4 O rg aniz ati o nal L e arnin g Theories and Technolo gy Introduction The purpose of this chapter is to provide readers with an understanding of organizational theory. The chapter covers some aspects of the history and context of organizational learning. It also defines and explains various learning protocols, and how they can be used to promote organizational learning. The overall objective of organizational learning is to support a process that guides individuals, groups, and entire communities through transformation. Indeed, evidence of organizational transformation provides the very proof that learning has occurred, and that changes in behavior are occurring. What is important in this regard is that transformation remains internal to the organization so that it can evolve in a progressive manner while maintaining the valuable knowledge base that is contained within the personnel of an organization. Thus, the purpose of organizational learning is to foster evolutionary transformation that will lead to change in behaviors and that is geared toward improving strategic performance. Approaches to organizational learning typically address how individuals, groups, and organizations “notice and interpret information and use it to alter their fit with their environments” (Aldrich, 2001, p. 57). As such, however, organizational learning does not direct itself toward, and therefore has not been able to show, an inherent link to success—which is a critical concern for executive management. There are two perspectives on organizational learning theory. On the one hand, the adoptive approach, pioneered by Cyert and March (1963), treats organizations as goal-oriented activity systems. These systems generate learning when repeating experiences that have either succeeded or failed, discarding, of course, processes that have failed. 63 64 IN F O RM ATI O N T EC HN O L O GY Knowledge development, on the other hand, treats organizations as sets of interdependent members with shared patterns of cognition and belief (Argyris & Schö n, 1996). Knowledge development emphasizes that learning is not limited to simple trial and error, or direct experience. Instead, learning is understood also to be inferential and vicarious; organizations can generate new knowledge through experimentation and creativity. It is the knowledge development perspective that fits conceptually and empirically with work on technological evolution and organizational knowledge creation and deployment (Tushman & Anderson, 1986). There is a complication in the field of organizational learning over whether it is a technical or social process. Scholars disagree on this point. From the technical perspective, organizational learning is about the effective processing of, interpretation of, and response to information both inside and outside the organization. “An organization is assumed to learn if any of its units acquires knowledge that it recognizes as potentially useful to the organization” (Huber, 1991, p. 89). From the social perspective, on the other hand, comes the concept that learning is “something that takes place not with the heads of individuals, but in the interaction between people” (Easterby-Smith et al., 1999, p. 6). The social approach draws from the notion that patterns of behavior are developed, via patterns of socialization, by evolving tacit knowledge and skills. There is, regrettably, a lack of ongoing empirical investigation in the area of organizational learning pertaining, for example, to in-depth case studies, to micropractices within organizational settings, and to processes that lead to outcomes. Indeed, measuring learning is a difficult process, which is why there is a lack of research that focuses on outputs. As Prange (1999, p. 24) notes: “The multitude of ways in which organizational learning has been classified and used purports an ‘organizational learning jungle,’ which is becoming progressively dense and impenetrable.” Mackenzie (1994, p. 251) laments that what the “scientific community devoted to organizational learning has not produced discernable intellectual progress.” Ultimately, organizational learning must provide transformation that links to performance. Most organizations seeking improved performance expect changes that will support new outcomes. The study of organizational learning needs an overarching framework under which O r ga niz ati o n a l L e a rnin g T heo rie s 65 an inquiry into the pivotal issues surrounding organizational change can be organized. Frameworks that support organizational learning, whether their orientation is on individuals, groups, or infrastructure, need to allow for natural evolution within acceptable time frames for the organization. This is the problem of organizational learning theory. It lacks a method of producing measurable results that executives can link to performance. While scholars seek outcomes through strategic learning, there must be tangible evidence of individual and organizational performance to ensure future investments in the concepts of learning. Technology, we should remember, represents the opportunity to provide outcomes through strategic learning that addresses transitions and transformations over a specific life cycle. We saw this opportunity occur in the Ravell case study; the information technology (IT) department used organizational learning. Specifically, individual reflective practices were used to provide measurable outcomes for the organization. In this case, the outcomes related to a specific event, the physical move of the business to a different location. Another lesson we can derive (with hindsight) from the Ravell experience is that learning was converted to strategic benefit for the organization. The concept of converting learning to strategic benefit was pioneered by Pietersen (2002). He established a strategic learning cycle composed of four component processes that he identified with the action verbs learn, focus, align, and execute. These are stages in the learning cycle, as follows: 1. Learn: Conduct a situation analysis to generate insights into the competitive environment and into the realities of the company. 2. Focus: Translate insights into a winning proposition that outlines key priorities for success. 3. Align: Align the organization and energize the people behind the new strategic focus. 4. Execute: Implement strategy and experiment with new concepts. Interpret results and continue the cycle. At Ravell, technology assisted in driving the learning cycle because, by its dynamic nature, it mandated the acceleration of the cycle that Pietersen (2002) describes in his stage strategy of implementation. Thus, Ravell required the process Pietersen outlined to occur within 66 IN F O RM ATI O N T EC HN O L O GY 6 months, and therein established the opportunity to provide ­outcomes. It also altered the culture of the organization (i.e., the evolution in culture was tangible because the transformation was concrete). We see from the Ravell case that technology represents the best opportunity to apply organizational learning techniques because the use of it requires forms of evolutionary-related change. Organizations are continually seeking to improve their operations and competitive advantage through efficiency and effective processes. As I have discussed in previous chapters, today’s businesses are experiencing technological dynamism (defined as causing accelerated and dynamic transformations), and this is due to the advent of technologically driven processes. That is, organizations are experiencing more pressure to change and compete as a result of the accelerations that technology has brought about. Things happen quicker, and more unpredictably, than before. This situation requires organizations to sense the need for change and execute that change. The solution I propose is to tie organizational theory to technological implementation. Another way of defining this issue is to provide an overarching framework that organizes an inquiry into the issues surrounding organizational change. Another dimension of organizational learning is political. Argyris (1993) and Senge (1990) argue that politics gets “in the way of good learning.” In my view, however, the political dimension is very much part of learning. It seems naï ve to assume that politics can be eliminated from the daily commerce of organizational communication. Instead, it needs to be incorporated as a factor in organizational learning theory rather than attempting to disavow or eliminate it, which is not realistic. Ravell also revealed that political factors are simply part of the learning process. Recall that during my initial efforts to create a learning organization there were IT staff members who deliberately refused to cooperate, assuming that they could “outlast” me in my interim tenure as IT director. But politics, of course, is not limited to internal department negotiations; it was also a factor at Ravell with, and among, departments outside IT. These interdepartmental relationships applied especially to line managers, who became essential advocates for establishing and sustaining necessary forms of learning at the organizational level. But, not all line managers responded with the same enthusiasm, and a number of them did not display a sense of authentically caring about facilitating synergies across departments. O r ga niz ati o n a l L e a rnin g T heo rie s 67 The irrepressible existence of politics in social organizations, however, must not in itself deter us from implementing organizational learning practices; it simply means that that we must factor it in as part of the equation. At Ravell, I had to work within the constraints of both internal and external politics. Nevertheless, in the end I was able to accomplish the creation of a learning organization. Another way one might look at the road bumps of politics is to assume that they will temporarily delay or slow the implementation of organizational learning initiatives. But, let us make no mistake about the potentially disruptive nature of politics because, as we know, in its extreme cases of inflexibility, it can be damaging. I have always equated politics with the dilemma of blood cholesterol. We know that there are two types of cholesterol: “good” ­cholesterol and “bad” cholesterol. We all know that bad cholesterol in your blood can cause heart disease, among other life-threatening conditions. However, good cholesterol is essential to the body. My point is simple; the general word politics can have damaging perceptions. When most people discuss the topic of cholesterol, they focus on the bad type, not the good. Such is the same with politics—that is, most individuals discuss the bad type, which often corresponds with their personal experiences. My colleague Professor Lyle Yorks, at Columbia University, often lectures on the importance of politics and its positive aspects for establishing strategic advocacy, defined as the ability to establish personal and functional influence through cultivating alliances through defining opportunities for the adding value to either the top or bottom line (Langer & Yorks, 2013). Thus, politics can add value for individuals by allowing them to initiate and influence relationships and ­conversations with other leaders. This, then, is “good” politics! North American cultural norms account for much of what goes into organizational learning theory, such as individualism, an emphasis on rationality, and the importance of explicit, empirical information. IT, on the other hand, has a broadening, globalizing effect on organizational learning because of the sheer increase in the number of multicultural organizations created through the expansion of global firms. Thus, technology also affects the social aspects of organizational learning, particularly as it relates to the cultural evolution of communities. Furthermore, technology has shown us that what works in one culture may not work in another. Dana Deasy, the former CIO of the 68 IN F O RM ATI O N T EC HN O L O GY Americas region/sector for Siemens AG, experienced the ­difficulties and challenges of introducing technology standards on a global scale. He quickly learned that what worked in North America did not operate with the same expectations in Asia or South America. I discuss Siemens AG as a case study in Chapter 8. It is my contention, however, that technology can be used as an intervention that can actually increase organizational learning. In effect, the implementation of organizational learning has lacked and has needed concrete systemic processes that show results. A solution to this need can be found, as I have found it, in the incorporation of IT itself into the process of true organizational learning. The problem with IT is that we keep trying to simplify it—trying to reduce its complexity. However, dealing with the what, when, and how of working with technology is complex. Organizations need a kind of mechanism that can provide a way to absorb and learn all of the complex pieces of technology. It is my position that organizational change often follows learning, which to some extent should be expected. What controls whether change is radical or evolutionary depends on the basis on which new processes are created (Argyris & Schö n, 1996; Senge, 1990; Swieringa & Wierdsma, 1992). Indeed, at Ravell the learning followed the Argyris and Schö n approach: that radical change occurs when there are major events that support the need for accelerated change. In other words, critical events become catalysts that promote change, through reflection. On the other hand, there can be nonevent-related learning, that is not so much radical in nature, as it is evolutionary. Thus, evolutionary learning is characterized as an ongoing process that slowly establishes the need for change over time. This evolutionary learning process compares to what Senge (1990, p. 15) describes as “learning in wholes as opposed to pieces.” This concept of learning is different from an event-driven perspective, and it supports the natural tendency that groups and organizations have to protect themselves from open confrontation and critique. However, technology provides an interesting variable in this regard. It is generally accepted as an agent of change that must be addressed by the organization. I believe that this agency can be seized as an opportunity to promote such change because it establishes a reason why organizations need to deal with the inevitable transitions brought O r ga niz ati o n a l L e a rnin g T heo rie s 69 about by technology. Furthermore, as Huysman (1999) points out, the history of organizational learning has not often created measurable improvement, particularly because implementing the theories has not always been efficient or effective. Much of the impetus for implementing a new technology, however, is based on the premise that its use will result in such benefits. Therefore, technology provides compelling reasons for why organizational learning is important: to understand how to deal with agents of change, and to provide ongoing changes in the processes that improve competitive advantage. There is another intrinsic issue here. Uses of technology have not always resulted in efficient and effective outcomes, particularly as they relate to a firm’s expected ROI. In fact, IT projects often cost more than expected and tend to be delivered late. Indeed, research performed by the Gartner Group and CIO Magazine (Koch, 1999) reports that 54% of IT projects are late and that 22% are never completed. In May 2009, McGraw reported similar trends, so industry performance has not materially improved. This is certainly a disturbing statistic for a dynamic variable of change that promises outcomes of improved efficiency and effectiveness. The question then is why is this occurring? Many scholars might consider the answer to this question as complex. It is my claim, however, based on my own research, that the lack of organizational learning, both within IT and within other departments, poses, perhaps, the most significant barrier to the success of these projects in terms of timeliness and completion. Langer (2001b) suggests that the inability of IT organizations to understand how to deal with larger communities within the organization and to establish realistic and measurable outcomes are relevant both to many of the core values of organizational learning and to its importance in attaining results. What better opportunity is there to combine the strengths and weaknesses of each of IT and organizational learning? Perhaps what is most interesting—and, in many ways, lacking within the literature on organizational learning—is the actual way individuals learn. To address organizational learning, I believe it is imperative to address the learning styles of individuals within the organization. One fundamental consideration to take into account is that of individual turnover within departments. Thus, methods to measure or understand organizational learning must incorporate the individual; how the individual learns, and what occurs when 70 IN F O RM ATI O N T EC HN O L O GY individuals change positions or leave, as opposed to solely focusing on the event-driven aspect of evolutionary learning. There are two sociological positions about how individual learning occurs. The first suggests that individual action derives from determining influences in the social system, and the other suggests that it emanates from individual action. The former proposition supports the concept that learning occurs at the organizational, or group level, and the latter supports it at the individual level of action and experience. The “system” argument focuses on learning within the organization as a whole and claims that individual action functions within its boundaries. The “individual” argument claims that learning emanates from the individual first and affects the system as a result of outcomes from individual actions. Determining a balance between individual and organizational learning is an issue debated by scholars and an important one that this book must address. Why is this issue relevant to the topic of IT and organizational learning? Simply put, understanding the nature of evolving technologies requires that learning—and subsequent learning outcomes—will be heavily affected by the processes in which it is delivered. Therefore, without understanding the dynamics of how individuals and organizations learn, new technologies may be difficult to assimilate because of a lack of process that can determine how they can be best used in the business. What is most important to recognize is the way in which responsive organizational dynamism (ROD) needs both the system and individual approaches. Huysman (1999) suggests (and I agree) that organizational versus individual belief systems are not mutually exclusive pairs but dualities. In this way, organizational processes are not seen as just top-down or bottom-up affairs, but as accumulations of history, assimilated in organizational memory, which structures and positions the agency or capacity for learning. In a similar way, organizational learning can be seen as occurring through the actions of individuals, even when they are constrained by institutional forces. The strategic integration component of ROD lends itself to the system model of learning to the extent that it almost mandates change— change that, if not addressed, will inevitably affect the competitive advantage of the organization. On the other hand, the cultural assimilation component of ROD is also involved because of its effect on individual behavior. Thus, the ROD model needs to be expanded to O r ga niz ati o n a l L e a rnin g T heo rie s 71 show the relationship between individual and organizational learning as shown in Figure 4.1. An essential challenge to technology comes from the fact that organizations are not sure about how to handle its overall potential. Thus, in a paradoxical way, this quandary provides a springboard to learning by utilizing organizational learning theories and concepts to create new knowledge, by learning from experience, and ultimately by linking technology to learning and performance. This perspective can be promoted from within the organization because chief executives are generally open to investing in learning as long as core business principles are not violated. This position is supported by my research with chief executives that I discussed in Chapter 2. Technology Organizational dynamism Symptoms and implications Acceleration of events that require different infrastructures and organizational processes Requires Strategic integration Cultural assimilation Organization structures (system) Individual actions Renegotiation of relationship Organizational learning techniques Figure 4.1   ROD and organizational learning. 72 IN F O RM ATI O N T EC HN O L O GY Organizational learning can also assist in the adoption of t­echnologies by providing a mechanism to help individuals manage change. This notion is consistent with Aldrich (2001), who observes that many organizations reject technology-driven changes or “pioneering ventures,” which he called competence-destroying ventures because they threaten existing norms and processes. Organizations would do well to understand the value of technology, particularly for those who adopt it early (early adopters), and how it can lead to competitive advantages. Thus, organizations that position themselves to evolve, to learn, and to create new knowledge are better prepared to foster the handling, absorption, and acceptance of technology-driven change than those that are not. Another way to view this ethic is to recognize that organizations need to be “ready” to deal with change— change that is accelerated by technology innovations. Although Aldrich (2001) notes that organizational learning has not been tied to performance and success, I believe it will be the technology revolution that establishes the catalyst that can tie organizational learning to performance. The following sections of this chapter expand on the core concept that the success of ROD is dependent on the uses of organizational learning techniques. In each section, I correlate this concept to many of the organizational learning theories and show how they can be tailored and used to provide important outcomes that assist the promotion of both technological innovation and organizational learning. Learning Organizations Business strategists have realized that the ability of an organization to learn faster, or “better,” than its competitors may indeed be the key to long-term business success (Collis, 1994; Dodgson, 1993; Grant, 1996; Jones, 1975). A learning organization is defined as a form of organization that enables, in an active sense, the learning of its members in such a way that it creates positive outcomes, such as innovation, efficiency, improved alignment with the environment, and competitive advantage. As such, a learning organization is one that acquires knowledge from within. Its evolution, then, is primarily driven by itself without the need for interference from outside forces. In this sense, it is a self-perpetuating and self-evolving system of individual O r ga niz ati o n a l L e a rnin g T heo rie s 73 and organizational transformations integrated into the daily processes of the organization. It should be, in effect, a part of normal organizational behavior. The focus of organizational learning is not so much on the process of learning but more on the conditions that allow successful outcomes to flourish. Learning organization literature draws from organizational learning theory, particularly as it relates to interventions based on outcomes. This provides an alternative to social approaches. In reviewing these descriptions of what a learning organization does, and why it is important, we can begin to see that technology may be one of the few agents that can actually show what learning organizations purport to do. Indeed, Ravell created an evolving population that became capable of dealing with environmental changes brought on by technological innovation. The adaptation of these changes created those positive outcomes and improved efficiencies. Without organizational learning, specifically the creation of a learning organization, many innovations brought about by technology could produce chaos and instability. Organizations generally tend to suffer from, and spend too much time reflecting on, their past dilemmas. However, given the recent phenomenon of rapid changes in technology, organizations can no longer afford the luxury of claiming that there is simply too much else to do to be constantly worrying about technology. Indeed, Lounamaa and March (1987) state that organizations can no longer support the claim that too-frequent changes will inhibit learning. The fact is that such changes must be taken as evolutionary, and as a part of the daily challenges facing any organization. Because a learning organization is one that creates structure and strategies, it is positioned to facilitate the learning of all its members, during the ongoing infiltration of technology-driven agents of change. Boland et al. (1994) show that information systems based on multimedia technologies may enhance the appreciation of diverse interpretations within organizations and, as such, support learning organizations. Since learning organizations are deliberately created to facilitate the learning of their members, understanding the urgency of technological changes can provide the stimulus to support planned learning. Many of the techniques used in the Ravell case study were based on the use of learning organizational techniques, many of which were pioneered by Argyris and Schö n (1996). Their work focuses on using 74 IN F O RM ATI O N T EC HN O L O GY “action science” methods to create and maintain learning organizations. A key component of action science is the use of reflective practices—including what is commonly known among researchers and practitioners as reflection in action and reflection on action. Reflection with action is the term I use as a rubric for these various methods, involving reflection in relation to activity. Reflection has received a number of definitions, from different sources in the literature. Depending on the emphasis, whether on theory or practice, definitions vary from philosophical articulation (Dewey, 1933; Habermas, 1998), to practice-based formulations, such as Kolb’s (1984b) use of reflection in the experiential learning cycle. Specifically, reflection with action carries the resonance of Schö n’s (1983) twin constructs: reflection on action and reflection in action, which emphasize reflection in retrospect, and reflection to determine which actions to take in the present or immediate future, respectively. Dewey (1933) and Hullfish and Smith (1978) also suggest that the use of reflection supports an implied purpose: individuals reflect for a purpose that leads to the processing of a useful outcome. This formulation suggests the possibility of reflection that is future oriented—what we might call “reflection to action.” These are methodological orientations covered by the rubric. Reflective practices are integral to ROD because so many ­technology-based projects are event driven and require individuals to reflect before, during, and after actions. Most important to this process is that these reflections are individually driven and that technology projects tend to accelerate the need for rapid decisions. In other words, there are more dynamic decisions to be made in less time. Without operating in the kind of formation that is a learning organization, IT departments cannot maintain the requisite infrastructure to develop products timely on time and support business units—something that clearly is not happening if we look at the existing lateness of IT projects. With respect to the role of reflection in general, the process can be individual or organizational. While groups can reflect, it is in being reflective that individuals bring about “an orientation to their everyday lives,” according to Moon (1999). “For others reflection comes about when conditions in the learning environment are appropriate” (p. 186). However, IT departments have long suffered from not having the conditions O r ga niz ati o n a l L e a rnin g T heo rie s 75 to support such an individual learning environment. This is why implementing a learning organization is so appealing as a remedy for a chronic problem. Communities of Practice Communities of practice are based on the assumption that learning starts with engagement in social practice and that this practice is the fundamental construct by which individuals learn (Wenger, 1998). Thus, communities of practice are formed to get things done by using a shared way of pursuing interest. For individuals, this means that learning is a way of engaging in, and contributing to, the practices of their communities. For specific communities, on the other hand, it means that learning is a way of refining their distinctive practices and ensuring new generations of members. For entire organizations, it means that learning is an issue of sustaining interconnected communities of practice, which define what an organization knows and contributes to the business. The notion of communities of practice supports the idea that learning is an “inevitable part of participating in social life and practice” (Elkjaer, 1999, p. 75). Communities of practice also include assisting members of the community, with the particular focus on improving their skills. This is also known as situ­ ated learning. Thus, communities of practice are very much a social learning theory, as opposed to one that is based solely on the individual. Communities of practice have been called learning in working, in which learning is an inevitable part of working together in a social setting. Much of this concept implies that learning, in some form or other will occur, and that it is accomplished within a framework of social participation, not solely or simply in the individual mind. In a world that is changing significantly due to technological innovations, we should recognize the need for organizations, communities, and individuals to embrace the complexities of being interconnected at an accelerated pace. There is much that is useful in the theory of communities of practice and that justifies its use in ROD. While so much of learning technology is event driven and individually learned, it would be shortsighted to believe that it is the only way learning can occur in an organization. Furthermore, the enormity and complexity of technology requires a 76 IN F O RM ATI O N T EC HN O L O GY community focus. This would be especially useful within the confines of specific departments that are in need of understanding how to deal with technological dynamism. That is, preparation for using new technologies cannot be accomplished by waiting for an event to occur. Instead, preparation can be accomplished by creating a community that can assess technologies as a part of the normal activities of an organization. Specifically, this means that, through the infrastructure of a community, individuals can determine how they will organize themselves to operate with emerging technologies, what education they will need, and what potential strategic integration they will need to prepare for changes brought on by technology. Action in this context can be viewed as a continuous process, much in the same way that I have presented technology as an ongoing accelerating variable. However, Elkjaer (1999) argues that the continuous process cannot exist without individual interaction. As he states: “Both individual and collective activities are grounded in the past, the present, and the future. Actions and interactions take place between and among group members and should not be viewed merely as the actions and interactions of individuals” (p. 82). Based on this perspective, technology can be handled by the actions (community) and interactions (individuals) of the organization as shown in Figure 4.2. Communities of practice: Social actions of how to deal with technology Allows groups to engage in discourse and examine the ongoing effects on the department/unit, including short/long-term education requirements, skills transfer and development, organizational issues, relationships with other departments and customers Event-driven individualbased learning The individual interacts with others and determines new methods of utilizing technology within his/her specific business objectives. Individuals use reflection as the basis of transformative learning. Figure 4.2   Technology relationship between communities and individuals. O r ga niz ati o n a l L e a rnin g T heo rie s 77 It seems logical that communities of practice provide the mechanism to assist, particularly, with the cultural assimilation component of ROD. Indeed, cultural assimilation targets the behavior of the community, and its need to consider what new organizational structures can better support emerging technologies. I have, in many ways, already established and presented the challenge of what should be called the “community of IT practice” and its need to understand how to restructure to meet the needs of the organization. This is the kind of issue that does not lend itself to event-driven, individual learning, but rather to a more community-based process that can deal with the realignment of departmental relationships. Essentially, communities of IT practice must allow for the continuous evolution of learning based on emergent strategies. Emergent strategies acknowledge unplanned action. Such strategies are defined as patterns that develop in the absence of intentions (Mintzberg & Waters, 1985). Emergent strategies can be used to gather groups that can focus on issues not based on previous plans. These strategies can be thought of as creative approaches to proactive actions. Indeed, a frustrating aspect of technology is its uncertainty. Ideas and concepts borrowed from communities of practice can help departments deal with the evolutionary aspects of technological dynamism. The relationship, then, between communities of practice and technology is significant. Many of the projects involving IT have been traditionally based on informal processes of learning. While there have been a number of attempts to computerize knowledge using various information databases, they have had mixed results. A “structured” approach to creating knowledge reporting is typically difficult to establish and maintain. Many IT departments have utilized International Organization for Standardization (ISO) 9000 concepts. The ISO is a worldwide organization that defines quality processes through formal structures. It attempts to take knowledge-based information and transfer it into specific and documented steps that can be evaluated as they occur. Unfortunately, the ISO 9000 approach, even if realized, is challenging when such knowledge and procedures are undergoing constant and unpredictable change. Technological dynamism creates too many uncertainties to be handled by the extant discourses on how organizations have dealt with change variables. Communities of practice provide an umbrella of discourses that are necessary to deal 78 IN F O RM ATI O N T EC HN O L O GY with ongoing and unpredictable interactions established by emerging technologies. Support for this position is found in the fact that technology requires accumulative collective learning that needs to be tied to social practices; this way, project plans can be based on learning as a participatory act. One of the major advantages of communities of practice is that they can integrate key competencies into the very fabric of the organization (Lesser et al., 2000). The typical disadvantage of IT is that its staff needs to serve multiple organizational structures simultaneously. This requires that priorities be set by the organization. Unfortunately, it is difficult, if not impossible, for IT departments to establish such priorities without engaging in concepts of communities of practice that allow for a more integrated process of negotiation and determination. Much of the process of communities of practice would be initiated by strategic integration and result in many cultural assimilation changes; that is, the process of implementing communities of practice will necessitate changes in cultural behavior and organization processes. As stated, communities-of-practice activities can be initiated via the strategic integration component of ROD. According to Lesser et al. (2000), a knowledge strategy based on communities of practice consists of seven basic steps (Table 4.1). Lesser and Wenger (2000) suggest that communities of practice are heavily reliant on innovation: “Some strategies rely more on innovation than others for their success. … Once dependence on innovation needs have been clarified, you can work to create new knowledge where innovation matters” (p. 8). Indeed, electronic communities of practice are different from physical communities. IT provides another dimension to how technology affects organizational learning. It does so by creating new ways in which communities of practice operate. In the complexity of ways that it affects us, technology has a dichotomous relationship with communities of practice. That is, there is a two-sided issue: (1) the need for communities of practice to implement IT projects and integrate them better into learning organizations, and (2) the expansion of electronic communities of practice invoked by technology, which can, in turn, assist in organizational learning, globally and culturally. The latter issue establishes the fact that a person can now readily be a member of many electronic communities, and in many different O r ga niz ati o n a l L e a rnin g T heo rie s 79 Table 4.1   Extended Seven Steps of Community of Practice Strategy STEP 1 2 3 COMMUNITIES-OF-PRACTICE STEP Understanding strategic knowledge needs: What knowledge is critical to success. Engaging practice domains: People form communities of practice to engage in and identify with. Developing communities: How to help key communities reach their full potential. 4 Working the boundaries: How to link communities to form broader learning systems. 5 Fostering a sense of belonging: How to engage people’s identities and sense of belonging. 6 Running the business: How to integrate communities of practice into running the business of the organization. Applying, assessing, reflecting, renewing: How to deploy knowledge strategy through waves of organizational transformation. 7 TECHNOLOGY EXTENSION Understanding how technology affects strategic knowledge, and what specific technological knowledge is critical to success. Technology identifies groups, based on business-related benefits; requires domains to work together toward measurable results. Technologies have life cycles that require communities to continue; treats the life cycle as a supporter for attaining maturation and full potential. Technology life cycles require new boundaries to be formed. This will link other communities that were previously outside discussions and thus, expand input into technology innovations. The process of integrating communities: IT and other organizational units will create new evolving cultures that foster belonging as well as new social identities. Cultural assimilation provides new organizational structures that are necessary to operate communities of practice and to support new technological innovations. The active process of dealing with multiple new technologies that accelerates the deployment of knowledge strategy. Emerging technologies increase the need for organizational transformation. capacities. Electronic communities are different, in that they can have memberships that are short-lived and transient, forming and re-forming according to interest, particular tasks, or commonality of issue. Communities of practice themselves are utilizing technologies to form multiple and simultaneous relationships. Furthermore, the growth of international communities resulting from ever-expanding global economies has created further complexities and dilemmas. Thus far, I have presented communities of practice as an infrastructure that can foster the development of organizational learning to support the existence of technological dynamism. Most of what I presented has an impact on the cultural assimilation component of ROD—that is, affecting organizational structure and the 80 IN F O RM ATI O N T EC HN O L O GY way things need to be done. However, technology, particularly the strategic integration component of ROD, fosters a more expanded vision of what can represent a community of practice. What does this mean? Communities of practice, through the advent of strategic integration, have expanded to include electronic communities. While technology can provide organizations with vast electronic libraries that end up as storehouses of information, they are only valuable if they are allowed to be shared within the community. Although IT has led many companies to imagine a new world of leveraged knowledge, communities have discovered that just storing information does not provide for effective and efficient use of knowledge. As a result, many companies have created these “electronic” communities so that knowledge can be leveraged, especially across cultures and geographic boundaries. These electronic communities are predictably more dynamic as a result of what technology provides to them. The following are examples of what these communities provide to organizations: • Transcending boundaries and exchanging knowledge with internal and external communities. In this circumstance, communities are extending not only across business units, but also into communities among various clients—as we see developing in advanced e-business strategies. Using the Internet and intranets, communities can foster dynamic integration of the client, an important participant in competitive advantage. However, the expansion of an external community, due to emergent electronics, creates yet another need for the implementation of ROD. • Creating “Internet” or electronic communities as sources of knowledge (Teigland, 2000), particularly for technical-­ oriented employees. These employees are said to form “communities of techies”: technical participants, composed largely of the IT staff, who have accelerated means to come into contact with business-related issues. In the case of Ravell, I created small communities by moving IT staff to allow them to experience the user’s need; this move is directly related to the larger, and expanded, ability of using electronic communities of practice. O r ga niz ati o n a l L e a rnin g T heo rie s 81 • Connecting social and workplace communities through sophisticated networks. This issue links well to the entire expansion of issues surrounding organizational learning, in particular, learning organization formation. It enfolds both the process and the social dialectic issues so important to creating well-balanced communities of practice that deal with organizational-level and individual development. • Integrating teleworkers and non-teleworkers, including the study of gender and cultural differences. The growth of distance workers will most likely increase with the maturation of technological connectivity. Videoconferencing and improved media interaction through expanded broadband will support further developments in virtual workplaces. Gender and culture will continue to become important issues in the expansion of existing models that are currently limited to specific types of workplace issues. Thus, technology allows for the “globalization” of organizational learning needs, especially due to the effects of technological dynamism. • Assisting in computer-mediated communities. Such mediation allows for the management of interaction among communities, of who mediates their communications criteria, and of who is ultimately responsible for the mediation of issues. Mature communities of practice will pursue self-mediation. • Creating “flame” communities. A flame is defined as a lengthy, often personally insulting, debate in an electronic community that provides both positive and negative consequences. Difference can be linked to strengthening the identification of common values within a community but requires organizational maturation that relies more on computerized communication to improve interpersonal and social factors to avoid miscommunications (Franco et al., 2000). • Storing collective knowledge in large-scale libraries and databases. As Einstein stated: “Knowledge is experience. Everything else is just information.” Repositories of information are not knowledge, and they often inhibit organizations from sharing important knowledge building blocks that affect technical, social, managerial, and personal developments that are critical for learning organizations (McDermott, 2000). 82 IN F O RM ATI O N T EC HN O L O GY Ultimately, these communities of practice are forming new social networks, which have established the cornerstone of “global connectivity, virtual communities, and computer-supported cooperative work” (Wellman et al., 2000, p. 179). These social networks are creating new cultural assimilation issues, changing the very nature of the way organizations deal with and use technology to change how knowledge develops and is used via communities of practice. It is not, therefore, that communities of practice are new infrastructure or social forces; rather, the difference is in the way they communicate. Strategic integration forces new networks of communication to occur (the IT effect on communities of practice), and the cultural assimilation component requires communities of practice to focus on how emerging technologies are to be adopted and used within the organization. In sum, what we are finding is that technology creates the need for new organizations that establish communities of practice. New members enter the community and help shape its cognitive schemata. Aldrich (2001) defines cognitive schemata as the “structure that represents organized knowledge about persons, roles, and events” (p. 148). This is a significant construct in that it promotes the importance of a balanced evolutionary behavior among these three areas. Rapid learning, or organizational knowledge, brought on by technological innovations can actually lessen progress because it can produce premature closure (March, 1991). Thus, members emerge out of communities of practice that develop around organizational tasks. They are driven by technological innovation and need constructs to avoid premature closure, as well as ongoing evaluation of perceived versus actual realities. As Brown and Duguid (1991, p. 40) state: The complex of contradictory forces that put an organization’s assumptions and core beliefs in direct conflict with members’ working, learning, and innovating arises from a thorough misunderstanding of what working, learning, and innovating are. As a result of such misunderstandings, many modern processes and technologies, particularly those designed to downskill, threaten the robust working, learning, and innovating communities and practice of the workplace. This perspective can be historically justified. We have seen time and time again how a technology’s original intention is not realized O r ga niz ati o n a l L e a rnin g T heo rie s 83 yet still productive. For instance, many uses of e-mail by individuals were hard to predict. It may be indeed difficult, if not impossible, to predict the eventual impact of a technology on an organization and provide competitive advantages. However, based on evolutionary theories, it may be beneficial to allow technologies to progress from driver‑to‑supporter activity. Specifically, this means that communities of practice can provide the infrastructure to support growth from individual-centered learning; that is, to a less event-driven process that can foster systems thinking, especially at the management levels of the organization. As organizations evolve into what Aldrich (2001) call “bounded entities,” interaction behind boundaries heightens the salience of cultural difference. Aldrich’s analysis of knowledge creation is consistent with what he called an “adaptive organization”—one that is goal oriented and learns from trial and error (individual-based learning)—and a “knowledge development” organization (systemlevel learning). The latter consists of a set of interdependent members who share patterns of belief. Such an organization uses inferential and vicarious learning and generates new knowledge from both experimentation and creativity. Specifically, learning involves sense making and builds on the knowledge development of its members. This becomes critical to ROD, especially in dealing with change driven by technological innovations. The advantages and challenges of virtual teams and communities of practice are expanded in Chapter 7, in which I integrate the discussion with the complexities of outsourcing teams. Learning Preferences and Experiential Learning The previous sections of this chapter focused on organizational learning, particularly two component theories and methods: learning organizations and communities of practice. Within these two methods, I also addressed the approaches to learning; that is, learning that occurs on the individual and the organizational levels. I advocated the position that both system and individual learning need to be part of the equation that allows a firm to attain ROD. Notwithstanding how and when system and individual learning occurs, the investigation of how individuals learn must be a fundamental part of any theory-to-practice effort, such as the present one. Indeed, whether 84 IN F O RM ATI O N T EC HN O L O GY one favors a view of learning as occurring on the organizational or on the individual level (and it occurs on both), we have to recognize that individuals are, ultimately, those who must continue to learn. Dewey (1933) first explored the concepts and values of what he called “experiential learning.” This type of learning comes from the experiences that adults have accrued over the course of their individual lives. These experiences provide rich and valuable forms of “literacy,” which must be recognized as important components to overall learning development. Kolb (1984a) furthered Dewey’s research and developed an instrument that measures individual preferences or styles in which adults learn, and how they respond to day-to-day scenarios and concepts. Kolb’s (1999) Learning Style Inventory (LSI) instrument allows adults to better understand how they learn. It helps them understand how to solve problems, work in teams, manage conflicts, make better career choices, and negotiate personal and professional relationships. Kolb’s research provided a basis for comprehending the different ways in which adults prefer to learn, and it elaborated the distinct advantages of becoming a balanced learner. The instrument schematizes learning preferences and styles into four quadrants: concrete experience , reflective observation , abstract con­ ceptualization , and active experimentation . Adults who prefer to learn through concrete experience are those who need to learn through actual experience, or compare a situation with reality. In reflective observation, adults prefer to learn by observing others, the world around them, and what they read. These individuals excel in group discussions and can effectively reflect on what they see and read. Abstract conceptualization refers to learning, based on the assimilation of facts and information presented, and read. Those who prefer to learn by active experimentation do so through a process of evaluating consequences; they learn by examining the impact of experimental situations. For any individual, these learning styles often work in combinations. After classifying an individual’s responses to questions, Kolb’s instrument determines the nature of these combinations. For example, an individual can have a learning style in which he or she prefers to learn from concrete experiences using reflective observation as opposed to actually “doing” the activity. Figure 4.3 shows Kolb’s model in the form of a “learning wheel.” The wheel graphically shows O r ga niz ati o n a l L e a rnin g T heo rie s 85 Concrete experience Learns from hands-on experience Active experimentation Seeks to find practical uses for ideas and theories Observes concrete situation and reflects on its meaning Reflective observation Interested in abstract ideas and concepts Abstract conceptualization Figure 4.3   Kolb’s Learning Style Inventory. an individual’s learning style inventory, reflecting a person’s strengths and weaknesses with respect to each learning style. Kolb’s research suggests that learners who are less constrained by learning preferences within a distinct style are more balanced and are better learners because they have available to them more dimensions in which to learn. This is a significant concept; it suggests that adults who have strong preferences may not be able to learn when faced with learning environments that do not fit their specific preference. For example, an adult who prefers group discussion and enjoys reflective conversation with others may feel uncomfortable in a less interpersonal, traditional teaching environment. The importance of Kolb’s LSI is that it helps adults become aware that such preferences exist. McCarthy’s (1999) research furthers Kolb’s work by investigating the relationship between learning preferences and curriculum development. Her Learning Type Measure (4Mat) instrument mirrors and extends the Kolb style quadrants by expressing preferences from an individual’s perspective on how to best achieve learning. Another important contribution in McCarthy’s extension of Kolb’s work is the inclusion of brain function considerations, particularly in terms of hemisphericity. McCarthy focuses on the cognitive functions associated with the right hemisphere (perception) and left hemisphere (process) of the brain. Her 4Mat system shows how adults, in each 86 IN F O RM ATI O N T EC HN O L O GY style quadrant, perceive learning with the left hemisphere of the brain and how it is related to processing in the right hemisphere. For example, for Type 1 learners (concrete experience and reflective observation), adults perceive in a concrete way and process in a reflective way. In other words, these adults prefer to learn by actually doing a task and then processing the experience by reflecting on what they experienced during the task. Type 2 learners (reflective observation and abstract conceptualization), however, perceive a task by abstract thinking and process it by developing concepts and theories from their initial ideas. Figure 4.4 shows McCarthy’s rendition of the Kolb learning wheel. The practical claim to make here is that practitioners who acquire an understanding of the concepts of the experiential learning models will be better able to assist individuals in understanding how they learn, how to use their learning preferences during times of M ea ns tio ta ni ap Ad If? W QIV QI Integrate Counsel ng hy ? Refine Examine Extend Image Try Define s Figure 4.4   McCarthy rendition of the Kolb Learning Wheel. t? ep ts ha W nc ill QII Co ? ow H Sk QIII O r ga niz ati o n a l L e a rnin g T heo rie s 87 transition, and the importance of developing other dimensions of learning. The last is particularly useful in developing expertise in learning from individual reflective practices, learning as a group in communities of practice, and participating in both individual transformative learning, and organizational transformations. How, then, does experiential learning operate within the framework of organizational learning and technology? This is shown Figure 4.5 in a combined wheel, called the applied individual learning for tech­ nology model, which creates a conceptual framework for linking the technology life cycle with organizational learning and experiential learning constructs. Figure 4.5 expands the wheel into two other dimensions. The first quadrant (QI) represents the feasibility stage of technology. It requires communities to work together, to ascertain why a particular technology might be attractive to the organization. This quadrant is Action learning a Fe ec gt it n If? en at h m e W pl n– Im io t QIV ea Cr e th ess in c o ng pr gi y ? ga log hy En no –W ch ty te ili sib gy lo o hn QI Communities of practice or tu ni tie s Figure 4.5   Combined applied learning wheel. or pp liz e lif driv e c er yc an le s d su pp ua yo nd ta ? en hat m re W su is– ea lys M na a pt og QII nc e ol QIII Co hn d an ? ng ow ni H an – Pl sign de Ex pl or in gt ec te r Knowledge Transformative management learning 88 IN F O RM ATI O N T EC HN O L O GY best represented by individuals who engage in group discussions to make better connections from their own experiences. The process of determining whether a technology is feasible requires integrated discourse among affected communities, who then can make better decisions, as opposed to centralized or individual and predetermined decisions on whether to use a specific technology. During this phase, individuals need to operate in communities of practice, as the infrastructure with which to support a democratic process of consensus building. The second quadrant (QII) corresponds to measurement and analysis. This operation requires individuals to engage in specific details to determine and conceptualize driver and supporter life cycles analytically. Individuals need to examine the specific details to understand “ what” the technology can do, and to reflect on what it means to them, and their business unit. This analysis is measured with respect to what the ROI will be, and which driver and supporter functions will be used. This process requires transformation theory that allows individuals to perceive and conceptualize which components of the technology can transform the organization. Quadrant 3 (QIII), design and planning, defines the “how” ­component of the technology life cycle. This process involves exploring technology opportunities after measurement and analysis have been completed. The process of determining potential uses for ­technology requires knowledge of the organization. Specifically, it needs the abstract concepts developed in QII to be integrated with tacit knowledge, to then determine possible applications where the technology can succeed. Thus, knowledge management becomes the predominant mechanism for translating what has been conceptualized into something explicit (discussed further in Chapter 5). Quadrant 4 (QIV) represents the implementation-and-creation step in the technology life cycle. It addresses the hypothetical question of “What if?” This process represents the actual implementation of the technology. Individuals need to engage in action learning techniques, particularly those of reflective practices. The implementation step in the technology life cycle is heavily dependent on the individual. Although there are levels of project management, the essential aspects of what goes on inside the project very much relies on the individual performances of the workers. O r ga niz ati o n a l L e a rnin g T heo rie s 89 Social Discourse and the Use of Language The successful implementation of communities of practice fosters heavy dependence on social structures. Indeed, without understanding how social discourse and language behave, creating and sustaining the internal interactions within and among communities of practice are not possible. In taking individuals as the central component for continued learning and change in organizations, it becomes important to work with development theories that can measure and support individual growth and can promote maturation with the promotion of organizational/system thinking (Watkins & Marsick, 1993). Thus, the basis for establishing a technology-driven world requires the inclusion of linear and circular ways of promoting learning. While there is much that we will use from reflective action concepts designed by Argyris and Schö n (1996), it is also crucial to incorporate other theories, such as marginality, transitions, and individual development. Senge (1990) also compares learning organizations with engineering innovation; he calls these engineering innovations “technologies.” However, he also relates innovation to human behavior and distinguishes it as a “discipline.” He defines discipline as “a body of theory and technique that must be studied and mastered to be put into practice, as opposed to an enforced order or means of punishment” (p. 10). A discipline, according to Senge, is a developmental path for acquiring certain skills or competencies. He maintains the concept that certain individuals have an innate “gift”; however, anyone can develop proficiency through practice. To practice a discipline is a lifelong learning process—in contrast to the work of a learning organization. Practicing a discipline is different from emulating a model. This book attempts to bring the arenas of discipline and technology into some form of harmony. What technology offers is a way of addressing the differences that Senge proclaims in his work. Perhaps this is what is so interesting and challenging about attempting to apply and understand the complexities of how technology, as an engineering innovation, affects the learning organization discipline—and thereby creates a new genre of practices. After all, I am not sure that one can master technology as either an engineering component, or a discipline. Technology dynamism and ROD expand the context of the globalizing forces that have added to the complexity of analyzing “the 90 IN F O RM ATI O N T EC HN O L O GY language and symbolic media we employ to describe, represent, interpret, and theorize what we take to be the facticity of organizational life” (Grant et al., 1998, p. 1). ROD needs to create what I call the “language of technology.” How do we then incorporate technology in the process of organizing discourse, or how has technology affected that process? We know that the concept of discourse includes language, talk, stories, and conversations, as well as the very heart of social life, in general. Organizational discourse goes beyond what is just spoken; it includes written text and other informal ways of communication. Unfortunately, the study of discourse is seen as being less valuable than action. Indeed, discourse is seen as a passive activity, while “doing” is seen as supporting more tangible outcomes. However, technology has increased the importance of sensemaking media as a means of constructing and understanding organizational identities. In particular, technology, specifically the use of e-mail, has added to the instability of language, and the ambiguities associated with metaphorical analysis— that is, meaning making from language as it affects organizational behavior. Another way of looking at this issue is to study the metaphor, as well as the discourse, of technology. Technology is actually less understood today, a situation that creates even greater reason than before for understanding its metaphorical status in organizational discourse—particularly with respect to how technology uses are interpreted by communities of practice. This is best shown using the schema of Grant et al. of the relationship between content and activity and how, through identity, skills, and emotion, it leads to action (Figure 4.6). To best understand Figure 4.4 and its application to technology, it is necessary to understand the links between talk and action. It is the activity and content of conversations that discursively produce identities, skills, and emotions, which in turn lead to action. Talk, in respect to conversation and content, implies both oral and written forms of communications, discourse, and language. The written aspect can obviously include technologically fostered communications over the Internet. It is then important to examine the unique conditions that technology brings to talk and its corresponding actions. O r ga niz ati o n a l L e a rnin g T heo rie s Skills Conversational activity Identity Conversational content 91 Action Emotions Figure 4.6   Grant’s schema— relationship between content and activity. Identity Individual identities are established in collaborations on a team, or in being a member of some business committee. Much of the theory of identity development is related to how individuals see themselves, particularly within the community in which they operate. Thus, how active or inactive we are within our communities, shapes how we see ourselves and how we deal with conversational activity and content. Empowerment is also an important part of identity. Indeed, being excluded or unsupported within a community establishes a different identity from other members of the group and often leads to marginality (Schlossberg, 1989). Identities are not only individual but also collective, which to a large extent contributes to cultures of practice within organizational factions. It is through common membership that a collective identity can emerge. Identity with the group is critical during discussions regarding emerging technologies and determining how they affect the organization. The empowerment of individuals, and the creation of a collective identity, are therefore important in fostering timely actions that have a consensus among the involved community. 92 IN F O RM ATI O N T EC HN O L O GY Skills According to Hardy et al. (1998, p. 71), conversations are “arenas in which particular skills are invested with meaning.” Watson (1995) suggests that conversations not only help individuals acquire “technical skills” but also help develop other skills, such as being persuasive. Conversations that are about technology can often be skewed toward the recognition of those individuals who are most “technologically talented.” This can be a problem when discourse is limited to who has the best “credentials” and can often lead to the undervaluing of social production of valued skills, which can affect decisions that lead to actions. Emotion Given that technology is viewed as a logical and rational field, the application of emotion is not often considered a factor of action. Fineman (1996) defines emotion as “personal displays of affected, or ‘moved’ and ‘agitated’ states—such as joy, love, fear, anger, sadness, shame, embarrassment,”—and points out that these states are socially constructed phenomena. There is a positive contribution from emotional energy as well as a negative one. The consideration of positive emotion in the organizational context is important because it drives action (Hardy et al., 1998). Indeed, action is more emotion than rational calculation. Unfortunately, the study of emotions often focuses on its negative aspects. Emotion, however, is an important part of how action is established and carried out, and therefore warrants attention in ROD. Identity, skills, and emotion are important factors in how talk actually leads to action. Theories that foster discourse, and its use in organizations, on the other hand, are built on linear paths of talk and action. That is, talk can lead to action in a number of predefined paths. Indeed, talk is typically viewed as “cheap” without action or, as is often said, “action is valued,” or “action speaks louder than words.” Talk, from this perspective, constitutes the dynamism of what must occur with action science, communities of practice, transformative learning, and, eventually, knowledge creation and management. Action, by contrast, can be viewed as the measurable outcomes that have been O r ga niz ati o n a l L e a rnin g T heo rie s 93 eluding organizational learning scholars. However, not all actions lead to measurable outcomes. Marshak (1998) established three types of talk that lead to action: tool-talk , frame-talk , and mythopoetic-talk : 1. Tool-talk includes “instrumental communities required to: discuss, conclude, act, and evaluate outcomes” (p. 82). What is most important in its application is that tool-talk be used to deal with specific issues for an identified purpose. 2. Frame-talk focuses on interpretation to evaluate the meanings of talk. Using frame-talk results in enabling implicit and explicit assessments, which include symbolic, conscious, preconscious, and contextually subjective dimensions. 3. Mythopoetic-talk communicates ideogenic ideas and images (i.e., myths and cosmologies) that can be used to communicate the nature of how to apply tool-talk and frame-talk within the particular culture or society. This type of talk allows for concepts of intuition and ideas for concrete application. Furthermore, it has been shown that organizational members experience a difficult and ambiguous relationship, between discourse that makes sense, and non-sense—what is also known as “the struggle with sense” (Grant et al., 1998). There are two parts that comprise non-sense: The first is in the difficulties that individuals experience in understanding why things occur in organizations, particularly when their actions “make no sense.” Much of this difficulty can be correlated with political issues that create “nonlearning” organizations. However, the second condition of non-sense is more applicable, and more important, to the study of ROD than the first—that is, nonsense associated with acceleration in the organizational change process. This area comes from the taken-for-granted assumptions about the realities of how the organization operates, as opposed to how it can operate. Studies performed by Wallemacq and Sims (1998) provide examples of how organizational interventions can decompose stories about non-sense and replace them with new stories that better address a new situation and can make sense of why change is needed. This phenomenon is critical to changes established, or responded to, by the advent of new technologies. Indeed, technology has many nonsensical or false generalizations regarding how long it takes to i­mplement a product, what might be the expected outcomes, and so on. Given 94 IN F O RM ATI O N T EC HN O L O GY the need for ROD—due to the advent of technology—there is a concomitant need to reexamine “old stories” so that the necessary change agents can be assessed and put into practice. Ultimately, the challenge set forth by Wallemacq and Sims is especially relevant, and critical, since the very definition of ROD suggests that communities need to accelerate the creation of new stories—stories that will occur at unpredictable intervals. Thus, the link between discourse, organizational learning, and technology is critical to providing ways in which to deal with individuals and organizations facing the challenge of changing and evolving. Grant’s (1996) research shows that sense making using media and stories provided effective ways of constructing and understanding organizational identities. Technology affects discourse in a similar way that it affects communities of practice; that is, it is a variable that affects the way discourse is used for organizational evolution. It also provides new vehicles on how such discourse can occur. However, it is important not to limit discourse analysis to merely being about “texts,” emotion, stories, or conversations in organizations. Discourse analysis examines “the constructing, situating, facilitating, and communicating of diverse cultural, instrumental, political, and socio-economic parameters of ‘organizational being’” (Grant, 1996, p. 12). Hence, discourse is the essential component of every organizational learning effort. Technology accelerates the need for such discourse, and language, in becoming a more important part of the learning maturation process, especially in relation to “system” thinking and learning. I propose then, as part of a move toward ROD, that discourse theories must be integrated with technological innovation and be part of the maturation in technology and in organizational learning. The overarching question is how to apply these theories of discourse and language to learning within the ROD framework and paradigm. First, let us consider the containers of types of talk discussed by Marshak (1998) as shown in Figure 4.7. These types of talk can be mapped onto the technology wheel, so that the most appropriate oral and written behaviors can be set forth within each quadrant, and development life cycle, as shown in Figure 4.8. Mythopoetic-talk is most appropriate in Quadrant 1 (QI), where the fundamental ideas and issues can be discussed in communities of practice. These technological ideas and concepts, deemed feasible, are 95 O r ga niz ati o n a l L e a rnin g T heo rie s Mythopoetic-talk: Ideogenic Frame-talk: Interpretive Tool-talk: Instrumental Figure 4.7   Marshak’s type of talk containers. Im pl em e a nt tio f? Fe a tI ha W n– QIV ili ty QI Tool-talk: Discuss-decide: Knowledge management Frame-talk: Transformative ni an Pl Tool-talk: Doing using reflective practices Mythopoetictalk: Ground ideas using communities of practice ng QIII sib d an de sig ? ow H n– ea M t? d an s aly an W is– m re su hy ? ha QII t en –W Figure 4.8   Marshak’s model mapped to the technology learning wheel. then analyzed through frame-talk, by which the technology can be evaluated in terms of how it meets the fundamental premises established in QI. Frame-talk also reinforces the conceptual legitimacy of how technology will transform the organization while providing appropriate ROI. Tool-talk represents the process of identifying applications and actually implementing them. For this reason, tooltalk exists in both QIII and QIV. The former quadrant represents 96 IN F O RM ATI O N T EC HN O L O GY the discussion-to-decision portion, and the latter represents the actual doing and completion of the project itself. In QIII, table-talk requires knowledge management to transition technology concepts into real options. QIV transforms these real options into actual projects, in which, reflecting on actual practices during implementation, provides an opportunity for individual- and organizational-level learning. Marshak’s (1998) concept of containers and cycles of talk and action are adapted and integrated with cyclical and linear maturity models of learning. However, discourse and language must be linked to performance, which is why it needs to be part of the discourse and language-learning wheel. By integrating discourse and language into the wheel, individual and group activities can use discourse and language as part of ref lective practices to create an environment that can foster action that leads to measurable outcomes. This process, as explained throughout this book, is of paramount importance in understanding how discourse operates with ROD in the information age. Linear Development in Learning Approaches Focusing only on the role of the individual in the company is an incomplete approach to formulating an effective learning program. There is another dimension to consider that is based on learning maturation. That is, where in the life cycle of learning are the individuals and the organization? The best explanation of this concept is the learning maturation experience at Ravell. During my initial consultation at Ravell, the organization was at a very early stage of organizational learning. This was evidenced by the dependence of the organization on eventdriven and individual reflective practice learning. Technology acted as an accelerator of learning—it required IT to design a new network during the relocation of the company. Specifically, the acceleration, operationalized by a physical move, required IT to establish new relationships with line management. The initial case study concluded that there was a cultural change as a result of these new relationships— cultural assimilation started to occur using organizational learning techniques, specifically reflective practices. After I left Ravell, another phase in the evolution of the company took place. A new IT director was hired in my stead, who attempted O r ga niz ati o n a l L e a rnin g T heo rie s 97 to reinstate the old culture: centralized infrastructure, stated operational boundaries, and separations that mandated anti-learning organizational behaviors. After six months, the line managers, faced with having to revert back to a former operating culture, revolted and demanded the removal of the IT director. This outcome, regrettable as it may be, is critical in proving the conclusion of the original study that the culture at Ravell had indeed evolved from its state, at the time of my arrival. The following are two concrete examples that support this notion: 1. The attempt of the new IT director to “roll back” the process to a former cultural state was unsuccessful, showing that a new evolving culture had indeed occurred. 2. Line managers came together from the established learning organization to deliver a concerted message to the executive team. Much of their learning had now shifted to a social organization level that was based less on events and was more holistic with respect to the goals and objectives of the organization. Thus, we see a shift from an individual-based learning process to one that is based more on the social and organizational issues to stimulate transformation. This transformation in learning method occurred within the same management team, suggesting that changes in learning do occur over time and from experience. Another way of viewing the phenomenon is to see Ravell as reaching the next level of organizational learning or maturation with learning. Consistent with the conclusion of the original study, technology served to accelerate the process of change or accelerate the maturation process of organizational learning. Another phase (Phase II) of Ravell transpired after I returned to the company. I determined at that time that the IT department needed to be integrated with another technology-based part of the business—the unit responsible for media and engineering services (as opposed to IT). While I had suggested this combination eight months earlier, the organization had not reached the learning maturation to understand why such a combination was beneficial. Much of the reason it did not occur earlier, can also be attributed to the organization’s inability to manage ROD, which, if implemented, 98 IN F O RM ATI O N T EC HN O L O GY would have made the integration more obvious. The initial Ravell study served to bring forth the challenges of cultural assimilation, to the extent that the organization needed to reorganize itself and change its behavior. In phase II, the learning process matured by accelerating the need for structural change in the actual reporting processes of IT. A year later, yet another learning maturation phase (phase III) occurred. In Ravell, Phase III, the next stage of learning maturation, allowed the firm to better manage ROD. After completing the merger of the two technically related business units discussed (phase II), it became necessary to move a core database department completely out of the combined technology department, and to integrate it with a business unit. The reason for this change was compelling and brought to light a shortfall in my conclusions from the initial study. It appears that as organizational learning matures within ROD, there is an increasing need to educate the executive management team of the organization. This was not the case during the early stages of the case study. The limitation of my work, then, was that I predominantly interfaced with line management and neglected to include executives in the learning. During that time, results were encouraging, so there was little reason for me to include executives in event-driven issues, as discussed. Unfortunately, lacking their participation fostered a disconnection with the strategic integration component of ROD. Not participating in ROD created executive ignorance of the importance that IT had on the strategy of the business. Their lack of knowledge resulted in chronic problems with understanding the relationship and value of IT on the business units of the organization. This shortcoming resulted in continued conflicts over investments in the IT organization. It ultimately left IT with the inability to defend many of its cost requirements. As stated, during times of economic downturns, firms tend to reduce support organizations. In other words, executive management did not understand the driver component of IT. After the move of the cohort of database developers to a formal business line unit, the driver components of the group provided the dialogue and support necessary to educate executives. However, this education did not occur based on events, but rather, on using the social and group dynamics of organizational learning. We see O r ga niz ati o n a l L e a rnin g T heo rie s 99 here another aspect of how organizational and individual learning methods work together, but evolve in a specific way, as summarized in Table 4.2. Another way of representing the relationship between individual and organizational learning over time is to chart a “maturity” arc to illustrate the evolutionary life cycle of technology and organizational learning. I call this arc the ROD arc. The arc is designed to assess individual development in four distinct sectors of ROD, each in relation to five developmental stages of organizational learning. Thus, each sector of ROD can be measured in a linear and integrated way. Each stage in the course of the learning development Table 4.2   Analysis of Ravell’s Maturation with Technology LEARNING PHASE I PHASE II Type of learning Individual reflective practices used to establish operations and line management. Line managers defend new culture and participate in less event-driven learning. Learning outcomes Early stage of learning organization development. Responsive organizational dynamism: cultural assimilation. Established new culture; no change in organizational structure. Responsive organizational dynamism: Strategic integration. Limited integration due to lack of executive involvement. Combination of event-driven and early-stage social organizational learning formation. Cultural assimilation stability with existing structures; early phase of IT organizational integration with similar groups. Early stages of value/needs based on similar strategic alignment. PHASE III Movement away from holistic formation of IT, into separate driver and supporter attributes. Learning approaches are integrated using both individual and organizational methods, and are based on functionality as opposed to being organizationally specific. Movement toward socialbased organizational decision making, relative to the different uses of technology. Mature use of cultural assimilation, based on IT behaviors (drivers and supporters). Social structures emphasize strategic integration based on business needs. 10 0 IN F O RM ATI O N T EC HN O L O GY of an organization reflects an underlying principle that guides the process of ROD norms and behaviors; specifically, it guides organizations in how they view and use the ROD components available to them. The arc is a classificatory scheme that identifies progressive stages in the assimilated uses of ROD. It reflects the perspective—­ paralleling Knefelkamp’s (1999) research—that individuals in an organization are able to move through complex levels of thinking, and to develop independence of thought and judgment, as their careers progress within the management structures available to them. Indeed, assimilation to learning at specific levels of operations and management are not necessarily an achievable end but one that fits into the psychological perspective of what productive employees can be taught about ROD adaptability. Figure 4.9 illustrates the two axes of the arc. The profile of an individual who assimilates the norms of ROD can be characterized in five developmental stages (vertical axis) along four sectors of literacy (horizontal axis). The arc characterizes an individual at a specific level in the organization. At each level, the arc identifies individual maturity with ROD, specifically strategic integration, cultural assimilation, and the type of learning process (i.e., individual vs. organizational). The arc shows how each tier integrates with another, what types of organizational learning theory best apply, and who needs to be the primary driver within the organization. Thus, the arc provides an organizational schema for how each conceptual component of organizational learning applies to each sector of ROD. It also identifies and constructs a path for those individuals who want to advance in organizational rank; that is, it can be used to ascertain an individual’s ability to cope with ROD requirements as a precursor for advancement in management. Each position within a sector, or cell, represents a specific stage of development within ROD. Each cell contains specific definitions that can be used to identify developmental stages of ROD and organizational learning maturation. Figure 4.10 represents the ROD arc with its cell definitions. The five stages of the arc are outlined as follows: Operational knowledge Figure 4.9   Reflective organizational dynamism arc model. Management level Organizational learning constructs Cultural assimilation Strategic integration Sectors of responsive organizational dynamism Department/unit view as other Integrated disposition Stable operations Organizational leadership O r ga niz ati o n a l L e a rnin g T heo rie s 101 Individual-based reflective practice Operations Organizational learning constructs Management level Figure 4.10   Responsive organizational dynamism arc. Operation and middle management Small group-based reflective practices Changes brought forth by technology need to be assimilated into departments and are dependent on how others participate View that technology can and will affect the way the organization operates and that it can affect roles and responsibilities Cultural assimilation Department/unit view as other Individual beliefs of Operations personnel strategic impact are understand that incomplete; individual technology has an needs to incorporate impact on strategic other views within the development, department or business particularly on existing unit processes Operational knowledge Strategic integration Sector variable Middle management Interactive with both individual and middle management using communities of practice Understands need for organizational changes; different cultural behavior new structures are seen as viable solutions Recognition that individual and department views must be integrated to be complete and strategically productive for the department/unit Integrated disposition Middle management and executive Interactive between middle management and executives using social discourse methods to promote transformation Organizational changes are completed and in operation; existence of new or modified employee positions Changes made to processes at the department/unit level formally incorporate emerging technologies Stable operations Executive Organizational learning at executive level using knowledge management Department-level organizational changes and cultural evolution are integrated with organization-wide functions and cultures Departmental strategies are propagated and integrated at organization level Organizational leadership 10 2 IN F O RM ATI O N T EC HN O L O GY O r ga niz ati o n a l L e a rnin g T heo rie s 10 3 1. Operational knowledge: Represents the capacity to learn, conceptualize, and articulate key issues relating to how technology can have an impact on existing processes and organizational structure. Organizational learning is accomplished through individual learning actions, particularly reflective practices. This stage typically is the focus for operations personnel, who are usually focused on their personal perspectives of how technology affects their daily activities. 2. Department/unit view as other : Indicates the ability to integrate points of view about using technology from diverse individuals within the department or business unit. Using these new perspectives, the individual is in position to augment his or her understanding of technology and relate it to others within the unit. Operations personnel participate in smallgroup learning activities, using reflective practices. Lower levels of middle managers participate in organizational learning that is in transition, from purely individual to group-level thinking. 3. Integrated disposition : Recognizes that individual and departmental views on using technology need to be integrated to form effective business unit objectives. Understanding that organizational and cultural shifts need to include all member perspectives, before formulating departmental decisions, organizational learning is integrated with middle managers, using communities of practice at the department level. 4. Stable operations : Develops in relation to competence in sectors of ROD appropriate for performing job duties for emerging technologies, not merely adequately, but competitively, with peers and higher-ranking employees in the organization. Organizational learning occurs at the organizational level and uses forms of social discourse to support organizational transformation. 5. Organizational leadership : Ability to apply sectors of ROD to multiple aspects of the organization. Department concepts can be propagated to organizational levels, including strategic and cultural shifts, relating to technology opportunities. Organizational learning occurs using methods of knowledge management with executive support. Individuals use their 10 4 IN F O RM ATI O N T EC HN O L O GY technology knowledge for creative purposes. They are willing to take risks using critical discernment and what Heath (1968) calls “freed” decision making. The ROD arc addresses both individual and organizational learning. There are aspects of Senge’s (1990) “organizational” approach that are important and applicable to this model. I have mentioned its appropriateness in regard to the level of the manager—­suggesting that the more senior manager is better positioned to deal with nonevent learning practices. However, there is yet another dimension within each stage of matured learning. This dimension pertains to timing. The timing dimension focuses on a multiple-phase approach to maturing individual and organizational learning approaches. The multiple phasing of this approach suggests a maturing or evolutionary learning cycle that occurs over time, in which individual learning fosters the need and the acceptance of organizational learning methods. This process can be applied within multiple tiers of management and across different business units. The ROD arc can also be integrated with the applied individual learning wheel. The combined models show the individual’s cycle of learning along a path of maturation. This can be graphically shown to reflect how the wheel turns and moves along the continuum of the arc (Figure 4.11). Figure 4.11 shows that an experienced technology learner can maximize learning by utilizing all four quadrants in each of the maturity stages. It should be clear that certain quadrants of individual learning are more important to specific stages on the arc. However, movement through the arc is usually not symmetrical; that is, individuals do not move equally from stage to stage, within the dimensions of learning (Langer, 2003). This integrated and multiphase method uses the applied individual learning wheel with the arc. At each stage of the arc, an individual will need to draw on the different types of learning that are available in the learning wheel. Figure 4.12 provides an example of this concept, which Knefelkamp calls “multiple and simultaneous” (1999), meaning that learning can take on multiple meanings across different sectors simultaneously. O r ga niz ati o n a l L e a rnin g T heo rie s ec gt in f? t tI en ha m e W pl n– Im tio a QIV e Cr Action learning Fe a QI sib ili ty e th ess in oc ng pr gi y ga log En no ch te gy lo o hn –W hy ? Communities of practice nal ratio O p e ledg e know or su pp ze lif driv e c er yc an les d or tu tu pp ni tie unit ent/ artm other p e D as view ep yo nc og nd ta ? en hat m re W su sis– a e y M nal a s Co ol QII ali d an ? ng ow ni H an – Pl sign de hn QIII te r Knowledge Transformative management learning Ex pl or in gt ec 10 5 rated Integ ition s o disp le Stab ns io t a oper l tiona niza ip a g r O ersh lead ith ity w atur m m f ls o ynamis leve d ased ational e r c In niz orga Figure 4.11   ROD arc with applied individual learning wheel. Figure 4.12 shows that the dimension variables are not necessarily parallel in their linear maturation. This phenomenon is not unusual with linear models, and in fact, is quite normal. However, it also reflects the complexity of how variables mature, and the importance of having the capability and infrastructure to determine how to measure such levels of maturation within dimensions. There are both qualitative and quantitative approaches to this analysis. Qualitative approaches typically include interviewing, ethnographic-type experiences over Figure 4.12   Sample ROD arc. Management level Organizational learning constructs Cultural assimilation Strategic integration Dimension variable Operational knowledge Department/unit view as other Integrated disposition Stable operations Organizational leadership 10 6 IN F O RM ATI O N T EC HN O L O GY O r ga niz ati o n a l L e a rnin g T heo rie s 10 7 some predetermined time period, individual journals or diaries, group meetings, and focus groups. Quantitative measures involve the creation of survey-type measures; they are based on statistical results from answering questions that identify the level of maturation of the individual. The learning models that I elaborate in this chapter are suggestive of the rich complexities surrounding the learning process for individuals, groups, and entire organizations. This chapter establishes a procedure for applying these learning models to technology-specific situations. It demonstrates how to use different phases of the learning process to further mature the ability of an organization to integrate technology strategically and culturally.
Purchase answer to see full attachment