Risk and uncertainty in R&D management

If we begin with certainties, we shall end in doubts; but if we begin with doubts, and are patient in them, we shall end in certainties. Risk and uncertainty permeate R&D management at all levels from project to strategy and at all stages from early to late. Recognising, evaluating, planning and controlling risk and uncertainty, efficiently and effectively, are significant challenges in the management of R&D. Some risks and uncertainties are inherent in the purpose and nature of R&D and some are externally generated. Risk and uncertainties may have both positive and negative aspects, which reflect opportunities and threats for a company. Two examples: In the early 1990s, a simple innovation called Short Message Service (SMS) was developed, more or less as a by-product of mobile communications (see Taylor and Vincent, 2006). At first, no one predicted a great future for this innovation, as there were several technical constraints like the restriction of 160 characters per message, the limitations of the alphanumeric character set, and the design of mobile devices. Besides technological aspects, particular social developments and here especially the early adoption of SMS by younger people, in combination with learning effects (represented in the emergence of an SMS ‘shorthand’), led to the great success of SMS nowadays. In the early 2000s, DaimlerChrysler and Deutsche Telekom founded a joint venture named Toll Collect to develop and build a highway truck-toll-collection system for the German Government. The project ended in a fiasco in the first attempt. In 2003, DaimlerChrysler took a charge of more than $250 million for running losses, and expected penalties for delays (see Edmondson, 2004). The German government cancelled the contract with Toll Collect, and only after laborious negotiations and searching for new partners for the joint venture a second attempt with lower technical expectations could be started and at the end finished successfully. These two examples show merely a small part of the great variety of risk and uncertainties. In this special issue, eight important aspects of risk and uncertainties will be discussed, both to extend the understanding of risk and uncertainties in R&D activities and to advance the state of the art in R&D management practice. Floricel and Ibanescu suggest to understand risk and uncertainty as a dynamic phenomenon resulting from environmental sources. They highlight four patterns of dynamic risks: (i) velocity as perceived intensity of directional change in the environment, (ii) turbulence as perceived discontinuity of environmental change with respect to past trends and anticipated directions, (iii) growth representing the perception of expanding opportunities inside the meso-level system, and (iv) instability as perception of a steady and diverse array of competitive moves by other strategic actors. In their paper they link the concept of dynamic risk with the management of innovation portfolios, while disclosing crucial relationships between the patterns of dynamic risk and attributes of portfolios. Sicotte and Bourgault refer to a different understanding of risk and uncertainty. Contrary to uncertainty, they interpret risk related to the impact of a single event that may occur or not. In their paper, they focus on uncertainties and link them with new product development project performance. First, they identify four types of uncertainties: (i) technical uncertainties, (ii) market uncertainties, (iii) fuzzyness, and (iv) complexity. Second, they define the performance dimension (effectiveness and efficiency) and co-moderator (project methodology and human resource adequacy). In an empirical study some relationships between those variables are found, suggesting a differential moderating effect of the four types of uncertainties on the performance dimension and comoderator. Stockstrom and Herstatt address the close relationship between planning and uncertainty in new product development. They emphasize the contradiction in new product development between rigorous planning and necessary flexibility, the latter caused by external and internal uncertainties. With a broad empirical research in Japanese electrical and mechanical engineering companies, they found evidence that planning is of certain value for different types of innovation projects. Millson and Wilemon investigate the relationships among new product quality, risk, technical development proficiency, and new product development entry strategies like in-house developments or joint ventures. Their definition of risk focuses on the negative aspects; as a consequence, they apply a model with three variables to characterize risk: (i) magnitude of loss, (ii) probability of loss, and (iii) exposure to potential loss. They found no evidence of differences in the quality or risk associated with any particular new product development entry strategy. This surprising result leads the authors to the conclusion that new product developers who achieve market and technology familiarity can expect to attain an equivalent level of new product quality as well as perceived risk from each of the various new product development entry strategies. A case-based and instrumental view is adopted by Leung and Isaacs. The authors give an overview to risk management tasks in the National Research Council of the Canadian Federal Government, a national research organization. They also focus on the negative aspects of risk and differentiate between strategic and operational risks, such as risks at the project, program, and portfolio level. In the paper they cover the range from risk assessment to risk treatment options, relating these instruments to experiences found at the National Research Council. The understanding of risk as variance of financial value is applied in the paper of Willigers and Hansen. They analyze projects in the pharmaceutical industry by means of different real option valuations. Real option valuation offers the possibility to receive a concrete value for the flexibility inherent in R&D projects. Pharmaceutical projects carry such flexibility, making them an ideal starting point to introduce real option valuation into the field of R&D management. The authors discuss certain situations, when real option valuation is particularly precious, and compare a new approach called least squares Monte Carlo real option valuation with well-established approaches. A more subtle aspect of risk and uncertainty is addressed in the paper of Kratzer, Gemeunden, and Lettl. They explore the dynamics of formal and informal networks in complex multi-team development projects. Such projects are increasing in number and, as there are many possible sources for conflicts, very uncertain. The major findings of the authors are that the weak overlap between formally ascribed design interfaces and informal communication networks increases effectiveness but decreases a team's efficiency. The risk of patent infringement is vital for many companies, both as a potential victim of another company's infringement and also as a potential infringer (mostly unconsciously) of other company's intellectual properties. Bergmann, Butzke, Walter, Fuerste, Moehrle, and Erdmann describe how to discover patent infringement with semantic patent analysis. In an interdisciplinary case study, they analyze a real infringement case in biotechnology. Based on this case, they show the usefulness of their approach for R&D management and prove the effectivity of semantic patent analysis as a means to detect patent infringement risk. Risk and uncertainties have many facets and impacts on R&D management. There is a multitude of theoretical accesses available to define and apply to these phenomena. While some have been taken and described in the papers, some others still await application. There are also a multitude of options for risk and uncertainties management in R&D, be it in companies or in public institutions, be it from the financial or the managerial side. Researchers and practitioners are invited to take these options; the journal welcomes further papers on this topic and its certain implications. Lothar Walter is a Senior Academic Advisor (Akademischer Oberrat) at the Institute for Project Management and Innovation (IPMI) at the University of Bremen, Germany. Before, he worked as project and sales manager for different German medical engineering enterprises. He studied physics, mathematics and biochemistry at the TU Darmstadt and obtained a doctorate in biophysics from the University of Bremen. His main areas of interest in technology and innovation management are industrial patent management and methodical invention (TRIZ). Martin G. Moehrle is Professor and director of the Institute for Project Management and Innovation (IPMI) at the University of Bremen, Germany, while at the same time holding the chair of Innovation and Competence Transfer. His area of work is technology and innovation management, and his preferred topics are industrial patent management, technology roadmapping, future research, multiproject management, and methodical invention (TRIZ). Prof. Moehrle obtained his doctorate and qualified as a university lecturer on transitional themes between technology management and business informatics.

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