INTRODUCTION
Historically, the focus of IT infrastructure has been to capture the knowledge of experts in a centralized repository (Davenport & Prusak, 1998; Grover & Davenport, 2001). These centralized databases contained knowledge that was explicit and historical (e.g., competitor pricing, market share), and the IT infrastructure served to facilitate functional decision-making or to automate routine tasks (i.e., in re-engineering). The users of technology approached the repository to obtain data in a narrowly defined domain (Broadbent et al. 1999). Consequently, IT originally played a significant yet ultimately limited role in the strategy creation process. Management information systems (MIS) arguably generated information that was less applicable to strategy creation, as noted in early writings on the linkage between MIS and strategic planning (Holmes, 1985; Lientz & Chen, 1981; Shank et al., 1985).
The active management of knowledge was similarly underdeveloped. Despite the fact that strategic decision makers had always emphasized the role of tacit knowledge, the actual importance of knowledge was not explicitly recognized. Formalized knowledge management (KM) (Davenport & Prusak, 1998), with its associated terminology and tools, is a recent development and, as such, did not inform the strategic planning process.
However, the shifts that have taken place in IT infrastructures over the last decade and the recent developments in knowledge management have brought them closer to the creators of strategy. Indeed, both IT and knowledge management are increasingly enablers in the contemporary strategic management practice.
1. IT infrastructure is transitioning in its focus from the functional work unit to a process orientation. Whereas computer systems were once the focal point, the new infrastructure is network-centric, with an emphasis on business knowledge (Broadbent et al., 1999). For example, traditional search engines utilized rule-based reasoning to identify elements matching specific search criteria; the “state-of-the-art” knowledge management systems employ case-based search techniques to identify all relevant knowledge components meeting the user’s request (Grover & Davenport, 2001). 2. IT now takes into account contexts that include cross-functional experts that are knowledgeable in a wide variety of potentially relevant issues. Additionally, there is a greater emphasis on the integration of infrastructure with organization, structure, culture (Gold et al., 2001), and organizational roles (Davenport & Prusak, 1998). In many ways, the newer IT infrastructures have enabled the garnering of explicit knowledge throughout the organization improving the speed of strategy creation.
The objective of this article is to outline how the developments in IT and KM are facilitating the evolution of strategic management to strategic experimentation in order to create quantum improvements in strategy creation and unprecedented developmental opportunities for the field of IT.
BACKGROUND
Information Technology (IT)
For the purposes of this chapter, IT is defined as physical equipment (hardware), software, and telecommunications technology, including data and image and voice networks employed to support business processes (Whitten & Bentley, 1998). The overarching plan for IT deployment within an organization is called the IT architecture. Technology infrastructure refers to the architecture as including the physical facilities, the services, and the management that support all computing resources in an organization (Turban et al., 1996).
Knowledge Management (KM)
As used in this chapter, data are objective, explicit pieces or units; information is data with meaning attached; and knowledge is information with an implied element of action.
Knowledge is the fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms (Davenport & Prusak, 1998, p. 5).
KM is “a set of business practices and technologies used to assist an organization to obtain maximum advantage from one of its most important assets—knowledge” (Duffy, 2000, p. 62). In other words, it is actively capturing, sharing, and making use of what is known, both tacitly, informally, and explicitly, within the organization. IT often facilitates knowledge management initiatives by integrating repositories (e.g., databases), indexing applications (e.g., search engines), and user interfaces. Davenport and Prusak (1998) note that KM also incorporates traditional management functions: building trust among individuals, allocating resources to KM, and monitoring progress.
Strategic Management
The concept of “strategy” explicated in strategic management is one of marketplace strategy (i.e., winning in the marketplace against competitors, entrenched or incipient). The underlying premise is that “to enjoy continued strategy success, a firm must commit itself to outwitting its rivals” (Fahey & Randall, 2001, p. 30). A large body of literature on strategic management has persuasively argued that effective strategy creation and execution are central to a firm’s performance (Covin et al., 1994).
Strategy creation involves both goal formulation— defined in terms of external stakeholders rather than operational milestones—and crafting of the strategic means by which to accomplish these goals (Hofer & Schendel, 1978). The means typically include business scope, competitive posture, strategic intent, and the organizational mechanisms for implementation. In practice, the process of strategy creation has often taken the form of strategic planning. Comprehensive strategic planning (Gluck et al., 1978) has historically been practiced in large corporations. A celebrated example is the use of scenarios by Royal-Dutch Shell. Planning usually consisted of several sequential stages of decision-making involving diagnosis, alternative development, evaluation and choice, and implementation. In each step, the strategic planners emphasized deliberate juxtaposition of “objective data” and careful analysis with top managementjudgment, thus highlighting the role of tacit knowledge.
Strategic planning has evolved over the years. Writing in the 1970s, Gluck et al. (1978) identified four phases of evolution: budgeting, long-range planning, strategic planning, and strategic management. Each phase of evolution incorporated the lessons from the earlier phases, but also took into account the emerging realities faced by corporations. Gluck et al. (1978) noted that during the 1980s the “strategic management” phase would represent the cutting edge of practice in the world.
TOWARD STRATEGIC EXPERIMENTATION
The 1990s witnessed a revolution in organizational environments often characterized as “hypercompetition” (D’Aveni, 1994). These environments have created three major imperatives for organizations: time compression, globalization, and technology integration (Narayanan, 2001). The increased environmental dynamism also contributes to an increase in the degree of uncertainty confronted by strategic managers, calling into question traditional planning practices. Consequently, a new type of strategy creation process is evolving, which is termed “strategic experimentation.” With this evolution, the relationship between strategy creation, knowledge management, and IT is undergoing a profound shift.
All four phases of strategic planning documented by Gluck et al. (1978) incorporated a sequential approach to strategy creation and execution, leading to the identification of one winning strategy that has the highest probability of success. Consequently, firms found it logical to commit the maximum available resources to the implementation of one wining strategy. The goal was to obtain a sustainable competitive advantage vis a vis the firm’s rivals, and to reduce uncertainty ex ante using analytical forecasting techniques as well as market research. This approach to planning seems to have been effective during the 1980s when the environment was moderately dynamic.
In hypercompetitive environments, market participants frequently confront great uncertainty over technological possibilities, consumer preferences, and viable business models. This high level of ambiguity often results in a situation where (a) traditional methods of ex ante uncertainty reduction (e.g., market research) fail, and (b) the costs and risks of the traditional “big bet” strategic management approach outweigh the advantages in terms of focus, decisiveness, and concentrated resource commitment. It is in this situation that the emerging strategic experimentation approach holds significant promise.
Strategic experimentation (Brown & Eisenhardt, 1998; McGrath, 1998; McGrath & MacMillan, 2000) draws on real-options reasoning (McGrath, 1997), discussions of exploration vs. exploitation, and trial-and-error learning (Van de Ven & Polley, 1992).
1. Companies engaging in strategic experimentation continually start, select, pursue, and drop strategic initiatives before launching aggressively those initiatives whose values are finally revealed (McGrath & MacMillan, 2000).
2. Strategic initiatives serve as low-cost probes (Brown & Eisenhardt, 1998) that enable the discovery of product technology and market preferences. They also serve as a stepping stone option for future competitive activity in that particular product-market domain.
3. The role of the strategic manager is to administer a portfolio of strategic initiatives that represent an appropriate mix of high and low uncertainty projects, and to maximize the learning from these real options (McGrath & MacMillan, 2000).
Strategic experimentation represents a fundamentally different view of the practice of strategic planning and the path to competitive advantage. Movement is emphasized over position in this approach. Thus, competitive advantage is viewed as temporary at best, and hence, innovation and learning are considered crucial to success. Strategic experimentation is especially appropriate for high velocity environments such as emerging product markets with high uncertainty surrounding both technology and customer preferences (e.g., the early Personal Digital Assistant, Internet appliance, and satellite-based telephony markets). Here, low-cost probes can be very effective in gaining knowledge and reducing uncertainty while minimizing exposure to the results of faulty assumptions.
THE ROLE OF IT AND KNOWLEDGE MANAGEMENT IN THE ERA OF STRATEGIC EXPERIMENTATION
Since strategic experimentation represents the cutting edge of ideas in strategic management, we should expect significant advances in tool development and utilization in the next few years that will enable us to move the idea towards normal organizational practice.
Strategic experimentation necessitates several major functions that should be performed by an organization. KM is critical in strategic experimentation; therefore, it is not surprising that many of the tools currently moving into practice have emerged from KM. Following are the four major strategic experimentation functions and the associated KM tools.
Rapid Decision-Making
The ability to quickly garner tacit knowledge in all phases of decision-making is a central requirement in strategic experimentation. Current KM tools to support this include visualization and prototyping, group decision facilitation, and knowledge representation. Each method attempts to reduce the time needed for a group to progress from problem identification to solution implementation. These tools help to coordinate the use of data, systems, tools, and techniques to interpret relevant information in order to take action (Little, Mohan, & Hatoun, 1982).
Integration of Learning from Experiments
Organizational learning, another core concept in strategic experimentation, requires that appropriate learning be distilled from each experiment. This orientation combines decision-making and learning. Initiatives judged to be failures are not merely weeded out; they become occasions for discovery of root causes. Nor are successes simply alternatives to back financially; successes often generate potential best practices. Current KM tools in use for this purpose include learning histories (Roth & Kleiner, 1998), group brainstorming, and shared communication platforms.
Diffusion of Learning
Organizational learning has to be diffused throughout the organization. Since formal organizational channels may stifle transmission of tacit knowledge, diffusion may require interactions among “communities of practice” (Grover & Davenport, 2001; Davenport & Prusak, 1998). An organizational architecture incorporating relevant tools and IT infrastructure has to be designed to support theses interactions. KM tools such as knowledge maps identifying the experts in specific areas and repositories of case histories, are evolving to include dynamic updating of repositories and focused search tools to reduce information overload.
Managing a Portfolio of Strategic Experiments
Finally, unlike in previous eras, strategic experimentation requires maintenance and management of a portfolio of initiatives (Narayanan et al., 2001). This has three major implications. First, the knowledge base for decisions has to be broader and richer, simply due to the increase in the number of initiatives. Second, the knowledge base becomes much more complex, since the initiatives themselves differ in terms of the mix of tacit and explicit knowledge. Thus, newer initiatives are likely to be more dependent on tacit knowledge, whereas mature ones can be augmented by explicit knowledge. Finally, the sheer number of people involved in the process will be larger, given specialized pockets of tacit knowledge that would have grown up around specific strategic initiatives. DSS and other rich data applications, including cognitive mapping, can be used to capture the knowledge and feedback.
Strategic Experimentation and Knowledge Management
IT can accelerate the development of strategic experimentation by designing infrastructures that accommodate the new KM demands imposed by this new mode of planning. Consider how each of the following functions can be enhanced by IT infrastructure development.
1. Future developments can significantly reduce the time expended in solution development through real time displays, and expand opportunities for geographically dispersed collaboration. Also, advanced multimedia and communication capabilities increase the benefits of GSS and DSS tools.
2. Learning from experiments can be enriched by qualitative database construction, multimedia enhancements to communication applications, and open platforms to permit the sharing of knowledge over various communication channels, including wireless media.
3. Today, diffusion is hampered by information overload that has intensified competition for the user’s attention (Hansen & Haas, 2001). To solve the problem, search tools should include separate parameters for content, rationale, and purpose of the query in order to isolate salient responses. Additionally, knowledge repositories must be maintained to ensure the contents are accurate and of high quality. Maintenance, currently provided by intermediaries (Markus, 2001), might be performed by faster automated systems.
4. Expert systems or neural networks may be developed to manage and track portfolios, promoting reuse of the knowledge captured.
The significant implication for IT infrastructure from our discussion is the need for technology integration (Narayanan, 2001) with both hard and soft technologies. IT infrastructure should exploit the potential for integration with other hard technologies such as telecommunications to enhance the organizational capacity for speed and the carrying capacity for tacit knowledge. Similarly,
IT should seek to interface with decision sciences to embed AI-based processing tools, and with cognitive theorists to capture the tacit knowledge pervasive in organizations.
CONCLUSIONS AND IMPLICATIONS
We have argued that the technological changes of the 1990s have ushered in the need for strategic experimentation as the metaphor for planning practice. Strategic experimentation involves (a) maintaining a portfolio of strategic thrusts, (b) rapid decision-making so that successful experiments are backed and failures are weeded out quickly, (c) learning from both successes and failures, and (d) diffusion of both explicit and tacit knowledge throughout the relevant segments of an organization. This phase requires fundamental shifts in our view of knowledge management—its significance, use, and tools. Finally, we have argued that the shift to strategic experimentation requires fundamental shifts in the development of IT infrastructure. Instead of developing in relative isolation to other disciplines, IT should focus on technology integration by working in close collaboration with the telecommunication technologies, artificial intelligence community, and managerial cognition scholars.
KEY TERMS
Exploration and Exploitation: Exploration refers to the process of discovery of knowledge, whereas exploitation refers to utilizing the knowledge. Similar to basic and applied research.
Information Technology (IT): Refers to the physical equipment (hardware), software, and telecommunications technology, including data, image, and voice networks, employed to support business processes.
Knowledge Management (KM): A set of business practices and technologies used to assist an organization to obtain maximum advantage of its knowledge.
Options: A financial option owes the holder the right, but not the obligation, to trade in securities at prices fixed earlier. Options in the sense used here confer to a firm the rights, but not the obligations, to choose a strategic alternative.
Strategic Experimentation: A form of strategic management in which firms continually start, select, pursue, and drop strategic initiatives before launching aggressively those initiatives whose values are finally revealed.
Strategic Management: The process of strategy creation and implementation. The concept of “strategy” as used here is one of marketplace strategy (i.e., winning in the marketplace against competitors, entrenched or incipient). Strategy creation involves both goal formulation—defined in terms of external stakeholders rather than operational milestones—and crafting of the strategic means by which to accomplish these goals. Implementation refers to the means of executing the created strategy.
