Behavioural Foundations Of The Dynamic Capabilities Framework Management Essay
Almost 15 years have passed since Teece et al (1997) conceptualized the notion of Dynamic Capabilities (DCs) as an extension of the widely acknowledged Resource Based View of the firm (Barney 1986, Dierickx & Cool, 1989; Peteraf, 1993; Penrose, 1959; Wernerfelt, 1989)
The concept of DCs has spurred on a huge array of further academic investigation in which researchers have adjusted (Barney, 1991; Conner, 1991) or fully rejected (Williamson, 1999) the original foundations of the concept. This has led to a large diversity in the fundamental construct upon which DCs should be understood and implemented.
Although most people agree that it is conceptually a good idea, there is still little agreement about what it truly means and even less agreement about "how to do it."
The framework has been frequently challenged in the literature, “called conceptually vague and tautological, with inattention to the mechanisms by which resources actually contribute to competitive advantage” (Eisenhardt and Martin, 2000).
This article offers a systematic literature review of the DCs framework up until now. The aim of this is to guide researchers in making the concept of DCs more nuanced and practically applicable by pointing out neglected areas which might become limiting factors when wishing to reap the benefits of the DCs framework promised by its instigators.
The pursuit of heterogenic performance of firms has been a question of utmost importance in the strategic management field for many decades. The evolution of theories of the firm suggesting different solutions to the realization of competitive edge has greatly sophisticated the requirements of management competences and helped widen the toolbox needed to succeed in an increasingly changing and complex world of business conduct.
The traditional logic of positioning (Porter, 1980) is deeply rooted in industrial economics, which propose that firms should look for industries with favourable conditions, illuminated by utilizing for example the “Five Forces Framework”. Having entered the industry successfully the firm should build up isolating mechanisms to help preserve their position and power.
These strategic suggestions are somewhat sound in market conditions which change only little or very slowly over time and where commitment to relatively stable resources would provide sufficient strength.
However even in such situations important impediments have been pointed out (Dierickx & Cool, 1989), which limit these tools’ scope and effectiveness when used solitarily.
The growing acknowledgement of the necessity to refine such static and one dimensional rationalization of firms’ heterogenic performance have led to the development of paradigms within which the recognition of the importance of firm resources and capabilities are key ingredients.
A fundamental outcome of this debate was the construct of the “Resource Based View” (RBV) (Barney 1986, Dierickx & Cool, 1989; Peteraf, 1993; Wernerfelt, 1989), suggesting that firms should be seen as bundles of resources and where the development of new capabilities would be a key driver of prosperity. Empirical research has shown that at great deal of performance differences within different industries stem from firm effects, rather than industry effects (Rumelt, 1991; McGahan & Porter, 1997; Eriksen & Knudsen, 2003). The VRIN framework (Barney, 1991; Conner and Prahalad, 1996; Nelson, 1991; Peteraf, 1993; Wernerfelt, 1984, 1995) was introduced into the analysis of firms, in order to detect, valuable, rare, inimitable and non-substitutable resources which would generate long term advantage.
The RBV framework has not gone without criticism (Mosakowski and McKelvey 1997; Priem & Butler, 2000) but it has been a very important factor igniting a change from pure economical foundations of firm heterogeneity towards bringing aspects of evolutionary theory into the quest for superior performance.
In 1997 Teece, Pisano & Shuen put forward their “Dynamic Capabilities Framework” as an extension and refinement of the RBV, and which could be perceived as a tool to which tries to answer a central question, namely; how can firm readily adapt to a constant changing environment? The concept of DCs has attracted attention in a wide array of general management literature (Eisenhardt & Martin, 2000; Helfat et al 2007; Makadok, 2001; Rindova & Kotha, 2001; Zollo & Winter, 2002; Winter, 2003). The attraction was mainly based upon the promise that the notion of DCs was a key contributing element in the pursuit of sustainable competitive advantage (SCA) and gave recognition to the growing importance of linking firms’ strategic choices and external environment into a more coherent bundle of tools with particular focus on firms situated in what some scholars has termed hypercompetitive environments (D’Aveni, 1994) or high-velocity environments (Bourgeois & Eisenhardt, 1988).
In such circumstances the necessity of rapid adjustments to sudden shocks and frequent shifts in the environmental conditions in which firms competes, becomes of paramount importance if firms wish to survive and grow (Teece et al, 1997).
The concept has evolved greatly over the years, but has not yet found a solid and definite position in the management tool box.
The main construct of this paper is the following; the first section will contain a structured overview of the key definitions of the DCs framework so far in the literature. This section will highlight the most important elements which collectively will provide the reader with the opportunity to follow the evolution of the concept and identify the ambiguities among researchers which have greatly contributed to the fragmentation of the actual practical use of ideas fundamental to the construct.
In the second main section I try not to come up with yet another definition of the concept, rather this section will critically assess the underlying assumptions which make up the behavioural foundations of the DCs framework. By looking at recent and most influential research in areas of organizational learning, routines, inertia and change, the aim of this section is to refine the framework and furthermore identify key elements which might be constraining factors in the practical use of the DCs framework. In the third and last section I discuss, compare and reflect upon the different identified inconsistencies in the literature concerning DCs and their underlying assumptions, in an attempt to point to essential future research areas which might prove fruitful if they were to be incorporated into the framework more explicitly.
2. Defining and delineating the concept of Dynamic Capabilities – a review of the literature
What are Dynamic Capabilities?
As mentioned in the introduction, prior streams of research has been centred around the topic of firms needing to navigate more safely through uncertain and dynamic environments (Schumpeter, 1942; Penrose 1959; Nelson & Winter 1982; Prahalad & Hamel, 1990; Teece, 1976, 1986a, 1986b, 1988; Hayes et al, 1988):, but it was not before Teece, Pisano & Shuen in 1997 published their article “Dynamic Capabilities and Strategic Management” that the interest in Dynamic Capabilities grew significantly. The DCs framework can be seen as a reaction to the rather static nature of the RBV framework which limits itself from explaining firms’ competitive advantage in changing environments.
Teece et al (1997) generally propose that the “Dynamic Capabilities Framework” offer an extended and complete manual on how to unlock the mysteries of how big firms’ can gain the ability to create, appropriate and sustain value in dynamic settings.
DCs are defined in a broad sense as being organizational routines (Nelson & Winter, 1982) through which managers adjust the firm’s resource base by acquiring/deleting, integrating and recombining resources. The existence of such routines determines the firm’s ability to integrate, build and reconfigure their competences to meet the requirements of a rapidly changing environment (Teece et al., 1997).
Focusing on changing environments, Teece et al can be seen as a direct link to Schumpeter (1934) and his attention to the essential entrepreneurial skills of the managers as being the most important driver of economic growth.
It is important to make note of that they in line with evolutionary economics assumes that DCs are build and not bought. This notion is important as it points towards the actual business processes, such as a firm’s asset position and its evolutionary path which makes the critical differences in firms’ level of competitive advantage and by such make DCs hard to imitate.
Teece et al is very unambiguous about that the Dynamic Capabilities are a defining feature of firm heterogeneity and therefore are a key source of SCA, and that management capability and behaviour is the most important hub for achieving it.
As mentioned, the article from 1997 spurred on an array of further investigation, each with a somewhat unique conceptualization. For a brief overview of key definitions from a selection of key authors please see appendix I.
In order to make the best possible overview, the following section of this literature review is decomposed into the following key essentials of DCs:
Definition; Relevant environment; Heterogeneity; Patterns in development; Effect
These elements are all common to the different researchers and this aggregation is useful in order to bring clarity in an otherwise highly fragmented stream of literature.
Nature & Function
The Teece et al (1997) article utilizes the label “ability” and/or “capacity” to define the nature of the DCs concept. By doing so, they point to the critical role of strategic management and more specifically, the top level manager and her entrepreneurial skills.
Furthermore, they defined the actual end point to which the special capability should work, namely integrate (or coordinate), build, and reconfigure internal and external competences of the firm. This clearly draws explicitly on the work done by Nelson & Winter (1982) and their evolutionary economic perspective incorporating routines, organizational learning and path dependencies.
Other authors like Zollo & Winter (2002) and Winter (2003) have used similar terminology of patterns or routines to define the concept. They see the DCs as being; “a hierarchy of higher-order Capabilities” which essentially governs the ordinary capabilities (lower level capabilities). DCs comprise a learned and stable pattern of collective activities which assist firms in situations that needs modification and adjustment of lower level operating routines. What this essentially means is that whenever a firm faces an uncertain situation the DCs creates stability and order for how to proceed with any change needed.
Eisenhardt & Martin (2000) are more explicit and advocates that DCs are specific and identifiable processes such as product development and strategic decision making. Because of this, DCs are possible to imitate and this mobility makes them of less value than the actual complexity of the resource configurations they create. DCs can in their view be seen as dependent on the situation and the level of learning the firm must engage in.
Wang & Ahmed (2007) argue DCs consist of three main components which are visible across a variety of studies, namely; adaptive capability, absorptive capability and innovative capability. These capabilities combined support a firm’s ability to integrate, reconfigure, renew and recreate its resource base in order to meet the changes in the environment. These capabilities are not different from Teece’s updated version of the DCs framework (2007) which contains three key elements; sensing, seizing and transforming.
As is evident from the above only marginal differences are seen, depending on the focus of the definitions brought forward by each contributor. There seems to be a broad agreement of the fact that DCs are those abilities within firms which help guide it through change and that these can be updated and modified. A key differencing factor is whether the DCs are simply a sophisticated and extraordinary form of efficient capabilities which can be learned or if these are situated above the “zero-level” capabilities and which are not easily identifiable within the firm.
But in which situations are DCs helpful and feasible to focus on?
Teece et al, 1997 focus primarily on hyper competitive markets where change is rapid, unpredictable and potentially competence destroying. The Teece 2007 paper essentially just refines that original view by stating that where managerial knowledge is weak and where the market is exposed to frequent shocks DCs are extremely relevant.
Eisenhardt & Martin (2000) somewhat takes the argument in another direction as they propose that primarily in markets where changes occur frequently but in a predictable manner the DCs are valuable.
In such incremental changing markets, DCs are systematic and very analytic in nature and draws on existing knowledge within the firm. In contrast within hyper-competitive markets they are simply experimental and incorporate new knowledge from the novel situation and will not be able to provide a predictable outcome. By such these statements are quite conflicting in respect to the usefulness of DCs in their original form (Teece et al, 1997).
Zollo & Winter (2002) elaborates further on these notions by stating that DCs are present even in markets characterized by lower rates of change, i.e. there are marked differences between the situation a firm is in and the value of having invested in DCs. 
Winter (2003), builds further on the Zollo & Winter (2002) paper and does stretch the concept of DCs a bit further. He postulates that it is by far not always a good idea or sound investment to even actively engage in a search for dynamic capabilities. The cost of building, maintaining and delivering results from DCs might easily outweigh the actual benefits if the changes are not frequently occurring and if they are not heavily competence destroying. In his paper it becomes clear that if, DCs are “higher-level” capabilities transformed into problem solving routines, which assist lower level capabilities to be modified according to the exogenous change, then they are firm specific even problem specific and no general rule can be applied and no general DC can be advocated. Even though Winter (2003) acknowledge that DCs are an important element for firms aiming to adapt to rapid changing environments, they are not in themselves sufficient to guide organizations through the darkness of an uncertain path.
By such the knowledge accumulation gained by recurring change can be turned into higher-level routinized patterns of behaviour which facilitate change, but the costs associated with doing so must be less than the expected benefits from having a routine specialized for one specific issue. Again ‘Ad Hoc’ problem solving might prove much more cost efficient when a firm inevitable will face novel problems even during a change process from which the organization has some prior knowledge.
The Helfat et al 2007 book draws on much of the recent literature of DCs but distinguishes itself especially from the earlier authors by stating that DCs assist the evolutionary/incremental change processes any firm must go through. Again, the emphasis is on problem specific capabilities, which are only feasible if the problems of change occur frequently and in a similar pattern.
The book is very clear in its statements that DCs are accountable for the “Evolutionary Fitness” of a firm and that the context specificity of them is the defining feature of investment in building such higher order routinized behaviour. Hereby Helfat et al support the view that no general rule for riches can be found in the DCs framework and that each situation require distinct routines which again are dependent on the firm’s history and existing knowledge base.
As noted, there has been a clear development of where DCs seems to promise the highest payoff. Some authors (Teece et al, 1997) tend to firmly stick to the full rationality (Hyper-rationality) approach following in the footsteps of traditional economics, while others like Winter (2003) try to incorporate further realistic assumptions into the framework, by making use of more behavioural elements.
In general there is a relative high level of diversity in when DCs help firm and when they should not be hunted for, but the central question of how to make DCs emerge is so far unanswered.
Patterns in development
Evolutionary economics play a central role in most of the recent conceptualizations of DCs, and evolve around a central theme – learning.
Teece et al (1997), emphasize that interorganizational learning stem from a collaborative activity among the network of individuals and business partners a firm has. This is nothing new and can be seen in a wide variety of past literature concerning this topic.
What is interesting is that Teece et al (1997) does not manage to explain the actual process of building up the DCs – they simply state that it might take years or even decades to have learned, integrated and leveraged the DCs into value adding activities.
Eisenhardt & Martin (2000) are a bit more detailed or honest if you will, in their approach.
The mechanisms, with which DCs are built, are repeated practice and hereby experience, past mistakes and the rate of experience. Furthermore they explicate the terms used in evolutionary economics of variation, selection and retention. Variation is the first step in decision making. This step comprises the hypothesis building of alternatives and this is carried out in a routinized way (routinized search). This stage is crucial in relative moderate dynamic markets because of the low utilization of resources. Selection is the second step and here the organization evaluates each alternative vector of decision variables which was generated in the first step. Dependent on which alternative carries the highest expected value, the organization now selects that option and move into the retention stage. Selection is at centre stage in high velocity markets due to the increased uncertainty of which alternative is the most promising. In the retention step the organization decides whether the chosen alternative should be further implemented (retained) or if it should be neglected based upon actual performance feedback. From here companies continue to compete in these evolutionary circles where the outcome of each ‘round’ is the variation of how firms reconfigure their resource base according to what their rivals have selected and retained (Cyert & March, 1963; Nelson & Winter, 1982). In this perspective the ability to select among a range of uncertain alternatives becomes a crucial skill of the organization, and could be seen as an overarching dynamic capability. However this proposition is still weak and far away from giving more precise answers of how organizations should increase their ability to select alternatives that improves company performance.
Zollo & Winter (2002) moved much closer to actually indentifying mechanisms that will assist organization facing uncertain situations. Organizational learning is here also central theme of DCs, but in addition to the semi-automatic stimuli-response view of experience accumulation, they propose that firms deliberately engage in distinctive cognitive processes.
One aspect of this is what they term; knowledge articulation, which means that through joint debate and performance evaluation practices, a firm can better control and structure their learning into meaningful, helpful and tangible guides. Such knowledge articulation processes should enable the firm to proceed with knowledge codification. Knowledge codification essentially means that the accumulated experience which has been articulated jointly within the firm now should become codified in manuals, blueprints and especially in organizational routines. This is a recurrent process where firms can constantly update their existing codified knowledge base by stating the implications of the existing codified “routines”. This notion I will return to in the second main section of this article.
What should be clear from the review so far is that researchers closely agree on the overall defining features of DCs, but the value of building and delivering them are a critical point of disagreement.
Explicating the view of differences in firm performance diverge slightly in the DCs literature.
In Teece et al 1997 there is a clear link to the RBV concept and heterogeneity as a unique and firm specific feature. Both Makadok, 2001 and Winter 2003 made the same argument, where the change is contextual and specific to the industry and the historic path of each firm. The idiosyncrasy of DCs is however not advocated by Eisenhardt & Martin (2000) in a similar way. They move closer towards a “best practice” perspective and suggest that some similarities across firms DCs are present. Such commonalities stem from the belief that there are several effective ways to achieve the same DCs. More specifically, firms have access to the same tool box of guidelines which help overcome different problems associated with change, and within this set of tools similar features can be observed and universally applied. They argue that it is in the details of DCs where the advantage may be found.
Teece et al (1997) argue the DCs framework was meant to explain exactly why firms differ in performance, i.e. DCs are a defining feature of competitive advantage, and can be a source of sustainable superior performance.
Zollo & Winter (2002) follow along these lines of thought and propose that in situations where DCs are useful, they will be a source of advantage over only focusing on existing routines. What is important to notice is that this article vastly disagrees that DCs are of any sound and viable importance for companies in rapid changing unpredictable markets whereas Teece et al 1997 builds their entire argument upon the need for firms to navigate in such conditions.
Eisenhardt & Martin 2000 are much more negative in their contribution. They state that any manager can build up the same capabilities just using different methods, and by such DCs in their view can only be a temporary competitive advantage and never a source of any sustainable superior performance. In moderately changing markets DCs are detailed and analytical processes, whereas in high velocity markets DCs become simple, highly experiential and fragile trial and error processes with very high unpredictability of the outcome. A key point they stress is that DCs themselves does not hold the key to SCA, but rather the timeliness and the fortuitous application of DCs which might create an advantage.
Zollo & Winter (2002) agree somewhat with this view as they state that DCs and even the higher-level learning capabilities must constantly be updated to prevent that a firm’s core competencies does not become core rigidities (Barton, 1992). Therefore in their view DCs are by no means a secure way to any SCA, as they are as fragile as the markets they should be applied to.
Winter (2003) follow up on these ideas by stressing the fact that in many situations DCs are associated with a significant opportunity cost, linking back to the use of “Ad Hoc” problem solving which might be a better solution as it can be rapidly deployed to the specific issue at a much lower cost that using DCs without loosing significant performance.
A more distant but related predicted outcome of the continual and constant recombination and reconfiguration of resources (defining feature of DCs), is what Van Valen (1973) termed; “The Red Queen Effect”. Originally used in evolutionary biological processes, where races was seen, and despite huge effort, not improving their ability to survive – they simply fight to keep up with everything around them, but in that sense stays in a status quo equilibrium where the probability of survival or death is randomly determined.
Barnett & Pontikes, 2005; Oliver, 1999 and Rindova and Kotha (2001) all used this analogy to describe the technology races observed in many innovative markets. DCs which essentially have the function of increasing the organization’s likelihood of survival and even provide it with durable superior advantages in such races is therefore questioned in this stream of literature.
In terms of “survival rate” or relative increased performance it could be argued that what Teece et al (1997) thoughts of DCs, are build upon the same notion to what Eldredge & Gould, 1972 called; ‘punctuated equilibrium’ where a firm must de/re-cohere to survive Schumpeterian shocks. In this line of thought, the whole suggestion about SCA seems to be obsolete, given the fact that each company constantly shift in and out of either modes of exploitation or exploration, and by such the aim is to reap the benefits of always being a first mover in the right markets. As D’Aveni (1994) pointed out, in high velocity markets the definition of SCA should be seen as a result of a series of CA and not a persistent and general bundle of resources and capabilities.
Having reviewed the key streams of literature which have all contributed to the present understanding of DCs, it should be clear that there is far from a general accepted way of defining, deploying and creating DCs and even less of the outcome the pursuit of such capabilities might deliver. It is however possible to group the different propositions into two main buckets of views; the ‘logical’ and the ‘difficult’ which hopefully assist the reader to fully understand where and how the different authors differ in the key aspects of the subject.
For a quick overview of how the two main streams of literature differ in their propositions, please consult appendix II.
In order to become able to further elaborate on the underpinning mechanisms of DCs the second main section will critically assess the behavioural concepts which needs to be considered along the side of the broadly and often blurry picture of DCs. Recent literature on key aspects of organizational development might prove to be very beneficial when wishing to harvest the value promised by a wide group of contributors to the DCs framework.
Assessing the underlying assumptions of Dynamic Capabilities
As noted in the fist main section, learning is a key ingredient of DCs.
It is however inadequately explored in Teece et al 1997 of how the organization should learn, i.e. build up dynamic capabilities. Zollo & Winter 2002 has a more comprehensive incorporation of the learning aspect and they propose a framework that links a range of learning mechanisms to the creation of DCs, namely; Experience accumulation, knowledge articulation and knowledge codification. Just like operational routines are built, retained and modified, the DCs carry the same characteristics, thus DCs can be seen as higher level routines which for example do not explicitly produce a new product but build up the capabilities which enable the organization to produce a new product.
Looking at routines in a broader perspective, Becker (2004) collects eight characteristics and six effects of routines in a range of literature. What is the key point to notice is that routines are build due to recurrent events which leads to a collective understanding throughout the organization of how to perform certain tasks. In this sense routines help to stabilize behaviour as they capture hard to codify knowledge (tacit) and acts as the collective “memory” of the organization. In stead of having to conduct manuals and blueprints every time a task have to be carried out, effective organizations rely on well functioning routinized problem solving processes which require low levels of resources. Routines are not fully static in nature, as they can be modified and adjusted to fit changing circumstances and by such does not limit themselves to only a preset range of problems. The change of routines is however not done instantaneously and if organizations are not aware of that their routines do not fit the present fitness landscape, due for example to an overemphasis on positive feedback, there is a clear risk of falling into a competency trap. Therefore routines must be carefully nursed and updated to limit the risk of becoming a hindrance.
Zollo & Winter (2002) also pointed this out. DCs are built upon prior accumulated knowledge and are path dependent in nature and therefore context specific. In that sense higher level routinized behaviour are important to the incremental evolutionary development of organizations, but are not the answer for how firms overcome rapid and unexpected change. Zollo & Winter (2002) does however propose that knowledge articulation processes can be speeded up by improving the communication channels within the organization and to tap into the knowledge of alliance partners. What they essentially propose is that an organization will be faster at adapting to novel situations if the internal and external network is shifted from what Cross et al 2005 calls, a “routine response” towards a ‘tailor made response” structure.
In an attempt to accommodate an important element of critique as seen above, Teece (2010) states that DCs are ‘something’ higher than routines; “DCs are more than routines, whether operational or higher-order, in that they embody a qualitative difference, namely conscious human action.” In this sense, Teece narrows down his framework further than from the original proposed layout, by focusing more solely on the aspect of the managerial mindset. A fundamental behavioural building block of Teece’s updated version is the entrepreneurial manager’s task of bundling and managing a range of DCs which must be chosen carefully to provide full benefits, namely sensing, seizing and transforming. Sensing and seizing encompass the manager’s ability to capture the value from an option by ensuring that the resources needed to support the opportunity is mobilized and that the organizational structure fits the chosen strategy. ‘Transforming’ is the continuous effort to renew the capabilities needed to sustain the competitive advantage. Teece furthermore states that there is no business model which facilitates such search for renewal of capabilities, and hereby puts tremendous emphasis on managerial skills.
Despite the rather superficial and inadequate effort to explain how stability should be sought in organizations exposed to a high velocity environment, I will follow the ‘conscious human action’ line of though and shift focus towards the behaviour of managers and other humans in general.
Managerial Cognition & Bounded rationality
Zollo & Winter (2002) made a distinction between an operating routine which exploits the current stream of revenue and one that has the purpose of enhancing future profits. They connote the second type of routines as being a search routine, and can be compared to the firm engaging in exploration.
As part of the debate of “why do big firms fail?”, there are important academic discussions (indsæt ref) of how firms should organize and strike the right between exploiting existing resources and exploring for new resources? As mentioned earlier, Teece et al 1997 and even more so in his 2010 paper, place a strong emphasis on the exploration part of strategy and that the responsibility of this task is inherent in the behaviour of the manager.
What essentially is needed, in this view, is that managers ensure that new emerging opportunities are discovered, assessed, implemented and leveraged to create and capture value. Current exploitative routinized processes should not be the concern for the manager, as they do not provide sufficient foundations of a sustainable superior performance, and by suggesting such entrepreneurial mindset, I will now review important streams of literature which help refine the understanding of how managers make decisions in general and in complex and novel situations.
Most organisational decision-making rests not on calculative and full rationality (Gavetti, 2005) but on the principle of satisficing and approximation (Simon, 1957; Cyert & March, 1963). It has furthermore been found that bounded rationality at senior management level critically affects how incumbent firms respond to environmental change (Eisenhardt & Martin, 2000; Tripsas & Gavetti, 2000).
The effect of bounded rationality is that managers even if they have access to adequate information regarding future events, alternatives or consequences of the decision alternatives, they are constrained by their cognitive limited resources to process all this information.
This gives rise to the phenomenon which was postulated by Simon (1955) that when decision makers are faced with complex and novel problems, they tend to rely on simplistic rules or heuristics which are based on prior experience and knowledge. This by effect often means that the decision maker creates a unique interpretation of a given situation that might not have any rational sound correlation to reality, i.e. it gives rise to biases (Huff, 1990; Tversky & Kahnemann, 1973, 1974)
Gigerenzer (2011) made a more positive contribution to the understanding of the bounded rationality approach and found that in some instances, the use of very simple and basic metrics to determine the optimum choice might be extremely effective (cost efficient).
What this essentially means is that any given organization, when confronted with an uncertain situation must find ways to process the information available. Despite the value of having an entrepreneurial skilled manager it seems impossible that she could be the determinant factor of successful adaptation. A single manager cannot process and comprehend all the information necessary to make the right decisions when working under high levels of uncertainty.
Galbraith (1974) offered some insight into how organizations should organize in order overcome the fact that managers cannot deal with such amount of complex and diverse information bits; Reduce the need to process information and Increase the information processing capacity. The second option is best suited to cope with high levels of uncertainty. In this option an organization structures the subunits into ‘Organismic’ entities, which mean having highly connected networks that are relatively independent of any one individual. This clearly limits the risk of information overload, but does not create a viable solution for organizations which face pervasive uncertainty. It does however point to the important note that organizations tend to rely on routinized behaviours, i.e. we do what has worked in the past, because we do not know any alternative solution which might be better. This is a natural outcome of not being able to comprehend and process all the information needed to accomplish a task.
Looking more directly into the DCs literature, there seems to be a large diversity of how the notion of bounded rationality should be applied into the framework there is little guidance.
There seems to be a widespread neglect of the existence of bounded rationality, and often papers are overly theoretical in their construct with little or no practical transferability.
Some convergence can be observed regarding these two streams of opinions, and Teece (2010) does seem to agree that it is very difficult for decision makers to balance the act of exploration and exploitation, but fails to further elaborate on mechanisms which should redeem such issues.
By advocating that the capabilities of managers are critical to the creation and application of DCs must be relaxed in the sense that human behaviour is constrained to often using simple heuristics which does not ensure an optimum solution for a novel problem.
However as Giovanni et al (2005) simulation model show, even though searchers (managers) a bounded rational, there are powerful tools which effectively compensate to some degree for this constrained cognitive ability. Despite the fact that humans are not super computers, they express quite simple solutions to very complex problems, and this can in many situations prove effective in decision making. The use of ‘analogies’ can
Gavetti & Levinthal (2000) provided some important findings to further nuance the bounded rationality concept. They made the distinction between experiential and cognitive search processes and depending on the environment (static vs. dynamic) different search processes proved to be most effective. They reaffirm the necessity for firms to engage in both trial and error learning as well as in search based on cognitive effort. The important point they make is that cognitive representations are not changeable without foregoing considerable experiential wisdom and that this is only cost-beneficially feasible in changing markets.
Despite these limiting factors there can be found more optimistic views on managerial capability to judge and comprehend in situations of uncertainty.