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Capabilities as Real Options Bruce Kogut and Nalin Kulatilaka Presented by Hui Chen(2014 Fall)

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Presentation on theme: "Capabilities as Real Options Bruce Kogut and Nalin Kulatilaka Presented by Hui Chen(2014 Fall)"— Presentation transcript:

1 Capabilities as Real Options Bruce Kogut and Nalin Kulatilaka Presented by Hui Chen(2014 Fall)

2 About the Authors Bruce Kogut Chaired Professor, Columbia University PhD, MIT (1983) Research Interests: Comparative and economic sociology, strategy, social entrepreneurship, and governance Nalin Kulatilaka Professor of Finance, Boston University PhD, MIT (1982) Research Interests: Contract design and financing 2

3 Agenda Strategy as Heuristic Strategy and Real Options The Organizational Ecology Perspective Complex Adaptive Systems and Option Theory Looking Outside & Inside the Firm Dynamic Valuation of the Critical Capability Set Competency Traps and Learning to Learn Conclusion 3

4 Strategy as Heuristic Heuristic:  Cognitive frame-the “representation” of the problem and solution space  Rules of search- the algorithms by which solutions are found in the represented solution space Definition: Procedure search in distinction to the substantive rationality of economics and operations research (Simon 1969) Strategy is often complex (multiple interactions between capabilities and market strategy) and often lacks a method of determining the optimal choice. In real time, searching for optimal strategies can be too costly or subject to recency effects. Heuristics can help reach a satisfactory decision but not necessarily optimal. The merit of a heuristic lies in its real-time utility, but trade-offs need to be made between routines as heuristics and misapplications. Strategizing is the application of imperfect heuristics to problem solving and implementation. A real option heuristic is a way to discern the value of particular paths of exploration in evolving environments as strategy is seen as the choice of capabilities that provide the appropriate flexibility for landscape changes. 4

5 Strategy and Real Options From a decision-theoretic perspective, the core competence framing readily lends itself to a real option interpretation. Three elements are jointly required for the application of a real options heuristic: (1) uncertainty, (2) future managerial discretion to exercise, and (3) irreversibility. Irreversibility: the inability to costlessly revisit an investment or decision  The importance of timing: Between making a decision to invest and its actual implementation during which the value of the investment will change due to competition, technology, etc. “Scarce” asset: a core competence is a scarce factor that embeds complex options on future opportunities (Barney 1986) Scarcity itself does not necessarily determine the value of a competence, but it may be associated with the competence permitting a firm to achieve a competitive position in the market price. 5

6 The Organizational Ecology Perspective The contribution of organizational ecology is to formulate more explicitly the relationship between environmental uncertainty and organizational strategies in a dynamic setting. Two kinds of uncertainty: smooth change and granular change (Generalists will do better than specialists in the latter setting) Differences of two models:  A hazard model: the probability of hitting a lower boundary in a stochastic diffusion process which governs the growth of the organization  A real option model: considers the upper boundary which is the probability of increasing growth by exercise rather than minimizing the hazard of death A dimension of distance: core and periphery-firms can be mapped onto a multidimensional space representing different combinations of technological and organizational practices. The correspondence between technologies and organizational practices might be set to set, coupled dynamically in their evolution. The costs of altering imply the existence of a range of inertia or hysteresis band, which increases with uncertainty. 6

7 Complex Adaptive Systems and Option Theory Option valuation is appropriate in complex and non-linear environments. Differences between experimentation and market exploration. Search is the application of products and services to new markets and landscapes. Experimentation is the learning of new techniques and combinations of technical and organizational elements. A useful heuristic in complex adaptive systems is to know the value of directional change in the landscape. This is what option theory does; it puts a value on the investment in the capability to change position in the landscape contingent on the environmental outcome. Real options look at the value of a position, where contours correspond to different valuations placed on the assets of an organization. Complex adaptive system thinking has found it difficult to give heuristic advice other than a framework. Baldwin and Clark(2000) propose a real options approach for understanding the choice of modules under unknown performance, but this cannot be applied to radical architectural change. 7

8 Looking Outside the Firm: Market Pricing It is not the static comparison of the capability and strategic factor that matters, but rather the information that is gleaned in the changes in prices over time. The price of other firms does not give the value of the core capability. Thus, real options can not be perfectly replicated to correlated assets. Valuation requires knowledge of the actual price dynamics of the factor price and the equilibrium risk-adjusted return. The way to identify the appropriate correlated asset is to decompose the market price into a bundle of attributes that pierces the revenue veil of the firm to see the underlying assets. The value of the capability depends on its contribution to the price of product or factor prices whose risk is spanned by traded assets in the economy. The value of the capability is thus obtained by explicitly specifying the profit function using these prices as an argument. 8

9 Changes in Quality Adjusted Price Model Where: Θ = quality-adjusted price μ = the expected growth rate of Θ σ = instantaneous volatility ΔZ = is standard Normal distributed dq = Poisson process with intensity parameter λ κ = random percentage jump amplitude conditional on the Poisson event occurring. This model includes unpredictable shifts in consumer preferences or incremental technical change and radical or discrete innovations. 9

10 Looking Inside the Firm: Capability Sets Even if two firms are competing in the same industry and market, movement in prices of the strategic asset influences differently their value because of the relationship between the capabilities of the firm and the profit opportunities. The authors describe this formally by using the notion of distance between discrete combinations of technology and organizational elements that define a capability. The authors first develop the notion of a capability set and then define the profit function of a firm in relation to its set of organizational and technological practices. 10

11 Impact of Switching Costs Where: Θ is a vector of quality-adjusted input and output prices and y is the vector or input and output levels that are determined by the capability set. This expression indicates that the firm’s ability to choose the best strategy is contingent on its organizational resources. 11

12 Dynamic Valuation of the Critical Capability Set When future values of θ evolve stochastically, the current decision influences all future decisions as well. The tight coupling of organization and technology is essential to understanding why capabilities radically change the understanding of strategy as not only the choice of entering markets, but also as the selection of competence. The way to fully analyze the implications of inertia is to write out explicitly the problem over time. To do this, we no longer work directly with a profit function, but instead with a value function. 12

13 In each period the producer chooses the capability c j l, that maximizes the value of the project. This choice can be interpreted as defining the dynamic capability as: The presence of switching costs makes a forward-looking analysis necessary. This definition of a dynamic capability defines the re- interpretation of a "core competence." Core competence is the capability set (i.e., combination of organization and technology elements) that permits the firm to dynamically choose the optimal strategy for a given price realization of the strategic factor. 13 Exploitation of the choice of current capabilities Persisting or switching in the future Value Function

14 Competency Traps and Learning to Learn Simply exploiting current capabilities leads to cumulative and incremental improvements, however, the firm’s accumulated learning in the old techniques can be a “competency trap”. The pitfall is that this learning increases the rigidity of the firm. Exploration increases the value of the option to switch to new capabilities by lowering the costs of switching. By exploring the current asset that can be recombined and coupled with new ones, a firm is able to reduce the risks of falsely choosing new capabilities and the costs of successfully adopting radical changes in its capabilities. 14

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16 Conclusions Real option analysis provides the theoretical foundations to the use of heuristics for deriving capabilities. Real options approach indicates that the value of the firm is found in its organizational capability to exploit current assets and explore future opportunities. Real options approach sheds light into the strategy literature on hysteresis, inertia, competency traps, learning, and the effects of radical versus incremental innovation, among others. 16


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