An Improvisational Model for Change Management: The Case of Groupware Technologies

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In her discussion of technology design, Suchman refers to two different approaches to open sea navigation — the European and the Trukese:

“The European navigator begins with a plan — a course — which he has charted according to certain universal principles, and he carries out his voyage by relating his every move to that plan. His effort throughout his voyage is directed to remaining ‘on course.’ If unexpected events occur, he must first alter the plan, then respond accordingly. The Trukese navigator begins with an objective rather than a plan. He sets off toward the objective and responds to conditions as they arise in an ad hoc fashion. He utilizes information provided by the wind, the waves, the tide and current, the fauna, the stars, the clouds, the sound of the water on the side of the boat, and he steers accordingly. His effort is directed to doing whatever is necessary to reach the objective.”1

Like Suchman, we too find this contrast in approaches instructive and use it here to motivate our discussion of managing technological change. In particular, we suggest that how people think about managing change in organizations most often resembles the European approach to navigation. That is, they believe they need to start with a plan for the change, charted according to certain general organizational principles, and that they need to relate their actions to that plan, ensuring throughout that the change remains on course.

However, when we examine how change occurs in practice, we find that it much more closely resembles the voyage of the Trukese. That is, people end up responding to conditions as they arise, often in an ad hoc fashion, doing whatever is necessary to implement change. In a manner similar to Argyris and Schön’s contrast between espoused theories and theories-in-use, we suggest that there is a discrepancy between how people think about technological change and how they implement it.2 Moreover, we suggest that this discrepancy significantly contributes to the difficulties and challenges that contemporary organizations face as they attempt to introduce and effectively implement technology-based change.

Traditional ways of thinking about technological change have their roots in Lewin’s three-stage change model of “unfreezing,” “change,” and “refreezing.”3 According to this model, the organization prepares for change, implements the change, and then strives to regain stability as soon as possible. Such a model, which treats change as an event to be managed during a specified period,4 may have been appropriate for organizations that were relatively stable and bounded and whose functionality was sufficiently fixed to allow for detailed specification. Today, however, given more turbulent, flexible, and uncertain organizational and environmental conditions, such a model is becoming less appropriate — hence, the discrepancy.

This discrepancy is particularly pronounced when the technology being implemented is open-ended and customizable, as in the case of the new information technologies that are known as groupware.5 Group-ware technologies provide electronic networks that support communication, coordination, and collaboration through facilities such as information exchange, shared repositories, discussion forums, and messaging. Such technologies are typically designed with an open architecture that is adaptable by end users, allowing them to customize existing features and create new applications.6 Rather than automating a predefined sequence of operations and transactions, these technologies tend to be general-purpose tools that are used in different ways across various organizational activities and contexts. Organizations need the experience of using groupware technologies in particular ways and in particular contexts to better understand how they may be most useful in practice. In such a technological context, the traditional change model is thus particularly discrepant.

The discrepancy is also evident when organizations use information technologies to attempt unprecedented, complex changes such as global integration or distributed knowledge management. A primary example is the attempt by many companies to redefine and integrate global value chain activities that were previously managed independently. While there is typically some understanding up-front of the magnitude of such a change, the depth and complexity of the interactions among these activities is fully understood only as the changes are implemented. For many organizations, such initiatives represent a new ball game, not only because they haven’t played the game before but because most of the rules are still evolving. In a world with uncertain rules, the traditional model for devising and executing a game plan is very difficult to enact. And, as recent strategy research has suggested, planning in such circumstances is more effective as an ongoing endeavor, reflecting the changing, unfolding environments with which organizations interact.7

In many situations, therefore, predefining the technological changes to be implemented and accurately predicting their organizational impact is infeasible. Hence, the models of planned change that often inform implementation of new technologies are less than effective. We suggest that what would be more appropriate is a way of thinking about change that reflects the unprecedented, uncertain, open-ended, complex, and flexible nature of the technologies and organizational initiatives involved. Such a model would enable organizations to systematically absorb, respond to, and even leverage unexpected events, evolving technological capabilities, emerging practices, and unanticipated outcomes. Such a model for managing change would accommodate — indeed, encourage —ongoing and iterative experimentation, use, and learning. Such a model sees change management more as an ongoing improvisation than a staged event. Here we propose such an alternative model and describe a case study of groupware implementation in a customer support organization to illustrate the value of the model in practice. We conclude by discussing the conditions under which such an improvisational model may be a powerful way to manage the implementation and use of new technologies.

An Improvisational Model for Managing Change

The improvisational model for managing technological change is based on research we have done on the implementation and use of open-ended information technologies. The model rests on two major assumptions that differentiate it from traditional models of change: First, the changes associated with technology implementations constitute an ongoing process rather than an event with an end point after which the organization can expect to return to a reasonably steady state. Second, all the technological and organizational changes made during the ongoing process cannot, by definition, be anticipated ahead of time.

Given these assumptions, our improvisational change model recognizes three different types of change: anticipated, emergent, and opportunity-based. These change types are elaborations on Mintzberg’s distinction between deliberate and emergent strategies.8 Here, we distinguish between anticipated changes — changes that are planned ahead of time and occur as intended — and emergent changes — changes that arise spontaneously from local innovation and that are not originally anticipated or intended. An example of an anticipated change is the implementation of e-mail software that accomplishes its intended aim to facilitate increased, quicker communication among organizational members. An example of an emergent change is the use of the e-mail network as an informal grapevine disseminating rumors throughout an organization. This use of e-mail is typically not planned or anticipated when the network is implemented but often emerges tacitly over time in particular organizational contexts.

We further differentiate these two types of changes from opportunity-based changes — changes that are not anticipated ahead of time but are introduced purposefully and intentionally during the change process in response to an unexpected opportunity, event, or breakdown. For example, as companies gain experience with the World Wide Web, they are finding opportunities to apply and leverage its capabilities in ways that they did not anticipate or plan before the introduction of the Web. Both anticipated and opportunity-based changes involve deliberate action, in contrast to emergent changes that arise spontaneously and usually tacitly from people’s practices with the technology over time.9

The three types of change build on each other iteratively over time (see Figure 1). While there is no predefined sequence in which the different types of change occur, the deployment of new technology often entails an initial anticipated organizational change associated with the installation of the new hardware and software. Over time, however, use of the new technology will typically involve a series of opportunity-based, emergent, and further anticipated changes, the order of which cannot be determined in advance because the changes interact with each other in response to outcomes, events, and conditions arising through experimentation and use.

One way of thinking about this model of change is to consider the analogy of a jazz band. While members of a jazz band, unlike members of a symphony orchestra, do not decide in advance exactly what notes each is going to play, they do decide ahead of time what musical composition will form the basis of their performance. Once the performance begins, each player is free to explore and innovate, departing from the original composition. Yet the performance works because all members are playing within the same rhythmic structure and have a shared understanding of the rules of this musical genre. What they are doing is improvising — enacting an ongoing series of local innovations that embellish the original structure, respond to spontaneous departures and unexpected opportunities, and iterate and build on each other over time. Using our earlier terminology, the jazz musicians are engaging in anticipated, opportunity-based, and emergent action during the course of their performance to create an effective, creative response to local conditions.

Similarly, an improvisational model for managing technological change in organizations is not a predefined program of change charted by management ahead of time. Rather, it recognizes that technological change is an iterative series of different changes, many unpredictable at the start, that evolve from practical experience with the new technologies. Using such a model to manage change requires a set of processes and mechanisms to recognize the different types of change as they occur and to respond effectively to them. The illustrative case we present next suggests that when an organization is open to the capabilities offered by a new technological platform and willing to embrace an improvisational change model, it can achieve innovative organizational changes.

The Case of Zeta

Zeta is one of the top fifty software companies in the United States, with $100 million in revenues and about 1,000 employees. It produces and sells a range of powerful software products that provide capabilities such as decision support, executive information, and marketing analysis. Zeta is headquartered in the Midwest, with sales and client-service field offices throughout the world.

Specialists in the customer service department (CSD) at Zeta provide technical support via telephone to clients, consultants, value-added resellers, Zeta client-service representatives in the field, and other Zeta employees who use the products. This technical support is often quite complex. Specialists typically devote several hours of research to each problem, often searching through reference material, attempting to replicate the problem, and reviewing program source code. Some incidents require interaction with members of other departments such as quality assurance, documentation, and product development. The CSD employs approximately fifty specialists and is headed by a director and two managers.

In 1992, the CSD purchased the Lotus Notes groupware technology within which it developed a new incident tracking support system (ITSS) to help it log customer calls and keep a history of progress toward resolving the customers’ problems. Following a successful pilot of the new system, the CSD decided to commit to the Notes platform and to deploy ITSS throughout its department. The acquisition of new technology to facilitate customer call tracking was motivated by a number of factors. The existing tracking system was a homegrown system that had been developed when the department was much smaller and Zeta’s product portfolio much narrower. The system was not real-time, entry of calls was haphazard, information accuracy was a concern, and performance was slow and unreliable. It provided little assistance for reusing prior solutions and no support for the management of resources in the department. The volume and complexity of calls to the CSD had increased in recent years due to the introduction of new products, the expanded sophistication of existing products, and the extended range of operating platforms supported. Such shifts had made replacement of the tracking system a priority, as the CSD managers were particularly concerned that the homegrown system provided no ability to track calls, query the status of particular calls, understand the workload, balance resources, identify issues and problems before they became crises, and obtain up-to-date and accurate documentation on work in progress and work completed. In addition, calls would occasionally be lost, as the slips of paper on which they were recorded would get mislaid or inadvertently thrown away.

· Introduction of ITSS.

The initial introduction of the new ITSS system was accompanied by anticipated changes in the nature of both the specialists’ and managers’ work. In contrast to the previous system, which had been designed to capture only a brief description of the problem and its final resolution, ITSS was designed to allow specialists to document every step they took in resolving a particular incident. That is, it was designed to enable the capture of the full history of an incident. As specialists began to use ITSS this way, the focus of their work shifted from primarily research — solving problems — to both research and documentation — solving problems and documenting work in progress.

The ITSS database quickly began to grow as each specialist documented his or her resolution process in detail. While documenting calls took time, it also saved time by providing a rich database of information that could be searched for potential resolutions. Moreover, this new database of information served as an unexpected, informal learning mechanism by giving the specialists exposure to a wide range of problems and solutions. As one specialist noted: “If it is quiet, I will check on my fellow colleagues to see what . . . kind of calls they get, so I might learn something from them . . . just in case something might ring a bell when someone else calls.” At the same time, however, using the ITSS database as a sole source of information did pose some risk because there were no guarantees of the accuracy of the information. To minimize this risk, the specialists tacitly developed informal quality indicators to help them distinguish between reliable and unreliable data. For example, resolutions that were comprehensively documented, documented by certain individuals, or verified by the customer were considered reliable sources of information.

In addition to these changes in specialists’ work, the CSD managers’ use of the new system improved their ability to control the department’s resources. Specialists’ use of ITSS to document calls provided managers with detailed workload information, which was used to justify increased headcount and adjust work schedules and shift assignments on a dynamic and as-needed basis. ITSS also supplied managers with more accurate information on specialists’ work process, for example, the particular steps followed to research and resolve a problem, the areas in which specialists sought advice or were stalled, and the quality of their resolutions. As managers began to rely on the ITSS data to evaluate specialists’ performance, they expanded the criteria they used to do this evaluation. For example, quality of work-in-progress documentation was included as an explicit evaluation criterion, and documentation skills became a factor in the hiring process.

· Structural Changes.

As the CSD gained experience with and better understood the capabilities of the groupware technology, the managers introduced a change in the structure of the department to further leverage these capabilities. This change had not been planned prior to the implementation of ITSS, but the growing reliance on ITSS and an appreciation of the capabilities of the groupware technology created an opportunity for the CSD to redistribute call loads. In particular, the CSD established “first line” and “second line” support levels, with junior specialists assigned to the first line, and senior specialists to the second line. The CSD created partnerships between the less experienced junior specialists and the more experienced senior specialists. Front-line specialists now took all incoming calls, resolved as many as they could, and then electronically transferred calls to their second-line partners when they were overloaded or had especially difficult calls. In addition to handling calls transferred to them, senior specialists were expected to proactively monitor their frontline partners’ progress on calls and to provide assistance.

While this partnership idea was conceptually sound, it regularly broke down in practice. Junior specialists were often reluctant to hand off calls, fearing that such transfers would reflect poorly on their competence or that they would be overloading their more senior partners. Senior specialists, in turn, were usually too busy resolving complex incidents to spend much time monitoring their junior partners’ call status or progress. In response to this unanticipated breakdown in the partnership idea, the CSD managers introduced another opportunity-based structural change. They created a new intermediary role that was filled by a senior specialist who mediated between the first and second lines, regularly monitored junior specialists’ call loads and work in progress, and dynamically reassigned calls as appropriate. The new intermediary role served as a buffer between the junior and senior specialists, facilitating the transfer of calls and relieving senior specialists of the responsibility to constantly monitor their frontline partners. With these structural changes, the CSD in effect changed the prior undifferentiated, fixed division of labor within the department to a dynamic distribution of work reflecting different levels of experience, various areas of expertise, and shifting workloads. In response to the new distribution of work, managers adjusted their evaluation criteria to reflect the changed responsibilities and roles within the CSD.

Another change that emerged over time was a shift in the nature of collaboration within the CSD from a primarily reactive mode to a more proactive one. Because all specialists now had access to the database of calls in the department, they began to go through each others’ calls to see which ones they could help with, rather than waiting to be asked if they had a solution to a particular problem (which is how they had solicited and received help in the past). This shift from solicited to unsolicited assistance was facilitated by the capabilities of the groupware technology, the complex nature of the work, existing evaluation criteria that stressed teamwork, and the long-standing cooperative and collegial culture in the CSD. Several specialists commented: “Everyone realizes that we all have a certain piece of the puzzle. . . . I may have one critical piece, and Jenny may have another piece. . . . If we all work separately, we’re never going to get the puzzle together. But by everybody working together, we have the entire puzzle”; “Here I don’t care who grabs credit for my work. . . . This support department does well because we’re a team, not because we’re all individuals.”10 Managers responded to this shift in work practices by adjusting specialists’ evaluation criteria to specifically consider unsolicited help. As one manager explained: “When I’m looking at incidents, I’ll see what help other people have offered, and that does give me another indication of how well they’re working as a team.”

· Later Changes.

After approximately one year of using ITSS, the CSD implemented two further organizational changes around the groupware technology. Both had been anticipated in the initial planning for ITSS, although the exact timing for their implementation had been left unspecified. First, the ITSS application was installed in three overseas support offices, with copies of all the ITSS databases replicated regularly across the four support sites (United States, United Kingdom, Australia, and Europe). This provided all support specialists with a more extensive knowledge base on which to search for possibly helpful resolutions. The use of ITSS in all the support offices further allowed specialists to transfer calls across offices, essentially enacting a global support department within Zeta.

Second, the CSD initiated and funded the development of a number of bug-tracking systems that were implemented within groupware and deployed in Zeta’s departments of product development, product management, and quality assurance. These bug-tracking applications were linked into ITSS and enabled specialists to enter any bugs they had discovered in their problem resolution activities directly into the relevant product’s bug-tracking system. Specialists could now also directly query the status of particular bugs and even change their priority if customer calls indicated that such an escalation was needed. Specialists in particular found this change invaluable. For the other departments, the link with ITSS allowed users such as product managers and developers to access the ITSS records and trace the particular incidents that had uncovered certain bugs or specific use problems. Only the developers had some reservations about the introduction of the bug-tracking application — reservations that were associated with the severe time constraints under which they worked to produce new releases of Zeta products.

In addition to the improved coordination and integration achieved with other departments and offices, the CSD also realized further opportunity-based innovations and emergent changes within its own practices. For example, as the number of incidents in ITSS grew, some senior specialists began to realize that they could use the information in the system to help train newcomers. By extracting certain records from the ITSS database, the specialists created a training database of sample problems with which newly hired specialists could work. Using the communication capabilities of the groupware technology, these senior specialists could monitor their trainees’ progress through the sample database and intervene to educate when necessary. As one senior specialist noted: “We can kind of keep up to the minute on their progress. . . . If they’re on the wrong track, we can intercept them and say, ‘Go check this, go look at that.’ But it’s not like we have to actually sit with them and review things. It’s sort of an on-line, interactive thing.” As a result of this new training mechanism, the time for new specialists to begin taking customer calls was reduced from eight weeks to about five.

Another change was related to access control. An ongoing issue for the CSD was who (if anybody) outside the CSD should have access to the ITSS database with its customer call information and specialists’ work- in-progress documentation. This issue was not anticipated before the acquisition of the technology. While the managers were worried about how to respond to the increasing demand for access to ITSS as the database became more valuable and word about its content spread throughout the company, they continued to handle each access request as it came up. Over time, they used a variety of control mechanisms ranging from giving limited access to some “trusted” individuals, generating summary reports of selected ITSS information for others, and refusing any access to still others. As one manager explained, only after some time did they realize that their various ad hoc responses to different access requests amounted to, in essence, a set of rules and procedures about access control. By responding locally to various requests and situations over time, an implicit access control policy for the use of ITSS evolved and emerged.

Zeta’s Change Model

Along with the introduction of the new technology and the development of the ITSS application, the CSD first implemented some planned organizational changes, expanding the specialists’ work to include work-in-progress documentation and adjusting the managers’ work to take advantage of the real-time access to workload information. (Figure 2 represents the change model around the groupware technology that Zeta followed in its CSD.) The changes were anticipated before introducing the new technology. As specialists and managers began to work in new ways with the technology, a number of changes emerged in practice, such as the specialists developing norms to determine the quality and value of prior resolutions, and managers paying attention to documentation skills in hiring and evaluation decisions.

Building on these anticipated and emergent changes, the CSD introduced a set of opportunity-based changes, creating junior-senior specialist partnerships to take advantage of the shared database and communication capabilities of the technology and then adding the new intermediary role in response to the unexpected problems with partnership and work reassignment. The CSD did not anticipate these changes at the start, nor did the changes emerge spontaneously in working with the new technology. Rather, the CSD conceived of and implemented the changes in situ and in response to the opportunities and issues that arose as it gained experience and better understood the new technology and their particular use of it. This change process around the group-ware technology continued through the second year at Zeta when some anticipated organizational changes were followed by both emergent and opportunity-based changes associated with unfolding events and the learning and experience gained by using the new technology in practice.

Overall, what we see here is an iterative and ongoing series of anticipated, emergent, and opportunity-based changes that allowed Zeta to learn from practical experience, respond to unexpected outcomes and capabilities, and adapt both the technology and the organization as appropriate. In effect, Zeta’s change model cycles through anticipated, emergent, and opportunity-based organizational changes over time. It is a change model that explicitly recognizes the inevitability, legitimacy, and value of ongoing learning and change in practice.

Enabling Conditions

Clearly, there were certain aspects of the Zeta organization that enabled it to effectively adopt an improvisational change model to implement and use the groupware technology. Our research at Zeta and other companies suggests that at least two sets of enabling conditions are critical: aligning key dimensions of the change process and dedicating resources to provide ongoing support for the change process. We consider each in turn.

Aligning Key Change Dimensions

An important influence on the effectiveness of any change process is the interdependent relationship among three dimensions: the technology, the organizational context (including culture, structure, roles, and responsibilities), and the change model used to manage change (see Figure 3). Ideally, the interaction among these three dimensions is compatible or, at a minimum, not in opposition.

First, consider the relation of the change model and the technology being implemented. When the technology has been designed to operate like a “black box,” allowing little adaptation by users, an improvisational approach may not be more effective than the traditional approach to technology implementation. Similarly, when the technology is well established and its impacts are reasonably well understood, a traditional planned change approach may be effective. However, when the technology being implemented is new and unprecedented and, additionally, is open-ended and customizable, an improvisational model providing the flexibility for organizations to adapt and learn through use becomes more appropriate. Such is the case, we believe, with the groupware technologies available today.

Second, the relation of the change model to organizational context is also relevant. A flexible change model, while likely to be problematic in a rigid, control-oriented, or bureaucratic culture, is well suited to an informal, cooperative culture such as the one at the CSD. In another study, we examined the MidCo organization’s successful adoption and implementation of CASE (computer-aided software engineering) tools within its information systems organization.11 While MidCo, a multinational chemical products company with revenues of more than $1.5 billion, was a relatively traditional organization in many ways, key aspects of its culture — a commitment to total quality management, a focus on organizational learning and employee empowerment, as well as a long-term outlook — were particularly compatible with the improvisational model it used to manage ongoing organizational changes around the new software development technology.

Finally, there is the important relationship between the technology and the organizational context. At Zeta, the CSD’s cooperative, team-oriented culture was compatible with the collaborative nature of the new groupware technology. Indeed, the CSD’s existing culture allowed it to take advantage of the opportunity for improved collaboration that the groupware technology afforded. Moreover, when existing roles, responsibilities, and evaluation criteria became less salient, the CSD managers expanded or adjusted them to reflect new uses of the technology. Compare these change efforts to those of Alpha, a professional services firm that introduced the Notes groupware technology to leverage knowledge sharing and to coordinate distributed activities.12 While the physical deployment of group-ware grew very rapidly, anticipated benefits were realized much more slowly. Key to the reluctance to use groupware for knowledge sharing was a perceived incompatibility between the collaborative nature of the technology and the individualistic and competitive nature of the organization. As in many professional services firms, Alpha rewarded individual rather than team performance and promoted employees based on “up or out” evaluation criteria. In such an environment, knowledge sharing via a global Notes network was seen to threaten status, distinctive competence, and power. In contrast to Zeta, managers at Alpha did not adjust policies, roles, incentives, and evaluation criteria to better align their organization with the intended use and capabilities of the technology they had invested in.

Dedicating Resources for Ongoing Support

An ongoing change process requires dedicated support over time to adapt both the organization and the technology to changing organizational conditions, use practices, and technological capabilities. Opportunity-based change, in particular, depends on the ability of the organization to notice and recognize opportunities, issues, breakdowns, and unexpected outcomes as they arise. This requires attention on the part of appropriate individuals in the organization to track technology use over time and to initiate organizational and technological adjustments that will mitigate or take advantage of the identified problems and opportunities.

At Zeta, the managers and technologists played this role, incorporating it into their other responsibilities. So, for example, the managers adjusted the structure of their department by introducing first-line/second-line partnerships to facilitate a dynamic division of labor and then made further adaptations by introducing an intermediary role to overcome some unanticipated difficulties associated with the initial change. Similarly, the technologists working with the CSD incorporated enhancements to the ITSS system as they realized ways to improve ease of use and access time. The CSD’s commitment to noticing and responding to appropriate changes did not end after the implementation of the technology. The managers clearly realized that the change process they had embarked on with the use of groupware was ongoing, as one manager noted: “We’ve had ITSS for two years. I’m surprised that the enthusiasm hasn’t gone away. . . . I think it’s because it’s been changed on a regular basis. . . . Knowing that [the changes are going to get implemented] keeps you wanting to think about it and keep going.”

Ongoing change in the use of groupware technology also requires ongoing adjustments to the technology itself as users learn and gain experience with the new technology’s capabilities over time. Without dedicated technology support to implement these adaptations and innovations, the continued experimentation and learning in use central to an improvisational change model may be stalled or thwarted. At Zeta, a dedicated technology group supported the CSD’s use of groupware and ITSS. Initially consisting of one developer, this group grew over time as groupware use expanded. After two years, the group included four full-time technologists who provided technology support for the various systems that had been deployed within Zeta via the Notes platform. The group also maintained strong ties with all their users through regular meetings and communications. This dedicated, ongoing technical support ensured that the technology would continue to be updated, adjusted, and expanded as appropriate.

The value of ongoing support to enable ongoing organizational and technological change was similarly important in another organization we studied, the R&D division of a large Japanese manufacturing firm.13 A newly formed product development team within the R&D division installed a groupware technology, the Usenet news system (a computer conferencing system). Similar to the CSD at Zeta, the team’s use of this new technology also iterated among anticipated, emergent, and opportunity-based changes over time. Here, a small group of users who had previously used the groupware technology took on the responsibility to manage and support its ongoing use for themselves and their colleagues. They tracked technology usage and project events as they unfolded, responded as appropriate with adjustments to communication policies and technology functionality, and proactively made changes to the team’s use of the conferencing system to leverage opportunities as they arose.

Conclusion

Global, responsive, team-based, networked — these are the watchwords for organizations of the nineties. As managers redesign and reinvent organizations in a new image, many are turning to information technologies to enable more flexible processes, greater knowledge sharing, and global integration. At the same time, effectively implementing the organizational changes associated with these technologies remains difficult in a turbulent, complex, and uncertain environment. We believe that a significant factor contributing to these challenges is the growing discrepancy between the way people think about technological change and the way they actually implement it.

We propose that people’s assumptions about technology-based change and the way it is supposed to happen are based on models that are no longer appropriate. Traditional models for managing technology-based change treat change as a sequential series of predefined steps that are bounded within a specified time. With these models as a guide, it makes sense to define — as the European navigator does —a plan of action in advance of the change and track events against the plan, striving throughout the change to remain on track. Deviations from the intended course — the anticipated versus the actual — then require explanation, the subtle (and sometimes not-so-subtle) implication being that there has been some failure, some inadequacy in planning, that has led to this deviation. Indeed, many organizational mechanisms such as budgeting and resource planning are based on these notions. The problem is that change as it actually occurs today more closely resembles the voyage of the Trukese navigator, and the models and mechanisms most commonly used to think about and manage change do not effectively support this experience of change.

We have offered here an improvisational change model as a different way of thinking about managing the introduction and ongoing use of information technologies to support the more flexible, complex, and integrated structures and processes demanded in organizations today. In contrast to traditional models of technological change, this improvisational model recognizes that change is typically an ongoing process made up of opportunities and challenges that are not necessarily predictable at the start. It defines a process that iterates among three types of change —anticipated, emergent and opportunity-based — and that allows the organization to experiment and learn as it uses the technology over time. Most importantly, it offers a systematic approach with which to understand and better manage the realities of technology-based change in today’s organizations.

Because such a model requires a tolerance for flexibility and uncertainty, adopting it implies that managers relinquish what is often an implicit paradigm of “command and control.”14 An improvisational model, however, is not anarchy, and neither is it a matter of “muddling through.” We are not implying that planning is unnecessary or should be abandoned. We are suggesting, instead, that a plan is a guide rather than a blueprint and that deviations from the plan, rather than being seen as a symptom of failure, are to be expected and actively managed.15

Rather than predefining each step and then controlling events to fit the plan, management creates an environment that facilitates improvisation. In such an environment, management provides, supports, and nurtures the expectations, norms, and resources that guide the ongoing change process. Malone refers to such a style of managing as “cultivation.”16 Consider again the jazz band. While each band member is free to improvise during the performance, the result is typically not discordant. Rather, it is harmonious because each player operates within an overall framework, conforms to a shared set of values and norms, and has access to a known repertoire of rules and resources. Similarly, while many changes at Zeta’s CSD were not planned, they were compatible with the overall objectives and intentions of the department’s members, their shared norms and team orientation, and the designs and capabilities of the technology.

Effectively executing an improvisational change model also requires aligning the technology and the organizational context with the change model. Such alignment does not happen automatically. It requires explicit, ongoing examination and adjustment, where and when necessary, of the technology and the organization. As such, mechanisms and resources allocated to ongoing support of the change process are critical. Tracking and noticing events and issues as they unfold is a responsibility that appropriate members of the organization need to own. Along with the responsibility, these organizational members require the authority, credibility, influence, and resources to implement the ongoing changes. Creating the environment; aligning the technology, context, and change model; and distributing the appropriate responsibility and resources are critically important in the effective use of an improvisational model, particularly as they represent a significant (and therefore challenging) departure from the standard practice in effect in many organizations.

An improvisational model of change, however, does not apply to all situations. As we have noted, it is most appropriate for open-ended, customizable technologies or for complex, unprecedented change. In addition, as one reviewer noted, “Jazz is not everyone’s ‘cup of tea.’. . . Some people are incapable of playing jazz, much less able to listen to what they consider to be ‘noise.’” We noted above that some cultures do not support experimentation and learning. As a result, they are probably not receptive to an improvisational model and are less likely to succeed with it. As these organizations attempt to implement new organizational forms, however, they too may find an improvisational model to be a particularly valuable approach to managing technological change in the twenty-first century.

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References

1. Berreman (1996, p. 347) as cited in:

L. Suchman, Plans and Situated Actions: The Problem of Human Machine Communication (Cambridge, England: Cambridge University Press, 1987), p. vii.

2. C. Argyris and D.A. Schön, Organizational Learning (Reading, Massachusetts: Addison Wesley, 1978).

3. K. Lewin, “Group Decision and Social Change,” in E. Newcombe and R. Harley, eds., Readings in Social Psychology (New York: Henry Holt, 1952), pp. 459–473; and

T.K. Kwon and R.W. Zmud, “Unifying the Fragmented Models of Information Systems Implementation,” in R.J. Boland, Jr., and R.A. Hirschheim, eds., Critical Issues in Information Systems Research (New York: John Wiley, 1987), pp. 227–251.

4. A.M. Pettigrew, The Awakening Giant (Oxford, England: Blackwell Publishers, 1985).

5. Not all groupware technologies are flexible and customizable (e.g., fixed-function e-mail systems). We are interested here only in those that are (e.g., Lotus Notes).

6. D. DeJean and S.B. DeJean, Lotus Notes at Work (New York: Lotus Books, 1991); and

T.W. Malone, K.Y. Lai, and C. Fry, “Experiments with OVAL: A Radically Tailorable Tool for Cooperative Work (Toronto, Canada: Proceedings of the Third Conference on Computer-Supported Cooperative Work, November 1992), pp. 289–297.

7. H. Mintzberg, “The Fall and Rise of Strategic Planning,” Harvard Business Review, volume 73, January–February 1994, pp. 107–114; and

R.G. McGrath and I.C. MacMillan, “Discovery-Driven Planning,” Harvard Business Review, volume 73, July–August 1995, pp. 44–54.

8. H. Mintzberg, “Crafting Strategy,” Harvard Business Review, volume 65, July–August 1987, pp. 66–75.

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Acknowledgments

We would like to thank the editor and reviewers for their helpful comments on an earlier version of this manuscript. We gratefully appreciate the research support of MIT’s Center for Coordination Science and Center for Information Systems Research.

Reprint #:

3821

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