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Turning innovation into profit
Abstract
The generic ?stage and gate process? is popularly accepted as a means for managing new product development. It advocates that a development project is divided into a series of pre-defined decision steps in order to balance investment against perceived market risk and return.
Its use implies a number of assumptions ? first that the product can be characterized as having features and customers benefits; and second that the market for such a product is identifiable.
This paper describes a process to assist decision making where these two assumptions do not apply. It provides suggestions to assist in the management and development of innovation and new technology, advocating that a marketing-based perspective of supply-led innovation is adopted.
Copyright
... Economic return through technology exploitation is the principle and urgent objective for pro¯t-seeking¯rms. Millier and Palmer [2001] claim that the use of innovation can bring substantial rewards and bene¯ts for both organizations and customers alike. Multinational companies could get¯nancial earnings from diversied market operation, which could compensate the technology innovation and acquisition costs and make pro¯t as well. ...
... Following such a strategy, organization is subjected to learn gradually how to reduce technical and commercial risks in order to gain more from high risk market. Management knowledge, pro¯ciency and readiness can be developed through incremental market development to minimize risk and maximize the probability of commercial success [Millier and Palmer (2001)]. This strategy is extremely important for an organization with limited resources. ...
The intention of this paper is to give an overview on the issue of technology exploitation within the context of globalization. Multinational companies which have extended business to the global market have more options regarding utilization of their technologies, thus having greater motivation and more chances for development. However, the global context also complicates technology exploitation. In this paper, we first address what technology exploitation means and the patterns of technology exploitation for multinational companies. Then, the benefits and risks of internationally exploiting technologies are discussed. Next, we shed light on some factors influencing the decision on technology exploitation patterns. Moreover, conceptual models helping firms’ option on technology exploitation pattern from perspectives of cost effectiveness and risk aversion are presented. By focusing on the technology exploitation patterns in the global market, this study holds several implications for the multinational companies to manage their efforts on realization of commercial value of technologies.
... Today, more and more enterprises are integrating their legacy systems with Internet-enabled applications and are changing their business processes to achieve e-business integration. Such e-business applications improve efficiency (Millier and Palmer, 2001; Porter, 2001; Palmer, 2002) by streamlining internal and external transaction processes, creating new markets for products and services and enhancing customer and supplier relationships. E-business is well defined as follows: ``Using global, Internet-connected computers to create new business relationships and transform old ones for real time-integrated business process and workflows'' (Klassen and Jacobs, 2001). ...
A great challenge for today’s companies is not only how to adapt to the changing business environment but also how to gain a competitive advantage from the way in which they choose to do so. As a basis for achieving such advantages, companies have started to seek to improve the performance of various operations. Forecasting is one of them; it is important to firms because it can help ensure that effective use of resources is made. In the market there are a number of off-the-shelf system products, which provide forecasts. The new trend, of moving traditional software packages to Web services, has pushed forecasting to a new dimension, named by the authors as “e-forecasting”. In this paper, a first approach to e-forecasting is made by throwing light on several aspects and a survey is presented which aims at identifying existing Web forecasting services.
... Today, more and more enterprises are interested in web applications (Serrano et al., 2002; Brooke and Ramage, 2001), changing their business processes to achieve e-business integration (Lumpkin and Dess, 2004; Disney et al., 2004). Such e-business applications improve efficiency (Millier and Palmer, 2001; Palmer, 2002) by streamlining internal and external transaction processes, create new markets for products and services, and enhance customer and supplier relationships. This study focuses on the efficient implementation of e-government in the tourism sector, as a powerful e-decision support system for tourism demand analysis and forecasting. ...
In tourism industry, information is of great importance in the decision-making process. Any information concerning the future evolution of tourism flow is indispensable both for the public and the private sector. Accurate tourism demand forecasts are essential in order to adjust their policy and corporate finance. This study proposes an e-government decision support system for tourism demand analysis and forecasting.
... Today, more and more enterprises are integrating their legacy systems with internet-enabled applications (Serrano et al., 2002;Brooke and Ramage, 2001) changing their business processes to achieve e-business integration (Lumpkin and Dess, 2004b;Disney et al., 2004aDisney et al., , 2004b. Such e-business applications improve efficiency (Millier and Palmer, 2001;Porter, 2001;Palmer, 2002), by streamlining internal and external transaction processes, create new markets for products and services and enhance customer and supplier relationships. E-business (Joao et al., 2002), is well defined as follows: ...
The term e-government refers to the use by government agencies of information technologies that have the ability to upgrade relations with citizens, businesses, and other arms of government. So far, most e-government activity has focused on publishing information via the internet rather than actively interacting with citizens (G2C) or business enterprises (G2B). Forecasting is undoubtedly one of the key processes in operations management and is based on sufficient historic data. Government is the key holder of the majority of crucial databases in the market and projections of those data are pretty important. Thus, forecasting systems are more than necessary for an effective government. Sectors such as healthcare management, real estate market, and financial markets are in great need of adequate forecasts. In the 21st century, e-forecasting replaces traditional forecasting and evangelises an indispensable part of e-government in a rapidly changing cyber world. This study presents a survey on the available bibliography and applications of forecasting systems within the e-government framework and proposes the basic architectural elements of a forecasting system for e-government.
... Further support of this strategy comes from Millier and Palmer (2001). They describe a process of identifying potential market applications for a new technology and then an assessment of the technological and commercial/market risks. ...
This review paper initially explains that the commercialization of an innovative new technology needs to be underpinned by an appropriate business model. The paper summarizes what has been previously proposed to be the components of a business model and makes the case that an extra one needs to be added and that two of them need interpreting in a special way in order to be appropriate for innovative technology commercialization. It is argued that the decision on what market to target may be crucial to the commercialization process as, often, initial failure may allow no second chances. A way of determining the most appropriate initial market is discussed as this market choice is a determinant of business model choice. Finally, conclusions are drawn on defining and devising business models for commercializing new technologies.
Because of the importance given to risk management, exploitation of available information and providing employees with clear guidance on the relationship between their role and overall aims of an organisation, most firms establish a clearly defined, formalised strategy to guide their operations. The purpose of the strategy is to define the benefit which provides the basis for the competitive advantage through which the company seeks to achieve a specified performance. Strategy implementation is achieved through utilisation of appropriate marketing and internal value-added activities (Chaston 2013).
Determining the value of innovation within the innovation process already means to innovate
Research states that the success of a specific innovation cannot be predicted. As a consequence, the value of such an innovation can only be stated very late in the development process, or even in retrospect. Based on C-K design-theory, our empirical research shows that professionals directly engaged in the design process are able to perform an early and complete valuation. The cognitive process of this valuation is extremely similar to the overall process of innovative design. Also, this process has tangible outputs, in particular local, dedicated management tools used as proofs of concepts.
JEL Codes : O32
Predicting which consumers will be amongst the first to adopt an innovative product is a difficult task but is valuable in allowing effective and efficient use of marketing resources. This paper examines the accuracy of predictions made about likely first adopters based on the most widely accepted theory and compares them to predictions made by examining the relevant past behavior of consumers. A survey of over 1000 consumers examined adoption of an innovative technology: compact fluorescent lightglobes. The results show that variables which were derived from a utility and awareness perspective were a more accurate and managerially useful predictor than the demographic variables derived from the widely accepted theory based on the work of Rogers. It is suggested that these alternative variables could be utilized more readily by marketing managers in many circumstances.
Seeks to address directly two assumptions that are inherent in current discussions concerning business and the role of technology. First, that business intelligence is, in fact, a feature of the business rather than the staff within that business. Businesses are simply entities with assets and capabilities but no cognitive processes, intelligence is a unique property of humans. Therefore there is a greater need to understand the social processes concerned in order to recognise this resource effectively. Second, that “e-business” is distinct from “business”. Uses original research in the area of technological innovation as the basis for developing a wider argument with respect to e-business. Argues that what is currently referred to as e-business is a relatively poorly developed bundle of technologies that have yet to achieve full application in order to deliver optimum benefit. Also discusses the e-business phenomenon, the role of technology and the importance of a social perspective of business to give more insightful understanding of the interactions between these areas.
The speed with which to move concepts to market is a fundamental issue facing new ventures and their parent corporate sponsors. Is rapid development from concept to market vital? What pressures are induced by the urgency of product introduction, and can they lead to poor decisions? Can a more deliberate pace be recommended? Widely diverse new business ventures outside a company's core business areas can prove problematic. While faster may be better, speed brings with it pressures that, for certain types of technological ventures, can lead to failure if they are not clearly understood and managed. Speed is relative to the capability of the venturing company and to the nature of the venture it is attempting. The studied company's experience shows that successful ventures, particularly the more risky and potentially rewarding, require commitment and persistence.
This article focuses on the predevelopment activities of the product innovation process: those often ignored steps that precede the actual development of the product. We first look at the mounting evidence that identifies holes in the way in which many industrial firms handle the predevelopment steps. The evidence also reveals that new product success and failure is often decided before the new product project even enters the product development phase. Second, we turn to ways that managers can, should and have improved the effectiveness of these early and crucial stages of the innovation process.
Industry pundits often take managers to task for their supposedly myopic approach to planning and decision making. These sweeping generalizations gloss over the complex challenges confronting the managers who must ensure that their firms enjoy ongoing revenue growth opportunities. In place of pat answers, those managers require analysis and planning tools that offer clearer insights into the effects their decisions have on their firms' continued business success. As Marv Patterson points out, however, determining the effects of product innovation decisions poses a particular challenge for management because the consequences of those decisions typically do not become evident until ions after the decisions have been made. Presenting a conceptual model that links product innovation activities to revenue growth, he identifies three drivers of revenue growth, and explains how these growth drivers are linked by a set of mathematical relationships that can be presented in the form of an enterprise-specific growth table. He applies the model to three types of enterprises, and he discusses the key implications that the model holds for the business leaders who must keep shareholders satisfied He depicts the relationship between a company and its customers as a closed-loop system in which the company converts labor parts, and material into products, which it delivers to customers. The company invests a portion of the resulting revenue stream in the resources that generate new products. By effectively, and continually applying a sufficiently large investment in this innovation engine, the company creates an ongoing stream of new products. The revenues from these new products more than offset the drop in revenues from products that are approaching obsolescence. He identifies three factors that drive revenue growth from these investments in the innovation engine: the fraction of revenues invested in product innovation, new product revenue gain, and the behavior of revenue over time for a particular business. Using a graph called a product vintage chart, he demonstrates that for a large company, the revenue contributions of a particular new-product year (or vintage) full into a regular pattern over time, which enables a company to determine mathematical relationships for revenue growth as a function of R&D investment and new product revenue growth. in this way, senior managers can gain clearer understanding of the interplay between product innovation, R&D investment revenue growth, and profitability over time. (C) 1998 Elsevier Science Inc.
Industry pundits often take managers to task for their supposedly myopic approach to planning and decision making. These sweeping generalizations gloss over the complex challenges confronting the managers who must ensure that their firms enjoy ongoing revenue growth opportunities. In place of pat answers, those managers require analysis and planning tools that offer clearer insights into the effects their decisions have on their firms' continued business success.
As Marv Patterson points out, however, determining the effects of product innovation decisions poses a particular challenge for management, because the consequences of those decisions typically do not become evident until long after the decisions have been made. Presenting a conceptual model that links product innovation activities to revenue growth, he identifies three drivers of revenue growth, and explains how these growth drivers are linked by a set of mathematical relationships that can be presented in the form of an enterprise-specific growth table. He applies the model to three types of enterprises, and he discusses the key implications that the model holds for the business leaders who must keep shareholders satisfied.
He depicts the relationship between a company and its customers as a closed-loop system in which the company converts labor, parts, and material into products, which it delivers to customers. The company invests a portion of the resulting revenue stream in the resources that generate new products. By effectively and continually applying a sufficiently large investment in this innovation engine, the company creates an ongoing stream of new products. The revenues from these new products more than offset the drop in revenues from products that are approaching obsolescence.
He identifies three factors that drive revenue growth from these investments in the innovation engine: the fraction of revenues invested in product innovation, new product revenue gain, and the behavior of revenue over time for a particular business. Using a graph called a product vintage chart, he demonstrates that for a large company, the revenue contributions of a particular new-product year (or vintage) fall into a regular pattern over time, which enables a company to determine mathematical relationships for revenue growth as a function of R&D investment and new product revenue growth. In this way, senior managers can gain clearer understanding of the interplay between product innovation, R&D investment, revenue growth, and profitability over time.
After pointing out some differences between theory and practice in segmenting industrial market, this article reviews the literature on the subject. The latter reveals that too mechanistic or too quantitative segmentation methods are quite inappropriate for the industrial environment where the markets are concentrated and the data sometimes rare. Based on this observation, the article, finally, looks at the problem from another angle by mixing formally a little intuition with the analysis. The end of the article is illustrated by an application of the method.
Recent years have witnessed a resurgence of academic and practitioner interest in new product development and in the way companies interact with their customers. While there has been considerable scientific progress in both research areas, very limited attention has been given to customer interaction in the new product development process as a means to increase new product success. This article reports on research assessing the performance impact of (1) the intensity of customer interaction in different stages of the new product development process and (2) the characteristics of the involved customers. The research is based on field interviews as well as statistical analyses of a sample in the machinery industry. Results indicate that customer interaction during certain stages (but not others) of the new product development process has a positive impact on new product success. The characteristics of the involved customers have a significant effect on new product success as well. As an example, collaborating with financially attractive customers or customers exhibiting lead user characteristics increases new product success.
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