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Portfolio Management in Double Unknown Situations: Technological Platforms and the Role of Cross-Application Managers

Olga Kokshagina, Pascal Le Masson, Benoit Weil and Patrick Cogez

This article investigates portfolio management in double unknown situations. Double unknown refers to a situation in which the level of uncertainty is high and both technology and markets are as yet unknown. This situation can be an opportunity for new discoveries, creation of new performance solutions and giving direction to portfolio structuring. The literature highlights that the double unknown situation is a prerequisite to designing generic technologies that are able to address many existing and emerging markets and create value across a broad range of applications. The purpose of this paper is to investigate the initial phases of generic technology governance and associated portfolio structuring in multi-project firms. We studied three empirical contexts of portfolio structuring at the European semicon- ductor provider STMicroelectronics. The results demonstrate that (1) portfolio management for generic technologies is highly transversal and comprises creating both modules to address market complementarities and the core element of a technological system – the platform, and (2) the design of generic technologies requires ‘cross-application’ managers who are able to supervise the interactions among innovative concepts developed in different business and research groups and who are responsible for structuring and managing technological and marketing exploration portfolios within the organizational structures of a company.

Introduction

Companies’ innovative performance de-pends strongly on efficient portfolio structuring and its management. However, companies increasingly operate in novel and unknown environments, fundamentally modifying the logic of decision making and rendering the typical planning approaches inadequate. In these situations, companies must adopt more flexible approaches to incor- porate learning and privilege interactions among projects and the corresponding envi- ronment. These significant changes in business environments and ever-growing competition are causing portfolio managers to cope with uncertainty by changing the strategic direc- tions of portfolios, balancing and prioritizing projects differently.

Recent advances in the portfolio manage- ment literature make it clear that dynamic environments and increasing complexity make risk management insufficient, and a high probability of unknown risks could cause companies to question their entire port- folio and even result in its failure (Pender, 2001; Geraldi, 2008; Olsson, 2008; Petit & Hobbs, 2010; Petit, 2012). Mullins and Sutherland (1998) demonstrated that firms operating in these environments require new practices to mitigate risks, manage uncertain- ties, and increase the likelihood of future success. Reflective learning, sensemaking, balancing to ensure flexibility of portfolios and decision making are underlined as crucial when working with portfolios amid uncertainty (Olsson, 2006; Perminova, Gustafsson & Wikström, 2008; Petit, 2012).

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While these approaches provide effective ways to examine and address uncertainty in portfolios, they generally treat uncertainty as a problem to be addressed or a challenge to overcome. Still, unknowns can be seen as opportunities to design new alternatives to cope with and lower risks. By focusing on a framework for conceptualization of the rela- tionship between ideation and project portfo- lio management, Heising (2012) showed that better organization of the initial stages of inno- vative portfolios and the connection between the operational phases of portfolio manage- ment and the fuzzy front end might increase companies’ innovative performance. As Geraldi (2008) underlines through a study of multi-project firms on the edge of chaos, these firms must operate on the edge of chaos by bringing order to high uncertainty situations.

Defined as unforeseeable uncertainty by Loch and colleagues (Loch, De Meyer & Pitch, 2006; Loch, Solt & Bailey, 2008), this situation is characterized by a team’s lack of awareness of an event’s existence or its probability of occur- ring. The difference between unforeseeable uncertainty and chaos is that in a situation of unforeseeable uncertainty, the team begins with reasonable assumptions and goals. In R&D contexts, this scenario often corresponds to a ‘double unknown’ situation in which neither technologies nor markets are known. In a double unknown situation, the nature of the risks is unknown; alternatives have not yet been formulated and thus their values cannot be determined. Markets are considered unknown because the product features that could make them successful are initially unknown (O’Connor & Rice, 2012). Neverthe- less, markets whose ex ante probability of existence is rather low can become important ex post. Technologies are unknown because while a variety of solutions might be designed for certain functions, none yet exists. In this situation, it remains unclear which emerging markets will succeed and which technologies will be more advantageous. These cases are often simply considered unmanageable, and the common approach is to wait until the unknowns are reduced.

In this paper, motivated by the importance of the early stages and pre-stages of portfolio existence, the idea is to profit from the double technological and market unknowns to create a portfolio that reduces these unknowns and to enable portfolio structuring and its effective management. By portfolio structuring, we refer to all the tasks involved in initially setting up a portfolio derived from an organization’s strategy, such as evaluating proposals and selecting projects (Unger,

Gemünden & Aubry, 2012). How can portfo- lios be structured in double unknown situations?

Maine and Garnsey (2006) have noted, in the case of advanced materials ventures, that the presence of technological and market uncertainties at early stages of exploration offers opportunities for the creation of generic technologies, i.e., technological platforms that are able to address many emerging markets. Importing ideas from broad networks, creat- ing environments for deep collaboration and technology-market matching processes are essential for the commercialization of generic technologies (Maine, Thomas & Utterback, 2014). The emergence of generic technology involves the exploration of both various nascent technical domains and many emerg- ing markets (Baldwin & Woodard, 2009; Gawer, 2014). Although the societal impor- tance of these pervasive technologies has been widely highlighted (Bresnahan & Trajtenberg, 1995; Keenan, 2003), the management of the initial stages of their development remains underexplored. However, this stage can be extremely challenging due to the high level of uncertainty, immaturity of technologies and markets, and difficulties in obtaining external financing, which often results in long develop- ment cycles. The exploration process involved in developing generic technology is often unclear. By designing a generic technology that is independent from any specific market requirements, we create a low-risk alternative that facilitates technology diffusion within various application domains. The creation of a portfolio that takes into account the logic of emerging generic technologies will offer a competitive advantage for a company where the latter aims to design this technology and implement it across different markets. This logic requires effective multi-project manage- ment. Moreover, the actors and their specific competencies in developing generic technol- ogies in the presence of multiple unknowns must be determined.

This paper aims to fill the gap between the technological platform and portfolio manage- ment literature amid high uncertainty by addressing the initial stages of platform devel- opment. We examine the following research question: what is portfolio management for generic technologies, and how can a portfolio be structured under technologies and markets that are as yet unknown?

The setting is the high-velocity semiconduc- tor industry, which is constantly confronted with competition, rapidly changing markets and rapid technological obsolescence, which together force the industry to explore both market and technological unknowns. For this

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investigation, a multiple qualitative case study approach (Yin, 2008) was used to provide new insights into the emerging phenomenon of portfolio management to address unknown risks.

This work demonstrates that portfolio structuring for generic technology comprises creating modules to address market complementarities and the core element of a technological system – the platform. The find- ings indicate that to account for generic technology’s exploration in high uncertainty, portfolio management must be highly trans- versal. Portfolio managers in double unknown situations address multiple emerging technol- ogies and markets and must assemble portfolios based on generic technologies. The reasoning associated with the design of generic technologies requires significant scien- tific effort, and the governance of this design process appears critical for the successful design of generic technologies and execution of the portfolio. The transversal case analysis illustrates that the design of generic technol- ogies requires a new managerial role, a ‘cross-application’ manager, who is capable of creating innovative concepts developed in dif- ferent business lines, creating interdependen- cies and supporting balance within the project portfolio. The role of the cross-application manager appears to be critical for successful portfolio structuring and management to account for successful generic technology design.

Theoretical Background

To guarantee a company’s long-term survival, its renewal and organizational growth must be ensured. PMI (2013) defines a project port- folio as ‘a collection of projects or programs and other work that are grouped together to facilitate effective management of that work to meet strategic business objectives’. Portfo- lio management enables strategic choices for a company and is crucial to prioritizing and selecting projects among various emerging options (Cooper, Edgett & Kleinschmidt, 2001; Lycett, Rassau & Danson, 2004; Olsson, 2007). Portfolios are subject to different uncertainties that can influence future out- comes and change the course of action. To ensure the success of portfolios, managers must address the different levels of risks and uncertainties (Perminova, Gustafsson & Wikström, 2008; Petit & Hobbs, 2010; Martinsuo, 2013). The literature review pre- sents current project portfolio management (PPM) practices in risks, uncertainty and unknowns.

Portfolio Management amid Risk

The literature on PPM considers risk manage- ment a crucial element to ensure portfolio success (Petit & Hobbs, 2010; Lee, 2011). Using a sample of 134 firms, Teller and Kock (2012) illustrated the positive correlation between risk management quality, measured as risk transparency and risk coping capacity, and the success of a project portfolio.

The PPM perspective addresses the poten- tial logic of risk mitigation (Olsson, 2008; Sanchez et al., 2009), focusing primarily on the known-unknowns category of risks (Petit, 2012). Classical models of risk management propose that the likelihood of success is highly proportional to the initial technological and market uncertainties.

When uncertainties are low, the nature of technologies and markets and the associated project alternatives can be determined. A deci- sion can be made in consideration of this risk when a manager can list all the possible out- comes associated with a decision and assign a probability of occurrence to each outcome. Classical risk management techniques provide methods to help decision makers cope with these uncertainties (Chapman, 1990; Lipshitz & Strauss, 1997). Portfolio risk management incorporates risk management at the level of each product and the portfolio itself. Greater visibility for stakeholders and decision makers can be achieved by improving common port- folio risk management (Olsson, 2008; Teller & Kock, 2012). Petit and Hobbs (2010) indicated that the drivers of change go beyond those considered in the PMI classifications and are not yet contemplated by the PMI standard. In these situations, risk management is not suffi- cient for managing high uncertainty and com- plexity in portfolios in dynamic environments (Petit, 2012). Thus, portfolios are largely built when these risks are reduced. However, organizations constantly cope with increasing levels of uncertainty, and to retain a leadership position in the market, they seek to innovate in environments that are unconventional for them.

Portfolio Management amid Uncertainty

Portfolios are subject to uncertainty when project alternatives can still be identified and when managing uncertainty consists of making the optimal choice between possible decisions and probable states of nature. Yet the outcome in this case is not fully known. The sources of uncertainty are numerous, includ- ing organizational complexity, external envi- ronments that comprise technical and market uncertainties, emerging standards, regula- tions, the context of the operating company of

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the unit, and industry volatility (Petit & Hobbs, 2010; Teller et al., 2012; Voss & Kock, 2013).

When uncertainty is high, probabilistic approaches are limited because the probabil- ities evolve during the process of exploration and cannot be correctly estimated initially (Loch, De Meyer & Pitch, 2006). In this case, uncertainty reduction approaches are mobi- lized to reduce these uncertainties and more advanced approaches for portfolio risk man- agement are required because the states of the environment are often impossible to predict and because probability-based risk manage- ment becomes irrelevant due to high market and technology volatility (Pender, 2001; Loch, Solt & Bailey, 2008; Petit, 2012).

Choices made under uncertainty are often driven by the maximization of expected utility. Utility is a function of profit that comprises the value of benefits associated with each state of nature weighted by its probability and the utility of the decision itself. It aims to select the most promising alternatives (maximal utility) from the predefined list. This theory relies on various derived techniques to cope with uncertainty management (Raiffa, 1968; Savage, 1972). The economic return of a portfolio depends greatly on technological and commercial uncertainties (Verworn, 2009). Real-options theory is suggested to guide investment decisions under uncertainty (Dixit & Pindyck, 1994; McGrath, 1997; O’Connor, 2008) by estimating whether the option to invest in a new technology is worth pursuing or by determining how the learning process influences the option value. Real-options pro- vides powerful tools that account for dynamic environments. For example, the real-options approach to project evaluation seeks to correct the deficiencies of traditional methods of valuation through the recognition that mana- gerial flexibility can bring significant value to projects (Carlsson et al., 2007).

Nevertheless, real-options approaches are limited when addressing high uncertainty because the learning that is considered in these techniques is based on the distribution of sub- jective probabilities associated with the states of nature (Oriani & Sobrero, 2008). The learn- ing process does not affect these states and the corresponding decisions, which is critical in unknown situations because new technologi- cal alternatives could emerge and new markets could be created during the exploration phase. Real-options approaches consider that the decisions and states of nature are independent. To apply real options, a decision maker must know the project’s potential, underlying assets, and needs based on the potential states of nature. Moreover, the estimated option

value should indicate the reliable actions to take (Huchzermeier & Loch, 2001). In the case of exploration in high uncertainty, these con- ditions can rarely be met. Additionally, new alternatives and unexpected results could emerge throughout the period of exploration.

Wouters, Roorda and Gal (2011) proposed a project portfolio option-value method that attempts to provide an overview of major chal- lenges and key criteria of success for compa- nies in the presence of many technological and marketing uncertainties and attempts to account for the interdependencies among proj- ects in a portfolio. Visual tools attempt to facili- tate interdependency management within a portfolio (Killen & Kjaer, 2012). A transparent risk management culture within organizations helps better reveal and manage interdepend- encies within various portfolio projects (Teller & Kock, 2012).

It is important to consider various types of interdependencies (Blau et al., 2004; Collyer & Warren, 2009). For example, Eilat, Golany and Shtub (2006) suggested to consider resource interactions, benefit interactions and technical dependencies between projects. Archer and Ghasemzadeh (1999) addressed financial interdependencies. Additionally, Killen et al. (2009) underlined the importance of outcome dependencies, which involve the re-use of the results within projects, including both technical and commercial aspects, and learn- ing dependencies that lead to incorporating the capabilities and knowledge gained through various projects. The interdependen- cies between projects are more complex when addressing unknowns (Mikkola, 2001; Chien, 2002) but complex interdependent systems can be a source of breakthroughs (Fleming, 2012). By studying the management of four portfolios in two large multidivisional corpo- rations, Petit and Hobbs (2010) examined PPM adapted for dynamic uncertain environments once a portfolio is selected. The authors demonstrated that the dynamic capabilities approach can be used to analyse the opera- tional levels within an organization (Killen, Hunt & Kleinschmidt, 2008; Killen et al., 2012; Petit, 2012).

Portfolio Management in Double Unknown Situations

Portfolio Structuring: Coping with Double Unknown Situations

In coping with uncertainty, PPM often consid- ers that projects are already identified within the portfolio. However, when the exploration phase is confronted with unknown environ- ments, markets are considered unknown because the product features that could make

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them successful are initially unrevealed (O’Connor & Rice, 2012). Technologies are unknown, which means that a variety of solutions might be designed, although none exists at the moment. This exploration of as-yet-undefined technologies and markets is precisely what is referred to as a double unknown situation. In this situation, it is ambiguous which emerging markets will succeed and which technological forms will be more advantageous. The identity of technol- ogy is not presumed, and future uses are not fixed (Gillier & Piat, 2011). In this situation, the projects in the portfolio are still undetermined.

Nevertheless, the initial stages of ideation are important for future portfolio success, and technological and market unknowns can be viewed as opportunities. By examining PPM relevance in uncertain and complex dynamic contexts, Martinsuo (2013) indicates that portfolios can be viewed as a means to open negotiations and to reconfigure and introduce flexibility into the decision-making process. Kock et al. (2011) underlined that technological innovativeness can increase the customer value of future products but also creates challenges for the innovating firm and its environment. Better organization of the fuzzy front end stages of project exploration contributes to the overall portfolio perfor- mance (Heising, 2012). The author noted that the existence of well-established literature on the ideation and fuzzy front end forms a sin- gular project perspective; the link with a more operational phase of portfolio manage- ment is missing. Moreover, Meskendahl (2010) indicated that when applied to PPM, a firm’s strategic orientation significantly influences its portfolio decisions and there- fore the structure of the portfolio. The portfo- lio structuring in double unknown situations remain understudied, and their alignment with more mature project portfolios within an organization must be investigated. How, then, can we cope with double unknown situations and structure the relevant project portfolios?

Portfolio Structuring and Management in Technological Contexts: Generic Technology Design

The double unknown situation is not rare, and Maine and Garnsey (2006) have noted that the presence of technological and market uncertainties at early exploration stages offers opportunities for the creation of generic tech- nologies, i.e., technological platforms that are able to address many emerging markets. The emergence of generic technologies involves

the exploration of both various nascent techni- cal domains and many emerging markets (Baldwin & Woodard, 2009; Gawer, 2014). Although the societal importance of these per- vasive technologies has been widely high- lighted (Bresnahan & Trajtenberg, 1995; Keenan, 2003), the management of the initial stages of their development and of portfolio structuring remains underexplored.

Existing research has shown that the design of generic technologies encompasses the architecture of a platform that allows the modularization of several market modules (Baldwin & Clark, 2000, 2006). As noted by Sawhney (1998), platform thinking should be driven by the definition of the common under- lying technology – the core element of the plat- form. The author demonstrated that firms must assess what is the core and what are the derivatives of the platform. Platform design becomes a strategic phase to define future firm direction. For example, while building its PC platform, IBM outsourced the operating system and central processing unit to Microsoft and Intel and did not perceive these important components as a part of a core plat- form (Bresnahan & Greenstein, 1999; Gawer & Cusumano, 2002).

To the best of our knowledge, no prior studies have investigated how a portfolio can be structured and managed in this case. Previ- ous studies on generic technologies have illus- trated the challenges associated with their development; among them, Maine and Garnsey (2006) highlight access to comple- mentary assets, capacity to finance the early design stages to demonstrate the value of generic technologies for multiple markets and the importance of ensuring efffective manage- ment and diffusion of generic technologies. We argue that better structuring and manage- ment of portfolios in double unknown situa- tions allows exploring multiple technological and market alternatives, accelerating the access to complementary assets and enabling the financing of the development states of early generic technologies.

Thus far, however, there has been little dis- cussion of portfolio structuring and manage- ment in unknown environments. The importance of the creation of learning and interdependencies is well established, and the need for expertise to handle the process of unknown exploration is clear. However, the answer to the following question remains unclear: What is portfolio management in double unknown situations for generic tech- nology, and how can a portfolio be structured under as-yet-unknown technologies and markets to account for successful generic tech- nology exploration?

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Methodology and Data

Research Design

The purpose of this work is to gain an under- standing of PPM for generic technology design in highly uncertain environments. Given the newness of this research field and the lack of available knowledge, a qualitative research methodology is recommended (Yin, 2008). This methodology is appropriate in our context because we focus on exploring a phenomenon within an organizational context. The study is conducted within the semiconductor industry, an environment in which the probability of the existence of generic technology is high and uncertainties are multiple (Olleros, 1986; Miyazaki, 1994). This paper is based primarily on an in-depth empirical study at the largest European semiconductor company, STMicroelectronics (ST), and is part of a longitudinal multidisci- plinary study of innovation practices at ST in collaboration with Mines ParisTech researchers.

Research Field

Semiconductors are fundamental elements of all modern electronic systems and computers, such as smartphones, tablets, personal com- puters, consumer electronics and telecommu- nication equipment. The growth in the demand for electronic components has dra- matically increased the demand for semicon- ductor devices leading to a creation of a 336 billion dollar industry (source: WSTS, 2015 accessed November 2014). To ensure growth, support demand and be at the leading edge of competition, industry players must be prepared for huge capital investment and R&D in the generation of rapidly chang- ing technology. However, the risks are high, and companies seek ways to analyse the cor- responding market structure and develop more reliable manufacturing strategies to secure their investments. As a result, the science-based semiconductor industry con- stantly looks for breakthrough innovations and double unknown situations are common.

The relevance to the semiconductor indus- try of exploring breakthrough innovations has been shown by various researchers (Cohen & Levinthal, 1989), particularly with respect to knowledge creation methods in science-based environments (Le Masson et al., 2012a; Robinson, Le Masson & Weil, 2012). Scholars have highlighted the challeng- ing environment in the semiconductor indus- try and the high rate of innovative technology developments that target market creation

(Dosi, 1982; Teece, 1986). The strong compe- tition and rapidly changing environments that characterize the semiconductor industry lead to exploring not only new technologies, but also new functionalities and new prod- ucts, while coping with the unknowns. It becomes clear that the pace of innovation in semiconductors is extremely high, and to develop successful innovation, companies such as ST must incorporate both market and technical dimensions, which places portfolio structuring as a key issue in dealing with double unknown situations. This industry is particularly relevant for our study, as it often has to engage in double unknown situations, and the pervasiveness of the use of semicon- ductors makes them a prime example of generic technologies (Olleros, 1986; Miyazaki, 1994).

Multiple Case Study

The multiple case study approach is particu- larly useful in understanding the influence of variability of context to experimentally validate findings and gain more general results (Eisenhardt, 1989). Multiple cases enable accounting for a more accurate level of abstraction and help achieve better generalizability. The different organizational contexts were selected to better reveal the phenomenon.

We conducted case studies of innovative technology development in multi-project con- texts at ST. The following three identified cases offer different frameworks and units of analy- sis, which permits different perspectives on the research questions: Case (1) portfolio structuring for projects issuing from innova- tion contests; Case (2) organized reflections on future portfolio structuring in a double unknown situation in the case of the Interna- tional Technology Roadmap for Semiconduc- tors (ITRS) ‘More than Moore’ technology working group; and Case (3) ex post analysis of a research project portfolio. These three con- texts represent different organizational set- tings and comprise various units of analysis (Table 1).

Because we lacked a theory of generic tech- nology design to guide the case selection, we verified that each case aimed to design a new object – a technological platform as opposed to the existing specific technologies – and that a variety of participants were involved in the cases’ elaboration. The cases were selected because all were subject to double technologi- cal and market unknowns, and all attempted to design generic technologies by profiting from double unknown situations and address- ing multiple existing and emerging markets (Table 1).

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Table 1. Data Description and Units of Analysis

Case 1 Case 2 Case 3

Description Open Innovation Contests – Business Innovation Process (3 consequent innovation challenges)

International Technology Roadmap for Semiconductors (ITRS) technology working group ‘More than Moore’

Ex-post analysis of a research project portfolio

Time period 2009–2012 2005–2013 2003–2010 Type of project Innovation exploration projects

accepted after the idea collection phase – 20 potential portfolios in 3 years from 221 ideas submitted

Working group composed of actors from various semiconductor companies (Intel, NXP and STMicroelectronics)

10 research project clusters (∼405 research projects)

Unit of analysis – technological platform and emerging portfolios

Example of one portfolio: 3DTouch platform based on active surface to elaborate haptic touch

Example: Generic functions identified for future platforms structuring – MEMS-based roadmap

Example: Bipolar technology addressing RF-based multiple markets

Organizational entities involved

Business units, and strategy, marketing and R&D groups

Companies’ representatives and ‘More than Moore’ technology working group leaders

R&D groups

Participants – Participants involved in the three contests from ST’s Grenoble and Crolles sites, including specialists from marketing and technical backgrounds and strategic and operational units, internal and external participants (interns and university students involved in ideation)

– Organizing committee

ITRS members included specialists from different companies (mostly R&D directors, innovation directors):

– Technology working group leaders

– Technology working group participants

400 research projects (each project lasted 3 years):

– 1 industrial PhD candidate per project

– at least two supervisors per project at the company: project leader and R&D group

– General R&D programme managers and Technology line managers

Primary data sources

– 20 semi-structured interviews (40 h)

– Observational activity of 16 (64 h) workshops named ‘Growing seeds’ to facilitate generic technology exploration and promote technology adoption throughout the company, 4 workshops by contest

– 17 face-to-face meetings

– 40 conference calls

– 30 semi-structured interviews (30 h)

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Table 1. Continued

Case 1 Case 2 Case 3

Interviewees – Members of the decision-making board (2 Chairmen – ST’s Vice Presidents; 2 project members – Business Units’ managers; and 2 sponsors – directors of ST’s Grenoble and Crolles sites)

– Members of the organizing committee – 8 interviewees from R&D and Business Units

– Leaders of 3 ideas selected – 3 interviewees (including 3DTouch project)

– 3 participants of 3DTouch Team

– Members of International Roadmap Committee (steering committee of ITRS) participated in 17 face-to-face meetings and 40 conference calls

– steering committee has two to four members from each sponsoring region (Europe, Japan, Korea, Taiwan and the US). Its mission is to provide guidance/coordination for the technology working group leaders

– Technology line managers responsible for each project cluster (5)

– R&D team managers (6)

– R&D specialists of Bipolar project portfolio: 4 from device development teams and 3 from design team

– PhD candidates in bipolar team (4)

– Collaborating laboratories (2)

– Business Units – 2 persons from automotive and interface groups (interested in bipolar-based technology)

– R&D financial structure (1)

– Project and programme management office specialists (2)

– Intellectual property management specialist (1)

Supporting documents

Internal press releases, innovation week programmes, flyers, the three databases associated with idea collection for each contest, evaluation committee assessment reports, presentations of selected ideas at various milestones, mail and survey results

ITRS conference calls of International Roadmap Committee (steering committee of ITRS) since 2005 (the fourth author attended), working documents of several specialized working groups of the ITRS and publicly available documents

Internal database of document workflow for each thesis project (including annual reports, project description, final document and resume presentation) and description of associated collaborative projects if PhD students were part of a more global European and international programme

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Researchers’ Roles in Portfolio Investigation

The first author was engaged in the collabora- tive action research with a company from 2010 until 2013 (Adler, Shani & Styhre, 2003). She was actively engaged in the study and collabo- rated with the practitioners. The fourth author is a company employee, and his involvement ensured privileged access to data collection and exploration. In Case 1, the fourth author’s role was to support activities related to organ- izing the innovation contests. The first author’s role varied in this case from purely observa- tional activity to supporting participants’ reflection and facilitating portfolio exploration issuing from ideas. In Case 1 the first and the fourth authors organized 20 semi-structured interviews (40 hours) and were engaged in the observation activity during the four work- shops organized by ST for contest participants. In Case 2, the fourth author conducted the data collection. He attended 17 face-to-face meet- ings and 40 conference calls of the Interna- tional Roadmap Community and is directly involved in the ‘More than Moore’ initiation of the ITRS. In Case 3, the study was conducted ex post and the first author role was to analyse the portfolios. In total, 30 semi-structured interviews were conducted by the first author (30 hours). Observations were compared and synthesized between the first and fourth authors. The second and third authors were not directly involved in the empirical research, and their participation allowed independent analysis of the data and ensured the establish- ment of cross-data observations.

Data Collection and Analyses

The information-gathering techniques used in this study were interviews, documentation and observations during meetings or confer- ences. The interviews followed semi- structured, open-ended guidelines. To learn about each case study, we interviewed a variety of company representatives and exter- nal collaborators associated with each portfo- lio from a variety of functional perspectives, including senior management and project and portfolio managers, and experts with commercial, marketing, financial, technologi- cal, research, development and operational backgrounds were involved and directly par- ticipated in executing, organizing, managing or decision-making roles within the portfolios. The backgrounds and experience of the inter- viewees varied within each case to ensure multiple sources of information (Table 1). Each interview lasted approximately 1–2 hours. The data from the interviews were transcribed and a representative set was used to establish common themes. This set was obtained

through a within-case analysis to reduce the data from each data setting, group the cases and ensure cross-case synthesis (Yin, 2008).

The internal validity and reliability of the chosen methodology were achieved through triangulation among the conducted case analy- sis, the derived analysis and judgements of company representatives. Feedback was solic- ited from the interviewees on the cross-case analysis. This procedure enabled continuous involvement of the firm according to the guidelines of engaged scholarship (van de Ven, 2007) and collaborative research (Shani, Coghlan & Coughlan, 2008). Overall, over a three-year period, the authors had frequent access to case information and organized feed- back sessions with company representatives. The cases were conducted separately over slightly different time periods. Comparative analysis was conducted after all the data were collected and grouped. To ensure visibility and gain further perspective on data analysis, steering committees were organized in which all the authors shared their insights with company representatives (as part of a longitu- dinal study with ST). The committee met every 3 months. This involvement allowed for understanding of multiple sources of influ- ence. In addition to the data collection, a review of secondary sources was conducted. These supporting documents included multi- ple sources of information (Table 1). In the fol- lowing sections, we briefly describe each case.

Case 1. Innovation Challenge

An innovation contest called the ‘Business Innovation Process’ was initially organized in 2009 by two geographical sites of STMicroelectronics in France (Crolles and Gre- noble, which house more than 6,400 employees) located in the Rhone Alpes region, which is known as the ‘French Silicon Valley’ in microelectronics and nanotechnology. The contest focused on transversality, ecosystem development and value for users and for ST on future innovative solutions to address several business areas. The process was launched with the goal: ‘to boost the Grenoble and Crolles sites’ contribution to ST value creation through better innovation and better use of local clus- ters’ (BIP, 2009b). The process involved phases of challenge initialization, idea generation, selection and idea development. The high number of ideas collected through each chal- lenge (33, 60 and 110) resulted in 20 selected projects that were built through idea grouping and generalization (over a three-year period).

Overall, of the 20 projects that issued from the contest, only the four that are still ongoing appear to be structured based on generic

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technology design. These projects seek to develop new technologies and orient them towards several emerging markets. The proj- ects were used to form their own generic technology-based portfolios by creating new complementary projects.

Case 2. ITRS ‘More Than Moore’ Technology Working Group

The ITRS aims to provide industry with roadmaps that ‘align’ the priorities among the various actors responsible for transforming an idea into growth through innovation. In their study of the ITRS, Le Masson et al. (2012b) demonstrated the possibility of collectively managing the innovation capabilities of the ecosystem by creating roadmaps that are largely driven by the predictable range of tech- nological change, which is known as Moore’s Law. Technology working groups of the ITRS International Roadmap Community are responsible for creating their roadmaps according to future transistor generation and the challenges associated with scaling. They address uncertainty reduction for predefined technological domains (i.e., system drivers, design and other components).

The ITRS first noted the ‘More than Moore’ trend in 2005. The ‘More than Moore’ addresses situations in which the goal is no longer miniaturization; the exploration is exposed to various emerging markets and technologies that involve the management of various parameters. This trend demonstrates that the decoupling of the market and tech- nology that is common in the semiconductor industry could no longer be supported; com- panies are now truly in double unknown situations, with many potential markets exhibiting high levels of uncertainty with regard to size, timing and needs, and with many potential technologies. In 2011, the European members of the committee wrote a ‘More than Moore’ white paper that guided the ITRS community to identify those ‘More than Moore’ technologies for which a roadmapping effort would be feasible and desirable (Arden et al., 2010). This committee seeks to ‘build the link between societal needs, markets and technologies well beyond the ITRS current practice, and is likely to require the involvement of many actors beyond the ITRS historical membership’ (Arden et al., 2010). The white paper pro- posed complementing the usual technology push approach of the ITRS by sketching the broad ‘application scenario’. Technology building blocks that should be roadmapped ‘have to enable functionalities to account for several applications and markets’ (Cogez

et al., 2013). The ‘More than Moore’ technol- ogy working group attempts to build a transversal roadmap based on generic func- tions. These generic functions are precisely the common technology needs of various future markets, which can in turn be used as templates for companies dealing with portfolio structuring in double unknown situations.

Case 3. Research Project Portfolio

The portfolio of PhD projects conducted within ST from 2002 to 2010 was considered for analysis. These projects are managed within the Technology R&D group. Overall, the data represent 405 thesis projects. The projects are classified according to the techno- logical group ownership (similar to the tech- nology working groups of the ITRS), in which each group owns its own portfolio. The analy- sis showed that the research groups primarily managed their project portfolios independently. Each research project lasts approximately 3–4 years, and the results are communicated within the groups and used to define goals for subsequent exploration. The available resources are shared within the groups.

Within the groups, the Advanced R&D group is largely responsible for the ‘More than Moore’ project exploration. Its portfolio (four groups of ten) directly incorporated market knowledge and thus resulted in faster market disruption. For example, the bipolar project portfolio (ten PhD projects involved from 2002–2010) and the corre- sponding roadmap were driven both by the increase in the optical communications data rate and the emergence of applications at higher frequencies (Chevalier et al., 2007). The portfolio was structured along the bipolar technology adapted for millimetre- wave applications. It is a technological plat- form based on a heterojunction bipolar transistor (HBT), which has many advantages over complementary metal oxide semicon- ductor (CMOS) devices, such as its low noise factor, higher voltage and higher resistance for the same speed (for further details, see Chevalier et al., 2007). The co-exploration of technology and markets enabled the introduction of this technology to various markets, such as rapid download, optical communication, medical and high- frequency markets. A previous study (Kokshagina et al., 2013) demonstrated that the technology behind this project was generic and that the portfolio was structured in order to support and introduce this tech- nology to several market areas.

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Results

Case Descriptions: Portfolio Structuring in Double Unknown Situations for Generic Technology

The case analysis enabled an examination of three cases structured around the portfolio establishment for generic technologies. From the three cases, only portfolios seeking to operate in multiple environments were taken into consideration. For each case, we investi- gated how a double unknown situation was tackled, how the portfolio was structured to ensure the exploration of generic technology and how the interdependencies were defined.

In Case 1, the technologies mastered by the two sites involved in this contest were diverse. These technologies were developed by the central R&D groups that are responsible for specific technological development, advanced R&D units that seek to explore immature and still-unknown technologies, external R&D centres that are involved in technological development with ST, and R&D groups that are associated with each business unit inde- pendent of the general R&D. On the technol- ogy side, the contest allowed the open participation of any employee from these groups. Likewise, the wording regarding the targeted uses and markets allowed for a wide variety of solutions involving the open partici- pation of all the business units and strategy and marketing units (Table 2). Hence, this process was clearly positioned in a situation of double unknowns (double technology and market exploration) and privileged open col- laboration and learning.

Case 2 was driven by the ‘More than Moore’ concept to account for technologies that do not necessarily follow the CMOS miniaturization trends and that represent a growing part of the total silicon-based semiconductor market. The sheer diversity of both those technologies and their potential applications render a roadmapping exercise very challenging. The heterogeneous integration of digital and non-digital functionalities into compact systems is one of the key drivers for a wide variety of application fields, such as communi- cations, automotive, environmental control, healthcare, security and entertainment. To maintain technological leadership, companies must be prepared for breakthroughs in their expertise, architecture and functionality and the chosen forms of business models. The role of the ‘More than Moore’ technology working group is to structure the exploratory activity in double unknown situations, and to deliver innovative solutions to the markets. Through ‘More than Moore’ technology working group

creation, the exploration of highly innovative technology concepts in double unknown situations is encouraged.

Similarly in Case 3, only portfolios that were well positioned to address the ‘More than Moore’ issue were chosen. For example, at ST, a micro-electro-mechanical-system (MEMS) started in 1996 when the MEMS Business Unit was created. This unit primarily analysed the state-of-the-art of the market. A project leader of MEMS development at ST, noted:

It was 2000, and there was no market or any customers yet! We had to create them, so we started by looking at what already existed. (Internal ST Document)

The intentional exploration of double unknowns and the generic character of the semiconductor industry allowed ST to profit from these unknowns to design common plat- forms. These common platforms, based on technological building blocks that address generic functions, are common for several emerging applications and allow building market modules by reusing a platform core. For example, in Case 1, a generic platform to develop ‘an active surface to simulate haptic touch sensations’ was thought to maximize the number of targeted environments, including e-commerce applications, consumer back type keyboards for visually-impaired people, auto- motive applications gaming, and medical diagnosis through surface simulation using MEMS or piezoelectricity actuator (Figure 1). This platform was developed from the initially submitted idea:

Based on the material properties (tissue, wood, leather, etc.), a MEMS actuator can simulate the surface of the object to the cus- tomer at home and help him to select and buy products online. This solution can be dedicated to medical applications, to estab- lish diagnostics at distance, [to] e-commerce applications. (BIP, 2009a)

The proposal was selected as a result of both its disruptive nature and its vast market poten- tial. The resulting generic technology indi- cated the method of developing a platform that addressed generic functions independent of the environment and dissociated them from the adaptable modules that included specific functions. Furthermore, platform enrichment was organized through portfolio creation, which included the development of both inter- dependencies to address the development of market modules by reusing generic technol- ogy, and management to ensure the deploy- ment of market complementarities and generic core enrichment. The generic haptic technol- ogy yielded by this idea gave rise to a portfolio

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Table 2. Generic Technology-Driven Portfolio and the Role of Cross-Application Manager

Case 1 Case 2 Case 3

Context: double unknown exploration Technological

complexity: High variety of technological domains

Optical sensors, image processing techniques, communication technology, haptic technology, 3D, RFID, sensors, MEMS, radars

Accelerometers and gyroscopes, microphones, and RF MEMS, including resonators, varactors, and switches

Etching, lithography, MEMS, 3D integration, bipolar, FD-SOI

High variety of application domains

Consumer, medical, entertainment, automotive domains, gaming, security, retail, navigation

Medical, automotive. energy, lighting, security, transport & mobility, communication

Consumer, medical, entertainment, automotive sectors, gaming, security, energy, lighting

Portfolio structure: generic technology and associated modules Example of emerging

platform Platform based on active

surface to elaborate haptic touch

MEMS technology-driven platform

Bipolar technology-driven platform based on hetero-junction bipolar transistor

Example of portfolio structuring

Specific projects based on: – developing market

complementarities, such as e-books, educational, social networks, gaming solutions, gesture learning and object customization, security were added

– further enrichment of the generic platform

– developing specific functions to address a list of market applications

Specific projects based on: – developing

accelerometers and gyroscopes, microphones, and RF MEMS, including resonators, varactors, and switches by building on the platform

– to address optical filters, picoprojectors, the electronic nose, microspeakers, ultrasound devices and other emerging products

Specific projects based on: – developing market

complementarities for high-frequency applications, such as targeting high-frequency applications: optical communications up to 100 Gb/s, automotive radar sensors at 77 GHz, wireless communications at 60 GHz, high-speed instrumentation, non-invasive imaging (medical and security) – enriching the platform itself

Result Four generic technology-driven portfolios led to successful generic portfolio creation

Generic technology-driven roadmaps to constitute platforms (generic function) and ensure the creation of variety of product families

Four generic technology-driven portfolios led to successful generic portfolio creation

Portfolio structure Formulation and execution of projects built on a specified set of generic technological platforms

Interdependencies High resource and technical interdependencies because of the common platform and resources

Managerial role: Cross-application manager (CAM) CAM Platform owners became

CAMs progressively Coordinator of technology

working group ‘More than Moore’

Technological leaders and technology line managers

Role of CAM – Ensure technological development of platforms and platform modules through project structuring and reuse

– Manage balance, resource allocation and coherence of portfolio

– Hold group together – pursue exploration of generic functions for both technologies and key application domains

– Ensure co-ordination among R&D groups to constitute a platform

– Establish collaboration with multiple business units

– Manage balance, resource allocation and coherence of portfolio

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that currently comprises several research proj- ects, collaborative projects with external research centres and industrial partners, and ongoing projects in business units to develop commercial products. The generic portfolio was established to explore new unknown environments by acquiring the necessary knowledge and expertise (Table 2).

In Case 2 (Figure 2), a new technology working group for MEMS exploration was spun off of the wireless technology working

group (where only MEMS used for radio fre- quency filtering applications were discussed) in 2011. MEMS, micron-size devices that can sense or manipulate the physical world, are exceptionally diversified. MEMS encompass the process-based technologies used to fabri- cate tiny integrated devices and systems that incorporate functionalities from different physical domains into one device. MEMS revolutionized various existing product domains and created new ones by bringing

Figure 1. Example of Generic Portfolio Structuring in Case 1: Haptic Technological Platform

Figure 2. Generic Roadmap Establishment in Case 2: More than Moore ITRS Technology Working Group

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together silicon-based microelectronics and micromachining technology (Bryzek, 1996).

MEMS technology became a hot topic in the industry around 2006 with its introduction first in gaming consoles and later rapid expan- sion into mobile phones and other devices; however, MEMS makers were at first reluctant to work together towards a roadmap because of scepticism about decoupling technology and product; some experts argued that in MEMS, the technology is the product. They finally agreed, nevertheless, to meet around one common issue: the testing of their devices, for which they felt not enough research was being conducted, while this issue represented both a sizable proportion of their costs and a demand from their customers. Once this com- munity was created around this common purpose, it was possible to introduce discus- sions about more general future needs, with several driving applications, such as tablets and smartphones. MEMS-based roadmaps comprise the generic platforms and specific projects to address pico-projectors, the elec- tronic nose, micro-speakers, ultrasound devices and other emerging products.

Throughout Cases 1 and 2, we observe that generic technology is designed for a range of emerging markets; it stimulates the creation of new applications and revolutionizes exist- ing ones. For example, the emergence of microfluidics in medical applications opens many possibilities for MEMS in drug delivery. Electronic nose applications that use MEMS principles are being developed for a wide range of healthcare and biomedical sectors

and are revolutionizing how this traditional sector operates (Table 2). To ensure wider applicability or flexibility of generic technol- ogy, the interdependencies need to be consid- ered carefully.

Within the bipolar research portfolio in Case 3 (Figure 3), project interdependencies (especially learning interdependencies) and technological uncertainties are effectively managed. The purpose of Si-based bipolar microwave technology is to combine the advantages of two types of transistors: the bipolar transistor for higher gain, higher switching speed, better noise performance and low consumption, and the CMOS transistor for higher density, better performance for logic operations, lower speed blocks, and control functions.

A high-frequency bipolar transistor with an improved back end (Chevalier et al., 2007) was designed to address all the environmental con- straints and succeed in several market appli- cations with low adaptation costs (such as automotive radar, fast download applications, medical, non-invasive imaging, optical com- munication). The project team that worked on the bipolar technology reconstructed a sort of artificial market space with Wi-Fi to enable high device connectivity and a wider scope than the alternatives that facilitated technology adoption by derivative markets later. The generic technology design enables maximiza- tion of the list of functions by superposing several applications. Instead of fixing the set of market applications and organizing explora- tion by minimizing resources spent, the team

Figure 3. Example of Generic Portfolio Structuring in Case 3: Bipolar-Based Platform

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inverted the reasoning by fixing the resources and maximizing the scope of the applications considered for platform building. Regarding the analysis of the PhD projects, the bipolar portfolio consists of 10 projects (2002–2010).

This portfolio, oriented toward generic tech- nology exploration, aimed to mobilize the resources from all the other research teams and build interdependences with various busi- ness units and external partners to better posi- tion the portfolio in multiple markets. Once the platform core was designed, the projects were launched to optimize the technology and address the predefined market applications. For example, a project started in 2005 aimed to ‘optimize the process of bipolar heterogeneous transistors for wireless communication and power amplification’ and thus, built a module to ensure greater openness of the bipolar plat- form (Figure 3).

All the examined portfolios shared a common platform – generic technology – and aimed to structure their portfolios by ensuring platform reuse for emerging market applica- tions. The value of flexibility was clearly inher- ent in generic technology. These three cases show that portfolio structuring is critical in ensuring the future core value, especially in the unknown exploration phase.

Portfolio Management in Double Unknown: Towards Cross-Application Management

The effect of cross-disciplinary exploration, exposure to unknown structures and the con- stant technology-market coordination process resulted in greater genericity in all of the ana- lysed cases. The multiple case analyses reveal that generic technology appears to succeed when managerial support is present and the transversal technological and market explora- tion is organized. For example, within the innovation process in Case 1, the project leaders who focused their attention on the generic functions succeeded in developing a generic platform for several markets. More important, the generic projects were the only ones that were considered successful within the context of these challenges (Table 2). The innovation contests played the role of innova- tion hubs or incubators to prioritize the col- laboration of various business and R&D units. These contests privileged the exploration of multiple emerging markets and new technol- ogies by creating interdependencies and reducing unknowns. The exploration relevant to generic technology aimed to propose a solu- tion that imposed the collaboration of several R&D groups to address the needs of several business units and stimulate the exploration of new markets. The proposals that resulted in

platforms attempted to create complementary projects and organize portfolios to explore both the generic construct and its market modules. By pursuing generic technology design, the manager’s role is to work on the generic aspects of the solution rather than prioritize specialization in more promising markets. For example, one of the potential cus- tomers was interested in using haptic technol- ogy for an eye-less keyboard application and haptic mouse that aimed to facilitate the adop- tion of the electronic devices by visually- impaired people or in conditions where access to the display was limited. If a manager chooses to address only these promising markets, then the transparency of a multi- touch capacitive solution required for smartphones and tablets would be difficult to even consider. In this case, the manager was able to design a portfolio in which functions specific to the market were managed in sepa- rate projects and in which the generic core was a common project that facilitated its reuse by the emerging market areas (Table 2). This manager, whom we propose to call the cross- application manager (CAM), was able to manage the links between the technological requirements and market needs (Figure 1). In contrast, a lack of collaboration within these roles and insufficient management of learning interdependencies might consequently lead to failure in generic technology exploration. Moreover, it is important to note the key role of the organizing committee, which did not seek to select the winner of the contest but privileged the accumulation of joint expertise in participants from different backgrounds. The committee privileged multi-market explo- ration and helped project leaders – future CAMs – build their network both internally and externally, and the team played the role of the interface among various technological and business groups. This team involved people from R&D, business units and strategic depart- ments (a total of approximately 15 specialists) (Table 2).

In Case 2, the transversal collaboration within ‘More than Moore’ and various tech- nology working groups and the exposure to disruptive markets led the ITRS to structure a portfolio of potential ‘More than Moore’ solu- tions. This portfolio presents the potential challenges that companies could meet and the directions that they could take to coordinate their scientific and development efforts. The idea of using generic functions and the incor- poration of market ideas permit the committee to structure the effort towards the portfolio of generic technologies (Figure 2).

The coordinators of the ‘More than Moore’ group play the role of CAMs within the ITRS

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community (Table 2). The existence of the tech- nology working group ‘More than Moore’ in Case 2 and its accomplishments, which were oriented towards the exploration of the double unknown, relies heavily on the involvement of its coordinator(s). CAMs privilege the con- struction of roadmaps in double unknowns based on the identification of generic functions (Cogez et al., 2013). The role of CAMs is to search for existing knowledge gaps in the landscape of technologies and markets to define the direction of technological develop- ment and identify interdependencies that can be built to acquire generic technology. CAMs do not seek to reduce uncertainty by choosing a particular technological trajectory but aim to structure unknowns to privilege generic tech- nology exploration. Their position within the ecosystem of the major players in the semicon- ductor industry facilitates their access to nec- essary information and enables them to test the relevance of their propositions. This case demonstrates that the highly co-ordinated activities of the individuals leading the ‘More than Moore’ trend have increased the impor- tance of this trend within the community. From its first mention in 2005, citations of ‘More than Moore’ reached 79 in 2011, and among 18 technology working groups within the ITRS, 11 cite ‘More than Moore’. Addition- ally, a purely ‘More than Moore’-oriented group was created in 2011 for MEMS portfolio exploration.

In Case 3, there were groups that established specific technology-market relationships. In this case, there was no need for transversal exploration towards the generic technologies; the idea was to reduce uncertainties and struc- ture project portfolios to attain higher benefits and increase the performance of the techno- logical solution. Once the levels of uncertainty are higher, the technology in question is likely to be generic, and the role of clusters for generic technology exploration will become advanta- geous. The presence of managers (the team coordinator and technology line managers) playing the role of CAMs enabled the company to build an interface within various business and R&D units and position technologies as generic at an earlier stage, which in turn allowed for more rapid technology appropria- tion by the market through the construction of previous interdependencies. The portfolio organization of the R&D projects enabled effec- tive exploration of the emerging market and technology spaces; it incorporated the clusters addressing unknowns, uncertainties and risks. The clusters addressing both unknown tech- nologies and markets require the presence of CAMs to co-ordinate exploration towards the design of successful generic technology.

Exposure to unknown markets and techno- logical structures provides an opportunity for CAMs to proceed towards generic technology development and build portfolios to address multiple markets. Portfolio structuring for generic technology requires CAMs to seek transversal ideas to address several market areas (existing and new) and new original technological solutions that are flexible and robust to address several emerging markets. CAMs aim to explore a variety of market applications while reusing the existing technological competences and developing new competences with minimal costs of re-adaptation between future modules. Although these transversal projects offer solu- tions for several business units (such as bipolar portfolio in Figure 3), they often pose challenges in terms of investment for technol- ogy development, managerial responsibility, technology ownership and time to market. For example, business units must decide how they will share the costs of platform development and which remaining costs they must pay for market complementarities. To ensure platform adaption by the various markets, CAMs must manage these organizational risks.

A common observation across cases shows that the successful implementation of generic technologies requires multiple roles to guide the technology and market exploration phases and their propagation, appropriation, commu- nication and management. Together these results show the similar nature of the CAM’s role that consists in co-ordinating the explora- tion between various technological and market groups to identify the opportunities within a portfolio and create balanced portfolios. The CAM must be able to mobilize technical experts to assess the technological character to estimate whether the emerging technology has the potential to address emerging market needs. The CAM defines generic technologies and organizes their exploration such that they are able to attract market functionality and stimulate further market exploration (Table 2).

Discussion and Conclusion

The goal of this paper is to investigate how portfolios can be structured in double techno- logical and market unknown situations by exploring the possibility of developing generic technologies and portfolio management for generic technologies.

Toward Portfolio Structuring in Unknown Situations

The importance of the ideation or fuzzy front end phases to the more operational phase of

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portfolio management is stressed by the litera- ture (Geraldi, 2008; Ozcan & Eisenhardt, 2009; Heising, 2012). This paper introduces an effec- tive method of originating high-performing portfolios within a company challenged by high uncertainty and a dynamic environment. Despite the challenges associated with envi- ronments with high uncertainty and high velocity common to high-tech industries, such as semiconductors (Cohen & Levinthal, 1989), this work shows that it is possible to account for portfolio management in unknown envi- ronments through the design of generic tech- nology that creates interdependencies within technologies and markets and that structures a portfolio to explore this technology and its market derivatives. Companies that engage in the exploration of generic technologies natu- rally link their portfolios with their strategic orientations. Our results indicate that it is pos- sible to structure portfolios based on generic technologies that structure unknowns instead of simply reducing them.

The economic success of a portfolio depends on its commercial and market success (Shenhar et al., 2001). To account for successful exploration, it was demonstrated that in unknown situations, management of both uncertainty and interdependency is crucial. In double unknown situations, the existence of multiple emerging market signals and techno- logical alternatives appear as prerequisites for the design of generic technologies to build portfolios across the emerging generic core. Project portfolios for generic technologies resolve unknowns by enhancing co-operation among technological, market and strategic research units and thus create synergies within portfolios (Cooper, Edgett & Kleinschmidt, 2001; Loch & Kavadias, 2008). Once a portfolio is structured, it resolves unknowns by structuring the exploration space. This mode of structuring portfolios around generic core and modules ensures the successful resolution of unknowns because the unknowns that are relevant to this particu- lar challenge are resolved. The earlier efforts in portfolio organization enabled reducing unknowns and accounting for higher genericity. The mode proposed in this paper certainly poses new ques- tions; however, for that particular situation, the unknowns are reduced due to portfolio structuring and new interdependencies created based on generic technologies.

The opportunity to design platforms and develop new platform-based portfolios helps companies ensure product variety and reduce complexity within product lines (Pruett & Thomas, 2008). This paper shows that the projects that attempt to design generic tech- nologies enable the organization and struc-

turing of portfolios under contexts of double unknown. The generic project is the core of a portfolio and must ensure its independence from the set of possible specific projects (such as specific market applications) and create interdependencies with the emerging markets. The generic platform must be attrac- tive for multiple markets and stimulate their creation.

Resource limitations require an organiza- tion to strategically allocate resources to a subset of possible projects (Dickinson, Thornton & Graves, 2001). Portfolio design based on generic technologies is helpful for building more balanced portfolios. The portfo- lio structuring for generic technologies that is examined in this study can help balance the levels of promise and interdependency of a platform owner and its derivatives, where the latter can exist in projects both within and outside the company. This portfolio is bal- anced by the constant resource inter- dependencies created during the portfolio structuring (Killen, Hunt & Kleinschmidt, 2008; Meskendahl, 2010). Additionally, plat- form development ensures that firms can access external resources by opening up the platform and attracting complementary innovators within a supportive ecosystem. The possibility of incorporating new projects over time signals the flexibility and easier adapta- tion of a portfolio in the face of new challenges (Olsson, 2006). As a result, long-term strategic and less risky application-specific projects are balanced within these portfolios. These contributions are rooted in the economic and organizational aspects of platform-based organizations (Baldwin & Woodard, 2009; Gawer, 2014) and ensure the efficient combi- nation of contributions from multiple project perspectives.

Cross-Application Manager and Corresponding Organizational Structures

The results indicate the existence of an actor(s) who has the expertise to identify missing tech- nologies and markets and construct interde- pendencies. We refer to this actor as a cross- application manager – an actor who is able to ensure interaction between the innovative concepts developed in different business and research lines. This role requires specialized capabilities to transversally invest in different fields to ensure the cross-application character of generic technologies, demonstrate the external uncertainties, stimulate the environ- ment and ensure the learning process in situa- tions involving unknowns (absent in the state of the art and characterized as knowledge gaps).

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The three cases discussed in this paper jointly show the relevance of this actor in dif- ferent situations and exhibit different forms of generic technology-based portfolios.

The figure of the CAM supports the changes in both markets and technological exploration and the operating conditions that are directly linked with the innovation capabilities of organizations. To ensure successful manage- ment of generic technologies, the cross- application manager must control a totality of the knowledge structure.

The platform leader and his role comprise the interaction with a large number of complementarities that occupy peripheral positions (Gawer, 2010). Similar to the plat- form leader, the role of the CAM comprises the interdependencies that accumulate to further promote the portfolio that is designed as a result of the platform. However, in addi- tion to the duties of platform leader, the CAM role also involves generic core identification and building. The CAM’s role is to ensure plat- form insertion into both existing markets that can generate profit in the short term and emerging markets to ensure long-term growth for generic technology. Through the process of unknown exploration, this actor permits the co-ordination of exploration activities within an organization. When co-ordinating portfolio structuring in the context of unknowns, the CAM encounters double difficulty because potential value is difficult to estimate due to the rapidly changing industrial environment and high volatility.

This study reveals that the CAM is respon- sible for (1) managing explorations in multiple technology and market areas simultaneously in a double unknown context; (2) knowing the functional structure of emerging and existing markets within various business units and their existing technological portfolios; (3) evaluating external and internal R&D techno- logical portfolios and revealing the character of technologies while identifying knowledge voids; and (4) identifying opportunities for generic technology development. Due to the specificity of the function of the CAM in con- ducting the reasoning in unknown situations, it appears important to distinguish this role from those that already exist, such as champi- ons, brokers, boundary spanners and heavy- weight project leaders (Keller & Holland, 1975; Wheelwright & Clark, 1992; Hargadon, 1998) because of the nature of the exploration in double unknowns. However, these roles are not contradictory. For example, similarly to boundary spanners, the CAM ensures effec- tive monitoring of the environment and per- forms boundary-spanning activity to link organizational structures (Keller & Holland,

1975), although the CAM’s specificity lies in the portfolio structuring based on the design of generic technologies. CAMs ensure knowl- edge brokering from where it is known to where it is unknown by spanning multiple markets and technologies and searching to engage in interdependent activities that enable innovation (Hargadon, 1998). A CAM may proceed as a knowledge broker once a genericity is designed and interdependencies are structured as activities within a portfolio. However, the specific competences that differ from knowledge broker functions are required to successfully structure portfolios based on generic technologies in unknown situations. A parallel situation involves a heavyweight project leader introduced by Wheelwright and Clark (1992). Heavyweight leaders (similar to CAMs) must ensure access to a variety of expertise across the organization, support a variety of functional organizations, and stimu- late and facilitate communications across func- tions (as in the example of heavyweight leader Scott Shamlin of HP). Like the heavyweight project leader, CAMs are addressing the cross- organizational challenges of large firms. However, CAMs’ objectives are different: they explore unknowns, aim to ‘mutate’ the exist- ing ecosystem by defining generic technol- ogies, ensure their innovative design across different functions that exist internally and externally, and structure the portfolio based on the emerging generic technology and organizational capabilities.

This figure may be challenging to identify, and the necessary level of expertise is difficult to achieve without relevant experience; however, this role appears necessary in designing generic technology and structuring portfolios. The cases show that the CAM is not necessarily one actor but can be a structure or a team (as in Cases 2 and 3).

Further Research and Implications

The work on innovative research portfolio management can lead to new tools and frame- works for companies confronting technical challenges of increasing complexity in addi- tion to shorter product life cycles. This envi- ronment forces firms to rely on R&D as a source of strategy, and companies are inclined to evaluate their technologies from a portfolio perspective in which a set or sub-set of R&D projects are evaluated together in relation to one another. This research creates new per- spectives for management of high levels of uncertainty in the process of exploring emerg- ing industrial sectors (Rothwell & Gardiner, 1989). Although the results from these three case studies in the semiconductor industry do not establish definite principles for how

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portfolios should be organized in double unknown situations, this article suggests a way of structuring high-performing portfolios based on generic technology. Portfolios struc- tured around generic technology require continuous co-ordination and exploitation (Müller, Martinsuo & Blomquist, 2008). Addressing the importance of high uncer- tainty and many unknowns, this work pro- vides the important insight that practitioners should address unknowns as opportunities to meet strategic objectives (Olsson, 2006, 2008; Perminova, Gustafsson & Wikström, 2008; Petit, 2012; Martinsuo, 2013).

This research demonstrates the importance of the CAM in structuring and guiding port- folios of generic technologies. This study contributes to examining the link between the organizational structures and necessary competences for portfolio organization to account for PPM in unknown environments. The empirical understanding of the issues of generic technology exploration in highly uncertain, dynamic environments and the associated role of management were added to the interdisciplinary PPM context. This research provides a new perspective on the strategic management of innovation through portfolio structuring.

Generally, the literature confirms the inter- est in developing generic technologies (Maine & Garnsey, 2006; Youtie Iacopetta & Graham, 2008). However, methods of organizing the development of generic radical technologies and associated management techniques remain understudied. In terms of the contribu- tion to the literature, the paper addresses the issue of designing generic technologies to provide insights into portfolio organization to account for genericity and define the impor- tance of the managerial role (defined here as the CAM) in accounting for the design of generic technology. However, this research is limited to the empirical context of the semi- conductor industry. The findings must be verified in the larger context and within various industries. The sample size should be increased, and the effect of the presence of generic technology on the success of the overall portfolio must be quantified. The con- ditions in which a company should pursue generic technology exploration within a port- folio and organize its exploration in the context of unknowns remain to be identified.

Finally, our findings bring new perspectives on creating high-performing portfolios built on generic technologies. High variety in port- folios often implies higher costs and greater resources required. By building portfolios in generic technologies in double unknown situations, a firm can ensure variety by lever-

aging the emerging platform. This research provides important insights into the govern- ance of double unknown situations and clari- fies the capability of actors in co-ordinating exploration and portfolio structuring for multi-project firms when both technology and markets are unknown.

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Olga Kokshagina (olga.kokshagina@mines- paristech.fr) is a postdoctoral research fellow at Mines ParisTech, France, with an interest in contributing to a deeper under- standing of the innovation processes and associated business models in novel and uncertain contexts. She carried out her PhD at the Centre for Management Science (CGS), MINES ParisTech. Her research was a part of the CIFRE programme conducted in collaboration with STMicroelectronics where the author was deeply engaged in a range of innovative projects. Her disserta- tion stands out by its contribution to the literature in engineering design, technology management and uncertainty and innova- tion management.

Pascal Le Masson (pascal.le_masson@ mines-paristech.fr) is Professor at the Center for Management Science, MINES ParisTech, France. He is Chair of Design Theory and Methods for Innovation, and Head of the Engineering Design curricu- lum at MINES ParisTech. With Armand Hatchuel and Benoit Weil, his research unfolds in three main directions: the analy- sis of innovation techniques such as creativ- ity, prototyping and user involvement processes; the organization of design- oriented organizations; and models of growth in design-based economies. Pascal has published several books and many journal articles. He co-chairs the Design Theory Special Interest Group of the Design Society with Yoram Reich (Tel Aviv Univer- sity) and Eswaran Subrahmanian (CMU).

Benoit Weil ([email protected]) is Profes- sor at the Center for Management Science, MINES ParisTech, France. He is Chair of Design Theory and Methods for Innovation, and Head of the Engineering Design cur- riculum of MINES ParisTech. His research focuses on the rationalization of collective actions. He has created the Research Pro- gramme on Design Activities with Profes- sor Armand Hatchuel. Together they proposed a new theory of design reasoning (C–K theory), which accounts for the dual expansion of knowledge and concepts char- acteristic of innovative design. He has pub- lished several papers and books.

Patrick Cogez ([email protected]) is Director, Universities and External Rela- tions at STMicroelectronics, France. He is STMicroelectronics representative with the Steering Committee of the International Technology Roadmap for Semiconductors, a member of the Micro- and Nanotechnol- ogy Evaluation Committee of the Cluster of Competitiveness MINALOGIC, and Chair- man of the Board of Grenoble Institute of Innovation, created in 2012 by Grenoble University to foster research and education in Human and Social Sciences for Innova- tion. A reflexive practitioner, Patrick has published several research papers analys- ing the dynamics of innovative projects and collaborative efforts in the semiconductor industry.

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