عوامل ساختاری تیم NPD (توسعه محصول جدید) برای توانایی تولید
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|2752||2009||13 صفحه PDF||سفارش دهید||8780 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Project Management, Volume 27, Issue 7, October 2009, Pages 690–702
We explore whether structural factors of NPD (new product development) team such as its physical co-location and team composition are still relevant and important in enhancing manufacturability as part of NPD performance in this highly virtualized coordination era as much as in the past before the Internet. We also examine how the analysis result is affected by the product’s innovativeness as well as other control variables like project duration and product type. In order to answer the research questions, we collected data on 127 projects of new product development at a global consumer electronics company. Based on our analysis, we conclude that whether the NPD members are physically co-located throughout the product development process and whether the team membership is balanced have profound implications for enhancing manufacturability.
Developing a new product successfully is an important competitive advantage for a firm. For successful new product development (NPD), a firm must be able to develop an innovative product that appeals to the customer and manufacture it in large quantity in order to reap profit from the mass market : its ability to manage the ramp-up production effectively, i.e., manufacturability, is essential to the eventual success of new product development. Manufacturability is a quality of new product development that ensures the product can be produced efficiently and reliably in the manufacturing process. It is measured by the time required to ramp-up production to desired volume levels, by production yields, or by product cost and quality levels . That is, a major link between developing a new product and manufacturing lies in the ability to restore the production system to high productivity and low yield loss as quickly as possible following the new product’s introduction  and . From an operations strategy perspective, therefore, reducing the defect rate during the ramp-up production process is an important measure for introducing the new product to the mass market fast and reliably. In this research, our primary focus is on such manufacturability: we explore how structural variables such as NPD team’s physical co-location and composition affect manufacturability. These variables represent structural characteristics of the NPD team, distinct from more qualitative, behavioral factors. In the past, especially during 1980s and early 1990s, i.e., before the concept of ‘virtual coordination’ was fully developed, researchers identified key variables, behavioral and structural, that could determine the cross-functional team (CFT) performance in new product development: physical proximity  and balanced composition  of the CFT membership were two of the most important structural variables, proposed in the literature. More recently, notably since mid 1990s, however, there have been fundamental changes in organizations, relating to emergence of virtual organizations : researchers  suggested that these virtual organizations would be logical forms for organizations in the future, weakening or even nullifying some of the research outcomes in the past. In this context, our research was motivated by a question, whether the structural variables such as physical proximity and CFT composition still remain relevant and important in deciding the NPD performance in this highly virtualized coordination era as much as in the past before the Internet. To answer the question, we collected and analyzed actual data on 127 new product development projects conducted in 2006 and 2007 at a global consumer electronics company. The paper is structured as follows. In the next section, we survey relevant literature. Then, we formally develop the research framework, explain the data and their collection process in detail, and suggest key hypotheses. In Section 4, we present data analysis and major outcomes from the analysis: the primary methods are multivariate and stepwise regression analysis and path analysis. Based on the analysis result, we derive managerial implications and discuss conclusions along with potential contributions of this research to the literature.
نتیجه گیری انگلیسی
We’ve tried to identify structural factors of an NPD team to improve manufacturability . Our analysis results indicate the following. First, it is strongly supported that both the co-location and the balanced composition are instrumental in improving manufacturability: as mentioned when suggesting hypotheses, our analysis result supports that the physical co-location should be still relevant and important in this highly virtualized coordination era; it is important to have a ‘right mix, i.e., balanced team, not just ‘any mix.’ But, although we conjectured that the co-loca- tion is more important for an incremental product whereas the balanced composition is more crucial for an innovative product, there seems to be little evidence that supports the conjecture strongly. A more in-depth investigation via path analysis, however, led us to conclude that the relationship might be less clear because the company has tendency to form a co-located team more often for an innovative prod- uct than for an incremental one. Overall the analysis conﬁrms our corollaries about the role played by the design and the marketing function. For an innovative product, the design function played the most signiﬁcant role in enhancing manufacturability, while the marketing’s role showed signiﬁcance for an incre- mental product. For manufacturability, the design function must play a signiﬁcant role for an innovative product: note that an innovative product poses novel challenges to the ﬁrm since it does not have enough experience and/or exper- tise that is readily applicable to the new innovative product, and thus the design function must continue to be heavily involved. On the other hand, when the ﬁrm tries to develop a new product derived from existing or previous ones, it does not have to spend much time on making sure the new product is ﬁt with the current manufacturing system technically and/or in an engineering sense. Rather, the ﬁrm has to incorporate market requirements into the new prod- uct throughout the NPD process as much as possible in a way to foster manufacturability. Our contribution to the literature is non-trivial. First, we’ve speciﬁcally focused on enhancing manufacturability, using the ramp-up production quality as the performance measure, and collected and analyzed high quality real data, which are very objective unlike those derived from survey questionnaires. In addition, we formally deﬁned two con- structs in a way much more reﬁned than those in the liter- ature: comparing physically co-located with purely virtual NPD teams has not been rigorously undertaken in the liter- ature; CFT balancedness has highlighted the importance of equal or balanced representation of each related function in the CFT, while the literature usually emphasized the diverse composition, leaving a possibility of biased or skewed team. A managerial implication is that managers have to understand two major structural factors of the NPD team that aﬀect manufacturability, the physical co-location and the balanced (not just diversiﬁed) composition of the CFT,even when highly sophisticated telecommunication systems are used for virtual coordination and the CFT members are all highly capable and have relevant expertise. In addition,they should pay extra attention to the role played by the design and the marketing function, depending on the level of innovativeness of the product in question.There are disadvantages as well as advantages in using data from a single company. Having a highly reliable and accurate data is probably the most valuable advantage. On the other hand, there might be an issue of wide applica- bility of the results to diﬀerent contexts and industries. Regarding generalizability, we point out one additional quality of the data we used: these data are not subjective data based on survey questionnaires, but hard data that have been formally and consistently recorded by the company throughout the new product development processes. Therefore, we believe we can overcome a critique concerned about generalizability.