Nature of the Capability
Once a new (technological or market) opportunity is sensed, it must be addressed through new products, processes, or ser- vices. This almost always requires investments in development and commercialization activity. Multiple (competing) investment paths are possible, at least early on. The quintessential example is the automobile industry, where in the early days different engine technologies—steam, electric, and gasoline—each had their cham- pions. Once a dominant design begins to emerge, strategic choices become much more limited. This paradigm, which was first offered by Abernathy and Utterback (1978) and then built upon by the author (Teece, 1986a), now has considerable evidence supporting it over a wide range of technologies (Klepper and Graddy, 1990; Utterback and Suarez, 1993; Malerba and Orsenigo, 1996). It implicitly recognizes inflexion points in technological and market evolution. These inflexion points impact investment requirements and strategic choices. Implications for investment decisions have been noted elsewhere (Teece, 1986a) and include staying flexible until the dominant design emerges and then investing heavily once a design looks like it can become the winner. Any strategy is, of course, likely to be fraught with hazards because of uncertainties. Moreover, the manner and time at which an enterprise needs to place its bets depend on competition in the “input” markets and on the identity of the enterprise itself. Mitchell (1991) suggests that the timing of resource commitments can differ according to the enterprise’s existing positions with respect to the relevant comple- mentary assets. Enterprises that are well positioned can wait, while those that are not must scramble.
Addressing opportunities involves maintaining and improving technological competences and complementary assets and then, when the opportunity is ripe, investing heavily in the particu- lar technologies and designs most likely to achieve marketplace acceptance. When network externalities are present, early entry and commitment are necessary. The presence of increasing returns means that if one network gets ahead, it tends to stay ahead. Getting ahead may require significant up-front investments. Cus- tomers will not want an enterprise’s products if there are strong network effects and the installed base of users is relatively small. Accordingly, one needs to strategize around investments decisions, getting the timing right, building on increasing return advan- tages, and leveraging products and services from one application to another. The capacity to make high-quality, unbiased but interre- lated investment decisions in the context of network externalities, innovation, and change is as rare as decision-making errors and biases are ubiquitous.
However, the issue that the enterprise faces is not just when, where, and how much to invest. The enterprise must also select or create a particular business model that defines its commer- cialization strategy and investment priorities. Indeed, there is considerable evidence that business success depends as much on organizational innovation, for example, design of business models, as it does on the selection of physical technology. This is true at the enterprise level as well as at the economy-wide level (Nelson, 2005). Indeed, the invention and implementation of business mod- els and associated enterprise boundary choices involve issues as fundamental to business success as the development and adoption of the physical technologies themselves. Business models impli- cate processes and incentives; their alignment with the physical technology is a much overlooked component of strategic manage- ment. The understanding of the institutional/organizational design issues is typically more limited than the understanding of the technologies themselves. This ignorance affords considerable scope for mistakes around the proper design of business models and the institutional structures needed to support innovation in both the private and public sectors.
In theory, one could imagine transactions between entities that scout out and/or develop opportunities, and those that endeavor to execute upon them. In reality, the two functions cannot be cleanly separated, and the activities must be integrated inside a single enterprise, where new insights about markets—particularly those that challenge the conventional wisdom—will likely encounter negative responses. The promoters/visionaries must somehow defeat the naysayers, transform internal views, and facilitate neces- sary investment. Some level of managerial consensus will be nec- essary to allow investment decisions to be made. Investment will likely involve committing financial resources behind an informed conjecture about the technological and marketplace future. How- ever, managers of established product lines in large organizations can sometimes have sufficient decision-making authority to starve the new business of financial capital. This posture can be buttressed by capital budgeting techniques that more comfortably support investments for which future cash flow can be confidently pro- jected. In short, the new can lose out to the established unless man- agement is sensitive to the presence of certain biases in accepted investment decision processes. An important class of dynamic capa- bilities emerges around a manager’s ability to override certain “dysfunctional” features of established decision rules and resource allocation processes.
It helps to begin by recognizing that decision-making processes in hierarchically organized enterprises involve bureaucratic features that are useful for many purposes, but they nevertheless may muzzle innovation proclivities. In particular, a formal expenditure process involving submissions and approvals is characteristic of “well-managed” companies. Decision making is likely to have a committee structure, with top management requiring reports and written justifications for significant decisions. Moreover, approvals may need to be sought from outside the organizational unit in which the expenditure is to take place. While this may ensure a matching up of expenditures to opportunities across a wider range of economic activity, it unquestionably slows decision making and tends to reinforce the status quo. Committee decision-making structures almost always tend toward balancing and compromise. But innovation is often ill served by such structures, as the new and the radical will almost always appear threatening to some constituents. Strong leaders can frequently overcome such tenden- cies, but such leaders are not always present. One consequence is a “program persistence bias”. Its corollary is various forms of “anti-innovation bias”, including the “anti-cannibalization” basis discussed in a later section. Program persistence refers to the fund- ing of programs beyond what can be sustained on the merits, and follows from the presence or influence of program advocates in the resource allocation process. This proclivity almost automatically has the countervailing effect of reducing funds available to new initiatives.
One should not be surprised, therefore, if an enterprise senses a business opportunity but fails to invest. In particular, incumbent enterprises tend to eschew radical competency-destroying innova- tion in favor of more incremental competency-enhancing improve- ments. The existence of layer upon layer of standard procedures, established capabilities, complementary assets, and/or adminis- trative routines can exacerbate decision-making biases against innovation. Incumbent enterprises, relying on (path-dependent) routines, assets, and strategies developed to cope with existing technologies, are handicapped in making and/or adopting radical, competency-destroying, noncumulative innovation (Nelson and Winter, 1982; Tushman and Anderson, 1986; Henderson and Clark, 1990). This is true whether the competence is external to the firm or internal to the firm.
Evidence also shows that decision-makers discount outcomes that are merely probable in comparison with outcomes that are certain. This has been called the certainty effect (Kahne- man and Lovallo, 1993). It contributes to excessive risk aver- sion when choices involve possible losses. Further, to sim- plify choices between alternatives, individuals generally evaluate options in isolation. Viewing each alternative as unique leads decision-makers to undervalue possibilities for risk pooling. This approach to decision making may produce inconsistent prefer- ences and decision biases (timid choices) that lead to outcomes that block innovation (Kahneman and Tversky, 1979; Kahne- man and Lovallo, 1993). An opposing bias to loss/risk aversion is excessive optimism. This leads to investment in low or negative return projects. As a result, entry decisions often fail. Audretsch (1995) found that over the period of 1976–86 the average 10- year failure rate in two-digit SIC manufacturing sectors ranged from 75.8 percent to 54.8 percent. Similar failure rates have been reported in other studies (Dunne et al., 1988; Klepper and Miller, 1995). However, these failure rates disguise wide vari- ation amongst particular enterprises and between new entrants and incumbents.
The existence of established assets and routines exacerbates problems of excessive risk aversion. Specifically, both the isolation effect and the certainty effect can be intensified by the existence of established assets, causing incumbent enterprises to become comparably more risk averse than new entrants. In terms of inno- vative activity, this excessive risk aversion leads to biased decision making and limits the probability that incumbent enterprises will explore risky radical innovations. In short, success in one period leads to the establishment of “valid” processes, procedures, and incentives to manage the existing business. This can have the unin- tended effect of handicapping the new business. The proficiency with which such biases are overcome and a new opportunity is embraced is likely to depend importantly on the quality of the enterprise’s routines, decision rules, strategies, and leadership around evaluating new investment opportunities. Business his- torians (e.g. Chandler, 1990a; Lazonick, 2005) and others have reminded us that over the long run the ability of enterprises to commit financing and invest astutely around new technologies is critical to enterprise performance.10
In regimes of rapid technological innovation, it is clear that making investment choices requires special skills not ubiquitously distributed amongst management teams. Nor are they ubiqui- tously distributed amongst investors.11 Resource/asset alignment and coalignment issues are important in the context of innovation, but they are quite different from portfolio balance issues faced by financial investors. The presence of increasing returns means that one also needs to strategize around investment decisions, getting the timing right, building on increasing return advan- tages, and leveraging products and services from one application to another. Value-enhancing investments inside the knowledge- based enterprise are often cospecialized12 to each other. Also, the nature of the portfolio “balance” needed inside the enter- prise is different from the portfolio balance sought by pure finan- cial investors. The economics of cospecialization are not the eco- nomics of covariance with which investors are familiar. In short, the task of making astute project-and-enterprise-level investment decisions is quite challenging because of cospecialization and irreversibilities.
The project finance and related literatures provide tools and clear decision rules for project selection once cash flows are spec- ified, uncertainty and/or risk are calibrated, and interdepend- encies between and amongst cash flows are ignored. However, the essence of the investment decision for the (strategic) man- ager is that it involves estimating interdependent future revenue streams and cost trajectories, and understanding a panoply of continuous and interrelated cospecialized investment issues.13 The returns to particular cospecialized assets cannot generally be neatly apportioned or partitioned. As a result, the utility of traditional investment criteria is impaired. Thus while project-financing cri- teria (e.g. discounted cash flow, payback periods, and the like) and techniques for decision making under uncertainty are well known, there is little recognition of how to value intangibles and take into account features such as cospecialization, irreversibility, and opportunity costs.14 Nor is the concept of a “strategic invest- ment” recognized in the finance literature. Finance theory provides almost no guidance with respect to how to estimate future cash flows, although making such estimates is as much, if not more, the essence of good decision making as are the methodologies and procedures for analyzing cash flow.
In short, managers need to make unbiased judgments under uncertainty around not just future demand and competitive responses associated with multiple growth trajectories, but also around the pay-offs from making interrelated investments in intangible assets. In the world of tangible assets, this can some- times be precisely modeled; not so for the world of cospecialized intangibles. In essence, the organizational challenge appears to be that in environments experiencing rapid change, activities are not fully decomposable. Cross-functional activities and associated investments must take place concurrently, rather than sequentially, if enterprises are to cut time-to-market for new products and processes. Managerial judgments (decision-making skills) take on great significance in such contexts. This was also true during prior centuries, as Alfred Chandler’s (1990a, 1990b) analysis of success- ful enterprises from the 1870s through the 1960s makes apparent. No matter how much analytical work is done, tacit investment skills are of great importance. Chandler further argues that success in the late-nineteenth century and much of the twentieth century came to those enterprises that pursued his “three-pronged” strat- egy: (1) early and large-scale investments behind new technolo- gies; (2) investment in product-specific marketing, distribution, and purchasing networks; and (3) recruiting and organizing the managers needed to supervise and coordinate functional activities. The first and second elements require commitment to investments where irreversibilities and cospecialization are identified. While the nature of required investments may have changed in recent decades (less decomposable/more interrelated), investment deci- sion skills remain important.
Source: Teece David J. (2009), Dynamic Capabilities and Strategic Management: Organizing for Innovation and Growth, Oxford University Press; 1st edition.