Strategic Tools in Dynamic Environments

A Framework

Bachelor Thesis, 2010

64 Pages, Grade: 1,2


Table of Contents

List of Abbreviations

List of Figures and Tables

1 Introduction
1.1 Problem Definition and Objective
1.2 Course of Investigation

2 Background
2.1 A Short Review of the History of Strategy
2.2 Strategy and Firm Performance
2.3 The Strategic Management Process
2.4 Dynamic Environments
2.4.1 Literature Review
2.4.2 Velocity
2.4.3 Complexity
2.4.4 Uncertainty
2.4.5 Unpredictability
2.5 Strategy in Dynamic Environments
2.6 Analysis Framework

3 Strategic Tools in Dynamic Environments
3.1 Literature Review
3.2 Basics of Strategic Tools
3.3 Use of Strategic Tools in Practice
3.4 SWOT
3.4.1 Basics of SWOT
3.4.2 Shortcomings of SWOT
3.4.3 SWOT in Dynamic Environments
3.5 Porter’s 5 Forces
3.5.1 Basics of Porter’s Five Forces
3.5.2 Shortcomings of Porter’s Five Forces
3.5.3 Porter’s Five Forces in Dynamic Environments
3.6 PEST Analysis
3.6.1 Basics of PEST Analysis
3.6.2 PEST Analysis in Dynamic Environments
3.7 Scenario Analysis and Forecasting
Strategic Tools in Dynamic Environments
3.7.1 Basics of Scenario Analysis and Forecasting
3.7.2 Critical Factors of Scenario Analysis and Forecasting
3.7.3 Scenario Analysis and Forecasting in Dynamic Environments
3.8 Discussion of Findings

4 A New Framework for Strategic Tools in Dynamic Environments
4.1 Foundations of the Framework
4.2 Opportunity Recognition
4.3 Opportunity Analysis
4.4 Opportunity Evaluation

5 Limitations

6 Conclusion

Reference List

Appendix I

Appendix II

List of Abbreviations

illustration not visible in this excerpt

List of Figures and Tables

Figure 1. The strategic management process

Figure 2. The SWOT analysis

Figure 3. Porter’s five forces

Figure 4. LoNGPESTEL analysis

Figure 5. Schematic representation of a scenario analysis

Figure 6. Classification of the analyzed strategic tools

Figure 7. Combination of four domains to new opportunities

Figure 8. Reduction of complexity along four domains

Figure 9. Reduction of unpredictability

Figure 10. Framework for the use of strategic tools in dynamic environments

Figure 11. Opportunity recognition for the iPhone

Figure 12. Identification of the iPhone’s features to reduce complexity

Figure 13. Process to reduce unpredictability for the iPhone

Figure 14. Key success factors and key characteristics of the iPhone

Figure 15. Implementation plan for the iPhone

Figure 16. Scenario analysis for the iPhone

Table 1. Overview of questions derived from the analysis framework

Table 2. The worldwide mobile phone market development

1 Introduction

1.1 Problem Definition and Objective

“The reason why firms succeed or fail is perhaps the central question in strategy” stated Porter (1991, p. 95). While traditional strategy approaches can soundly answer this central question in stable environments, these approaches are not directly applicable to dynamic environments and there is currently no final and complete answer that determines the causes for a company’s failure or success with their strategies in dynamic environments (Wirtz, Mathieu, & Schilke, 2007, pp. 295-296). Nevertheless, there are many examples of companies that outperform their competitors even in dynamic environments, such as Microsoft and Intel (Hagel, Brown, & Davison, 2008; Wirtz et al., 2007), and there are many examples of companies that have not been successful at all, such as Siemens and BenQ with their mobile phone division (Wearden, 2007).

One critical point of each strategy is the strategic management process during which the strategy is developed and implemented and during which strategic tools such as the famous SWOT analysis or Porter’s five forces are used, for example, to structure or collect data. The purpose of this paper is to explore if strategic tools developed in stable environments are still suitable in dynamic environments or if there are certain constraints. Therefore, the paper builds on existing literature to develop a thorough understanding of dynamic environments and successful patterns of strategy in dynamic environments, and based on this understanding, an analysis framework is developed to analyze several strategic tools.

The new finding is that the use of strategic tools is still desirable in dynamic environments, but that there are limitations that must be considered to obtain useful results when using tools. This finding is used to develop a categorization of strategic tools (Figure 6) and to propose a new framework for the use of strategic tools in dynamic environments (Figure 10).

1.2 Course of Investigation

The paper consists of three main parts. The first part describes the theoretical background. It starts with a brief history of research in the field of strategy, and outlines the current point of view in strategy research. A short section is dedicated to reviewing the relationship between strategy and company performance to reinforce the importance of strategy for companies. Then the steps of the strategic management process that are relevant and addressed by this paper are outlined.

In the following part, stable environments are differentiated from dynamic environments. A first literature review is used to compare frameworks that are used to describe and characterize dynamic environments. Based on this review four dimensions are identified. Those four dimensions are the key to understand dynamic environments. They help to explain the process for developing strategies and the use of strategic tools in dynamic environments. A second literature review reveals successful patterns of strategy in dynamic environments. Those patterns are analyzed with regard to the four dimensions and then the theoretical part concludes with an analysis framework (Table 1). This analysis framework covers all parts from the theoretical background section and is used in the next section to analyze the strategic tools.

The second part is concerned with the analysis of the strategic tools in dynamic environments. After a short literature review and a basic introduction to strategic tools, four strategic tools are presented with some extensions and shortcomings. Then the feasibility for their use in dynamic environments is evaluated. The result of the study is twofold: First, the tools are classified into four categories (see Figure 6) and, second, a new framework for the use of strategic tools in dynamic environments is proposed.

This framework with its three steps is outlined in the third part. Each of the three steps is described in detail and the framework is complemented with an illustrative application to a fictitious case in Appendix II.

Finally, the limitations of the research and some general conclusions with suggestions for further research are presented.

2 Background

2.1 A Short Review of the History of Strategy

While a review of all popular strategy approaches would go beyond the scope of this work, a fundamental understanding of the most common approaches is crucial. The history of strategy and strategic management started in the 1960s with major works of Chandler (1969), Ansoff (1965), and Andrews (1971) and because management strategy consulting firms such as The Boston Consulting Group and McKinsey followed those ideas, they became quickly anchored in the industry (Abplanalp & Lombriser, 2005, p. 22).

In the following, four approaches to strategy that have developed over the last 50 years will be presented. The traditional, process-oriented idea defines strategy “as the determination of the basic long-term goals and objectives of an enterprise, and the adoption of courses of action and allocation of resources necessary for carrying out these goals” (Chandler, 1969, p. 13). Ansoff (1988, as cited in Abplanalp & Lombriser, 2005, p. 22) already noted that strategy does not directly lead to an action, but specifies the borders to determine the future direction of an enterprise. Additionally, since strategy is future-oriented and based on imperfect information, he stresses that strategy and its goals need to be reconsidered and readjusted over time.

While the traditional approach focuses on the process of developing a strategy, the capability-approach, mainly shaped by Michael E. Porter, focuses more on the content of strategies (Abplanalp & Lombriser, 2005, p. 22). Porter promotes the idea that “key structural features of industries determine the strength of the competitive forces and hence industry profitability” (Porter, 1980, p. 4). Thus, a company needs to find a defendable position in the industry where the “company can best defend itself against these competitive forces or can influence them in its favor” (Porter, 1980, p. 4). To achieve long-term and superior firm performance, the understanding of the industry and the defendable position of a company have to be translated into a competitive advantage by a cost advantage, which means that a company produces cheaper than other companies, or by a differentiation advantage, which means that a company can deliver benefits exceeding those of competitors’ products (Porter, 1985, pp. 3-12). As appealing Porter’s ideas are, today the prevailing opinion is that positioning within Porter’s parameters is too static, especially in dynamic environments, and the thereof derived competitive advantages are often not sustainable but only temporary and unstable (Beal, 2001; Davis, Eisenhardt, & Bingham, 2009, p. 439).

Mintzberg (1978) argues that there are three kinds of strategy: (a) intended strategies that are realized are deliberate strategies, (b) intended strategies that do not get realized are unrealized strategies, and (c) realized strategies that were never intended are emergent strategies. The idea of emergent strategies was at that time new and implies that “an environment imposes a pattern of action on an organization” (Mintzberg & Waters, 1985, p. 259) and, thus, strategies do not always have to be the result of rational strategy planning, but can also emerge out of the environment without intervention of a company.

Strategy approaches from the 1990s assume that firm performance is less determined by the market environment, but more by the company’s ambitions and the creative use of resources and successful companies set aims that are beyond their possibilities and resources (Abplanalp & Lombriser, 2005, p. 24).

Prahalad and Hamel (1990) introduced the idea of core competencies: Even if companies have highly diversified product portfolios, all their activities can often be reduced to some basic core competencies. For example, Casio has core competencies in “miniaturization, microprocessor design, material science, and ultrathin precision casing - the same skills it applies in its miniature card calculators, pocket TVs, and digital watches” (Prahalad & Hamel, 1990, p. 82). Those core competencies are the origin of competitive advantage.

Based on the finding that strategies might be affected more by internal factors and the fact that environments become increasingly dynamic, firms are required to adjust their competitive positions and strategies more often and, therefore, a need for dynamic strategies arose (Abplanalp & Lombriser, 2005, pp. 24-25). A promising approach is the resource-based view of the firm (RBV) that supposes “that when firms have resources that are valuable, rare, inimitable, and nonsubstitutable . . ., they can achieve sustainable competitive advantage by implementing fresh value-creating strategies” (Eisenhardt & Martin, 2000, p. 1105). While the “RBV has not adequately explained how and why certain firms have competitive advantage in situations of rapid and unpredictable change” (Eisenhardt & Martin, 2000, p. 1106), the RBV has been extended by dynamic capabilities. Dynamic capabilities are “the firm's ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” (Teece, Pisano, & Shuen, 1997, p. 516). Nevertheless, as Porter (Porter, 1991, pp. 107-109) points out there are still many unsolved questions and, thus, currently no comprehensive theory exists that explains strategy in dynamic environments.

While many of the older approaches are seen as out-dated, they still contain fundamental and basic ideas that current approaches are based on. Therefore, the basic ideas of competitive advantages, strategies as an instrument of long-term goals that do not necessarily lead to certain actions, and emergent strategies are still valid today and should be kept in mind in the following.

2.2 Strategy and Firm Performance

More than 50 years of research in the field of strategy leads to the inevitable question whether strategic planning has a positive influence on firm performance. As simple as the question seems, it is rather difficult to answer. As a review of Rhyne (1986, pp. 424- 425) shows there has been a wide variety of studies that all come to different conclusions, and due to this variety only three meta-studies will be reviewed here. Greenley (1986) reviews ten studies and draws two conclusions: (a) the available data at that point of time is “far from conclusive in establishing a relationship between strategic planning and company performance” (p. 108) and (b) even if there is no empirical evidence, strategic planning does provide a range of advantages and intrinsic values, such as a better understanding of the environment, improved employee morale, and better resource allocation (Greenley, 1986, pp. 107-108).

Boyd (1991) aggregates the results of 29 studies, which sum up about 2496 organizations, and finds that earlier research shows that strategic planning improves company performance, while later research tended not to prove this. Capon, Farley, and Hurlbert (1994) criticize Boyd’s study as Boyd omitted one major study of Fortune 500 companies. They extend Boyd’s work with this study and find a positive, but small, relationship between strategic planning and performance. C.C. Miller and Cardinal (1994) come to similar results with their meta-analysis of 26 other studies.

In conclusion, a relationship between strategic planning and firm performance exists, even though it seems to be small. Yet, the idea of intrinsic value is an important one that cannot be directly measured in financial terms.

2.3 The Strategic Management Process

This section shows which steps of the strategic management process are addressed by this paper. Literature is consistent about the four broad steps of the strategic management process, even if there are some minor deviations (e.g. Abplanalp & Lombriser, 2005, p. 47; Alkhafaji, 2003, p. 1; Fink, Marr, Siebe, & Kuhle, 2005, p. 372; Goodstein, Nolan, & Pfeiffer, 1993, p. 8). The process is depicted in Figure 1 as a cycle because the process is reoccurring over time since with changing conditions, strategy needs to be adjusted.

It starts with strategic analysis, during which information about the internal and external environment of a company is gathered and later aggregated (Goodstein et al., 1993, p. 11). Important factors within the external environment are the macro environment, the industry environment, and the competitive environment (Goodstein et al., 1993, pp. 11-12). The next step is called strategy development, sometimes also strategy formulation, where based on existing data, the actual strategy is developed. The development of the strategy often consists of a mission and a vision, which explain the what and why, and strategies for the strategic business units and the enterprise as a whole (Abplanalp & Lombriser, 2005, pp. 49-50). The next and most critical step is the strategy implementation, during which the strategy is rolled-out and managers should include it in their every day decisions. In the final step, strategy evaluation and control, the company monitors in an ongoing process if the strategy is implemented in the desired way and if the premises are still valid with regard to changing conditions (Abplanalp & Lombriser, 2005, pp. 387-389).

Strategic tools play an essential support role within the strategic management process (Clark, 1997, p. 418) and can be found within all four steps. Many strategic tools, however, are focussed on gathering informations about the environment and the organization and, therefore, are related to the strategic analysis. For example, Porter’s five forces and the political, economic, sociological, and technological analysis (PEST) are analysis tools that are environment-oriented (Simon & Gathen, 2002, pp. 188-190), while the value chain analysis and core competencies are internal, organziation-oriented tools (Simon & Gathen, 2002, pp. 62-69, 201). The strength, weakness, opportunity, and threat analysis (SWOT) relates strategic analysis to strategy development as it combines internal and external perspectives to potential strategies (Abplanalp & Lombriser, 2005, p. 197). The best example for strategy implementation is probably the balanced scorecard that helps measuring the implementation success of a strategy (Simon & Gathen, 2002, pp. 156-157). The balance scorecard, however, can also be used as a strategy evaluation and control tool as it shows whether strategic goals have been reach.

This paper deals with strategic tools in dynamic environments and, therefore, will analyze tools that are related to the environment analysis and those tools are mainly found within the strategic analysis.

2.4 Dynamic Environments

2.4.1 Literature Review

In the following, four dimensions will be introduced that describe the characteristics of dynamic environments.

While other papers often mingle several dimensions to describe dynamic environments (Bourgeois & Eisenhardt, 1988, p. 816; Brown & Eisenhardt, 1997, p. 20; Pisano, 1994) or use only single terms such as uncertainty (Courtney, Kirkland, & Viguerie, 1997; Marlin, Hoffman, & Lamont, 1994), turbulence (Grant, 2003; D. Miller, 1987), volatility (Grant, 2003), or dynamism (Brown & Eisenhardt, 1997; Wirtz et al., 2007), this paper uses four dimensions that comprises all those other dimensions.

The four dimensions rely on the basic definitions used by Davis et al. (2009), yet, they are extended to draw a broader picture. The dimensions are: velocity, complexity, uncertainty, and unpredictability. It is important that the dimensions are still correlated, meaning that, for instance, high-velocity environments may be accompanied by a high degree of uncertainty (Eisenhardt, 1989, p. 545).

Based on the highly cited work of Hannan and Freeman (1977), Wholey and Brittain (1989) developed a model to measure dynamic environments along frequency, amplitude, and predictability. In the framework used here, frequency is captured by velocity; amplitude is partly captured by complexity and partly by uncertainty; and predictability is captured just with the opposite, unpredictability.

D. Miller and Friesen (1983) also developed, based on many other works, a threedimensional model to examine dynamic environments. While the four dimensions used in this paper are abstract, they use already concrete and industry-related dimensions that often mingle several of the four dimensions and, hence, the four dimensions completely cover their three dimensions. Concluding, it can be said that the four dimensions cover mainly all dimensions that have been proposed by other papers.

2.4.2 Velocity

While velocity, in absolute terms, can be defined as “the speed or rate at which new opportunities emerge” (Davis et al., 2009, p. 423), in relative terms it means that new futures arrive more quickly in dynamic environments than in stable environments (Brown & Eisenhardt, 1997, p. 20).

The construct of the term opportunity used here is the idea of an external, future- oriented factor that consists of the opportunity itself as a possibility for increased firm performance and the quickly arriving futures. The opportunity itself might be beneficial for the firm, while the futures often involve change for firms and, therefore, in some cases might not be beneficial for the firm. In all cases, however, an opportunity is triggered by an environmental change. In the following, the term opportunity is used in the sense of this construct.

Environmental changes can be very small and can arise out of four different domains to form an opportunity. Two domains, demand and competition, are determined by the market the firm is operating in; technology can be an internal and external domain; and regulations are an external domain, given, for instance, by authorities or governments (Bourgeois & Eisenhardt, 1988, p. 816). One result of changes in those domains is the “predictable obsolescence of knowledge and competitive advantage“ (Floricel & Ibanescu, 2008, p. 458) because new opportunities require adjusted knowledge and might render existing competitive advantages, for example because of new technology, useless. This obsolescence of knowledge is one reason for the “continuous innovation that occurs in many high-velocity industries” (Brown & Eisenhardt, 1997, p. 16). Most of the papers analyzing velocity-related topics do this in the technology-driven industries such as microprocessor or mobile phone industry (Bourgeois & Eisenhardt, 1988; Brown & Eisenhardt, 1997; Eisenhardt, 1989; Vilkamo & Keil, 2003).

The definition of velocity in itself does not imply any information about the probability, predictability, complexity, or success about those opportunities. These factors arise in combination with the other dimensions. Environments with a high velocity, however, are attractive, since they offer many opportunities managers can choose from (Davis et al., 2009, p. 441).

2.4.3 Complexity

Complexity is defined “as the number of features of an opportunity that must be correctly executed to capture that opportunity” (Davis et al., 2009, p. 423). This means that each opportunity is equipped with features and if a firm wants to successfully take advantage of an opportunity it must address those features correctly. For example, a firm must correctly execute a number of steps of a plan (Davis et al., 2009, p. 423). Furthermore, this implies that if an opportunity has more features, the probability that all necessary features are addressed becomes lower and, therefore, the opportunity becomes more complex. The link between complexity and environment is that opportunities emerge out of the environment, therefore, making the environment complex. Thus, complex environments are particularly unattractive as with high complexity the probability that the necessary features are addressed correctly falls, which leads to lower performance (Davis et al., 2009, p. 442). While the definition above is only unidimensional, Duncan (1972, p. 325) adds a second dimension that describes the heterogeneity or homogeneity of the features over time. Based on this definition, Tung (1979) relates it to managerial tasks and proved that with increasing complexity, this means with a higher number of features and a higher degree of heterogeneity amongst the features, “the CEO's cognitive abilities to grasp and comprehend the relationships that exist among” (p. 675) the features become limited which is then perceived as uncertainty. Cannon and John (2007, p. 314) provide a framework for measuring the overall complexity of an environment. While measuring complexity is not the purpose of this work, their four different domains, including competitive complexity, market diversity, resource complexity, and process/facility complexity, are interesting to evaluate the strategic tools later on.

Davis et al. (2009, p. 420) present an interesting paper of Sine, Haveman, and Tolbert (2005) that illustrates complexity with a real case. The paper is about the risk of opportunities for entrepreneurs in the new independent power sector in the United States. The complexity of the sector arises from the opportunity contingencies in the fields of technology, production process selection (Sine et al., 2005, pp. 214-215) and regulatory aspects (Sine et al., 2005, pp. 208-209). While the complexity in this industry arises from opportunity contingencies, it also shows that complexity must not always be accompanied by velocity.

2.4.4 Uncertainty

While Davis et al. (2009) define ambiguity “as lack of clarity such that it is difficult to interpret or distinguish opportunities” (p. 424), they do not distinguish it from uncertainty, even though, they mention uncertainty several times (Davis et al., 2009, p. 423). Schrader, Riggs, and Smith (1993, p. 74) already mention that ambiguity and uncertainty are often used as interchangeable concepts, even if frameworks to distinguish them exist. Therefore, the definition of ambiguity of Davis et al. (2009) is extended and clarified. Schrader et al. (pp. 77-78) state that ambiguity is the missing link between variables and their functional relationships and, therefore, the outcome of an opportunity would not be known, while under uncertainty the possible outcomes or futures are identified, however, uncertainty is “characterized by a lack of information” (Schrader et al., 1993, p. 76), but the variables and their functional relationships are known (Schrader et al., 1993, p. 77). Therefore, uncertainty can also be seen as a subset of ambiguity. For example, the lack of information leads to the perceived uncertainty that was explained with the complex opportunities in the previous section.

While one might argue that under total ambiguity, that means, there is no clarity of the possible outcomes, the concept of strategy might be rendered useless, this work will concentrate on uncertainty, as do most papers dealing with strategy (e.g. Andersen, 2004; Courtney et al., 1997; Eisenhardt, 1989; Grant, 2003; D. Miller & Friesen, 1983; Porter, 1991). Duncan (1972) adds to uncertainty the aspect of “not knowing the outcome of how much the organization would lose if the decision were incorrect” (p. 318). When later analyzing strategic tools in terms of uncertainty, it is important to check whether (a) clarity is improved by giving assistance in interpreting or distinguishing opportunities, (b) uncertainty is reduced by adding missing information, and (c) the outcome becomes more obvious in terms of potential losses. Examples for markets with high uncertainty are nascent markets, such as the nanotechnology market (Davis et al., 2009, p. 420).

2.4.5 Unpredictability

Interestingly, unpredictability is used in many papers without further defining it (e.g. Floricel & Ibanescu, 2008, p. 495; Grant, 2003, p. 495; Wirtz et al., 2007, p. 303) and, therefore, this definition relies on the basic definition of unpredictability as “the amount of disorder or turbulence in the flow of opportunities such that there is less consistent similarity or pattern” (Davis et al., 2009, p. 424). In other terms, unpredictability means that the experience gained with opportunities in the past is not directly transferable to new opportunities and that each opportunity needs to be re-evaluated. Additionally, this means that in “more unpredictable environments, changes are less foreseeable” (Hannan & Freeman, 1977, as cited in C. C. Miller, ogilvie, & Glick, 2006, p. 104).

While unpredictability affects opportunities, it affects on a second dimension the behavior of external factors, too. D. Miller (1987, p. 62) relates, based on other works, unpredictability to the behavior of customers, suppliers, and competitors, as well as to the unknown rate of change in market trends and innovation in the industry. Especially, growth markets, such as the Web 2.0 or wireless service market, are characterized by high unpredictability (Davis et al., 2009, p. 420), since they are young markets and have no consistent pattern of opportunities.

2.5 Strategy in Dynamic Environments

While there is currently no universal solution for strategies in dynamic environments, there are some clear trends identifiable. To identify those trends 28 papers from 1983 until 2009 related to strategies in dynamic environments have been reviewed, and among 15 of them similar recommendations could be identified that will be presented here.

The most common pattern identified recommended broader strategy alternatives that allow companies more flexibility (Bourgeois & Eisenhardt, 1988, p. 831; Brauer & Schmidt, 2006, pp. 220-221; Brown & Eisenhardt, 1997, p. 20; Bryan, 2002; Courtney et al., 1997, pp. 74-75; Eisenhardt, 1989, pp. 555-556; Grant, 2003, p. 509). In dynamic environments new opportunities arrive more quickly and the outcome of those opportunities is uncertain. Therefore, “options give managers more possible responses. When the future does arrive, managers are more likely to have something readily available to do and can more quickly adjust” (Brown & Eisenhardt, 1997, p. 20) and “the probability of being surprised by an unanticipated future” (Brown & Eisenhardt, 1997, p. 20) is lowered. Brauer and Schmidt (2006, p. 220) propose that firms may “sway off course” and then “pull back on course” depending on upcoming opportunities, which means that firms should allow for flexibility if there are promising opportunities. Bryan (2002) and Courtney et al. (1997), who are writing more from a practitioner’s perspective, call this idea portfolio of initiatives and portfolio of actions. As opportunities emerge faster in dynamic environments, and the time windows of opportunities close quickly due to the high velocity, companies need to act more swiftly (Davis et al., 2009, p. 441). Prerequisite to act swiftly is the use of real-time information (Eisenhardt, 1989, p. 550), real-time control, and active-anticipation of those opportunities (Ansoff & Sullivan, 1993, p. 19). The consequence is that strategic decisions must be made in short time-frames (Bourgeois & Eisenhardt, 1988, p. 830) and that strategic plans are only prepared for shorter time horizons (Grant, 2003, p. 509).

Closely related to the use of real-time information is the generation of information. Decision teams in dynamic environments use “more information than the slower decision makers” (Eisenhardt, 1989, p. 549) and the data is generated using highly analytical processes including industry, competitors, strengths and weaknesses, target markets, scenario analysis, and technology development (Bourgeois & Eisenhardt, 1988, p. 827; Courtney et al., 1997, pp. 71-72). With more information available uncertainty is reduced and, furthermore, features can be better identified such that complexity is also reduced.

Another re-appearing pattern is that successful strategies are not necessarily decided by top management. Several papers propose the idea of decentralized strategy making and ownership (Andersen, 2004; Bourgeois & Eisenhardt, 1988, p. 831; Feurer, Chaharbaghi, & Distel, 1995, p. 13; Grant, 2003, p. 508). This means that strategies are formulated by employees that will also be responsible for executing them. One advantage is, for example, that they are closer to the market and customers. As they have more information and better insight, they can deal better with uncertainty, complexity, and unpredictability of opportunities. Yet, as Feurer et al. (Feurer et al., 1995, p. 14) mention, it is still important to find the right balance between decentralization and maintaining an overall alignment because even in dynamic environments, strategy is still a tool to overcome the principal-agent problem (Porter, 1991, p. 96).

Thus, one task of top management is to set company-wide goals for the strategy. Especially in dynamic environments, clear and explicit goals are important as they act as an anchor for actions (Bourgeois & Eisenhardt, 1988, p. 829). The same was observed by Grant (2003, p. 509), who noted that companies should put more emphasis on broadly defined goals than on strategic planning with detailed programs of action. The goals serve as guidelines and allow companies to capture unforeseen opportunities if they are within those goals, while plans of action prohibit capturing new opportunities as detailed steps are already specified. This is within the idea of simple rules described in Davis et al. (2009) that allow for more flexibility and efficiency in terms of “creating high-quality, innovative products while responding to market shifts” (p. 416).

Related to simple rules is the structure of a company. Davis et al. (2009) examined the optimal structure of firms operating in dynamic environments with a stochastic model. While one may doubt that the structure of a firm can be modelled as rules in dynamic and fluid organizational structures, such as the matrix or mesh structure, their findings are still interesting. They could prove that a trade-off between efficiency and flexibility exists. A lack of structure in a company inhibits the error-free execution of opportunities, while too much structure reduces the range of possible opportunities, but “that it is safer to err on the side of too much structure (efficiency) than on the side of too little (flexibility)” (Davis et al., 2009, p. 437).

Another very interesting perspective developed by Fowler, King, Marsh, and Victor (2000) is to move away from the product-centred view because “a product-centered perspective on strategy is much more helpful in providing a way to explain a firm’s current competitive advantage than in making strategies that create competitive advantage in the future” (Fowler et al., 2000, p. 358). It is proposed that companies develop technological, market-driven, and integration competencies (Fowler et al., 2000, p. 358). Technological competencies refer to the ability to possess and develop knowledge that can be used to create desired outcomes (Fowler et al., 2000, p. 361). For example, Intel developed a specialization in optical lithography, which is used to produce microprocessors, and could employ this technology over six processor generations, while preventing imitations by competitors (Chaudhuri & Tabrizi, 1999, p. 124). Market-driven competencies include customer knowledge, customer access, and competitors knowledge (Fowler et al., 2000, p. 362). Integration competencies deal with the problem that market-driven and technological competencies need to be combined for successful products and that new competencies need to be developed (Fowler et al., 2000, pp. 364-365). Considering this approach under the four dimensions of dynamic environments, it makes sense because focusing too much on products might ignore opportunities that could be captured with technological and market-driven competencies.

One final approach that will be presented here, is the idea that became well-known as blue ocean strategies (Kim & Mauborgne, 2009). While the previous approaches are mainly from an outside-in perspective, so that companies adapt their strategies to environmental changes, the idea of blue ocean strategies is an inside-out approach, meaning that companies shape their environment (Courtney, 2001; Courtney et al., 1997, pp. 72-74; Kim & Mauborgne, 2004). The idea of a blue ocean is to not to fight over existing demand, but to create new demand and uncontested market space (Kim & Mauborgne, 2004, pp. 77-78, 81). Kim and Mauborgne (2009) cite Nintendo with the Wii, with which they created a totally new market of video gaming players, as an example. As tempting as this idea might seem, this strategy and its consequences must be carefully evaluated. Shaping may decrease uncertainty in an uncertain market because it makes it more probable that one desired industry scenario occurs (Courtney et al., 1997, p. 76), however, it leaves the other three dimensions out of sight. A blue ocean strategy might decrease velocity, as there are less opportunities coming up, increase unpredictability, as there is no known pattern from the past, or increase complexity, as the opportunities become more complex since the market is completely new. Additionally, Courtney (2001) states that companies that want to implement successfully a blue ocean strategy need several characteristics such as “a clear vision of an industry's future evolution . . . ; deep pockets; a strong reputation; a leadership position in a related business; world-class technology, innovation skills, or both; and operational excellence” (pp. 47-48) and he cites the example of Iridium, a company that wanted to shape the satellite telephone market and completely failed because technology was not mature (Courtney, 2001, p. 47).

All patterns mentioned are good clues that should be considered when drafting strategies in dynamic environments. Strategic tools should encourage the use of those patterns and, thus, those patterns are part of the analysis framework.

2.6 Analysis Framework

Based on the theory outlined above, a framework to analyze strategic tools in dynamic environments has been developed. The analysis of the tools is conducted along three dimensions: (a) fit with basic strategy parameters, (b) fit with the four dimensions of dynamic environments, (c) alignment with strategic patterns in dynamic environments. An overview of the questions derived from this framework can be seen in Table 1. The analysis of fit with basic strategy parameters consists of three parts. In the first part, the focus of the tools is examined. Even if tools are analysis-oriented, they might induce users to derive actions instead of goals or guidelines. Actions would drive a strategy to an action plan instead of a goal-oriented, long-term instrument. Tools can have different time focuses. They can induce goals as short-term or long-term goals, while the data, they gather, can be past-oriented data, present-oriented, or future-oriented data. Lastly, the tool is examined to determine if it clearly addresses one of the four dimensions of dynamic environments or if it mingles some dimensions.

In the second part, the tool with regard to the four dimensions of dynamic environments is analyzed more thoroughly. As velocity deals with the speed of upcoming opportunities, the tool should prove that it can capture several, new opportunities in the domains of demand, competition, technology, and regulations. Complexity arises because features of opportunities become blurred. Therefore, a tool should help distinguish features of opportunities arising from market diversity, competitive complexity, resource complexity, and process/facility complexity.


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Strategic Tools in Dynamic Environments
A Framework
European Business School - International University Schloß Reichartshausen Oestrich-Winkel
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Porters 5 Forces, SWOT, Szenario Analyse, Dynamische Umwelten, PEST, Uncertainty, Velocity, Unpredictability, Complexity, Dynamic Environments, Scenario Analysis
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Cornelius Herzog (Author), 2010, Strategic Tools in Dynamic Environments, Munich, GRIN Verlag,


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Title: Strategic Tools in Dynamic Environments

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