Technological Level and Product Development Cycle Time

This article investigates the link between product development cycle time and technological level in the final product, using a sample of 11 new car development projects. Reducing cycle time can create competitive advantages, but it also may lead to the development of technologically inferior products. Time is needed to digest and analyze technological problems. The conclusions from our study support the notion of a relationship between cycle time and technological level. Thus, there are important choices to be made regarding the desired level of technological maturity in the final product. This affects the required cycle time. Simply reducing the cycle time may not always be feasible or desirable     

Differential Effects of the Primary Forms of Cross Functional Integration on Product Development Cycle Time

In markets characterized by high rates of technological and market change product life cycles tend to be shorter, resulting in the increased importance of competing on the basis of product development cycle time. For firms operating in these dynamic market environments, competing on the basis of cycle time may not only be a source of competitive advantage, but in some industries may actually be essential for survival.
In this investigation the relative importance of five forms of cross functional integration and R&D integration of information or knowledge from past projects were explored in terms of their effects on product development cycle time. The five forms of cross functional integration included R&D/marketing integration, R&D/customer integration, R&D/manufacturing integration, R&D/supplier integration, and strategic partnerships. A sample of 65 U.S. and Scandinavian high technology firms (or strategic business units) were studied. The sample included firms from the computer, telecommunications, instruments, specialty chemicals, biotechnology, and software industries.
The results demonstrated that R&D integration of knowledge from past projects explained the largest degree of variation in product development cycle time. R&D/marketing integration and R&D/customer integration explained the next largest degree of variation in cycle time reduction. Cross cultural generalizability tests demonstrated that the results were generalizable across the U.S. and Scandinavian samples of firms. In addition, the results were found to be generalizable across industry or product category for five of the six forms of integration.     

Product Innovativeness and Entry Strategy: Impact on Cycle Time and Break-even Time

New product development time, or cycle time, has become a critical competitive variable, particularly for small high-tech manufacturing firms. The business press is filled with examples about large firms that have successfully reduced cycle time. This article investigates the relative impact of product innovation and entry strategy on cycle time and initial market performance of small firms. Using a sample of seventy-three small manufacturing firms, Abdul Ali, Robert Krapfel, Jr., and Douglas LaBahn find that faster product development is associated with shorter break-even time. Their results also indicate that these firms are achieving shorter cycle time not by sacrificing product quality, but by keeping the technical content of the product simple. Past research has not taken into account this relationship, and this may be one of the reasons why researchers have often suggested conflicting impact of entry strategy on market performance.     

Measuring New Product Success: The Difference that Time Perspective Makes

Management is often criticized for overemphasizing short-term profits at the expense of long-term growth. On the other hand, although numerous studies have explored the factors underlying new product success and failure, such studies rarely distinguish between short- and long-term success. In fact, little research has been conducted to explore the relationship between a company's time perspective and its choice of criteria for measuring new product success. For that matter, little consensus exists as to just what we mean by the term success. Expanding on work done by a PDMA task force on measurement of new product success and failure, Erik Jan Hultink and Henry S.J. Robben identify 16 core measures of new product success. In a survey of large Dutch companies, they explore managers' perceptions of new product success, hypothesizing that the importance attached to each of the 16 core measures depends on the company's time perspective. For example, they propose that criteria such as development cost and speed-to-market are more important in the short term, and return-on-investiment (ROI) is more important in the long term. The study also examines the type of market served, the innovation strategy, and the perceived innovativeness of the company's products. It is hypothesized that these factors will influence the importance the company attaches to the core measures of new product success. For example, it is expected that speed-to-market is probably more important for technological innovators than for fast imitators or cost minimizers. The findings support the hypothesis that the firm's time perspective influences the perceived importance of the core measures of success. For the short term, the respondents emphasize product-level measures such as speed-to-market and whether the product was launched on time. In the long term, the focus is on customer acceptance and financial performance, including attaining goals for profitability, margins, and ROI. Four factors are perceived as being equally important for short-term and long-term success: customer satisfaction, customer acceptance, meeting quality guidelines, and product performance level. Customer satisfaction was found to be the most important measure, regardless of a company's time perspective. Contrary to expectations, the perceived importance of the 16 core measures does not differ on the basis of the type of market, the innovation strategy, or the product's perceived innovativeness. In addition, the firm's functional orientation—technology push or market pull—does not affect the importance attached to the core measures of new product success.     

An Interim Report on Measuring Product Development Success and Failure

This article represents findings of a PDMA task force studying measures of product development success and failure. This investigation sought to identify all currently used measures, organize them into categories of similar measures that perform roughly the same function, and contrast the measures used by academics and companies to evaluate new product development performance. The authors compared the measures used in over seventy-five published studies of new product development to those surveyed companies say they use. The concept of product development success has many dimensions and each may be measured in a variety of ways. Firms generally use about four measures from two different categories in determining product development success. Academics and managers tend to focus on rather different sets of product development success/failure measures. Academics tend to investigate product development performance at the firm level, whereas managers currently measure, and indicate that they want to understand more completely, individual product success.     

Product Development Time Performance: Investigating the Effect of Interactions between Drivers

Rapid and punctual new product development (NPD) has become a top priority in many organizations as competitors rush to commercialize emerging technologies and to satisfy customer needs. Despite the importance of this issue, conceptual models or systematic testing of specific drivers that could improve time performances in NPD are few and far between. There is, however, a lack of extensive empirical research into whether “interactions” between different drivers affect time performances. This article aims to investigate whether drivers can interact and can influence time performances with a “synergistic” effect. A survey was carried out in order to study the effects of two‐way driver interactions on “launch on time” and “launch against an accelerated schedule.” Three groups of drivers within the development‐process, organizational‐mechanisms, and strategic‐capabilities were considered. As this is an exploratory study, two‐way interactions between drivers of different groups were analyzed in order to detect which drivers had a synergistic effect on time performances. The study was based on a sample of 85 manufacturing firms producing mainly industrial goods. The NPD program within each company was considered, i.e., the new products developed and launched in the last three years. The statistical approach used is suitable for exploratory surveys. In the first phase, the G‐correlation test was used to verify the effects of single drivers in order to help interpret the results regarding two‐way driver interactions. In the second phase, regression models with two‐way driver interaction were performed with both linear and logistic regression in order to discover which significant models had a significant driver interaction. The resulting 13 models showed that interactions played an important role in determining time performances. The following are some of the most interesting results, as they have managerial implications. The NP Strategic Guide (clear definition and communication of new product goals) interacts with and enhances the influence of other drivers, such as predevelopment tasks, project manager use, and supplier and customer involvement. Technological and up‐front staff capabilities create important interactions with product definition and with customer involvement, which avoids development delays. Furthermore, the authors of this study discovered that the adoption of an overlapping approach without a high level of interfunctional team use may not be time efficient. Thus, if a firm has to work to a tight development schedule, it should seek and should integrate any possible synergistic effects between team use and overlapping development phases. The insights into interactions provide useful information that can be used when setting priorities and can help to attain higher performances by adopting a combination of selected drivers. In particular, the best practices, which many studies have highlighted, do influence time performances that depend mainly on the so‐called strategic‐capabilities drivers. These latter variables, unlike practices and activities, require a complex learning process. The path toward improvements within the development‐process requires both long periods of time and an integrated view of the process; hence, improvements cannot be achieved by simply applying common practices. Therefore, analysis of interactions within the NPD field looks promising and requires further study.     

Increasing Learning and Time Efficiency in Interorganizational New Product Development Teams*

Despite the growing popularity of new product development across organizational boundaries, the processes, mechanisms, or dynamics that leverage performance in interorganizational (I‐O) product development teams are not well understood. Such teams are staffed with individuals drawn from the partnering firms and are relied on to develop successful new products while at the same time enhancing mutual learning and reducing development time. However, these collaborations can encounter difficulties when partners from different corporate cultures and thought worlds must coordinate and depend on one another and often lead to disappointing performance. To facilitate collaboration, the creation of a safe, supportive, challenging, and engaging environment is particularly important for enabling productive collaborative I‐O teamwork and is essential for learning and time efficient product development. This research develops and tests a model of proposed factors to increase both learning and time efficiency on I‐O new product teams. It is argued that specific behaviors (caring), beliefs (psychological safety), task‐related processes (shared problem solving), and governance mechanisms (clear management direction) create a positive climate that increases learning and time efficiency on I‐O teams. Results of an empirical study of 50 collaborative new product development projects indicate that (1) shared problem solving and caring behavior support both learning and time efficiency on I‐O teams, (2) team psychological safety is positively related to learning, (3) management direction is positively associated with time efficiency, and (4) shared problem solving is more strongly related to both performance dimensions than are the other factors. The factors supporting time efficiency are slightly different from those that foster learning. The relative importance of these factors also differs considerably for both performance aspects. Overall, this study contributes to a better understanding of the factors that facilitate a favorable environment for productive collaboration on I‐O teams, which go beyond contracts or top‐management supervision. Establishing such an environment can help to balance management concerns and promote the success of I‐O teams. The significance of the results is elevated by the fragility of collaborative ventures and their potential for failure, when firms with different organizational cultures, thought worlds, objectives, and intentions increasingly decide to work across organizational boundaries for the development of new products.     

Balancing Development Costs and Sales to Optimize the Development Time of Product Line Additions*

Development teams often use mental models to simplify development time decision making because a comprehensive empirical assessment of the trade‐offs across the metrics of development time, development costs, proficiency in market‐entry timing, and new product sales is simply not feasible. Surprisingly, these mental models have not been studied in prior research on the trade‐offs among the aforementioned metrics. These mental models are important to consider, however, because they define reality, specify what team members attend to, and guide their decision making. As such, these models influence how development teams make trade‐offs across the four metrics to try to optimize new product profitability. Teams with such an objective should manage to a development time that minimizes development costs and to a proficient market‐entry timing that maximizes new product sales. Yet many teams use mental models for development time decision making that focus either just on development costs or on proficiency in market‐entry timing. This survey‐based study uses data from 115 completed NPD projects, all product line additions from manufacturers in The Netherlands, to demonstrate that there is a cost to simplifying decision making. Making development time decisions without taking into account the contingency between development time and proficiency in market‐entry timing can be misleading, and using either a sales‐maximization or a cost‐minimization simplified decision‐making model may result in a cost penalty or a sales loss. The results from this study show that the development time that maximizes new product profitability is longer than the time that maximizes new product sales and is shorter than the development time that minimizes development costs. Furthermore, the results reveal that the cost penalty of sales maximization is smaller than the sales loss of development costs minimization. An important implication of the results is that, to determine the optimal development time, teams need to distinguish between cost and sales effects of development time reductions. To determine the relative impact of these effects this study also estimates the elasticities of development costs, new product sales, and new product profitability with regard to development time. Armed with this knowledge, development teams should be better equipped to make trade‐offs among the four metrics of development time, development costs, proficiency in market‐entry timing, and new product sales.     

Organizing for Product Development Projects

How should companies organize to support the development of new products? Erik Larson and David Gobeli assessed the relative effectiveness of five different project management structures by comparing the performance of 540 development projects in terms of cost, schedule and technical performance. The findings contradict Peters and Waterman's popular conclusion that project teams are superior to matrix structures for developing new products and services. Both the balanced matrix and project matrix compared favorably with project teams in terms of cost, schedule and technical performance. Furthermore, the project matrix received a stronger recommendation from managers than the project team. Little support was found for either the functional or functional matrix approach to project management.     

Cycle Time in Packaged Software Firms

Reduction of cycle time (i.e., time to market) is a fundamental competitive strategy in many industries. With the current proliferation of personal computer (PC) technology, software developers face intense competition. However, unlike their counterparts in other consumer goods markets, product development managers in the software industry appear to be less concerned with (or even aware of) cycle time than they are with other competitive variables. To explore the role of cycle-time reduction in the process of developing software packages, Erran Carmel conducted a study of 15 software package companies in the Washington-Baltimore metropolitan area. The survey results indicate that software package developers are generally unaware of cycle-time reduction as a management concept. Instead, software developers tend to focus on rapid development, with an emphasis on “crunch” periods of intense effort aimed at meeting a deadline. During these periods of peak activity, 87% of the developers in core teams worked more than 56 hours per week and 47% worked more than 71 hours per week. In terms of the organizational variables necessary for cycle-time reduction, all of the survey respondents point to the importance of a small, cohesive, core development team, similar to a cross-functional team. Members of the core team are entrepreneurial and share a common vision of the product's design, use, and long-term direction. As for the development variables associated with cycle-time reduction, the software companies in the survey typically do not use process models or risk analysis techniques. Similarly, they devote scant resources to automated tools. For the majority of the firms in the survey, annual investment in automated software development tools is less than $1,000 per developer. On the other hand, reuse (as embodied in object-oriented design and development) and incremental innovation are important to all of the sample firms. Although quality assurance (QA) activities are not addressed in the innovation literature, QA is a significant cycle-time component in software development. As demonstrated by the industry practice of releasing products with long lists of known defects, the software product category clearly has quality problems. With the current boom in new users, pressure will grow for improved quality. To remain competitive, software developers need to determine how they can better integrate QA activities into the development process while reducing cycle time.     

Product Development

This study investigates the prevalence of product-development courses at accredited educational institutions. The authors assess pedagogical approaches and instructional materials used in these courses. The analysis is based on a survey of 320 accredited business schools, supplemented by an archival review of other business schools' catalogs. The results suggest considerable growth in the number of product development/management courses compared to a decade ago. Four textbooks dominate the market, but other contenders for adoption are available. Cases are commonly used to facilitate understanding of presented issues. Geographic differences show that schools located in the Northeast, Midwest, and West are more likely to address product-related issues in their business curricula.     

The Moderating Effect of Environmental Uncertainty on New Product Development and Time Efficiency*

This empirical study examines the influence of environmental uncertainty on industrial product innovation. The present study addresses what is believed to be a shortcoming in the new product development literature and explores potential effects of environmental uncertainty on the development process, project organization, and on project timeliness with a sample of development projects in two countries, Canada and Australia. When looking at the combined sample of 182 completed projects, this study finds that the perceived market‐related project environment has a direct and positive impact on time efficiency. Further, this research finds that a higher degree of technological uncertainty moderates the relationship between development process, project organization and time efficiency. Consequently, innovating companies may benefit by adapting some of their development approaches to different environmental conditions and to varying degrees of uncertainty. However, when examining country‐specific effects, the results change quite significantly. In particular, the findings indicate that environmental uncertainty in the Canadian sample neither directly impacts time efficiency, nor does it have any moderating effect. Instead, technical proficiency in the development process, project team organization, and process compression appear to be viable strategies to increase time‐efficient development. In contrast, the results of the Australian study suggest that perceived market and technological uncertainty impact time efficiency. In particular, under conditions of technological unpredictability, project team organization increases time efficiency, whereas process compression appears to decrease time‐efficient product development. However, process compression seems to be a viable strategy in environments characterized by lower technological uncertainty. The results also point to the importance of disaggregating data when studying product development processes across countries.     

New Product Development Structures: The Effect of Customer Overload on Post-Concept Time to Market

In corporate policy statements, seminars, journal articles—even in television commercials—the message comes through loud and clear: To remain competitive, we must do a better job of listening to our customers. Through close contact with customers, designers can more accurately identify market requirements, quickly refine product specifications, and thus reduce time to market. However, too much customer input can create confusion and duplication of effort, which ultimately increases time to market. In other words, some firms run the risk of over-listening to their customers. In a study of three global players in the electronic component industry, Srikant Datar, Clark Jordan, Sunder Kekre, Surendra Rajiv, and Kannan Srinivasan explore the effects of having too much input from customers. Specifically, they examine the relationship between a company's new product development structure and the volume of customer input, which in turn can affect time to market. The high-tech, fast-cycle firms examined in this study employ two distinct new product development structures: concentrated and distributed. A concentrated structure locates all product designers in one facility. This facilitates cross-product learning among designers, but limits designers' contact with customers and process engineers. A distributed structure disperses new product development among numerous manufacturing sites, giving designers close contact with customers and process engineers. However, a distributed structure limits designers' opportunities for cross-product learning. Analysis of 220 new product efforts reveals that the distributed structure offered a time-to-market advantage as long as these firms efficiently managed the level of customer interaction. When designers received input on the product design from no more than 25 customers, the distributed structure provided shorter time to market than the concentrated structure. Beyond the 25-customer level, time-to-market performance of the distributed structure degraded quickly and at an increasing rate. In such cases, more effective management of customer interaction might allow firms employing a distributed structure to enjoy the benefits not only of customer input, but also of improved coordination between product designers and process engineers.     

Metrics for strategic alliance control

The paper develops a feedback control model of product development alliance management. The model allows us to place alliance review, and the metrics for this review, in the context of the control problems facing the alliance manager. We then specify a set of alliance review metrics, and outline the characteristics which they must have. Managers have a pressing need for such metrics, given the management challenges of alliances and the difficulties companies face in making them work effectively. The control model is then expanded to allow for changes in the nature of the alliance itself and inter-project learning. The development of the models and of the metrics is guided by the experiences of a large electronic systems manufacturer in alliances with a number of smaller strategic technology suppliers.     

Exploring Mediating and Moderating Influences on the Links among Cycle Time,Proficiency in Entry Timing,and New Product Profitability*

Development cycle time is the elapsed time from the beginning of idea generation to the moment that the new product is ready for market introduction. Market‐entry timing is contingent upon the new product's cycle time. Only when the product is completed can a firm decide whether and when to enter the market to exploit the new product's window of opportunity. To determine the right moment of entry a firm needs to correctly balance the risks of premature entry and the missed opportunity of late entry. Proficient market‐entry timing is therefore defined as the firm's ability to get the market‐entry timing right (i.e., neither too early nor too late). The literature has produced divergent evidence with regard to the effects of development cycle time and proficiency in market‐entry timing on new product profitability. To explain these disparities this study (1) explores the mediating roles of development costs and sales volume in the relationships among development cycle time, proficiency in market‐entry timing, and new product profitability, respectively; and it (2) explores the moderating influence of product newness on the relationship between development cycle time and development costs and that of new product advantage on the link between proficiency in market‐entry timing and sales volume. The results from a survey‐based study of 72 manufacturers of industrial products in the Netherlands suggest that development costs mediate the relationship between development cycle time and new product profitability and that sales volume mediates the link between proficiency in market‐entry timing and new product profitability. In addition, the findings indicate that new product advantage strengthens the positive relationship between proficiency in market‐entry timing and sales volume. The results provide no evidence for a moderating effect of product newness. These results have important implications because to maximize new product profitability managers need to distinguish between costs and demand side effects of development cycle time and market‐entry timing on new product profitability. Keeping this distinction in mind should help them to better determine the relative profit impact of investments in cycle time reduction or improved entry timing. Moreover, the findings suggest that highly advantaged products that enter the market at the right time may have a highly attenuated sales volume. It also implies that new products with lower advantage may have very little leeway in hitting the “sweet spot” in market. The message is that “doing the right thing” (i.e., to develop a highly advantaged new product) may be at least as important as correctly balancing the risks of premature entry and the missed opportunity of late entry.     

Product Development as Core Competence: How Formal Product Development Practices Differ for Radical,More Innovative,and Incremental Product Innovations

Although universally recognized as an important consideration in building product development (PD) competency, the effect of a firm's ability to vary its PD practices to develop winning products has been given scant attention in large‐scale, multiorganizational, quantitative studies. This research explores differences in formal new PD practices among three project types—incremental, more innovative, and radical. Using a sample of 380 business units, this research investigates how development practices differ across these three classes of innovation with respect to the formal PD process, project organization, PD strategy, organizational culture, and senior management commitment. Our results diverge from several commonly held beliefs about formal PD processes and the management of radical versus incremental innovations. Our results indicate that radical projects are managed less flexibly than incremental projects. Instead of being an offshoot of less strategic planning, radical projects are just as strategically aligned as incremental projects. Instead of being informally introduced entrepreneurial adventures, radical projects are often the result of more formal ideation methods. While these results may be counterintuitive to suppositional models of how to radical innovation happens, it is the central theme of this research to show how radical innovation actually happens. Our findings also provide a foundation for reexamining the role of control in the management of innovation. As the level of innovativeness increased, so too did the amount of controls imposed—e.g., less flexibility in the development process, more professional, full‐time project leadership, centralized executive oversight for new products, and formal financial assessments of expected NP performance.     

Changing Strategies and Tactics for New Product Development

There has been a considerable amount of effort and writing devoted to improving the new product development process during the last two decades. Although there have been some surprises in this literature and in reports from the field on how to manage this complex business process, we now have a good view of the state-of-the-art practices that work and do not work to accelerate commercial success of new ventures. We know much less about how firms change their strategies for new product development.
In this article, we report on a study to investigate how companies change the way they originate and develop new products in manufacturing. We made no prior assumptions about what best practices might be for changing the direction of the new product development process, but we reasonably were sure there would be trends in how companies were attempting to create this strategic change. Even though one size does not fit all, there were significant trends in our findings.
We studied eight manufacturing firms using in-depth, open-ended interviews and were surprised to find that most of these companies are beginning to develop products that are new to the firm, industry, and the world (nearly half, or 10 of 21 new product projects), where they had not been eager for radical change in the past. These newer products likely are to be driven by a combination of market and technology forces, with general requirements being directed by internal forces: middle and top management. Results also indicate significantly that being able to marshal resources and capabilities is easier if change is less demanding and less radical, but when middle managers are driving the conversion of general requirements into specifications, resource issues have yet to be resolved. Implications of these findings are discussed for companies aspiring to change the entire process of new product development in their firms based on these significant results.     

Integrating Cross-Border Knowledge for Transnational New Product Development

Multi‐source knowledge integration, though widely regarded as fundamental for developing new products, remains obscurely understood and a significant challenge for organizations to accomplish. Prior research provides many insights on the approaches by which organizations transfer knowledge; however, how such transferred knowledge gets effectively embodied in products remains uncertain. Also unclear is whether different approaches for knowledge transfer differ in their effectiveness at realizing integration. This study analytically separates the transfer of cross‐border knowledge from its embodiment into products. It examines cross‐border knowledge transfer based on three different approaches: namely, the use of cross‐national teams, cross‐national communication, and cross‐national collaboration in the development of new transnational products. It examines cross‐border knowledge embodiment based on the extent to which new transnational products developed balance standardization with adaptation. The study uses a cross‐sectional survey administered to key members of transnational new product development teams in leading multinational companies across the world. The survey focuses on manufactured products that were developed across several industries: consumer products, consumer durables, and industrial products. Results from 90 new transnational product introductions surveyed reveal that knowledge integration is effective only when knowledge is transferred through cross‐national collaboration, and not when transferred through cross‐national teams and cross‐national communication. As integrating cross‐border knowledge in the development of transnational products involves making difficult trade‐offs for balancing standardization with adaptation, transferring knowledge through cross‐national collaboration stands out as being critical for successful outcomes. Although cross‐national teams and cross‐national communication enhance knowledge flows, they do not result in effective knowledge integration when developing new transnational products. These findings highlight an important point: All knowledge transfer approaches may not necessarily achieve knowledge integration. Hence, it is essential to systematically probe into the interrelationships between knowledge transfer and its effective integration and to identify an underlying set of contingencies that provide insights into when and why some knowledge transfer approaches are better than others at integrating knowledge.