The big questions
The nature of existential questions has changed in recent times. Existential risks rather than existential reasons now busy our minds. And increasingly so in light of mounting global challenges and crises. How will they be resolved if at all? Is there sustainability?
Deniers apart, most of us agree that most contemporary global challenges and crises not only are man-made (anthropogenic) but also require man-made solutions, in particular technological ones besides political, economic, legal and behavioral. Such technological solution approaches in turn necessitate coordinated R&D efforts across governments, industry and universities on a grander scale than ever before to provide the crisis critical technologies and innovations called for.
Judging from past crises necessity rather than opportunity appears to be the true mother of invention (although the literature gives a mixed verdict on the dynamic interplay between technology push vs demand pull factors in various types and stages of innovation processes). This is true also for the current Corona pandemic crisis, which has called forth many inventions and technology adoptions at a surprising pace. However, sheer necessity is not enough. It has to be matched with actors, activities and assets (resources) to explore and exploit invention possibilities which might proliferate but still might be insufficient. This brings management into the picture, and especially technology and innovation management since technological inventions often are necessary as well as costly to explore and exploit. New technologies moreover play a dual role as not only providing solutions to a problem but also potential problems with side-effects, misuse or overuse (e.g. of antibiotics or plastics), calling for more seasoned, integrated and long term technology management. This dual nature of new technologies is apparent in many of the global challenges and crises that are currently recognized. The current Corona pandemic crisis might not have been generated by new technologies (although some say so) but certainly the global spread of it was reinforced by transportation technologies. The latest – but arguably not last – global financial crisis around 2010 was in no small measure reinforced by new algorithms, digital networks and “financial engineering”. The big question then is: What is the role of technology and innovation management research in the various crises and global challenges ahead – and vice versa?
In what follows below the phrase technology management is taken in a broad sense and will include R&D and innovation management and policy as well as technology based entrepreneurship.
The purpose of this article is to explore – in all modesty – this challenging question and make a quest for reorienting traditional technology management more towards global challenges and their possible ensuing crises. As a fairly large and growing body of knowledge, anchored in universities and industry, the field has by and large developed in the absence of global challenges in the past. The field has nevertheless much to contribute in its current radically changing context, but it has to develop much more to that end in the future.
Global challenges and crises come in many varieties with some shared features – such as mostly being man-made with both causes and cures being technology related and interdependent – and with some specific features as to levels and rates of aggravation, warning signals, urgency etc. As the Corona pandemic crisis draws to a close in the sense that the initially sudden and unexpected pandemic is becoming endemic, there are signs of relief similar to how the effects of the likewise sudden and unexpected financial crisis eventually became contained and less worrisome. On the other hand, climate change is a well recognized challenge at a far larger scale with a collective concern at an all time high, still pinning hopes to its manageability because of its pressing but after all gradual nature. However, it becomes harder and harder to remain hopeful, not the least after the insufficient achievement at the recent COP meeting in Glasgow (meeting no. 26!). A contrasting example is an outbreak of nuclear warfare, being a major concern and X-risk (existential risk) since the 1950s, a crisis that indeed could be sudden and totally impossible to “manage”. In fact the limited manageability in this case is paradoxically by design in order to create credibility of a retaliation threat, a credibility that would be lost by a defender with the possibility to back off, which would be the individually rational defensive strategy and thus in turn invite an attack. (As proved in game theory and eccentrically explained by Dr. Strangelove in the movie.) This is a perfect – and frightening – example of how reducing the likelihood of a crisis to occur may increase its consequences if it after all occurs. A kind of opposite response to a crisis may also occur, i.e. the crises is allowed to escalate temporarily in order to increase the possibilities to eventually curtail it. (“Things have to get worse to get better.”) An example is the rapid spread of infection during the Corona pandemic which in fact significantly speeded up R&D and clinical trials of vaccines and to some extent also herd immunity. In both examples technology management are faced with challenging trade-offs and ethical questions.
The management of technology
General managerial responses to global challenges and crises are adaptation, mitigation and innovation, raising issues about trade offs, suitable strategy mixes for different actors and financing (see e.g. Spence 2011). As to relevant technological innovations they also come in many varieties and with differing roles.
How can these crisis critical technologies be incentivized and managed and what can the field of technology management contribute with in this context? As described in an earlier article in this journal technology management has developed as an academic field in the last 50+ years with an impressive list of knowledge contributions, e.g. regarding various technological phenomena like technological convergence, competition, races, substitution, diffusion, diversification, disruption, transitions, lock-in, etc. However, a dominant perspective has been how companies can manage such phenomena strategically and more generally how R&D and innovation processes in firms and industries could be incentivized and organized more effectively to increase innovativeness and local or national industrial competitiveness. At the same time a wider innovation systems perspective has evolved (as reviewed in Granstrand and Holgersson 2020), as well as technology and innovation policy studies but altogether somewhat disconnected to technology management. There has also been a certain disconnect between studies of entrepreneurs (actors), studies of technologies and innovations (assets), and studies of R&D (activities). The there are the usual disconnects between different levels of analysis (micro, meso, macro) and disciplinary perspectives although management is interdisciplinary by nature.
The grand nature of global challenges and technological response strategies obviously calls for more integrative approaches in technology management as well as in science and technology areas in general, albeit with the understanding that it is far easier to call for more integrative or holistic approaches than to pursue them. This implies among other things that technology management studies at the traditional micro level have to be designed to include more meso and macro level factors as well, such as sustainability and innovation policies, and in so doing also involve even more disciplines, such as political science, law and value ethics besides engineering sciences, economics and behavioral sciences.
The changing climate
Take climate change as an example. To meet that global challenge industries have to make several major technology transitions from fossil to non-fossil energy sources of various kinds (“green technologies”) for cars, steel, houses etc. at an unprecedented scale and synchronized pace across firms. To manage such technology transitions at firm level requires considerations of sustainability (economic, ecological, social), regulations, political issues, governmental policies, new market mechanisms for trading emission rights, collaborations and competition (“coopetition”), technology licensing, pricing and financing among others. In these cases technological necessity has become a commercial opportunity for some lead companies and countries and a survival threat to others. However, market mechanisms left on their own typically fail to swiftly generate and diffuse new substitute technologies, although some economists claim that proper market designs and price mechanisms will be sufficient. Also governments typically fail in “picking winners” among uncertain technologies, unlock technological lock-ins on the demand and/or supply side of their economies and kick-start new markets. That being said, governments after all have various technology and innovation policy measures that may not only mitigate market failures but enhance and complement market mechanisms not only for generating new technologies but also for widespread adoption and diffusion of them. The latter is not the least important in case of major transitions. R&D subsidies on the supply side can then be combined with technology procurement and tax deductions on the demand side as an example of a good mix of policy measures. Finally governments can and should also provide an institutional framework that is conducive to innovation and diffusion. In general governmental roles have and will become more important in meeting global challenges and crises, to some extent comparable to how the government and a military-industry complex (or ecosystem for that matter) have been crucial in times of war. Thus the whole issue of innovation governance through markets and/or management has become crisis critical at both micro, meso and macro level.
The necessary major technology transitions involve technological leapfrogging into radical and likely disruptive technologies without sufficient room for intermediate hybrid solutions and gap fillers between major new product generations, parallel solution approaches in R&D and technological diversity that the technology management literature in the past has advocated for managing technology transitions. The urgency to meet climate goals and commitments in the short and long run has moreover prompted a high pace in making these transitions. This high pace in turn easily leads to unbalances in the industrial system and its supply chains, reflected for instance in shortages of and high prices on electricity, key strategic metals, semiconductors and other complementary resources with few substitutes. Again markets and prices are arguably too slow in coordinating and whole new industrial and innovation ecosystems have to be built by management and/or government decisions rather than by markets alone. Waiting costs and mover advantages grow fast and economies of speed rather than economies of scale and scope take prominence in investment and financing decisions. Uncertainty grows as policy objectives are set for signalling reasons more long-term than ever, often far beyond the mandate period of current managers and politicians, thereby complicating accountability. Thus, current politicians, company boards and technology managers are taken into deep unchartered waters with a broad range of large risks – technical, commercial, economic, legal, political – which have to be weighed against each other in the shadow of existential risks.
The productivity of R&D
As to responses to challenges and crises new technologies and innovations are thus urgently needed and typically in turn need urgent adoption and diffusion on a broad scale (like vaccines). This raises the issue of R&D productivity, especially in terms of timely R&D effectiveness (rather than solely in terms of output/input resource efficiency). The “speed-to-market” and time-based management literature and experiences are rich and long-standing. As to R&D managerial approaches – such as concurrent engineering, internal competition and external collaboration (open innovation) – together with research tools – such as computers and communication – have proven to increase innovation speed from idea to market but possibly at the cost of reduced resource productivity, quality and safety. There are also studies showing a likely decline of R&D productivity at macro level due to many factors, prompting the authors to ask “Are new ideas harder to find?” (see Bloom et al.2017). At micro level much is known about how various barriers to creativity and innovation can slow down or misdirect R&D, e.g. autocracy, lack of resources or organizational conflicts between managers (of which much is known in practice but not in the literature).
On the other hand the Corona pandemic crisis has shown with no small surprise how fast several new vaccines could be developed – and approved – and also how to organize, digitalize and automate R&D in new ways. At the same time the crisis crowded out some R&D in other areas. Studies of this phenomenon as a natural experiment will be highly interesting and valuable as a demonstrator of improvement potential in an innovation ecosystem. Any researcher moreover knows how much leverage there is in R&D processes if necessity kicks in or for that matter competition as in the case of the HUGO-project for mapping the human genome. Collaboration and extra resources can speed up R&D (but also sometimes slow it down) as could various technological research tools (AI, computer modeling, demonstrators, etc.). Another case illustrating how R&D productivity can be significantly improved is provided by AstraZeneca who already in 2011 launched a corporate wide project aimed at improving the R&D productivity through a set of measures, called the 5R framework (see Morgan et al. 2018). Still there are limits how much time you can buy with more resources, tools and technology management.
Thus R&D speed and productivity can be enhanced with various means – managerial, economic, legal, behavioral and technological. However, R&D speed and productivity is clearly not an end in themselves but means to innovation and economic growth, in turn means for value creation and then not primarily at company level but at societal level as the ultimate end. Value creation in turn is creating resources for additional R&D, innovation, growth and value creation. Fig. 1 illustrates this by a circular (rather than linear) innovation model.
The model illustrates the key dynamics and the need for a controllable positive feedback for sustainable growth and value creation, although the model is simple with many factors and relations suppressed. Here it must be noted that both growth and value creation can be negative. This is not necessarily a bad thing since imminent value destruction creates a sense of urgency and necessity, and mothering of invention in turn.
This is particularly likely as a result of crises and the dual nature of technologies mentioned in the beginning. The financial crisis and the Corona pandemic are good recent examples which may be joined by climate change in the future. Economic growth is not intrinsically counteracting sustainable value creation (although often portrayed as such in popular debate) but can and must be controlled within some limits (set e.g. by prices, rules and regulations). Institutional variables and exogenous constraints (resources, laws of nature etc.) surround the innovation and diffusion processes and also function as controlling factors at higher levels of governance, particularly important for meeting global challenges.
Ex interim the Corona pandemic crisis has provided a stress test of institutions, where international agreements have partially failed in face of fatal vaccine nationalism while the patent system has stood the test and the global innovation ecosystem has improved. The Corona pandemic crisis has also enhanced technology management practices (and theorizing prospects) and elevated its role for meeting future global challenges and crises.