Oper Excell 3

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4 oRg aniz aTional le aRning TheoRies anD TeChnology

Introduction

The purpose of this chapter is to provide readers with an under- standing 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 organiza- tional 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 organiza- tional 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 indi- viduals, 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 suc- ceeded or failed, discarding, of course, processes that have failed.

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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 empha- sizes 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 experi- mentation and creativity. It is the knowledge development perspec- tive 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 organiza- tion 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 con- cept 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 per- formance expect changes that will support new outcomes. The study of organizational learning needs an overarching framework under which

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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 the- ory. It lacks a method of producing measurable results that executives can link to performance. While scholars seek outcomes through stra- tegic learning, there must be tangible evidence of individual and orga- nizational performance to ensure future investments in the concepts of learning. Technology, we should remember, represents the oppor- tunity 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 learn- ing. Specifically, individual reflective practices were used to provide measurable outcomes for the organization. In this case, the out- comes 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 out- lines 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 con- cepts. 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

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6 months, and therein established the opportunity to provide outcomes. It also altered the culture of the organization (i.e., the evolution in cul- ture 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 competi- tive 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 orga- nizational theory to technological implementation. Another way of defining this issue is to provide an overarching framework that orga- nizes 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 elimi- nated from the daily commerce of organizational communication. Instead, it needs to be incorporated as a factor in organizational learn- ing 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 rela- tionships 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.

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The irrepressible existence of politics in social organizations, however, must not in itself deter us from implementing organizational learn- ing 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 dis- cuss the bad type, which often corresponds with their personal expe- riences. 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 per- sonal 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 indi- viduals 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 empha- sis on rationality, and the importance of explicit, empirical informa- tion. 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 commu- nities. Furthermore, technology has shown us that what works in one culture may not work in another. Dana Deasy, the former CIO of the

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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 oper- ate 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 prob- lem 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 com- plex pieces of technology.

It is my position that organizational change often follows learn- ing, 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 fol- lowed 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 non- event-related learning, that is not so much radical in nature, as it is evolutionary. Thus, evolutionary learning is characterized as an ongo- ing 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 perspec- tive, and it supports the natural tendency that groups and organiza- tions 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

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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 implement- ing 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 com- pleted. In May 2009, McGraw reported similar trends, so industry performance has not materially improved. This is certainly a disturb- ing 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 ques- tion 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

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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 lat- ter 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 boundar- ies. 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 impor- tant 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 technolo- gies 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 organi- zations 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 assim- ilation component of ROD is also involved because of its effect on individual behavior. Thus, the ROD model needs to be expanded to

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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.

Organizational dynamism

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

Symptoms and implications

Technology

Figure 4.1 ROD and organizational learning.

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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 “pio- neering 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 com- petitive 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 revolu- tion 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 pro- motion 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 mem- bers in such a way that it creates positive outcomes, such as innovation, efficiency, improved alignment with the environment, and competi- tive 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

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and organizational transformations integrated into the daily processes of the organization. It should be, in effect, a part of normal organiza- tional behavior. The focus of organizational learning is not so much on the process of learning but more on the conditions that allow suc- cessful outcomes to flourish. Learning organization literature draws from organizational learning theory, particularly as it relates to inter- ventions 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 organi- zations 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 organi- zation, 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, orga- nizations can no longer afford the luxury of claiming that there is simply too much else to do to be constantly worrying about technol- ogy. 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 technologi- cal 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

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“action science” methods to create and maintain learning organiza- tions. A key component of action science is the use of reflective prac- tices—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, defini- tions 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 reflec- tion 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 sup- ports 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 individu- als 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 infra- structure 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 reflec- tion 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

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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 com- munities 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 participat- ing 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 indi- vidual. 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 technol- ogy 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

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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 technolo- gies 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 commu- nity, 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 technol- ogy 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 organiza- tion 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

�e 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.

Event-driven individual- based learning

Figure 4.2 Technology relationship between communities and individuals.

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It seems logical that communities of practice provide the mecha- nism 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 struc- tures 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 con- tinuous 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 tech- nology is significant. Many of the projects involving IT have been tra- ditionally 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 estab- lish 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 for- mal 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 cre- ates 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

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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 prac- tices; 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 organi- zation (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 inno- vation than others for their success. … Once dependence on innova- tion 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 dichoto- mous relationship with communities of practice. That is, there is a two-sided issue: (1) the need for communities of practice to imple- ment IT projects and integrate them better into learning organiza- tions, 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

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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 infra- structure that can foster the development of organizational learn- ing to support the existence of technological dynamism. Most of what I presented has an impact on the cultural assimilation com- ponent of ROD—that is, affecting organizational structure and the

Table 4.1 Extended Seven Steps of Community of Practice Strategy

STEP COMMUNITIES-OF-PRACTICE STEP TECHNOLOGY EXTENSION 1 Understanding strategic knowledge

needs: What knowledge is critical to success.

Understanding how technology affects strategic knowledge, and what specific technological knowledge is critical to success.

2 Engaging practice domains: People form communities of practice to engage in and identify with.

Technology identifies groups, based on business-related benefits; requires domains to work together toward measurable results.

3 Developing communities: How to help key communities reach their full potential.

Technologies have life cycles that require communities to continue; treats the life cycle as a supporter for attaining maturation and full potential.

4 Working the boundaries: How to link communities to form broader learning systems.

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.

5 Fostering a sense of belonging: How to engage people’s identities and sense of belonging.

The process of integrating communities: IT and other organizational units will create new evolving cultures that foster belonging as well as new social identities.

6 Running the business: How to integrate communities of practice into running the business of the organization.

Cultural assimilation provides new organizational structures that are necessary to operate communities of practice and to support new technological innovations.

7 Applying, assessing, reflecting, renewing: How to deploy knowledge strategy through waves of organizational transformation.

The active process of dealing with multiple new technologies that accelerates the deployment of knowledge strategy. Emerging technologies increase the need for organizational transformation.

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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 strate- gic 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 knowl- edge. 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 pro- vides to them. The following are examples of what these communi- ties 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 inte- gration of the client, an important participant in competitive advantage. However, the expansion of an external commu- nity, 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 “com- munities of techies”: technical participants, composed largely of the IT staff, who have accelerated means to come into con- tact with business-related issues. In the case of Ravell, I cre- ated 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.

81orGAnIz AtIonAl le ArnInG theorIes

• 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 cre- ating 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 dis- tance 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 cul- ture will continue to become important issues in the expan- sion 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 media- tion allows for the management of interaction among com- munities, 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 commu- nity that provides both positive and negative consequences. Difference can be linked to strengthening the identification of common values within a community but requires organiza- tional maturation that relies more on computerized commu- nication 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 informa- tion 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).

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Ultimately, these communities of practice are forming new social networks, which have established the cornerstone of “global connectiv- ity, 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 inte- gration 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 technolo- gies 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 repre- sents 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 learn- ing, or organizational knowledge, brought on by technological inno- vations 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 clo- sure, 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 assump- tions and core beliefs in direct conflict with members’ working, learn- ing, and innovating arises from a thorough misunderstanding of what working, learning, and innovating are. As a result of such misunder- standings, many modern processes and technologies, particularly those designed to downskill, threaten the robust working, learning, and inno- vating 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

8 3orGAnIz AtIonAl le ArnInG theorIes

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 communi- ties 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 cre- ation 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 (system- level 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 experi- mentation and creativity. Specifically, learning involves sense mak- ing 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 vir- tual 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 learn- ing, particularly two component theories and methods: learning organizations and communities of practice. Within these two meth- ods, 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 investi- gation of how individuals learn must be a fundamental part of any theory-to-practice effort, such as the present one. Indeed, whether

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one favors a view of learning as occurring on the organizational or on the individual level (and it occurs on both), we have to recog- nize 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 bal- anced 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 assimila- tion of facts and information presented, and read. Those who prefer to learn by active experimentation do so through a process of evaluat- ing consequences; they learn by examining the impact of experimen- tal 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

8 5orGAnIz AtIonAl le ArnInG theorIes

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 interper- sonal, 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 devel- opment. 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 asso- ciated with the right hemisphere (perception) and left hemisphere (process) of the brain. Her 4Mat system shows how adults, in each

Concrete experience

Abstract conceptualization

Learns from hands-on

experience

Observes concrete

situation and reflects on its

meaning

Seeks to find practical uses for ideas and

theories

Interested in abstract ideas and concepts

Active experimentation

Reflective observation

Figure 4.3 Kolb’s Learning Style Inventory.

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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 reflec- tive 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 mod- els will be better able to assist individuals in understanding how they learn, how to use their learning preferences during times of

M eaning

Co nc

ep tsW

ha t?

Skills

How?

W hy?

Ad ap

tat ion

s

If?

Integrate QIV

QIII

QI

QII Try Define

Refine Examine

ImageExtend

Counsel

Figure 4.4 McCarthy rendition of the Kolb Learning Wheel.

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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

Engaging in the

technology process

Co nc

ep tu

ali ze

dr ive

r a nd

su pp

or ter

lif e c

yc lesM

ea su

rem en

t a nd

an aly

sis –W

ha t?

Exploring technology opportunities

Planning and

design–How?

Feasibility–W hy?

Im ple

me nti

ng te

ch no

log y

Cr ea

tio n–

W ha

t I f?

Action learning

QIV

QIII

QI

QII

Knowledge management

Transformative learning

Communities of practice

Figure 4.5 Combined applied learning wheel.

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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 infra- structure with which to support a democratic process of consensus building.

The second quadrant (QII) corresponds to measurement and analy- sis. This operation requires individuals to engage in specific details to determine and conceptualize driver and supporter life cycles ana- lytically. Individuals need to examine the specific details to under- stand “ 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 explor- ing 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 conceptual- ized 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 ques- tion of “What if?” This process represents the actual implementation of the technology. Individuals need to engage in action learning tech- niques, particularly those of reflective practices. The implementation step in the technology life cycle is heavily dependent on the indi- vidual. 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.

8 9orGAnIz AtIonAl le ArnInG theorIes

Social Discourse and the Use of Language

The successful implementation of communities of practice fosters heavy dependence on social structures. Indeed, without understand- ing 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 impor- tant 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 inclu- sion 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 theo- ries, such as marginality, transitions, and individual development.

Senge (1990) also compares learning organizations with engineer- ing innovation; he calls these engineering innovations “technologies.” However, he also relates innovation to human behavior and distin- guishes it as a “discipline.” He defines discipline as “a body of theory and technique that must be studied and mastered to be put into prac- tice, as opposed to an enforced order or means of punishment” (p. 10). A discipline, according to Senge, is a developmental path for acquir- ing certain skills or competencies. He maintains the concept that cer- tain 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 under- stand the complexities of how technology, as an engineering innova- tion, 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 glo- balizing forces that have added to the complexity of analyzing “the

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language and symbolic media we employ to describe, represent, interpret, and theorize what we take to be the facticity of organi- zational 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 tech- nology affected that process? We know that the concept of dis- course 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 dis- course 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 lan- guage, 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 meta- phor, 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 organiza- tional 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 writ- ten 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 condi- tions that technology brings to talk and its corresponding actions.

91orGAnIz AtIonAl le ArnInG theorIes

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 margin- ality (Schlossberg, 1989).

Identities are not only individual but also collective, which to a large extent contributes to cultures of practice within organiza- tional factions. It is through common membership that a collec- tive 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 fos- tering timely actions that have a consensus among the involved community.

Skills

Identity

Emotions

Action

Conversational activity

Conversational content

Figure 4.6 Grant’s schema— relationship between content and activity.

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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 “techni- cal 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 emo- tional 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 ratio- nal 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 actu- ally leads to action. Theories that foster discourse, and its use in orga- nizations, 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 learn- ing, and, eventually, knowledge creation and management. Action, by contrast, can be viewed as the measurable outcomes that have been

9 3orGAnIz AtIonAl le ArnInG theorIes

eluding organizational learning scholars. However, not all actions lead to measurable outcomes. Marshak (1998) established three types of talk that lead to action: tool­talk , frame­talk , and mythopoetic­talk :

1. Tool­talk 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. Frame­talk focuses on interpretation to evaluate the mean- ings of talk. Using frame-talk results in enabling implicit and explicit assessments, which include symbolic, conscious, pre- conscious, and contextually subjective dimensions.

3. Mythopoetic­talk 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 con- cepts 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 cor- related 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, non- sense associated with acceleration in the organizational change pro- cess. 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 nonsensi- cal or false generalizations regarding how long it takes to implement a product, what might be the expected outcomes, and so on. Given

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the need for ROD—due to the advent of technology—there is a con- comitant 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, organiza- tional 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 communicat- ing 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 learn- ing effort. Technology accelerates the need for such discourse, and language, in becoming a more important part of the learning matura- tion 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 dis- course and language to learning within the ROD framework and par- adigm. 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

9 5orGAnIz AtIonAl le ArnInG theorIes

then analyzed through frame-talk, by which the technology can be evaluated in terms of how it meets the fundamental premises estab- lished in QI. Frame-talk also reinforces the conceptual legitimacy of how technology will transform the organization while provid- ing appropriate ROI. Tool-talk represents the process of identifying applications and actually implementing them. For this reason, tool- talk exists in both QIII and QIV. The former quadrant represents

Mythopoetic-talk: Ideogenic

Frame-talk: Interpretive

Tool-talk: Instrumental

Figure 4.7 Marshak’s type of talk containers.

Planning and design–How?

Im ple

me nt

ati on

–W ha

t I f?

Tool-talk: Doing using reflective

practices

QIV

QIII

QI

QII

Tool-talk: Discuss-decide:

Knowledge management

Frame-talk: Transformative

Mythopoetic- talk: Ground ideas using

communities of practice

Feasibility–W hy?

M ea

su rem

en t a

nd an

aly sis

–W ha

t?

Figure 4.8 Marshak’s model mapped to the technology learning wheel.

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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 matu- rity 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 incom- plete 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 mat- uration 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 event- driven 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 rela- tionships 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

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to reinstate the old culture: centralized infrastructure, stated opera- tional boundaries, and separations that mandated anti-learning orga- nizational 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 execu- tive 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 organi- zational 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 matu- ration 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,

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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 matura- tion, 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 depart- ment 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, lack- ing 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

9 9orGAnIz AtIonAl le ArnInG theorIes

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 organiza- tional 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 inte- grated 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 PHASE III

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.

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.

Learning outcomes

Early stage of learning organization development.

Combination of event-driven and early-stage social organizational learning formation.

Movement toward social- based organizational decision making, relative to the different uses of technology.

Responsive organizational dynamism: cultural assimilation.

Established new culture; no change in organizational structure.

Cultural assimilation stability with existing structures; early phase of IT organizational integration with similar groups.

Mature use of cultural assimilation, based on IT behaviors (drivers and supporters).

Responsive organizational dynamism: Strategic integration.

Limited integration due to lack of executive involvement.

Early stages of value/needs based on similar strategic alignment.

Social structures emphasize strategic integration based on business needs.

10 0 INFORMATION TECHNOLO GY

of an organization reflects an underlying principle that guides the process of ROD norms and behaviors; specifically, it guides orga- nizations 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 opera- tions 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 illus- trates 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 character- izes 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 spe- cific definitions that can be used to identify developmental stages of ROD and organizational learning maturation. Figure 4.10 rep- resents the ROD arc with its cell definitions. The five stages of the arc are outlined as follows:

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10 3orGAnIz AtIonAl le ArnInG theorIes

1. Operational knowledge: Represents the capacity to learn, con- ceptualize, 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 inte- grate points of view about using technology from diverse indi- viduals 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 small- group learning activities, using reflective practices. Lower levels of middle managers participate in organizational learn- ing that is in transition, from purely individual to group-level thinking.

3. Integrated disposition : Recognizes that individual and depart- mental views on using technology need to be integrated to form effective business unit objectives. Understanding that organizational and cultural shifts need to include all mem- ber 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 sec- tors of ROD appropriate for performing job duties for emerg- ing 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 strate- gic and cultural shifts, relating to technology opportunities. Organizational learning occurs using methods of knowledge management with executive support. Individuals use their

10 4 INFORMATION TECHNOLO GY

technology knowledge for creative purposes. They are will- ing 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 posi- tioned 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 organiza- tional 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 differ- ent 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 indi- vidual 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 con- cept, which Knefelkamp calls “multiple and simultaneous” (1999), meaning that learning can take on multiple meanings across dif- ferent sectors simultaneously.

10 5orGAnIz AtIonAl le ArnInG theorIes

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

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10 6 INFORMATION TECHNOLO GY

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10 7orGAnIz AtIonAl le ArnInG theorIes

some predetermined time period, individual journals or diaries, group meetings, and focus groups. Quantitative measures involve the cre- ation 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 indi- viduals, 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.

10 9

5 manag ing oRg aniz aTional le aRning anD TeChnology

The Role of Line Management

In Chapter 1, the results of the Ravell case study demonstrated the importance of the role that line managers have, for the success of imple- menting organizational learning, particularly in the objective of inte- grating the information technology (IT) department. There has been much debate related to the use of event-driven learning. In particular, there is Senge’s (1990) work from his book, The Fifth Discipline. While overall, I agree with his theories, I believe that there is a need to critique some of his core concepts and beliefs. That is, Senge tends to make broad generalizations about the limits of event-driven education and learning in organizations. He believes that there is a limitation of learn- ing from experience because it can create limitations to learning based on actions—as he asks: “What happens when we can no longer observe the consequences of our actions?” (Senge, 1990, p. 23).

My research has found that event-driven learning is essential to most workers who have yet to learn through other means. I agree with Senge that not all learning can be obtained through event-oriented thinking, but I feel that much of what occurs at this horizon pertains more to the senior levels than to what many line managers have to deal with as part of their functions in business. Senge’s concern with learn- ing methods that focus too much on the individual, perhaps, is more powerful, if we see the learning organization as starting at the top and then working its way down. The position, however, particularly with respect to the integration of technology, is that too much dependence on executive-driven programs to establish and sustain organizational learning, is dangerous. Rather, the line management—or middle managers who fundamentally run the business—is best positioned to make the difference. My hypothesis here is that both top-down and bottom-up approaches to organizational learning are riddled with

110 INFORMATION TECHNOLO GY

problems, especially in their ability to sustain outcomes. We cannot be naï ve—even our senior executives must drive results to maintain their positions. As such, middle managers, as the key business drivers, must operate in an event- and results-driven world—let us not under- estimate the value of producing measurable outcomes, as part of the ongoing growth of the organizational learning practicum.

To explore the role of middle managers further, I draw on the inter- esting research done by Nonaka and Takeuchi (1995). These research- ers examined how Japanese companies manage knowledge creation, by using an approach that they call “middle-up-down.” Nonaka and Takeuchi found that middle managers “best communicate the contin- uous iterative process by which knowledge is created” (p. 127). These middle managers are often seen as leaders of a team, or task, in which a “spiral conversion process” operates and that requires both executive and operations management personnel. Peters and Waterman (1982), among others, often have attacked middle managers as representing a layer of management that creates communication problems and inef- ficiencies in business processes that resulted in leaving U.S. workers trailing behind their international competitors during the automobile crisis in the 1970s. They advocate a “flattening” of the never-ending levels of bureaucracy responsible for inefficient operations. However, executives often are not aware of details within their operating depart- ments and may not have the ability or time to acquire those details. Operating personnel, on the other hand, do not possess the vision and business aptitudes necessary to establish the kind of knowledge creation that fosters strategic learning.

Middle managers, or what I prefer to identify as line managers (Langer, 2001b), possess an effective combination of skills that can pro- vide positive strategic learning infrastructures. Line managers under- stand the core issues of productivity in relation to competitive operations and return on investment, and they are much closer to the day-to-day activities that bring forth the realities of how, and when, new strategic processes can be effectively implemented. While many researchers, such as Peters and Waterman, find them to be synonymous with backward- ness, stagnation, and resistance to change, middle managers are the core group that can provide the basis for continuous innovation through strategic learning. It is my perspective that the difference of opinion regarding the positive or negative significance middle managers have

111MAnAGInG orGAnIz AtIonAl le ArnInG

in relation to organizational learning has to do with the wide-ranging variety of employees who fall into the category of “middle.” It strikes me that Peters and Waterman were somewhat on target with respect to a certain population of middle managers, although I would not char- acterize them as line managers. To justify this position, it is important to clearly establish the differences. Line managers should be defined as pre-executive employees who have reached a position of managing a business unit that contains some degree of return on investment for the business. In effect, I am suggesting that focusing on “middle” manag- ers, as an identifiable group, is too broad. Thus, there is a need to further delineate the different levels of what comprises middle managers, and their roles in the organization.

Line Managers

These individuals usually manage an entire business unit and have “return-on-investment” responsibilities. Line managers should be categorized as those who have middle managers reporting to them; they are, in effect, managers of managers, or, as in some organiza- tions, they serve a “directorial” function. Such individuals are, in many ways, considered future executives and perform many low-end executive tasks. They are, if you will, executives in training. What is significant about this managerial level is the knowledge it carries about operations. However, line managers are still involved in daily operations and maintain their own technical capabilities.

First­Line Managers

First-line individuals manage nonmanagers but can have supervisory employees who report to them. They do not carry the responsibility for a budget line unit but for a department within the unit. These managers have specific goals that can be tied to their performance and to the department’s productivity.

Supervisor

A supervisor is the lowest-level middle manager. These individu- als manage operational personnel within the department. Their

112 INFORMATION TECHNOLO GY

management activities are typically seen as “functions,” as opposed to managing an entire operation. These middle managers do not have other supervisors or management-level personnel reporting to them.

We should remember that definitions typically used to character- ize the middle sectors of management, as described by researchers like Peters, Nonaka, and others, do not come from exact science. The point must be made that middle managers cannot be categorized by a single definition. The category requires distinctive definitions within each level of stratification presented. Therefore, being more specific about the level of the middle manager can help us determine the man- ager’s role in the strategic learning process. Given that Nonaka and Takeuchi (1995) provide the concept of middle-up-down as it related to knowledge management, I wish to broaden it into a larger sub- ject of strategic learning, as a method of evolving changes in culture and organizational thinking. Furthermore, responsive organizational dynamism (ROD), unlike other organizational studies, represents both situational learning and ongoing evolutionary learning require- ments. Evolutionary learning provides a difficult challenge to organi- zational learning concepts. Evolutionary learning requires significant contribution from middle managers. To understand the complexity of the middle manager, all levels of the organization must be taken into consideration. I call this process management vectors.

Management Vectors

Senge’s (1990) work addresses some aspects of how technology might affect organizational behavior: “The central message of the Fifth Discipline is more radical than ‘ radical organization redesign’— namely that our organizations work the way they work, ultimately because of how we think and how we interact” (p.  xiv). Technology aspires to be a new variable or catalyst that can change everyday approaches to things—to be the radical change element that forces us to reexamine norms no longer applicable to business operations. On the other hand, technology can be dangerous if perceived unre- alistically as a power that possesses new answers to organizational performance and efficiency. In the late 1990s, we experienced the “bust” of the dot-com explosion, an explosion that challenged conven- tional norms of how businesses operate. Dot-coms sold the concepts

113MAnAGInG orGAnIz AtIonAl le ArnInG

that brick-and-mortar operations could no longer compete with new technology-driven businesses and that “older” workers could not be transformed in time to make dot-com organizations competitive. Dot-coms allowed us to depart from our commitment to knowledge workers and learning organizations, which is still true today.

For example, in 2003, IBM at its corporate office in Armonk, New York, laid off 1,000 workers who possessed skills that were no lon- ger perceived as needed or competitive. Rather than retrain work- ers, IBM determined that hiring new employees to replace them was simply more economically feasible and easier in terms of trans- forming their organization behaviors. However, in my interview with Stephen McDermott, chief executive officer (CEO) of ICAP Electronic Trading Community (ETC), it became apparent that many of the mystiques of managing technology were incorrect. As he stated, “Managing a technology company is no different from manag- ing other types of businesses.” While the technical skills of the IBM workers may no longer be necessary, why did the organization not provide enough opportunities to migrate important knowledge work- ers to another paradigm of technical and business needs? Widespread worker replacements tell us that few organizational learning infra- structures actually exist. The question is whether technology can pro- vide the stimulus to prompt more organizations to commit to creating infrastructures that support growth and sustained operation. Most important is the question of how we establish infrastructures that can provide the impetus for initial and ongoing learning organizations. This question suggests that the road to working successfully with tech- nology will require the kind of organizational learning that is driven by both individual and organization-wide initiatives. This approach can be best explained by referring to the concept of driver and sup- porter functions and life cycles of technology presented in Chapter 3. Figure 5.1 graphically shows the relationship between organizational structure and organizational learning needs. We also see that this relationship maps onto driver and supporter functionality.

Figure 5.1 provides an operational overview of the relations between the three general tiers of management in most organizations. These levels or tiers are mapped onto organizational learning approaches; that is, organizational/system or individual. This mapping follows a general view based on what individuals at each of these tiers view or

114 INFORMATION TECHNOLO GY

seek as their job responsibilities and what learning method best sup- ports their activities within their environment. For example, execu- tive learning focuses on system-level thinking and learning because executives need to view their organizations in a longer-term way (e.g., return on investment), as opposed to viewing learning on an indi- vidual, transactional event way. Yet, executives play an integral part in long-term support for technology, as an accelerator. Their role within ROD is to provide the stimulus to support the process of cultural assimilation, and they are also very much a component of strategic integration. Executives do not require as much event-driven reflective change, but they need to be part of the overall “social” structure that paves the way for marrying the benefits of technology with organi- zational learning. What executives do need to see, are the planned measurable outcomes linked to performance from the investment of coupling organizational learning with technology. The lack of execu- tive involvement and knowledge will be detrimental to the likelihood of making this relationship successful.

Operations, on the other hand, are based more on individual prac- tices of learning. Attempting to incorporate organizational vision and social discourse at this level is problematic until event-driven learning is experienced individually to prove the benefits that can be derived from reflective practices. In addition, there is the problem of the credibility of a learning program. Workers are often wary of new

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Figure 5.1 Three-tier organizational structure.

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programs designed to enhance their development and productivity. Many question the intentions of the organization and why it is mak- ing the investment, especially given what has occurred in corporations over the last 20 years: Layoffs and scandals have riddled organizations and hurt employee confidence in the credibility of employer programs.

Ravell showed us that using reflective practices during events pro- duces accelerated change, driven by technological innovation, which in turn, supports the development of the learning organization. It is important at this level of operations to understand the narrow and pragmatic nature of the way workers think and learn. The way opera- tions personnel are evaluated is also a factor. Indeed, operations per- sonnel are evaluated based on specific performance criteria.

The most complex, yet combined, learning methods relate to the middle management layers. Line managers, within these layers, are engrossed in a double-sided learning infrastructure. On one side, they need to communicate and share with executives what they perceive to be the “overall” issues of the organization. Thus, they need to learn using an organizational learning approach, which is less dependent on event-driven learning and uses reflective practice. Line managers must, along with their senior colleagues, be able to see the business from a more proactive perspective and use social-oriented methods if they hope to influence executives. Details of events are more of an assumed responsibility to them than a preferred way of interacting. In other words, most executives would rather interface with line manag- ers on how they can improve overall operations efficiently and effec- tively, as opposed to dealing with them on a micro, event-by-event basis. The assumption, then, is that line managers are expected to deal with the details of their operations, unless there are serious problems that require the attention of executives; such problems are usually cor- related to failures in the line manager’s operations.

On the other side are the daily relationships and responsibilities managers face for their business units. They need to incorporate more individual-based learning techniques that support reflective practices within their operations to assist in the personal development of their staff. The middle management tier described in Figure 5.1 is shown at a summary level and needs to be further described. Figure 5.2 pro- vides a more detailed analysis based on the three types of middle man- agers described. The figure shows the ratio of organizational learning

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to individual learning based on manager type. The more senior the manager, the more learning is based on systems and social processes.

Knowledge Management

There is an increasing recognition that the competitive advantage of organizations depends on their “ability to create, transfer, utilize, and protect difficult-to-intimate knowledge assets” (Teece, 2001, p. 125). Indeed, according to Bertels and Savage (1998), the dominant logic of the industrial era requires an understanding of how to break the learning barrier to comprehending the information era. While we have developed powerful solutions to change internal processes and organizational structures, most organizations have failed to address the cultural dimensions of the information era. Organizational knowledge creation is a result of organizational learning through stra- tegic processes. Nonaka and Takeuchi (1995) define organizational knowledge as “the capability of a company as a whole to create new knowledge, disseminate it throughout the organization, and embody it in products, services, and systems” (p. 3). Nonaka and Takeuchi use the steps shown in Figure 5.3 to assess the value and chain of events surrounding the valuation of organization knowledge.

Supervisor

High individual- based learning

High org/system- based learning

Individual

System

Manager Director

Figure 5.2 Organizational/system versus individual learning by middle manager level.

Knowledge creation

Continuous innovation

Competitive advantage

Figure 5.3 Nonaka and Takeuchi steps to organizational knowledge.

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If we view the Figure 5.3 processes as leading to competitive advan- tage, we may ask how technology affects the chain of actions that Nonaka and Takeuchi (1995) identify. Without violating the model, we may insert technology and observe the effects it has on each step, as shown in Figure 5.4.

According to Nonaka and Takeuchi (1995), to create new knowl- edge means to re-create the company, and everyone in it, in an ongo- ing process that requires personal and organizational self-renewal. That is, knowledge creation is the responsibility of everyone in the organization. The viability of this definition, however, must be ques- tioned. Can organizations create personnel that will adhere to such parameters, and under what conditions will senior management sup- port such an endeavor?

Again, technology has a remarkable role to play in substantiat- ing the need for knowledge management. First, executives are still challenged to understand how they need to deal with emerging tech- nologies as this relates to whether their organizations are capable of using them effectively and efficiently. Knowledge management provides a way for the organization to learn how technology will be used to support innovation and competitive advantage. Second, IT departments need to understand how they can best operate within the larger scope of the organization—they are often searching for a true mission that contains measurable outcomes, as defined by the entire organization, including senior management. Third, both execu- tives and IT staff agree that understanding the uses of technology is a continuous process that should not be utilized solely in a reactionary

Knowledge creation: Technology provides more dynamic shifts in knowledge, thus accelerating the number of knowledge-creation events that can occur.

Continuous innovation: Innovations are accelerated because of the dynamic nature of events and the time required to respond—therefore, continuous

innovation procedures are more significant to have in each department in order to respond to technological opportunities on an ongoing basis.

Competitive advantage: Technology has generated more global competition. Competitive advantages that depend on technological innovation

are more common.

Figure 5.4 Nonaka and Takeuchi organizational knowledge with technology extension.

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and event-driven way. Finally, most employees accept the fact that technology is a major component of their lives at work and at home, that technology signifies change, and that participating in knowledge creation is an important role for them.

Again, we can see that technology provides the initiator for understanding how organizational learning is important for com- petitive advantage. The combination of IT and other organizational departments, when operating within the processes outlined in ROD, can significantly enhance learning and competitive advantage. To expand on this point, I now focus on the literature specifically relat- ing to tacit knowledge and its important role in knowledge man- agement. Scholars theorize knowledge management is an ability to transfer individual tacit knowledge into explicit knowledge. Kulkki and Kosonen (2001) define tacit knowledge as an experience-based type of knowledge and skill and as the individual capacity to give intuitive forms to new things; that is, to anticipate and preconcep- tualize the future. Technology, by its very definition and form of being, requires this anticipation and preconceptualization. Indeed, it provides the perfect educational opportunity in which to practice the transformation of tacit into explicit knowledge. Tacit knowledge is an asset, and having individual dynamic abilities to work with such knowledge commands a “higher premium when rapid organic growth is enabled by technology” (Teece, 2001, p.  140). Thus, knowledge management is likely to be greater when technological opportunity is richer.

Because evaluating emerging technologies requires the ability to look into the future, it also requires that individuals translate valu- able tacit knowledge, and creatively see how these opportunities are to be judged if implemented. Examples of applicable tacit knowledge in this process are here extracted from Kulkki and Kosonen (2001):

• Cultural and social history • Problem-solving modes • Orientation to risks and uncertainties • Worldview organizing principles • Horizons of expectations

I approach each of these forms of tacit knowledge from the per- spective of the components of ROD as shown in Table 5.1.

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It is not my intention to suggest that all technologies should be, or can be, used to generate competitive advantage. To this extent, some technologies may indeed get rejected because they cannot assist the organization in terms of strategic value and competitive advantage. As Teece (2001) states, “Information transfer is not knowledge transfer and information management is not knowledge management, although the former can assist the latter. Individuals and organizations can suffer from information overload” (p. 129). While this is a significant issue for many firms, the ability to have an organization that can select, interpret,

Table 5.1 Mapping Tacit Knowledge to Responsive Organizational Dynamism

TACIT KNOWLEDGE STRATEGIC INTEGRATION CULTURAL ASSIMILATION

Cultural and social history

How the IT department and other departments translate emerging technologies into their existing processes and organization.

Problem-solving modes

Individual reflective practices that assist in determining how specific technologies can be useful and how they can be applied.

Technology opportunities may require organizational and structural changes to transfer tacit knowledge to explicit knowledge.

Utilization of tacit knowledge to evaluate probabilities for success.

Orientation to risks and uncertainties

Technology offers many risks and uncertainties. All new technologies may not be valid for the organization.

Tacit knowledge is a valuable component to fully understand realities, risks, and uncertainties.

Worldviews Technology has global effects and changes market boundaries that cross business cultures. It requires tacit knowledge to understand existing dispositions on how others work together.

Review how technology affects the dynamics of operations.

Organizing principles

How will new technologies actually be integrated? What are the organizational challenges to “rolling out” products and to implementation timelines? What positions are needed, and who in the organization might be best qualified to fill new responsibilities?

Identify limitations of the organization; that is, tacit knowledge versus explicit knowledge realities.

Horizons of expectations

Individual limitations in the tacit domain that may hinder or support whether a technology can be strategically integrated into the organization.

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and integrate information is a valuable part of knowledge management. Furthermore, advances in IT have propelled much of the excitement surrounding knowledge management. It is important to recognize that learning organizations, reflective practices, and communities of prac- tice all participate in creating new organizational knowledge. This is why knowledge management is so important. Knowledge must be built on its own terms, which requires intensive and laborious interactions among members of the organization.

Change Management

Because technology requires that organizations accelerate their actions, it is necessary to examine how ROD corresponds to theories in organizational change. Burke (2002) states that most organiza- tional change is evolutionary; however, he defines two distinct types of change: planned versus unplanned and revolutionary versus evolu- tionary. Burke also suggests that the external environmental changes are more rapid today and that most organizations “are playing catch up.” Many rapid changes to the external environment can be attrib- uted to emerging technologies, which have accelerated the divide between what an organization does and what it needs to do to remain competitive. This is the situation that creates the need for ROD.

The catching-up process becomes more difficult because the amount of change required is only increasing given ever-newer technologies. Burke (2002) suggests that this catching up will likely require planned and revolutionary change. Such change can be mapped onto much of my work at Ravell. Certainly, change was required; I planned it, and change had to occur. However, the creation of a learning organiza- tion, using many of the organizational learning theories addressed in Chapter 4, supports the eventual establishment of an operating organization that can deal with unplanned and evolutionary change. When using technology as the reason for change, it is then important that the components of ROD be integrated with theories of organi- zational change.

History has shown that most organizational change is not success- ful in providing its intended outcomes, because of cultural lock-in. Cultural lock­in is defined by Foster and Kaplan (2001) as the inability of an organization to change its corporate culture even when there

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are clear market threats. Based on their definition, then, technology may not be able to change the way an organization behaves, even when there are obvious competitive advantages to doing so. My con- cern with Foster and Kaplan’s conclusion is whether individuals truly understand exactly how their organizations are being affected—or are we to assume that they do understand? In other words, is there a pro- cess to ensure that employees understand the impact of not changing? I believe that ROD provides the infrastructure required to resolve this dilemma by establishing the processes that can support ongoing unplanned and evolutionary change.

To best show the relationship of ROD to organizational change theory, I use Burke’s (2002) six major points in assisting change in organizations:

1. Understanding the external environment: What are competitors and customers’ expectations? This is certainly an issue, specif- ically when tracking whether expected technologies are made available in the client– vendor relationship. But, more critical is the process of how emerging technologies, brought about through external channels, are evaluated and put into produc- tion; that is, having a process in place. Strategic integration of ROD is the infrastructure that needs to facilitate the moni- toring and management of the external environment.

2. Evaluation of the inside of the organization: This directly relates to technology and how it can be best utilized to improve internal operations. While evaluation may also relate to a restructuring of an organization’s mission, technology is often an important driver for why a mission needs to be changed (e.g., expanding a market due to e-commerce capabilities).

3. Readiness of the organization: The question here is not whether to change but how fast the organization can change to address technological innovations. The ROD arc provides the steps necessary to create organizations that can sustain change as a way of operation, blending strategic integration with cultural assimilation. The maturation of learning: moving toward sys- tem-based learning also supports the creation of infrastruc- tures that are vitally prepared for changes from emerging technologies.

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4. Cultural change as inevitable: Cultural assimilation essentially demands that organizations must dynamically assimilate new technologies and be prepared to evolve their cultures. Such evolution must be accelerated and be systemic within business units, to be able to respond effectively to the rate of change created by technological innovations.

5. Making the case for change: It is often difficult to explain why change is inevitable. Much of the need for change can be sup- ported using the reflective practices implemented at Ravell. However, such acceptance is directly related to the process of time. Major events can assist in establishing the many needs for change, as discussed by Burke (2002).

6. Sustaining change: Perhaps the strongest part of ROD is its ability to create a process that is evolutionary and systemic. It focuses on driving change to every aspect of the organization and provides organizational learning constructs to address each level of operation. It addresses what Burke (2002) calls the “prelaunch, launch, postlaunch, and sustaining,” in the important sequences of organizational change (p. 286).

Another important aspect of change management is leadership. Leadership takes many forms and has multiple definitions. Technology plays an interesting role in how leadership can be presented to orga- nizations, especially in terms of the management style of leadership, or what Eisenhardt and Bourgeois (1988) have coined as “power cen- tralization.” Their study examines high-velocity environments in the microcomputer industry during the late 1980s. By high velocity, they refer to “those environments in which there is a rapid and discon- tinuous change in demand, competitors, technology, or regulation, so that information is often inaccurate, unavailable, or obsolete” (p. 738). During the period of their study, the microcomputer industry was undergoing substantial technological change, including the introduc- tion of many new competitors. As it turns out, the concept of high velocity is becoming more the norm today given the way organizations find themselves needing to operate in constant fluxes of velocity. The term power centralization is defined as the amount of decision-making control wielded by the CEO. Eisenhardt and Bourgeois’s study finds that the more the CEO engages in power-centralized leadership,

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the greater the degree of politics, which has a negative impact on the strategic performance of the firms examined. This finding suggests that the less democratic the leadership is in high-velocity environ- ments, the less productive the organization will be. Indeed, the study found that when individuals engaged in team learning, political ten- sion was reduced, and the performance of the firms improved.

The structure of ROD provides the means of avoiding the high- velocity problems discovered by the Eisenhardt and Bourgeois (1988) study. This is because ROD allows for the development of more indi- vidual learning, as well as system thinking, across the executive ranks of the business. If technology is to continue to establish such high velocities, firms need to examine the Eisenhardt and Bourgeois study for its relevance to everyday operations. They also need to use orga- nizational learning theories as a basis for establishing leadership that can empower employees to operate in an accelerated and unpredict- able environment.

Change Management for IT Organizations

While change management theories address a broad population in organizations, there is a need to create a more IT-specific approach to address the unique needs of this group. Lientz and Rea (2004) estab- lish five specific goals for IT change managers:

1. Gain support for change from employees and non-IT managers.

2. Implement change along measurements for the work so that the results of the change are clearly determined.

3. Implement a new culture of collaboration in which employees share more information and work more in teams.

4. Raise the level of awareness of the technology process and work so that there is less of a tendency for reversion.

5. Implement an ongoing measurement process for the work to detect any problems.

Lientz and Rea’s (2004) position is that when a new culture is instilled in IT departments, it is particularly important that it should not require massive management intervention. IT people need to be self-motivated to keep up with the myriad accelerated changes in the

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world of technology. These changes occur inside IT in two critical areas. The first relates to the technology itself. For example, how do IT personnel keep up with new versions of hardware and software? Many times, these changes come in the form of hardware (often called system) and software upgrades from vendors who require them to maintain support contracts. The ongoing self-management of how such upgrades and changes will ultimately affect the rest of the organization is a major challenge and one that is difficult to manage top-down. The second area is the impact of new or emerg- ing technologies on business strategy. The challenge is to develop IT personnel who can transform their technical knowledge into busi- ness knowledge and, as discussed, take their tacit knowledge and convert it into explicit, strategic knowledge. Further understanding of the key risks to the components of these accelerated changes is provided as follows:

System and software version control: IT personnel must continue to track and upgrade new releases and understand the impact of product enhancements. Some product-related enhance- ments have no bearing on strategic use; they essentially fix problems in the system or software. On the other hand, some new releases offer new features and functions that need to be communicated to both IT and business managers.

Existing legacy systems: Many of these systems cannot support the current needs of the business. This often forces IT staff to figure out how to create what is called “workarounds” (quick fixes) to these systems. This can be problematic given that workarounds might require system changes or modifications to existing software. The risk of these changes, both short and long term, needs to be discussed between user and IT staff communities of practice.

Software packages (off­the­shelf software): Since the 1990s, the use of preprogrammed third-party software packages has become a preferred mode of software use among users. However, many of these packages can be inflexible and do not support the exact processes required by business users. IT personnel need to address users’ false expectations about what software packages can and cannot do.

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System or software changes: Replacement of systems or software applications is rarely 100% complete. Most often, remnants of old systems will remain. IT personnel can at times be insensi- tive to the lack of a complete replacement.

Project completion: IT personnel often misevaluate when their involvement is finished. Projects are rarely finished when the software is installed and training completed. IT staff tend to move on to other projects and tasks and lose focus on the like- lihood that there will be problems discovered or last-minute requests made by business users.

Technical knowledge: IT staff members need to keep their techni- cal skills up to date. If this is not done, emerging technolo- gies may not be evaluated properly as there may be a lack of technical ability inside the organization to map new technical developments onto strategic advantage.

Pleasing users : While pleasing business users appears to be a good thing, it can also present serious problems with respect to IT projects. What users want, and what they need, may not be the same. IT staff members need to judge when they might need assistance from business and IT management because users may be unfairly requesting things that are not feasible within the constraints of a project. Thus, IT staff must have the ability to articulate what the system can do and what might be advisable. These issues tend to occur when certain business users want new systems to behave like old ones.

Documentation: This, traditionally, is prepared by IT staff and contains jargon that can confuse business users. Furthermore, written procedures prepared by IT staff members do not con- sider the entire user experience and process.

Training: This is often carried out by IT staff and is restricted to covering system issues, as opposed to the business realities surrounding when, how, and why things are done.

These issues essentially define key risks to the success of imple- menting technology projects. Much of this book, thus far, has focused on the process of organizational learning from an infrastructure per- spective. However, the implementation component of technology possesses new risks to successfully creating an organization that can

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learn within the needs of ROD. These risks, from the issues enumer- ated, along with those discussed by Lientz and Rea (2004) are sum- marized as follows:

Business user involvement: Continuous involvement from busi- ness users is necessary. Unfortunately, during the life of a proj- ect there are so many human interfaces between IT staff and business users that it is unrealistic to attempt to control these communications through tight management procedures.

Requirements, definition, and scope: These relate to the process by which IT personnel work with business users to deter- mine exactly what software and systems need to accomplish. Determining requirements is a process, not a predetermined list that business users will necessarily have available to them. The discourse that occurs in conversations is critical to whether such communities are capable of developing require- ments that are unambiguous in terms of expected outcomes.

Business rules: These rules have a great effect on how the organi- zation handles data and transactions. The difference between requirements and business rules is subtle. Specifically, busi- ness rules, unlike requirements, are not necessarily related to processes or events of the business. As such, the determina- tion of business rules cannot be made by reviewing proce- dures; for example, all account numbers must be numeric.

Documentation and training materials: IT staff members need to interact with business users and establish joint processes that foster the development of documentation and training that best fit user needs and business processes.

Data conversion: New systems and applications require that data from legacy systems be converted into the new formats. This process is called data mapping; IT staff and key business users review each data field to ensure that the proper data are rep- resented correctly in the new system. IT staff members should not be doing this process without user involvement.

Process measurement: Organizations typically perform a post- completion review after the system or software application is installed. Unfortunately, this process measurement should occur during and after project completion.

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IT change management poses some unique challenges to imple- menting organizational learning, mostly because managers cannot conceivably be available for all of the risks identified. Furthermore, the very nature of new technologies requires that IT staff mem- bers develop the ability to self-manage more of their daily functions and interactions, particularly with other staff members outside the IT department. The need for self-development is even more critical because of the existence of technological dynamism, which focuses on dynamic and unpredictable transactions that often must be han- dled directly by IT staff members and not their managers. Finally, because so many risks during technology projects require business user interfaces, non-IT staff members also need to develop better and more efficient self-management than they are accustomed to doing. Technological dynamism, then, has established another need for change management theory. This need relates to the implementation of self-development methods. Indeed, part of the reason for the lack of success of IT projects can be attributed to the inability of the core IT and business staff to perform in a more dynamic way. Historically, more management cannot provide the necessary learning and reduc- tion of risk.

The idea of self-development became popular in the early 1980s as an approach to the training and education of managers, and managers to be. Thus, the focus of management self-development is to increase the ability and willingness of managers to take responsibility for themselves, particularly for their own learning (Pedler et al., 1988). I believe that management self-development theory can be applied to nonmanagers, or to staff members, who need to practice self-manage- ment skills that can assist them in transitioning to operating under the conditions of technological dynamism.

Management self-development draws on the idea that many peo- ple emphasize the need for learner centeredness. This is an impor- tant concept in that it ties self-development theory to organizational learning, particularly to the work of Chris Argyris and Malcolm Knowles. The concept of learner centeredness holds that individuals must take prime responsibility for their own learning: when and how to learn. The teacher (or manager) is assigned the task of facilitator—a role that fosters guidance as opposed to direct initiation of learning. In many ways, a facilitator can be seen as a mentor whose role it is to

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guide an individual through various levels of learning and individual development.

What makes self-development techniques so attractive is that learners work on actual tasks and then reflect on their own efforts. The methods of reflective practice theory, therefore, are applicable and can be integrated with self-development practices. Although self- development places the focus on the individual’s own efforts, manag- ers still have responsibilities to mentor, coach, and counsel their staff. This support network allows staff to receive appropriate feedback and guidance. In many ways, self-development relates to the professional process of apprenticeship but differs from it in that the worker may not aspire to become the manager but may wish simply to develop better management skills. Workers are expected to make mistakes and to be guided through a process that helps them reflect and improve. This is why self-development can be seen as a management issue as opposed to just a learning theory.

A mentor or coach can be a supervisor, line manager, director, or an outside consultant. The bottom line is that technological dyna- mism requires staff members who can provide self- management to cope with constant project changes and risks. These individu- als must be able to learn, be self-aware of what they do not know, and possess enough confidence to initiate the required learning and assistance that they need to be successful (Pedler et al., 1988). Self-development methods, like other techniques, have risks. Most notable, is the initial decrement in performance followed by a slow increment as workers become more comfortable with the process and learn from their mistakes. However, staff members must be given support and time to allow this process to occur; self-development is a trial-and-error method founded on the basis of mastery learning (i.e., learning from one’s mistakes). Thus, the notion of self-development is both continuous and discontinuous and must be implemented in a series of phases, each having unique outcomes and maturity. The concept of self-development is also consistent with the ROD arc, in which early phases of maturation require more individual learning, particularly reflective practices. Self-development, in effect, becomes a method of indirect man- agement to assist in personal transformation. This personal trans- formation will inevitably better prepare individuals to participate

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in group- and organizational-level learning at later stages of maturation.

The first phase of establishing a self-development program is to create a “learning-to-learn” process. Teaching individuals to learn is a fundamental need before implementing self-development techniques. Mumford (1988) defines learning to learn as

1. Helping staff to understand the stages of the learning process and the pitfalls to not learning

2. Helping staff to find their own preferences to learning 3. Assisting staff in understanding their present learning prefer-

ences and how to deal with, and overcome, learning weaknesses 4. Helping staff to build on their learning experience and apply

it to their current challenges in their job

The first phase of self-development clearly embraces the Kolb (1999) Learning Style Inventory and the applied individual learn- ing wheel that were introduced in Chapter 4. Thus, all staff members should be provided with both of these learning wheels, made aware of their natural learning strengths and weaknesses, and provided with exercises to help them overcome their limitations. Most important is that the Kolb system will make staff aware of their shortfalls with learning. The applied individual learning wheel will provide a per- spective on how individuals can link generic learning preferences into organizational learning needs to support ROD.

The second phase of self-development is to establish a formal learn- ing program in which staff members

1. Are responsible for their own learning, coordinated with a mentor or coach

2. Have the right to determine how they will meet their own learning needs, within available resources, time frames, and set outcomes

3. Are responsible for evaluating and assessing their progress with their learning

In parallel, staff coaches or mentors

1. Have the responsibility to frame the learning objectives so that they are consistent with agreed-on individual weaknesses

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2. Are responsible for providing access and support for staff 3. Must determine the extent of their involvement with mentor-

ing and their commitment to assisting staff members achieve stated outcomes

4. Are ultimately responsible for the evaluation of individual’s progress and success

This program must also have a formal process and structure. According to Mossman and Stewart (1988), formal programs, called self-managed learning (SML), need the following organization and materials:

1. Staff members should work in groups as opposed to on their own. This is a good opportunity to intermix IT and non- IT staff with similar issues and objectives. The size of these groups is (typically) from four to six members. Groups should meet every two– three weeks, and should develop what are known as learning contracts . Learning contracts specifically state what the individual and management have agreed on. Essentially, the structure of self-development allows staff members to experience communities of practice, which by their very nature, will also introduce them to group learning and system-level thinking.

2. Mentors or coaches should preside over a group as opposed to presiding over just one individual. There are two benefits to doing this: (1) There are simply economies of scale for which managers cannot cover staff on an individual basis, and (2) facilitating a group with similar objectives benefits interac- tion among the members. Coaches obviously need to play an important role in defining the structure of the sessions, in offering ideas about how to begin the self-development pro- cess, and in providing general support.

3. Staff members need to have workbooks, films, courses, study guides, books, and specialists in the organization, all of which learners can use to help them accomplish their goals.

4. Typically, learning contracts will state the assessment meth- ods. However, assessment should not be limited only to indi- viduals but also should include group accomplishments.

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An SML should be designed to ensure that the learning program for staff members represents a commitment by management to a for- mal process, that can assist in the improvement of the project teams.

The third phase of self-development is evaluation. This process is a mixture of individual and group assessments from phase II, coupled with assessments from actual practice results. These are results from proven outcomes during normal workday operations. To garner the appropriate practice evaluation, mentors and coaches must be involved in monitoring results and noting the progress on specific events that occur. For example, if a new version of software is implemented, we will want to know if IT staff and business users worked together to determine how and when it should be implemented. These results need to be formally communicated back to the learning groups. This process needs to be continued on an ongoing basis to sustain the effects of change management. Figure 5.5 represents the flow of the three phases of the process.

The process for self-development provides an important approach in assisting staff to perform better under the conditions of technologi- cal dynamism. It is one thing to teach reflective practice; it is another

Individual learning contracts Learning styles inventory

Self-managed learning program communities of practice IT and non-IT staff

Phase 1: Establish

learning to learn

objectives

Phase 2: Create formal

learning program

Make necessary changes to self-

development learning

Individual and group assessment monitor operations for measurable outcomes

Phase 3: Implement evaluation

Figure 5.5 Phases of self-development.

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to get staff members to learn how to think in a manner that takes into consideration the many risks that have plagued systems and software projects for decades. While the role of management continues to play a major part in getting things done within strategic objectives, self- development can provide a strong learning method, that can foster sustained bottom-up management, which is missing in most learning organizations.

The Ravell case study provides some concrete evidence on how self-development techniques can indeed get results. Because of the time pressures at Ravell, I was not able to invest in the learning-to- learn component at the start of the process. However, I used informal methods to determine the learning preferences of the staff. This can be accomplished through interviews in which staff responses can pro- vide a qualitative basis for evaluating how specific personnel prefer to learn. This helped me to formulate a specific training program that involved group meetings with IT and non-IT-oriented groups.

In effect, phase II at Ravell had two communities. The first com- munity was the IT staff. We met each week to review progress and to set short-term objectives of what the community of IT wanted to accomplish. I acted as a facilitator, and although I was in a power position as their manager, I did not use my position unless there were clear signs of resistance in the team (which there were in specific situ- ations). The second community was formed with various line manager departments. This is where I formed “dotted-line” reporting struc- tures, which required IT staff members also to join other commu- nities of practice. This proved to be an invaluable strategy because it brought IT and business users together and formed the links that eventually allowed IT staff members to begin to learn and to form relationships with the user community, which fostered reflective thinking and transformation.

As stated, there are setbacks at the start of any self-development program, and the experience at Ravell was no exception. Initially, IT staff members had difficulty understanding what was expected of them; they did not immediately perceive the learning program as an opportunity for their professional growth. It was through ongo- ing, motivated discourse in and outside of the IT community that helped achieve measurable increments of self-developmental growth. Furthermore, I found it necessary to integrate individual coaching

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sessions with IT staff. While group sessions were useful, they were not a substitute for individual discussions, which at times allowed IT staff members to personally discuss their concerns and learning requirements. I found the process to be ultimately valuable, and I maintained the role of coach, as opposed to that of a manager who tells IT staff members what to do in every instance. I knew that direct management only would never allow for the development of learning.

Eventually, self-development through discourse will foster identity development. Such was the case at Ravell, where both user and IT groups eventually came together to form specific and interactive com- munities of practice. This helped form a clearer identity for IT staff members, and they began to develop the ability to address the many project risk issues that I defined in this chapter. Most important for the organization was that Ravell phase I built the foundation for later phases that required more group and system thinking among the IT ranks.

Evaluation of the performance at Ravell (phase III of the self- development process) was actually easier than expected, which means that if the first two phases are successful, evaluation will naturally be easy to determine. As reflective thinking became more evident in the group, it was easier to see the growth in transformative behavior; the IT groups became more proactive and critical by themselves, without necessarily needing my input. In fact, my participation fell into more of a supporter role; I was asked to participate more when I felt needed to provide a specific task for the group. Evaluation based on perfor- mance was also easier to determine, mainly because we had formed interdepartmental communities and because of the relationships I established with line managers.

Another important decision we made and one that nurtured our evaluation capabilities was the fact that line managers often joined our IT staff meetings. So, getting feedback on actual results was always open for discussion.

Viewing self-development in the scope of organizational learning and management techniques provides an important support method for later development in system thinking. The Ravel experience did just that, as the self-development process inevitably laid the foun- dation for more sophisticated organizational learning, required as a business matures under ROD.

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Social Networks and Information Technology

The expansion of social networks, through the use of technological innovations, has substantially changed the way information flows in and out of a business community. Some companies, particularly in the financial services communities, have attempted to “lock out” social network capabilities. These attempts are ways for organizations to control, as opposed to change, behavior. Historically, such controls to enforce compliance have not worked. This is particularly relevant because of the emergence of a younger generation of workers who use social networking tools as a regular way to communicate and carry out discourse. Indeed, social networking has become the main vehicle for social discourse both inside and outside organizations. There are those who feel that the end of confidentiality may be on the horizon. This is not to suggest that technology executives give up on security—we all know this would be ludicrous. On the other hand, the increasing pressure to “open” the Web will inevitably become too significant to ignore. Thus, the technology executive of the future must be prepared to provide desired social and professional networks to their employees while figuring out how to minimize risk—certainly not an easy objec- tive. Organizations will need to provide the necessary learning tech- niques to help employees understand the limits of what can be done.

We must remember that organizations, governments, and busi- nesses have never been successful at controlling the flow of information to any population to or from any specific interest group—inevitably, information flows through. As stated by Cross and Thomas (2009), “The network perspective could trigger new approaches to organiza- tion design at a time when environmental and competitive conditions seem to be exhausting conventional wisdom” (p. 186). Most important is the understanding that multinational organizations need to think globally and nationally at the same time. To do this, employees must transform their behavior and how they interact. Controlling access does not address this concern; it only makes communication more difficult and therefore does not provide a solution. Controls typically manifest themselves in the form of new processes and procedures. I often see technology executives proclaiming the need to change pro- cesses in the name of security without really understanding that they are not providing a solution, but rather, fostering new procedures that

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will allow individuals to evade the new security measures. As Cross and Thomas (2009) point out, “Formal structures often overlook the fact that every formal organization has in its shadow an informal or ‘ invis- ible’ organization” (p.  1). Instead, technology executives concerned with security, need to focus on new organizational design to assist businesses to be “social network ready.” ROD must then be extended to allow for the expansion of social network integration, including, but not limited to, such products as Linkedln, Facebook, and Twitter. It may also be necessary to create new internal network infrastruc- tures that specifically cater to social network communication.

Many software application companies have learned that compat- ibility in an open systems environment is a key factor for success- ful deployment of an enterprise-wide application solution. Thus, all applications developed within or for an organization need to have compatibility with the common and popular social network products. This popularity is not static, but rather, a constant process of deter- mining which products will become important social networks that the company may want to leverage. We see social networks having such an impact within the consumer environment—or what we can consider to be the “market.” I explained in my definition of ROD that it is the acceleration of market changes—or the changing relationship between a buyer and seller—that dictates the successes and failures of businesses. That said, technology executives must focus their attention on how such networks will require their organizations to embrace them. Obviously, this change carries risks. Adapting too early could be overreacting to market hype, while lagging could mean late entry.

The challenge, then, for today’s technology leaders is to create dynamic, yet functional, social networks that allow businesses to compete while maintaining the controls they must have to protect themselves. The IT organization must concentrate on how to provide the infrastructure that allows these dynamic connections to be made without overcontrol. The first mission for the technology executive is to negotiate this challenge by working with the senior management of the organization to reach consensus on the risk factors. The issues typically involve the processes, behavior patterns, and risks shown in Figure 5.6.

Ultimately, the technology executive must provide a new road map that promotes interagency and cross-customer collaboration in a way

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that will assist the organization to attain a ROD culture. Social net- works are here to stay and will continue to necessitate 24/7 access for everyone. This inevitably raises salient issues relating to the manage- ment structure within businesses and how best to manage them.

In Chapter 2, I defined the IT dilemma in a number of contexts. During an interview, a chief executive raised an interesting issue that relates to the subject: “My direct reports have been complaining that because of all this technology that they cannot get away from—that their days never seem to end.” I responded to this CEO by asking,

Business process

Design a social network that allows participants to respond dynamically to customer and business needs

Aspired behavior patterns Risks

Users understand the inherent limits to what can be communicated outside the organization, limit personal transactions, and use judgment when foreign e-mails are forwarded.

Users cannot properly determine the ethics of behavior and will not take the necessary precautions to avoid exposing the organization to outside security breaches.

Discern which critical functions are required for the social network to work effectively and maintain the firm's competitive positioning

Users are active and form strategic groups (communities of practice) that define needs on a regular basis and work closely with IT and senior management.

Users cannot keep up with changes in social networks, and it is impossible to track individual needs and behaviors.

Provide a network design that can be scaled as needs change within the budget limitations of the organization

�e organization must understand that hard budgets for social networking may not be feasible. Rather, the network needs are dynamic, and costs must be assessed dynamically within the appropriate operating teams in the organizations.

Reality tells us that all organizations operate within budget limitations. Large organizations find it difficult to govern dynamically, and smaller organizations cannot afford the personnel necessary to manage dynamically.

Create a social network that “flattens” the organization so that all levels are accessible

Particularly large organizations need to have a network that allows its people better access to its departments, talent, and management. In the 1980s, the book In Search of Excellence (Peters & Waterman, 1982) was the first effort to present the value of a “flatter” organizational structure. Social networks provide the infrastructure to make this a reality.

With access come the challenges of responding to all that connect to the system. �e organization needs to provide the correct etiquette of how individuals respond dynamically without creating anarchy.

Figure 5.6 Social network management issues.

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“Why are they e-mailing and calling you? Is it possible that tech- nology has exposed a problem that has always existed?” The CEO seemed surprised at my response and said, “What do you mean?” Again, I responded by suggesting that technology allowed access, but perhaps, that was not really the problem. In my opinion, the real problem was a weakness in management or organizational structure. I argued that good managers build organizations that should handle the questions that were the subject of these executives’ complaints. Perhaps the real problem was that the organization or management was not handling day-to-day issues. This case supports my thesis that technology dynamism requires reevaluation of how the organization operates and stresses the need to understand the cultural assimilation abilities of dealing with change.

Another interesting aspect of social networks is the emergence of otherwise invisible participants. Technology-driven networks have allowed individuals to emerge not only because of the access determi- nant but also because of statistics. Let me be specific. Network traffic can easily be tracked, as can individual access. Even with limited his- tory, organizations are discovering the valued members of their com- panies simply by seeing who is active and why. This should not suggest that social networks are spy networks. Indeed, organizations need to provide learning techniques to guide how access is tracked and to highlight the value that it brings to a business. As with other issues, the technology executive must align with other units and individuals; the following are some examples:

• Human resources (HR): This department has specific needs that can align effectively with the entire social network. Obviously, there are compliance issues that limit what can be done over a network. Unfortunately, this is an area that requires reassessment: In general, governance and controls do not drive an organization to adopt ROD. There are other fac- tors related to the HR function. First, is the assimilation of new employees and the new talents that they might bring to the network. Second, is the challenge of adapting to ongoing change within the network. Third, is the knowledge lost of those who leave the organization yet may still want to partici- pate socially within the organization (friends of the company).

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• Gender: Face-to-face meetings have always shown differences in participation by gender. Men tend to dominate meetings and the positions they hold in an organization. However, the advent of social virtual networks has begun to show a shift in the ways women participate and hold leadership positions among their peers. In an article in Business Week (May 19, 2008), Auren Hoffman reports that women dominate social network traffic. This may result in seeing more women-centric communication. The question, then, is whether the expan- sion of social networks will give rise to more women in senior management positions.

• Marketing: The phenomenon of social networking has allowed for the creation of more targeted connectivity; that is, the abil- ity to connect with specific clients in special ways. Marketing departments are undergoing an extraordinary transformation in the way they target and connect with prospective custom- ers. The technology executive is essentially at the center of designing networks that provide customizable responses and facilitate complex matrix structures. Having such abilities could be the differentiator between success and failure for many organizations.

One can see that the expansion of social networks is likely to have both good and bad effects. Thus far, in this section I have discussed the good. The bad relates to the expansion of what seems to be an unlim- ited network. How does one manage such expansion? The answer lies within the concept of alignment. Alignment has always been critical to attain organizational effectiveness. The heart of alignment is deal- ing with cultural values, goals, and processes that are key to meet strategic objectives (Cross & Thomas, 2009). While the social net- work acts to expose these issues, it does not necessarily offer solutions to these differences. Thus, the challenge for the technology executive of today is to balance the power of social networks while providing direction on how to deal with alignment and control—not an easy task but clearly an opportunity for leadership. The following chapters offer some methods to address the challenges discussed in this chap- ter, and the opportunities they provide for technology executives.