Abstract Rules are essential for organizations to operate. Applying new rules is a common situation in organizations. The new rules may not be well tailored to the specific context of organizations and modifications will be needed.


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NameAbstract Rules are essential for organizations to operate. Applying new rules is a common situation in organizations. The new rules may not be well tailored to the specific context of organizations and modifications will be needed.
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Absorption of New Organizational Rules:
How Are the New Rules

Adjusted to Context?

Abstract
Rules are essential for organizations to operate. Applying new rules is a common situation in organizations. The new rules may not be well tailored to the specific context of organizations and modifications will be needed. Organizations that succeed in adjusting new rules to their context can gain competitive advantage. Under what circumstances and how organizations adjust new rules to their specific context are the questions this study investigates. By adjust we mean making modifications in the rules in relation to the circumstances the organization faces. Modifications may be by degree of fidelity, or match between what the rules intend and their actual implementation, and uniformity, the extent to which implementation of the rules is similar across users.

Rules are accumulations and residues of learning and problem-solving processes (March, Schulz and Zhou, 2000) that reflect learning an organization has done. They are carriers of organizational knowledge that develop in response to internal and external pressures. They also encourage and initiate new learning. This duality of organization’s rules requires further investigation. How does an organization react when a new rule is applied, what is the process of implementation of this new rule, and, when applying the same rule in different organizations, why are the results different?

Rules are explicit, while routines are tacit (Nelson and Winter, 1982). Rules are written and enforceable, while routines are implicit, inferred from practice and remembered by doing. Although rules and routines are essential for organizations to operate, change in these rules and routines over time has not been adequately investigated. Rules and routines are not only carriers of knowledge, as is usually claimed (Argote, 2000), but also can be the drivers of new knowledge creation. The dynamics of rule generation and implementation lead not only to the birth of new rules but also to rule adjustment. This paper presents a framework for showing how rules become adjusted to an organization’s context over time, how they are carried out as routines, and how the routines change through cycles of knowledge creation.

Knowledge creation cycles lead to continuous modifications of rules so that the rules better fit organizational context. The conversion mechanisms for knowledge creation that Nonaka (1994) has proposed are a major contribution to the development of organizational learning theory (Lewin, 1994). Yet the effects of knowledge conversion processes and their relationship to rule guided behavior and performance have not been adequately explored. While Nonaka’s (1994) theory is powerful, there are few field examples. Based on Nonaka’s (1994) theory, we explain the relationship between rule requirements and rule implementation (March, Schulz, and Zhou, 2000), the effects of rules on an organization’s existing routines (Nelson and Winter, 1982) and how this process leads to the creation of new routines.

The purpose of our study is to derive insights and develop a deeper understanding of how knowledge creation mechanisms at the same time enforce and strengthen routine behavior and act to change it. Our framework for understanding the effects of rules on organizational routines and organizational adjustment is derived from case studies. We did careful analysis of two cases (Yin, 1994) of implementation of the ISO 9000 quality assurance standard (Cole, 1999) using the literature on the dynamics of rules (March, Schulz, and Zhou, 2000) and routines (Nelson and Winter, 1982, Cohen and Bacdayan, 1994), and knowledge creation (Nonaka, 1994; Nonaka, and Takeuchi 1995; and Krogh, Nonaka, and Nishiguchi, 2000) to structure the analysis. Research on the dynamics of organizational rules has concentrated on the birth of rules and not on how rules change over time during implementation (March, Schulz and Zhou, 2000: 3). This study concentrates on how rules change. We begin the paper with the theoretical background, extract propositions, and then analyze the cases about the effects of rules on organizational routines and adjustment.

Rules, Routines, and Organizational Adjustment
New rules can be ambiguous and conflict with an organization’s existing rules and routines. In the way they are implemented they incorporate existing organizational knowledge that is private (Matusik and Hill, 1998) and neither generic nor ambiguous. The private knowledge is embedded in stable routines derived from an organization’s past experience. As repetitive patterns of activity, these routines are a source of organizational competence and competitive advantage (Cohen and Bacdayan, 1994; Douglas and Judge, 2000). As reservoirs of organizational memory (Argote and Ingram, 2000), they constitute codings of inferences from the organization’s experience and the experience of other organizations (Nelson and Winter, 1982, p.97; Cohen and Bacdayan, 1994).

When introduced, organization members must find a fit between new rules and the organization’s old rules and routines (Meyer and Goes, 1988). The old rules and routines represent past knowledge, which has been well suited to the organization’s needs. Over time, learning from experience, members of the organization have to develop means to operate with the new rules. They have to learn how to recognize problems in these rules, how to mobilize attention to these problems, and how to organize coalitions to support changes in these rules, should changes be necessary. Drawing inferences from experience, organization members have to arrive at new routines to use the rule (Meyer and Goes, 1988). This mechanism, where organization members create routines to use rules (see Figure 1) (March, Schulz and Zhou, 2000), affects organizational performance and leads to further revision in rules, routines, and organizational performance (Zbaracki, 1998).

Figure 1

Rules, Routines, and Organizational Adjustment

Organizational

Performance

Rules

(explicit knowledge)

Routines

(implicit knowledge)



Organizational

Adjustment
Routines and Change. Rules that become routines are reinforced over time by repetition as organization members regularly apply them. Lessons encoded in the routines represent knowledge about past problems; they are solutions to yesterday’s problems, but they may not be adequate in dealing with current challenges (March, Schulz and Zhou, 2000). Routines play an important role in organizational learning processes because they retain lessons learned in the past. Since the organizational environment is not stable, in cases where routines are solutions to yesterday problems they help with recurrent problems, but they may not assist in meeting contemporary demands (March, Schulz and Zhou, 2000).

The processes by which organization members suspend their existing routines and initiate changes in rules are not clear. Nelson and Winter (1982) raise the issue of how routines are changed and the question of how the continuity of routinized behavior operates to channel change. March, Schulz and Zhou (2000) suggest that although routines produce stability, they also produce instability and change when organization members use existing routines to search for solutions to unexpected problems with which current routines fail to deal.

A factor that motivates change in routines is an organization’s response to internal and external problems. When existing routines fail to successfully deal with emerging problems, a search for new routines, which can become the material from which new rules are fashioned, is activated. If the new routines stabilize the situation, they may be formalized. That is, they will take on official status as rules and become a more permanent part of the organization’s behavior. However, as long as performance is satisfactory and performance problems not noticed, there is less likely to be change in an organization’s routines or its rules. Only when performance falls below a threshold is attention likely to be directed to the area associated with the failure. Occasional lapses are dealt with by allowing exceptions to the rules, or changes in interpretation, rather than by formal rule revision.

On the one hand, performance feedback buttresses rule-reinforcing mechanisms. Positive performance promotes rules becoming more fixed as routines. It supports sticking to the rules since when performance is positive organization members perceive the rules as favorable. They are satisfied with the rules and not interested in deviations. If the outcomes are good, there is no reason to change. Ironically, negative or no change in performance also can have this effect. If performance declines or does not improve, organization members reason that it is because they are not sufficiently sticking to the rules. However, performance feedback also can lead to rule change. It depends on how organization members respond to this feedback.

Rich feedback loops can enhance and accelerate knowledge creation and enable learning and knowledge acquisition (Senge, 1990; Argote, 1999). By paying attention to feedback, organization members may become conscious of how the results they achieve are a by-product of their routines (Cohen and Bacdayan, 1994) and how the routines can, and should be, modified. Organization members can experiment and learn about the cause and effect relations between the routines they follow and the outcomes they attain.

Reaction to problems is a possible change mechanism, yet there may be a more proactive stance, a mechanism in which routinized behavior itself acts to encourage and channel change before a problem has been raised and rises to the surface. A proactive response can occur when knowledge is created (Nonaka, 1994) through routinzed behavior itself. The routinized behavior becomes a source of new knowledge and understanding, which is incorporated into rules and standard practice. The difference between routine changes as a reaction to problems and routine changes based on knowledge brought to the forefront from practice may be a matter of degree. Nonetheless, there is a difference in whether an outside trigger is needed that comes from the failure of routines to deal adequately with a situation, or whether routinzed behavior itself yields new knowledge from its very undertaking. Carrying out a routine can be a source of discovery, a test of ideas. It depends on the consciousness with which the routines are carried out, the attentiveness of those carrying out the routines, their motivations, the discretion they have, and their room to show initiative. The organization must be willing to make adjustments and have in place a mechanism for learning.

Creating New Organizational Knowledge. Routines are recurrent and automatic processes operating as organizational memory and hence they contain a significant component of non-verbal, unconscious, and unarticulated knowledge (Nelson and Winter, 1982: 99; Cohen and Bacdayan, 1994). When the tacit elements in routines become explicit, they can channel change and formal learning can take place. Examples of the process by which tacit elements become explicit are when useful questions arise in the form of puzzles or anomalies relating to prevailing routines, or problem solving responses are evoked because of difficulties with existing routines (March, Schulz and Zhou, 2000). When there are puzzles or anomalies and problem solving responses are evoked, then the tacit elements may be discussed, verbalized, and committed to writing, and when put into words, however imprecisely there is an opportunity for broadening the discussion, spreading knowledge, and learning.

Tacit knowledge, embedded in everyday routines (Polanyi, 1966; Nonaka and Takeuchi, 1995; Scharmer, 1999) as subjective insights or emotions, exists in non-articulated, personal, and hard to verbalize or communicate form (Polanyi, 1966; Nonaka and Takeuchi, 1995; Scharmer, 1999). It may include mental models and bodily skills that are rooted in a person’s actions and that incorporate a person’s ideals and values as well as his or her experience. In contrast to tacit knowledge, explicit knowledge contains understandings about action that are in concrete and communicable form (Polanyi, 1966; Nonaka and Takeuchi, 1995). It can be expressed in words, numbers, diagrams, figures, formulas, and blueprints, and can be more easily and more broadly shared than tacit knowledge.

Routine behavior leads to the creation of tacit knowledge, but for tacit knowledge, which has its origins in routine behavior, to be a source of learning, this knowledge needs to be made explicit (Nonaka, 1994). It needs to become a rule. By converting tacit knowledge to explicit knowledge, members of an organization can increase their understanding of how the routines they follow lead to specific results (Cohen and Bacdayan, 1994). With this awareness, they can refine and improve the routines. Hence, Nonaka (1994) and Nonaka, Reinmoeller, and Senoo, (1999) have suggested that organizational knowledge is created through a continuous dialogue between what is tacitly understood and what is explicitly known (see Figure 2), with:

  • explicit to explicit being a process of reconfiguring current knowledge through sorting, adding to, re-categorizing, and rearranging existing rules;




  • tacit to explicit being a process of acknowledging learning embedded in routines and making this knowledge explicit;




  • explicit to tacit being a process of assuring the carrying out of refashioned rules as routines in the way rule-makers intend; and




  • tacit to tacit being a process of extracting and developing new knowledge from the shared experience of carrying out the routines.


We propose that:

1:knowledge creation leads to adjustment of rules to organizational contexts; and that
2: knowledge creation is a dialog between tacit and explicit knowledge.

Figure 2:

Rule Adjustment to Context
Applying a new rule
Explicit Explicit
Rule

Tacit Explicit

Tacit Tacit
Routine

Tacit Explicit

Explicit Tacit

Tacit Tacit

Method

The research design we use to develop these propositions is a comparative case analysis of ISO 9000 implementation (Yin, 1984; Eisenhardt, 1989; Brown and Eisenhardt, 1997). We investigate the ISO 9000 quality assurance standard using ISO 9000 as operationalization of the idea of introducing new rules (Cole, 1999). ISO 9000 requires that firms have set rules and procedures for product design, manufacture, delivery, service, and support and that they demonstrate adherence to these routines. By having these rules and demonstrating that they adhere to them, their quality is supposed to go up. The motivation for being registered to the ISO 9000 standard combines the need to satisfy customer requirements with the need to make quality improvements (Anderson, Daly, and Johnson, 1999). The International Standards Organizations in Geneva published ISO 9000 in 1987. Over 100 countries have adopted ISO 9000. ISO 9000 provides customers with assurance that registered suppliers have a quality system to which they must adhere. To guarantee compliance, independent, third party auditors evaluate the suppliers' procedures and carry out site visits. Twice a year they return to the facility to re-verify that it is in compliance.

Although ISO 9000 is a major new organizational innovation its adoption and impact have only started to be studied. We collected data though interviews, observations, and available measures and documentation at two facilities. In total, we did in-depth interviews with 28 people on the management teams at the two facilities (See Appendix A: Case Study Protocol). At both facilities the staff interviewed came from such functions as auditing (both internal and external), quality management, manufacturing, engineering, software development, and documentation.

For our understanding of the facilities’ absorption of a new rule, we relied on the interpretations of the people we interviewed. We looked for common understandings that they shared. We searched for consensus views among those interviewed, some of whom had been at the facilities for more than the ten-year time period covered in the cases and some who had not, but who nevertheless had understandings of the facilities’ histories and the major events that shaped the direction that the facilities took. To the extent possible, we tried to corroborate what the people interviewed said by using the documents. To do the analysis, we used a structured, open-ended interview guide, took copious notes, and collected and read documents that the people gave us. Typically, the interviews lasted from 1 to 1.5 hours and were taped. We also took handwritten notes, and while on-site collected relevant documents. The interview team discussed its impressions with company representatives and had off-site debriefings. We triangulated information from diverse individuals and documents and tried to create a cohesive whole. The published material, interview transcripts and notes, documents, discussions, and debriefings provided the basis for the case studies we wrote.

On this basis, we wrote case studies that rested on broadly shared opinions and versions of events. After completing the case studies, we allowed our main contact and other knowledgeable persons at the facilities to review the cases and incorporated their comments into revised versions.

A limitation of this approach is that the findings are based on the participants’ subjective understandings and perceptions. Another limitation is that the findings have been organized and assembled by outside researchers who may not have completely understood what they were told and how the various pieces of information that they were given fit together.
Results

We present relevant excerpts from the cases, draw comparisons, and derive insights about the process of rule absorption and adjustment to organizational context. A few key concepts (see Table 1) distill the information collected, the rich detail and supporting evidence. They condense our insights into a somewhat parsimonious framework. These concepts were plausible ones that emerged from our reading of the literature and the cases (Glaser and Strauss 1967). As can be seen from the Table, there are differences and similarities in how ISO 9000 is implemented in the two cases. The first case is interspersed with large-scale changes in organizational performance and organizational adjustment; the second is more continuous, with fewer ruptures of this nature. In both cases, the facilities absorb new rules and go through similar stages in knowledge creation, but the large-scale organizational performance and adjustment changes in the first case lead to different results.

Table 1

Rule Absorption and Adjustment




Case A

Case B

Organizational Context

X

X

Organizational Performance

X

X

Organizational Adjustment

X




Organizational Performance

X




Organizational Adjustment

X




Absorption of New Rules

X

X

-explicit to explicit

X

X

-tacit to explicit

X

X

-explicit to tacit

X

X

Organizational Performance

X




Organizational Adjustment

X




-tacit to tacit

X

X

-tacit to explicit

X

X

-explicit to tacit

X

X

Organizational Performance

X




Organizational Adjustment

X




-tacit to tacit

X

X


Particularly noteworthy is the difference in the tacit to explicit process highlighted in the table. At this point in the process, the Case A organization streamlines and contracts its ISO 9000 system, while the Case B organization expands and further develops its system. Case A is an example of convergence, with convergence meaning integrating, narrowing, and exploiting rules for a confined purpose (Van de Ven et. al., 1999). The dominant mode in the convergent stage is exploitation and it involves routinization, customization, and consolidation. Case B is an example of divergence with divergence meaning branching out, expanding, and exploring ideas new directions (Van de Ven et. al., 1999). In the divergent stage, rules expand, and the dominant mode is exploration involving innovation, learning, and making changes in rules and going beyond their literal requirements. We aim to show that these contrasting cycles of convergence and divergence depend on context, that is on performance and organizational adjustments organizations make. Case A is more an instance of adjustments made in response to performance swings, while Case B is more an instance of continuity in performance and knowledge brought to the forefront from practice. To preserve confidentiality we have used fictitious names in referring to these organizations.

Context

GCI

Global Computers Inc. (GCI) Secor is located about 75 miles Southeast of a large metropolitan area, in a town called Secor of about 100,000 people. Since the mid-1950s, the facility’s mission had been connected to midrange computers. Started in 1956 as a manufacturing facility, it began in the early 1960s to design, develop, market, and manufacture its own line of midrange computer products. It changed from being a manufacturing facility to mainly being a development lab for GCI products. It attracted high level people with strong educational backgrounds, and the environment was considered by most employees to be stimulating, exciting, and fast paced. In 1990, GCI Secor had 6,750 employees, about 1.8% of the workforce of GCI as a whole. The employees at Secor, about 2/3rd of whom were engineers, programmers, and other professionals, generated about 10% of GCI’s worldwide revenue. They were one of seven units of GCI U.S., the main site for the business systems line, and responsible for the worldwide development and U.S. manufacturing of business system products. GCI Secor also had responsibility for the development and manufacturing of devices, which were used in GCI’s midrange and personal computers and sold to other original equipment manufacturers. GCI Secor had sister manufacturing facilities in other countries. The midrange computer market in which it competed was estimated to be worth about $26 billion, to which it offered a full range of products costing from $10,000 to $1 million. Though GCI Secor sold to some large companies, most of its customers were small and mid-size businesses (100 to 1,000 employees), 60% of whom were in Europe and the Pacific Rim. Along with DEC, Fujitsu, Hewlett Packard (HP), and Nixdorf, it controlled 60% of this market. Another 200 or so companies also competed in this market.
TI

The roots of Telecomm International Inc. (TI) are as a supplier to the military, but it now functions as a global provider of a broad range of telecommunications equipment. Incorporated in 1961, its corporate headquarters and principal offices are located outside a large metropolitan center. The industry to which TI belongs is highly competitive and is characterized by rapid technological change and frequent product innovation. The demand for telecommunications transmission capacity and services is growing at a rapid rate because of the convergence of computers, fax, cell phones, and the Internet. TI’s products compress, aggregate, segregate, and cross-connect signals that move through copper wires, fiber optics, wireless, and cable. Because they create bandwidth and expand network capacity, they improve performance and provide additional revenue-producing services that meet network operators’ needs. At the start of 1999, about 40% of the company’s employees were involved in manufacturing, about 30% of its employees were devoted to research, with around three-quarters of them engaged in software development, and about 20% of its employees were involved in marketing. TI’s largest customer was Deutsche Telecom (6% of total sales). TI competes with some of the world’s largest and most well-regarded telecommunications suppliers including Alcatel, Ascend Communications, Cisco, Ericsson, Lucent, Mitsubishi, NEC, Nokia, Northern Telecom, Siemens, and 3Com. In 1998, 24% of TI’s sales were in North America, 48% were in Europe, 20% were in Africa, Asia, and Australia, and 8% were elsewhere.
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