QFD) are developed to rank the strategic actions (SAs), or the ECs of Iran mobile cellular telecommunication. QFD is a widely used customer-driven tool for which the success of its applications may be the result of some of its benefits, such as greater customer focus. It uses a matrix called House of Quality (HOQ) to translate Customer Attributes (CAs) into ECs. However, due to the high degree of subjectivity in constructing the HOQ, the application of fuzzy logic provides an efficient tool to handle the subjective assessments. On the other hand, taking into consideration the gap between the current state and the positive ideal state for each CA, TOPSIS is used to rank CAs in a first model. In addition, in a second model, using the analytic hierarchy process (AHP), more criteria are taken into consideration in ranking CAs. Also, a fuzzy utility factor, B_j, is used to rank SAs in both models. Both presented models have the ability to capture the vagueness of human thinking style, and let customer oriented organizations, such as MCI, derive benefits from the voice of the customer (VOC) in a more expressive way.     

QFD—linking the customer to the product development process as a part of the TQM concept

LKAB is one of the world's leading sup-pliers of advanced iron ore products. Its most important markets are the blast furnace based steelworks of Europe. As a result of customers' demands for ever-better products, LKAB has begun to apply Quality Function Deployment (QFD) to its product development pro-grammes. QFD, originally developed in Japan, is a technique which utilises a series of matrices to translate customers' requirements into technical specifications that the producer can use. So far the methodology has mainly been used in the manufacturing industry, with very few applications in process industry.
When launching its QFD project, LKAB began by making strenuous efforts to acquire credible and relevant customer data. Experience after one year's work has been encouraging; the QFD technique has proved to be an effective instrument for feeding customers' requirements into the product development process. In addition, it serves as a guide to setting priorities for research projects. The technique promises to become an established tool in the cornpany's Total Quality Management programme.     

Customer-Driven Product Development Through Quality Function Deployment in the U.S. and Japan

Quality Function Deployment is a tool for bringing the voice of the customer into the product development process from conceptual design through to manufacturing. It begins with a matrix that links customer desires to product engineering requirements, along with competitive benchmarking information, and further matrices can be used to ultimately link this to design of the manufacturing system. Unlike other methods originally developed in the U.S. and transferred to Japan, the QFD methodology was born out of Total Quality Control (TQC) activities in Japan during the 1960s and has been transferred to companies in the U.S. This article reports on the results of a 1995 survey of more than 400 companies in the U.S. and Japan using QFD. The research questions investigated in this study were developed both inductively from QFD case studies in the U.S. and Japan and deductively from the literature. The reported results are in part counterintuitive. The U.S. companies reported a higher degree of usage, management support, cross‐functional involvement, use of QFD driven data sources, and perceived benefits from using QFD. For the most part, the main uses of QFD in the U.S. were restricted to the first matrix (“House of Quality”) that links customer requirements to product engineering requirements and rarely was this carried forward to later matrices. U.S. companies were more apt to use newly collected customer data sources (e.g., focus groups) and methods for analyzing customer requirements. Japanese companies reported using existing product data (e.g., warranty) and a broader set of matrices to a greater extent. The use of analytical techniques in conjunction with QFD (e.g., simulation, design of experiments, regression, mathematical target setting, and analytic hierarchy process) was not wide spread in either country. U.S. companies were more likely to report benefits of QFD in improving cross‐functional integration and better decision‐making processes compared to Japanese companies. Possible reasons for these cross‐national differences as well as their implications are discussed.     

Product competence exploitation and exploration strategies: The impact on new product performance through quality and innovativeness

The ability to manage existing assets and capabilities (exploitation) and the development of new capabilities (exploration) are arguably among the most relevant new product success factors. However, while exploitation-related capabilities are based on certainties regarding the efficiency of a company, exploration-related capabilities require the analysis of new technologies and processes. In existing literature, there is a gap concerning the trade-off between the exploitation and exploration of competences. Based on the theoretical background of Resource Based Theory, Dynamic Capabilities Theory and Discovery and Creation Theory, a model is proposed to analyze this gap. In this study, which examines 197 manufacturing organizations, we build on the dualities of the two types of competences and their impact on speed-to-market and market performance. The findings indicate that the choice between exploitation and exploration depends on the goals of new product development. While exploitation increases product objective quality, exploration enhances product innovativeness to the firm. Furthermore, we found that both exploitation and exploration constitute important success factors when it comes to launching new products. Finally, moderate effects of competitive intensity and market turbulence are also examined. High levels of market turbulence improve the results of exploitation, while low levels of competitiveness may encourage exploration.     

供应链可靠度管理中的模糊QFD应用

在供应链管理（SCM）中,人们更关注于寻找一种系统的方法,能够在计划阶段对可靠度进行评估。提出了一种模糊QFD模型,使其能够在供应链管理的过程中,传达用户需求与设计参数间的模糊关系;同时提出一套模糊的决策程序：模糊多准则决策．用来寻找一组CRT设计中可靠度需求性能的最优解。主要目的是找出合适的可靠性测试等级,以便使每一条供应链中模糊需求与产品生产参数之间的关系更加合理,以满足用户的需求。     

Product price and performance level in one market or two separated markets under various cost structures and functions

Market characteristics, including intrinsic demand and customer sensitivity on price and product performance level, are distinct at different markets. Comparisons of various product development strategies in one market or two geographically separated markets are conducted for three classes of products: development intensive products (DIPs) with constant unit cost, marginal cost-intensive products (MIPs) with constant fixed cost, and marginal and development intensive products (MDIPs) with non-constant unit cost and fixed cost. Results show that larger demand size, less customer sensitivity on price and/or more sensitivity on performance level lead to more profit, a higher sale price and a not-lower product performance. The customer reservation or the saturation performance level should be generally adopted though the optimal performance level does exist occasionally. Unit cost and/or fixed cost must increase in performance at an increasing rate for the existence of one optimal performance level. Due to the impact of demand size, one high-end (low-end) MDIP or DIP could be introduced into one low-end (high-end) market at a different price if the demand size is significantly large in the low-end market. For DIPs, offering one niche high-end product is not worse than offering the low-end product into two markets. For MIPs with negligible fixed cost, the product line strategy is not worse than the standard product development strategy. Additionally, the product cost reduction approach adopted in one product line has significant effects on the best product development strategy and sequence.     

Optimal pricing and order policies with B2B product returns for fashion products

We study optimal pricing and order policies in supply chain management of fashion products (e.g., a fashion apparel category) with consideration of product returns between supply chain partners (B2B). In order to study channel performance and optimal policies, two stochastic models for centralized channel and decentralized channel are, respectively, developed to handle new fashion and off-season product sales. In the centralized channel, closed-form solutions for optimal order and pricing decisions are proposed for new fashion products. Further, in a decentralized channel, the Stackelberg game model is proposed to derive the optimal Stackelberg equilibrium solution, and then a buy-back contract is designed to coordinate the channel. We also perform parameter analysis on performance of the two channel models. Numerical analysis is finally presented to validate our theoretical results and compare channel performances.     

Product configurator impact on product quality

More and more firms today rely on product configurators to more efficiently and effectively meet increasingly diverse customers’ needs. In literature, however, the discussion of the performance outcomes of product configurator use is limited and largely based on anecdotal evidence. Our paper contributes to fill this gap by developing and empirically testing hypotheses about the relationship between product configurator use and product quality. We find empirical support for the hypotheses that product configurator use improves product quality and that this relationship is negatively moderated by the difficulty for a company to determine the needs of its target market. We conclude by discussing implications of our findings for both research and practice.     

Theory of constraints and the combinatorial complexity of the product-mix decision

The theory of constraints (TOC) proposes that, when production is bounded by a single bottleneck, the best product mix heuristic is to select products based on their ratio of throughput per constraint use. This, however, is not true for cases when production is limited to integer quantities of final products. Four facts that go against current thought in the TOC literature are demonstrated in this paper. For example, there are cases in which the optimum product mix includes products with the lowest product margin and the lowest ratio of throughput per constraint time, simultaneously violating the margin heuristic and the TOC-derived heuristic. Such failures are due to the non-polynomial completeness (NP-completeness) of the product-mix decision problem, also demonstrated here.     

Integrating the Kano model into a robust design approach to enhance customer satisfaction with product design

The aesthetic qualities of products are critical factors in achieving higher customer satisfaction. This study presents a robust design approach incorporating the Kano model to obtain the optimal combination of design form elements. This can effectively enhance customer satisfaction and aesthetic product qualities with multiple-criteria characteristics. The Kano model is used to better understand the relationship between performance criteria and customer satisfaction, and to resolve trade-off dilemma in multiple-criteria optimization by identifying the key criteria in customer satisfaction. The robust design approach combines grey relational analysis with the Taguchi method to optimize subjective quality with multiple-criteria characteristics. This simultaneously yields the optimal aesthetic performance and reduces the variations in customer evaluations. Based on Kano model analysis, a weight adjustment process determines the weight of each product criterion for achieving the desired customer satisfaction performance. This process guides the prioritizing of multiple criteria, leading to higher customer satisfaction. A mobile phone design experiment was conducted to verify the benefits of using the proposed integrative approach. Results show that the generated optimal mobile phone design can effectively enhance overall aesthetic performance and customer satisfaction. Although mobile phone designs are the examples of this study, the proposed method may be further used as a universal robust design approach for enhancing customer satisfaction and product quality with multiple-criteria characteristics.     

The joint impact of quality and innovativeness on short-term new product performance

In the last decade a number of conceptualizations of product quality and innovativeness have been suggested, and academics as well as managers have begun to understand that the relationships between quality, innovativeness and new product performance are more complicated than they may initially seem to be. While an innovation-oriented strategy depends on the exploration of new possibilities through search, risk-taking and experimentation, a high quality strategy requires the exploitation of existing certainties through efficiency, standardization and control. In this research, we demonstrate that the interaction effects of quality (objective and subjective) and innovativeness (for the firm and for the customer) on new product performance are different than the isolated impact of these variables. In addition, by focusing on the main and joint impact of these variables on short-term new product performance, we provide valuable recommendations for new product launch decisions.“The pure and simple truth is rarely pure and never simple.”—Oscar Wilde     

The roles of stakeholder support and procedure-oriented management on asset recovery

As the management of returned products is fast becoming a business trend caused by pressure for compliance, asset recovery is increasingly viewed as a fertile area for firms to reduce cost and improve quality. Environmental management is a viable approach for Chinese manufacturers to respond to the escalating international quest for conserving the environment, to tackle the problem of rising raw material costs, and to improve product quality by analyzing returned products. To reach the goals of cost reduction and product quality improvement, manufacturers need to understand how asset recovery can be leveraged through procedure-based practices and stakeholder support to enhance performance. Product type, characterized by different levels of demand uncertainty and time-to-market, may affect the outcomes of asset recovery adoption and should also be taken into account. Drawing on the environmental management and business logistics literature, we provide empirical insights on asset recovery adoption using survey data collected from export-oriented Chinese manufacturers. We find that asset recovery and stakeholder support are complementary in strengthening manufacturers' financial performance regardless of product type. In addition, the performance impact of asset recovery can be substantial when manufacturers' environmental management practices are less procedural, allowing flexibility in the logistics management of product flows.     

Economic feasibility analysis of flexible material handling systems: A case study in the apparel industry

Flexible material handling systems (MHS) have been widely used to enhance productivity involved with product proliferation, and thus far, only fixed-track MHSs such as Eton systems in the apparel industry are commonly used. This paper explores the economic feasibility of a flexible MHS using free-ranging automated guided vehicles (AGV) with a local positioning system (LPS) for the apparel industry. A component-based and modified activity-based costing methodology is proposed to estimate the additional cost of adopting flexible MHSs, and then the internal rate of return (IIR) and payback periods are applied to evaluate the project economic performance. Results show that adopting flexible MHSs has a promising IIR which is larger than 30%.     

The role of the Internet in new product performance: A conceptual investigation

Past research has extensively investigated the role of the Internet in enhancing the effectiveness and efficiency of the new product development (NPD) process. Although the process implications of the use of the Internet in NPD have received considerable attention in the literature, very little is written about the Internet's performance implications in NPD. Recognizing the importance of new product success and the growing trends in the use of the Internet in NPD, this paper investigates the role of the Internet in new product performance. Building on previous studies, this article develops theoretical explanations for the impacts of the use of the Internet in NPD on new product success and presents testable research propositions. It also outlines relevant conditions that might moderate the strength of the impacts.     

Hybrid particle swarm optimization with mutation for optimizing industrial product lines: An application to a mixed solution space considering both discrete and continuous design variables

This article presents an artificial intelligence-based solution to the problem of product line optimization. More specifically, we apply a new hybrid particle swarm optimization (PSO) approach to design an optimal industrial product line. PSO is a biologically-inspired optimization framework derived from natural intelligence that exploits simple analogues of collective behavior found in nature, such as bird flocking and fish schooling. All existing product line optimization algorithms in the literature have been so far applied to consumer markets and product attributes that range across some discrete values. Our hybrid PSO algorithm searches for an optimal product line in a large design space which consists of both discrete and continuous design variables. The incorporation of a mutation operator to the standard PSO algorithm significantly improves its performance and enables our mechanism to outperform the state of the art Genetic Algorithm in a simulated study with artificial datasets pertaining to industrial cranes. The proposed approach deals with the problem of handling variables that can take any value from a continuous range and utilizes design variables associated with both product attributes and value-added services. The application of the proposed artificial intelligence framework yields important implications for strategic customer relationship and production management in business-to-business markets.     

Antecedents and Consequences of Creativity in Product Innovation Teams

The generation of creative ideas and their manifestation as new products (NPs) are fundamental innovation activities of product innovation teams. Despite the importance of generating creative ideas at the fuzzy front end of the product innovation process, our understanding of antecedents and consequences of creativity of product innovation teams is limited. Drawing on Shane and Ulrich's organization design perspective of innovation, this study aims at examining the intermediary role of creativity as a critical link between team dynamics and product competitive advantage. In this study, the authors focus on NP and marketing program (MP) creativity in product innovation teams. They develop and empirically test a model that examines how internal and external team dynamics influence NP and MP creativity, and how NP and MP creativity affect product competitive advantage as a strategic innovation outcome. The study uses 206 matched responses from senior managers and product team leaders in high‐tech manufacturing firms in the United States to avoid common‐method bias. The authors use maximum likelihood estimation in a structural equation model to empirically test the proposed model. They find that two separate dimensions of creativity—novelty and meaningfulness—are differentially affected by team dynamics. For example, NP novelty as a result of divergent process is predominantly influenced by external team factors such as market‐based reward system and planning process formalization. On the other hand, NP meaningfulness as a result of convergent process is dominantly influenced by internal team factors such as social cohesion and superordinate identity. In addition, MP novelty is determined by social cohesion, superordinate identity, planning process formalization, and encouragement to take risks, while MP meaningfulness is influenced by social cohesion and planning process formalization. Our findings also suggest that NP novelty and meaningfulness, but not MP novelty and meaningfulness, play important intermediary roles in determining product competitive advantage. This study contributes to narrowing the important gap in the literature by examining the effect of team dynamics on creativity and by linking creativity to strategic innovation outcomes. Our study suggests that a firm's ability to manage team dynamics toward generating creative NPs and MPs constitutes a dynamic capability that can provide a competitive advantage over the competition.     

What contributes to the enhanced use of customer, competition and technology knowledge for product innovation performance? : A survey of multinational industrial companies' subsidiaries operating in China

This study extends an emerging research area in knowledge management to new product development by empirically examining the factors associated with the use of different types of knowledge flows from various sources and product innovation performance (i.e., market success of new products) in the multinational companies' subsidiaries in China. The findings seem to indicate the vitality of considering a broad spectrum of knowledge management related variables such as a subsidiary's product development strategy, market conditions it faces, its knowledge capacity and knowledge support structure. Furthermore, we found that subsidiaries with better performance are generally excel in the use of competition knowledge flow, the development of moderate innovative products, communication among different functional departments or product development groups, the codification of knowledge, and a supportive culture.     

Improving the quality of corporate technical planning: dynamic analogues of QFD

This paper proposes a forecasting methodology based on a combination of QFD and S-curve analysis, In process industries there is a need to strengthen the linkages between process attributes, product attributes, and customer requirements. Industry planning processes accept the relationship between technological positioning, project portfolios, and market life cycles, but specific methods are seldom discussed.
QFD(Quality Function Deployment) can be used to translate customer requirements into product specifications and in turn to specify the process capabilities required to meet those customer requirements. The paper recommends that managements use analogues of QFD adapted to the need for dynamic changes in process capability.
This approach would focus on the interaction between key variables of customer requirements and the technological capabilities of the firm and its competitors, at present and in the future. Historical industry-wide capabilities would be projected through S-curve analysis, while customer requirements can be related to these capabilities through information from QFD studies focused on future customer requirements. Because of their potential complexity, these analyses should deal with only a very limited number of interacting attributes and special care should be given to the management of their implementation.