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Article Excerpt
1. Introduction
Where constant changes and high uncertainties are the norm, a learning orientation toward quality improvement becomes critical to sustained organizational performance (Sitkin et al. 1994). Learning and knowledge creation are related. Prior studies have investigated learning in quality, but most have inferred knowledge from some forms of learning (e.g. Lapre and Van Wassenhove 2001, Mukherjee et al. 1998). There is limited study on the direct impact on knowledge itself. In the knowledge-based view of the firm, knowledge represents a strategic resource that the firm uses to develop sustained competitive advantage (Kogut and Zander 1992). In this study, knowledge is defined as new ideas, improved understanding, and the capability of a team doing a quality project. To better capture how knowledge is generated, we differentiate knowledge from learning. We study learning as behaviors that involve information seeking, discussions, and asking questions. Therefore, learning behaviors can be viewed as a process variable and knowledge created as an outcome measure. Given the cognitive nature of knowledge creation and learning, we investigate two cognition-influencing mechanisms--method-driven and psychologically driven--and their influence on organizational members' cognitive processes to learn in a quality improvement setting. The method mechanism represents a structured and technical approach, and the psychological mechanism an unstructured and social approach, to knowledge creation and learning. While it is possible that a strong adherence to a method such as Six Sigma could stifle learning behaviors and hinder improvement efforts, it is also possible that the psychological effects could dominate the method effects because of human biases against following a method (Boiral 2003). The relative importance of the method and psychological effects on learning behaviors and knowledge creation, however, has not been directly examined in prior literature.
This research found that the method mechanism and psychological mechanism exhibit different and independent effects on learning behaviors and knowledge creation. The method mechanism influences learning behaviors, while the psychological mechanism affects knowledge directly. This finding suggests that the value of adhering to a method in quality improvement settings, such as Six Sigma, may lie in modifying the learning behaviors, which combines well with the effect of the psychological mechanism on knowledge creation. Such combined effects can alter the learning path of a firm and have an impact on the effectiveness and sustainability of a quality program. This study uses Six Sigma as an example, but the theory is not based entirely on Six Sigma.
2. Theoretical Development
Among some researchers, quality management is viewed as problem solving: "Quality management is the quest for improvement in organizational routines through the application of a particular collection of problem-solving heuristics and techniques" (Winter 1994, p. 93). The use of the scientific method is a distinctive feature in quality improvement that represents an important source of learning (Hackman and Wageman 1995). It is associated with conceptual learning and the creation of know-why in quality improvement projects (Mukherjee et al. 1998). Besides the scientific method, problem-solving heuristics--such as the flow chart and cause-and-effect diagram--help teams use their knowledge collectively to identify and analyze opportunities to improve quality (Hackman and Wageman 1995, p. 314). Quality improvement projects usually assume a structured process much like a traditional problem-solving model with problem identification and diagnosis, followed by solution generation and implementation (MacDuffie 1997, March and Simon 1958). A commonly applied problem-solving model in quality management is the PDCA (Plan-Do-Check-Act) cycle (Deming 1986, Shewhart 1939). Taken together, a typical quality improvement process combines a problem-solving model and a collection of statistical and nonstatistical tools.
In a Six Sigma project, these problem-solving elements are integrated into an overall structured method, consisting of specific problem-solving steps with recommended statistical and nonstatistical tools in each step. The Six Sigma method can be defined as "A method that sequences and links improvement tools into an overall approach" (Snee 2000, p. x). Using this structured method is a key component in Six Sigma projects (Pande et al. 2000). A structured method such as Six Sigma can provide a rational and systematic way of capturing and generating knowledge. Like artificial intelligence, it assumes a programmatic approach to learning and creating knowledge (Ericsson and Hastie 1994). From this vantage point, a structured method that is a standardized problem-solving process, can be viewed as a metaroutine that systematizes the problem-solving process (Adler et al. 1999). A structured method, then, represents a cognition-influencing mechanism that leads to learning behaviors and knowledge created in quality improvement teams.
Besides a structured method, quality improvement contains a psychological component. Any sense of threats, such as punishment for failures and fear of judgment, can pose a negative effect on the cognitive processes in people and prevent the organizational members from learning effectively and identifying opportunities for quality improvement (MacDuffie 1997, p. 499). In the organizational learning literature, Edmondson (1999) developed a sociopsychological construct called psychological safety that affected team learning. Psychological safety is a shared belief held by team members that the team is safe for interpersonal risk taking. A psychologically safe environment frees the team members to explore various problems as opportunities for quality improvement. Viewing problems as opportunities is particularly important at the problem-definition stage (MacDuffie 1997). The larger the opportunities defined in early problem definition, the greater the amounts of learning and improvement tend to follow (Levin 2000, p. 631). Psychological safety, thus, represents another mechanism that influences the cognitive processes in teams. We studied these two specific mechanisms--method-driven and psychologically driven--that influence the cognitive processes leading to learning behaviors and knowledge created in quality teams.
Quality management settings are learning oriented; however, ineffective implementation can result in learning failures and antilearning group norms (Hackman and Wageman 1995, p. 333). Causes of such problems include misalignment between the reality and rhetoric (Zbaracki 1998) and resistance among organization members, which generally result in inconsistencies in quality implementation (Boiral 2003). Benner and Tushman (2003) argued that inconsistencies in quality could be caused by the tension between exploitation and exploration. Exploitative learning is variance reducing and exploratory learning is variance seeking (McGrath 2001). Learning in quality settings, however, is generally associated with the reduction of variation (Anderson et al. 1994, p. 485). Variance reduction is most evident in process management techniques--mapping processes, improving processes, and adhering to improved processes--that emphasize efficiency and incremental knowledge (Benner and Tushman 2003). Adhering to a method such as Six Sigma can be viewed as predominantly variance reducing and exploitative. In contrast to variance reducing, variance seeking is associated with creativity and generation of novel ideas and innovative solutions that require divergent thinking and access to a variety of alternatives. Variation fosters creative abrasion between diverse viewpoints producing learning about new ideas for innovations (Leonard-Barton 1995). Although organizational members may use a number of tools in quality improvement, nonroutine and less familiar problems are likely to require creativity (Victor et al. 2000, p. 109). When people are put into a psychologically safe environment, creativity and exploration are likely to occur. The difference between variance-seeking (exploratory) and variance-reducing (exploitative) activities, however, can lead to tension in quality settings (Benner and Tushman 2003). To a certain extent, investigating the relative importance of method and psychological mechanisms could offer a better understanding of this potential tension in quality management.
Few empirical studies relate quality and learning. In a case study of quality improvement in three auto assembly plants, MacDuffie (1997) studied the problem-solving process in three specific problem categories--water leaks, paint defects, and functional electrical defects. He found that quality improvement can benefit from rich data that capture multiple perspectives of a problem, from being flexible in categorizing problems, and from organizational structures that facilitate the development of common language to discuss problems. Effective quality improvement depends on how the organization influences its members' cognitive processes and presents problems as learning opportunities. Levin (2000) also studied auto assembly plants, but he focused on car models produced from year to year. He found that the largest amount of learning and improvement happened before introducing the newest car model (disruptive learning). Subsequent introductions represented only minor updates and incremental improvements (the learning curve effect).
Quality improvement depends not only on the production experience, but also on the intensity of offline quality improvement activities and transfer of knowledge over time. In quality improvement projects, Mukherjee et al. (1998) investigated why some projects are more effective than others and found considerable variation along two dimensions of learning in quality improvement projects--conceptual learning (know-why) and operational learning (know-how). Subsequent studies found that projects that acquired both know-why and know-how accelerated the factory's learning rate (Lapre et al. 2000), and that management buy-in and knowledge diversity facilitated knowledge creation and transfer of technological knowledge to other factories (Lapre and Van Wassenhove 2001). Quality-based learning is a function of proactive investment in quality improvement and autonomous learning-by-doing rather than reactive learning from defect reduction (Ittner et al. 2001). Generally, quality-based learning is studied mostly as learning curve models (e.g., Fine 1986, Li and Rajagopalan 1997).
Although prior studies have investigated some forms of learning, there is limited understanding of the direct impact on knowledge. Studying knowledge and learning behaviors together enables us to investigate their relations and interactions with respect to the method and psychological mechanisms and to understand knowledge as a strategic resource. Instead of...
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