Chapter 1: Introduction

According to Groff and Jones, Knowledge Management can be defined as “The tools, techniques, and strategies to retain, analyse, organize, improve, and share business expertise” (Groff and Jones, 2003). It involves the collection, management and apportionment of the tacit as well as explicit knowledge throughout the organization. Moreover, in this case study, the knowledge management has been used to improve the learning and performance of the professionals through the concept of Knowledge Life Cycle and the Critical Incident Analysis framework in a walk-in software help desk situated in a research university. For an organisation, the knowledge base of its employee is the key for the competitive edge and this case study shows how the management of knowledge in an organisation will help their employees in identifying the critical incidents and share the information related to it with the team. Such an approach will increase the effectiveness of the team to deal with the unknown incidents and improve their responsiveness towards it.

Chapter 2: Literature Review

The objective of this chapter is to give an overview of the literature surrounding the concepts of this study. The theory of knowledge and the knowledge life cycle are studied as well as the supporting concepts focused on the Theory of Organisational Knowledge Creation by Nonaka, Takeuchi and Tokama. The critical success factors related to the management of knowledge life cycle are discussed. Moreover, a vital concept that lays the foundation for this study is the literature surrounding how knowledge should be studied in organisations, so the chapter ends with the HPT model and its relationship with IDT. It also covers the study related to the Critical Incident Technique (CIT).

Definitions of Knowledge

Many definitions of knowledge proposed by several authors exist and they all emphasize on relationship between knowledge and information, how they are not synonymous or interchangeable. According to Kerssens-Van Drongelen, De Weerd-Nederhof, and Fisscher (1996) define knowledge as “information internalized by means of research, study or experience that has value for the organization”. Davenport, De Long and Beers (1998) give a more detailed definition that defines knowledge as “information combined with experience, context, interpretation, and reflection; a high value form of information that is ready to apply decisions and actions”. Hence, Knowledge can be defined as the meaningful set of information that adopts a pragmatic view of knowledge focused on the organisational context (Nonaka & Van Krogh, 2009).

Knowledge Life Cycle

According to Fahey and Prusak (1998), knowledge can be viewed as a flow. As a flow, it is apparent that the knowledge is changing and can be embedded in the day to day activities of the organisation. In relation to this, several authors have proposed that knowledge can be viewed as a life cycle. The complexities of all the model varies but they all start from “create” phase and provide a way to break down how knowledge flows through an organisation. Three representations of knowledge life cycle will be examined in this discussion:

Haney’s Model. Haney (2006) proposes that knowledge be viewed as a life cycle with seven phases (see figure 1). The first two phases are to create or learn and identify. They initiate the start of the knowledge life cycle through acquisition. Before or after acquisition, identification of what is important and useful to organisation is done. The third phase is to organise and codify the knowledge and can be stored in secured and easily accessible location. The final three phases involve distribution, usage and maintenance of the knowledge. Maintaining also involves monitoring the usage of knowledge and training & support for users (Haney, 2006).

Brikinshaw and Sheehan’s Model. This model represents the knowledge life cycle as a S-curve where knowledge cycles through four stages, “creation, mobilization, diffusion and commodization”. Time is an added variable in this knowledge life cycle because as knowledge progresses through the various stages of the life cycle, the people who have access to it increases.

Creation is the stage where an idea is conceived and the knowledge is in the individual’s head. This is considered as an abstract insight gained through experience and experimenting. Mobilization is where the idea moves from the individual’s head and takes a form which can be shared and tested. Diffusion is where the idea is fully developed if it survives the mobilization phase. Now the idea is publicly available for others to learn and replicate. Lastly, commodization is where the idea becomes a part of a discipline that it becomes a common knowledge. Moreover, the speed of flow of knowledge varies in different contexts. Factors like competition stealing information, information leakage, and intentional documentation and sharing increases the rate of knowledge flow while factors like intellectual property rights and the extend that the knowledge is hard to imitate, decreases the rate of flow.

Salisbury’s Model. Salisbury (2008) presents a more simplistic view of knowledge as a life cycle which consist of three phases, create, preserve and disseminate. Salisbury’s Model emphasize on the problem solving, thus makes it suitable for this case study as the study seeks to examine the flow of knowledge that evolves from critical incidents. Creation occurs when a new or unique problems are solved holistically, Preservation involves the documentation of the problem and how it was solved while Dissemination involves the knowledge sharing among employees as well as the stakeholders affected.

The next iteration of the ongoing knowledge life cycle will help create new knowledge when it is used to solve future problems which will further improve the competence of the organisation.

Types of Knowledge

Throughout the knowledge life cycle, knowledge takes different forms and functions. However, explicit and tacit are among the most widely used classifications of knowledge (Gourlay, 2006; Rosenberg, 2012). Explicit knowledge can be articulated and documented, which makes it easy to share. This knowledge can be found in books or manuals and is used in formal training as well (Nonaka, 1994; Nonaka & Takeuchi, 1995; Rosenberg, 2012; Smith, 2001). However, Tacit knowledge is the knowledge that is in people’s heads. It comprises of intuition and common sense. It is not verbalized but plays a vital role in how people solve problems or devise solutions. It is best developed and shared in informal ways, through work experiences, interacting with co-workers or coaching (Smith, 2001). Nonaka and Takeuchi (1995) categorised tacit knowledge in two dimensions: technical and cognitive. They used the phrases like “know-how” and “how-to-pin-down” to describe the technical dimension while cognitive dimension refers to the perceptions and innate patterns of thinking.

Knowledge Management

The transformation of tacit knowledge into explicit knowledge is crucial because it provides an organisational view of knowledge rather than an individual view, which benefits the entire community. This is one of the key objective of the knowledge management. Thus, “knowledge management is the process of controlling or directing the creation, identification, organization, storage and dissemination, and maintenance of knowledge to support strategic goals” (Haney, 2006, p. 620). Such a KM environment in an organisation encourages the flow of knowledge among the employees and help them maintain a competitive advantage. This supports organisational learning and facilitate the flow of knowledge (Birkinshaw & Sheehan, 2002; Haney, 2006; Salisbury, 2008).

Organisational Knowledge: Evolution and Creation

The study of organisational knowledge is not a new discipline. Classical works of economists such as Edith Penrose and Fredrick Hayek and philosophers such as Michael Polanyi focused on the team work and the importance of organisational members’ knowledge to a firm’s economic processes (Easterby-Smith and Lyles, 2011). The most popular work emerges from the work of Nonaka and colleagues in the Theory of Organisational Knowledge Creation (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001). Their theory is based on the interaction of between tacit and explicit knowledge and that the organisational knowledge creation is derived from the interrelationship between the tacit and explicit. It emphasizes on knowledge creation on varying levels within an organisation such as individual, group and organisational. Nonaka and Takeuchi proposed a knowledge creating spiral and the knowledge conversion process to capture the individual knowledge and assimilate it to organisational knowledge.

Knowledge Conversion Model. According to Nonaka and colleagues, knowledge is created through the interaction between the explicit and tacit knowledge in four knowledge conversion processes referred as SECI model (Socialisation, Externalisation, Combination and Internalisation). This model illustrates how personal knowledge gets transformed into the organisational knowledge. That is, from tacit knowledge to tacit knowledge (Socialization), from tacit knowledge to explicit knowledge (Externalization), from explicit knowledge to explicit knowledge (Combination), and from explicit knowledge to tacit knowledge (Internalization).

Knowledge Spiral. Knowledge conversion is not a linear process, it is a continuous dynamic spiral through the four modes of knowledge conversion. Nonaka and Takeuchi refers elevation and movement of knowledge as the “cross-levelling” of the knowledge and they assert that the spiral starts from the socialisation through interaction. This build something where members of the organisation can share experiences and schema. Then through dialogue, externalisation happens where members express the tacit knowledge. Then the combination mode is activated by connecting previous and newly formed explicit knowledge. Then all the newly formed knowledge is applied and integrated in practice. Internalisation is triggered by “learning by doing”.

Tripartite layered model of knowledge creation. The SECI model is now part of a tripartite layered model of knowledge creation where all the elements must interact to form a spiral of knowledge creation (Nonaka, Toyama, et al., 2001; Nonaka, Toyama, & Konno, 2000). The other components of the model are “(b) ba, platforms for knowledge creation; and (c) knowledge assets, or the inputs, outputs and moderator of the knowledge creation process” (Nonaka, Toyama, et al., 2001, p. 493). Ba. According to Nonaka and colleagues (Nonaka & Konno, 1998; Nonaka, et al., 2001; Ikujiro Nonaka, Ryoko Toyama, & Noboru Konno, 2000), ba is a Japanese concept that basically means “place” in English and evolved out of the work of Japanese philosopher Kitaro Nishida and was later expanded by Shimizu. However, in the context of the tripartite model ba is defined as, “a context in which knowledge is shared, created, and utilized, in recognition of the fact that knowledge needs context in order to exist” (Nonaka, Toyama, et al., 2001, p. 499). Ba is crucial to the knowledge creation process and emphasize the importance of teams in creating shared context and it is through interaction in this shared context that new knowledge 28 emerges and knowledge moves from the individual to the organization (Ikujirō Nonaka & Hirotaka Takeuchi, 1995). Ba refers to place in the most generic sense and is not limited to a physical space, but includes virtual and mental space, as well as a combination.

Critical Success Factors

Studies (Cho, 2011; Gold, Malhotra, & Segars, 2001; Haney, 2006; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001) have identified several success factors that foster an organization’s effective iteration and management of the knowledge life cycle. These factors tend to span a wide range of organizational areas from people, culture, to technology. According to Haney (2006), there are seven critical success factors that must be considered when managing the knowledge life cycle: people, culture, technology, processes, structure, leadership, and measurement. Gold et al. (2001) proposed similar factors in the form of knowledge 35 capabilities. They group many of the factors mentioned by Haney (2006) under two broad categories of knowledge capabilities: Knowledge Infrastructure Capability (technology, structure, culture) and Knowledge Process Capability (acquisition, conversion, application, protection). Cho (2011) modified the KM capabilities framework proposed by Gold et al. (2001) by adding incentive under knowledge infrastructure capability. Nonaka and Takeuchi (1995) refer to the success factors as enabling conditions and posit that an organization must foster these conditions for knowledge to spiral effectively through the knowledge life cycle. The enabling conditions are intention, autonomy, fluctuation and creative chaos, redundancy and requisite variety.

HPT (Human Performance Technology) and IDT (Instructional Design and Technology)

Some definitions of IDT allow one to see a clear distinction between the two fields, with IDT being focused on instructional solutions and HPT being more general to performance improvement (Gustafson & Branch, 2002; Smith & Ragan, 1999). However, other definitions incorporate HPT into the definition of instructional design making it difficult to see a distinction (Rothwell & Kazanas, 2008). This could be since “trainers are transitioning away from their traditional role of emphasizing instructional solutions and moving toward solutions designed to address the root causes of performance problems” (Rothwell, Hohne, & King, 2007, p. 13). The International Society for Performance Improvement defines HPT on their website as: A systematic approach to improving productivity and competence uses a set of methods and procedures — and a strategy for solving problems — for realizing opportunities related to the performance of people. More specific, it is a process of selection, analysis, design, development, implementation, and evaluation of programs to most cost-effectively influence human behaviour and accomplishment. It is a systematic combination of three 39 fundamental processes: performance analysis, cause analysis, and intervention selection, and can be applied to individuals, small groups, and large organizations. (ISPI, 2012) In defining HPT Klein (2010) highlights the link to IDT by stating that, “human performance technology (HPT) expands the scope of instructional design and technology (IDT) by employing the systems approach to address a problem or realize an opportunity” (p.135).

HPT model. The HPT model (see Figure 8) is proposed by researchers (Haney, 2006; Massey et al., 2005; Schwen et al., 1998) as an effective framework to study KM practices in a 40 organization and has been successfully used to study knowledge flow, structure and patterns in organizations. The HPT model was initially designed by Deterline and Rosenberg and was published in 1992 by the International Society for Performance Improvement (ISPI). The model acts as a guideline for practitioners, providing them with specific things to do, illustrating feedback loops, and focusing on examining the interrelationships that exist among various organizational factors (Van Tiem, Moseley, & Dessinger, 2000).

Performance analysis of need or opportunity. The performance analysis of need or opportunity stage, as the current HPT model (Figure 8) illustrates, includes organizational analysis, environmental analysis, gap analysis and, cause analysis. In performance analysis, the HPT practitioner investigates the current situation in the organization. This involves learning about the organization’s culture, policies, processes, and exactly what is happening. The practitioner also tries to capture the desired situation and expectations. Therefore, the performance analysis phase focuses on three primary areas: ascertaining the current performance state of the organization, the desired 43 performance state and the gaps between desired and actual performance (Rothwell, 2000; G. Rummler & Brache, 1995; Van Tiem et al., 2000). Environmental factors are also examined, since they impact performance as well.

Critical incident technique. CIT is a cognitive task analysis method (Crandall et al., 2006; Hanson & Brophy, 2012). CIT has its roots in Industrial Organizational Psychology since World War II where it was developed by John Flanagan who used it to analyze 50 success and challenges of aviation training (Butterfield, Borgen, Amundson, & Maglio, 2005; Flanagan, 1954; Hettlage & Steinlin, 2006). Since its inception over fifty-years ago, CIT has evolved and is recognized as a very reliable and valid tool for qualitative investigations (Butterfield et al., 2005; Chell, 2004; Chell & Pittaway, 1998). CIT does not refer to a strict specific set of rules, but the methodology is governed by principles that must be adjusted to meet the needs of the context and subject being studied (Flanagan, 1954) The main principles are that facts surrounding an incident can be effectively studied through collection of various perspectives, and data should only be collected regarding activities that have proven to have a significant impact on what is being studied (Flanagan, 1954). CIT also helps with eliciting authentic information; as interviewees become immersed in their narratives they tend to give detailed responses and not what they think the interviewer would like to hear and in the process, tacit knowledge is evoked (Hettlage & Steinlin, 2006).

Chapter 3: Review of KMS

Studying SHD through the lens of the knowledge life cycle approach allowed for a detailed understanding of the flow of knowledge and the identification of the KM gaps. This case study therefore, validates using this approach for other organizational case studies that aim to investigate knowledge flow within an organization. The iterative and interconnected nature of the knowledge life cycle was confirmed, as well as the importance of systems and processes that facilitate the entire knowledge life cycle. All phases must be facilitated for efficient KM to occur and by extension organizational learning (Alavi & Leidner, 2001; Argyris & Schön, 1996; Dalkir, 2011; Nonaka, 1994; Salisbury, 2008, Van Tiem et al., 2012). The knowledge life cycle is enabled by both individual and environmental factors in a system that integrates KM and its core work processes (Dalkir, 2011; Nonaka, 1994; Salisbury, 2008; Van Tiem et al., 2012). The process of “making” connections through the knowledge life cycle is quite like the principles of the Theory of Organizational Knowledge Creation (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001).

Knowledge life cycle and the theory of organizational knowledge creation. The knowledge life cycle as observed in SHD, is a constantly renewing cycle where existing knowledge is built on to form new knowledge. The way the flow of knowledge occurred through making internal and external connections within a shared space, or as a “connecting platform,” aligns with Nonaka and colleagues’ (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka & Konno, 1998; Nonaka et al., 2000; Nonaka, Toyama, et al., 2001) SECI conversion model and the concept of ba. The SECI conversion model is based on the premise that knowledge is created through various conversion modes between tacit and explicit knowledge (socialization, externalization, combination, and internalization), as individuals interact with each other within a shared space called ba. The whiteboard was very central to the knowledge flow of SHD and enabled all the knowledge conversion modes which facilitated movement along the knowledge life cycle.

1. It was evident that the technicians had a lot of tacit knowledge. In trying to explain the problems, they could articulate the reasons behind the actions. This is a form of what Nonaka & Takeuchi (1995) call externalization, where tacit knowledge is converted to explicit.
2. Externalization was also seen whenever a technician wrote on the whiteboard.
3. An example of Nonaka & Takeuchi’s (1995) idea of internalization (explicit to tacit) was when a technician wrote something on the whiteboard and another technician integrated that knowledge to solve a new problem or even connected the ideas to what was already done to find a solution. This is also an example of the knowledge life cycle occurring, with the application of preserved knowledge that has been disseminated being used to create new knowledge. This indicates the iterative and interconnected nature of the knowledge life cycle.
4. Combination (explicit to explicit) was evidenced when information was combined on the whiteboard and then used to create a website tutorial or add to the wiki, enabling creation, dissemination and preservation.
5. Socialization was also evident; Nonaka and colleagues highlight that for socialization to occur, there must be some shared experience and this is in fact where the knowledge creating spiral begins. Working on trying to solve critical incidents together created a shared experience for SHD members and having the whiteboard and an open area in which to work, their “ba”, fostered this. The comment by the supervisor that he had learned more from the technicians than he had from any explicit source aligns with socialization.

It also highlights that not all knowledge can be captured explicitly in an organization, but by having a shared space or environment that connects members with various expertise in the organization knowledge flows (Dalkir, 2011; Rosenberg, 2012; Salisbury, 2008). In the context of SHD, this worked through asking for help and extending help, which were influenced by awareness of expertise. As Salisbury (2008) points out, organizational knowledge is complex and platforms are needed to connect people for organizational learning to occur. Salisbury (2008) asserts that organizations can manage the knowledge through “direct connection [emphasis added] between two or more people or by facilitating processes where those who need to know something can be connected [emphasis added] to those who know it”. From the discussion above a relationship between the knowledge life cycle and the Theory of Organizational Knowledge Creation (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001) was established. This relationship was hinted on in Salisbury’s (2008) article where he proposed a Collaborative Cognition model that integrated the knowledge life cycle as an extension of the SECI knowledge conversion model (socialization, externalization, combination, internalization).

Moreover, the Theory of Organizational Knowledge Creation (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001) useful in explaining the “how” of the knowledge life cycle confirms that viewing an organization’s KM activities through the lens of the knowledge life cycle is not sufficient on its own to describe the dynamics of KM in an organization, as Dalkir (2011) points out: From a practical perspective, in order to manage knowledge, it is also necessary to have an organizing principle-a framework-to classify the different activities and functions needed to deal with all the knowledge-related work within and between organizations. This framework is often encapsulated in the form of a theory or model of KM. Thus, organizations and/or researchers wishing to use the knowledge life cycle approach to study an organization should be sure to complement it with a KM theory or model that matches the context studied.

Impact of individual and environmental factors. Several authors have posited that KM involves multiple factors to be effective, which include, culture, leadership, and technology, as well as others (Cho, 2011; Haney, 2006; Mertins et al., 2001; Nonaka & Takeuchi, 1995; Rosenberg, 2012). The findings from this study indicate that complementary individual and environmental factors are needed for effective KM to occur. Nonaka and Takeuchi (1995) specifically address five enablers to navigating the knowledge life cycle: intention, autonomy, fluctuation and creative chaos, redundancy and, requisite variety. SHD exhibited intention and autonomy through its culture, mission, vision, and leadership. For example, SHD’s visions of having a system for “consolidating” their knowledge, is an example of intention. The culture proved to be a positive one that enabled the workers to work together and exercise a level of autonomy which led to knowledge creation. Nonaka and Takeuchi (1995) speak of fluctuation and creative chaos as vehicles for creating knowledge. One characteristic of this is to have some form of structure, but with room for comfort with ambiguity. SHD has a systematic way of doing things, as seen in their various processes. However, by dealing with critical incidents, fluctuation is created and creative chaos begins, thus leading to knowledge creation. Nonaka and Takeuchi (1995) emphasize that creative chaos can only work if people are reflecting while acting and this may explain why SHD did not go in a state of panic whenever a critical incident occurred, as the whiteboard system allowed them to “reflect while in action.” According to Nonaka and Takeuchi (1995) redundancy refers to organizational members having a shared repertoire through repeated engagement in similar activities. This was evidenced through the training sessions, and access to the wiki and other knowledge bases. Redundancy was also created through disseminating information on the whiteboard which was visible and central. The other enabler is requisite variety, which refers to having varying skillsets among workers. This was the case for SHD; all the workers had the basic technical knowledge and skillset that was needed in addition to their varying skills. It is commendable that both environmental and individual factors that enable movement along the knowledge life cycle were evidenced in SHD. This is in line with the literature that purports that these factors will influence how knowledge flows and will affect any implementation of a KM system or changes to an existing one (Cho, 2011; Gold, Malhotra, & Segars, 2001; Haney, 2006; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001).

Alignment between core work processes and the knowledge life cycle. For knowledge to spiral through an organization, the connecting platform must not only connect the workers and their processes, but should also ensure that the processes of the knowledge life cycle are connected (Dalkir, 2011; Heisig, 2001; Rosenberg, 2012; Salisbury, 2008). SHD’s biggest challenge, as seen from the data, is tying the phases together. If the phases are fragmented then the value is lost. This situation is not unique to SHD. According to Heisig (2001), KM activities are integrated in the day to day activities and so it is not normal for tools and processes to be geared towards creating, disseminating, and preserving knowledge, rather they are designed to accomplish various work related task. Heisig (2001) provides an example of the results of such disconnection between the knowledge life cycle and core work tasks that is applicable to SHD, that of a database being built, but not used by members or lessons learned are not generated from the application of knowledge. The whiteboard worked for SHD as it provided the interconnectivity between the core processes and the knowledge life cycle. One core process of SHD is to find solutions for computer problems and the whiteboard provided a way for that knowledge to be created, disseminated and temporarily preserved. However, it was not as effective as it could be, due to limitations of space and permanence. Birkinshaw and Sheehan (2002) highlight that there is value in studying organizational knowledge from a life cycle perspective because it gives an opportunity to see where the strengths and weaknesses of an organization are and strategize accordingly. The results of such an analysis would reveal the level of connectivity and identify gaps between KM strategies and core processes of the organization. Based on the evidence provided, SHD does a very excellent job at creating knowledge, but its weakest area was preserving knowledge in a form that could be integrated with its existing processes, so that it can be applied and fed back into the knowledge life cycle. Knowledge was preserved in the “heads” of organizational members. However, because these are student workers and some workers are temporary, there is a risk that information may not be passed on. As Argyris and Schön, (1996) point out, organizational knowledge gets lost if the only holding place is in the heads of its members; preventing true organizational learning from occurring. SHD’s most pressing need seems to be environmentally related in the form of a technology tool. Although there could be possible improvements with regards to individual capability such as searching for information more effectively, the technicians demonstrated that they possessed the dominant knowledge, skills, and capabilities to effectively perform their tasks. All the intersecting fields of this research: KM, IDT, HPT, and organizational learning share the tenet that technology should not be selected without first examining the context in which the system will be used.

Chapter 4: Critical Discussion

SHD was the population for this case study and thus by working for SHD all consenting employees were potential participants of this study. This case study adopted a phasic approach and participants varied primarily by participation in the Critical Incident Analysis, and Understanding the System phases of this study. Significant amount of the contextual information was collected from the leadership team comprised of the director of information technology, the manager of information systems and the SHD supervisor. In the framework influenced by HPT that was used for data collection and analysis of this study, the Understanding the System phase was broken down into Organizational Analysis and Environmental Analysis. Organizational Analysis aimed primarily at ascertaining the vision, mission, goals and strategies of SHD and more specifically the vision as it pertains to KM, while Environmental Analysis zoomed in on the reality of SHD and how things are done especially with regards to KM.

Organizational analysis summary. SHD is a growing organization with visions of expanding services. One of their distinguishing features is that they ensure that all problems are fixed; if they can’t fix it they will refer the student to someone who will fix it. Their motto of “to work on it until it’s fixed” helps them in meeting their measure of success, which is that students have technology they can use in class. The leadership structure may be described as middle-top down as the supervisor reports to the manager and the manager reports to the director. Despite varying hierarchal levels the director, supervisor, and manager work as a team. Planning is done together in a form of brainstorming meeting. Regarding KM, SHD has a vision of using technology to integrate their KM processes and make the process more seamless and efficient

Environmental analysis. The main body that influences the operations of SHD is the college’s council that determines the computer requirements. They have an input in determining the requirements and the director is a member of the council. A genuine interest in helping others and autonomy and input were two dominant themes that emerged in describing SHD’s culture and was seen at all hierarchical levels of the organization. SHD ensures that the technicians hired are in line with their culture and possess more than just technical skills. SHD has several technology and non-technology resources in place that enable them to work efficiently. Among the technology resources/systems are a log in system and file server, and among the nontechnology resources/systems are two whiteboards and an information sheet.

Summary of Critical Incident Analysis. For the Critical Incident Analysis phase of this study data was collected using CIT for a focus group session, in Summer, 2013, and for individual interviews with technicians in Fall, 2013. The focus group session provided baseline data of previous experiences with critical incidents. In Fal1, 2013 11 critical incidents were reported and a total of 19 individual reports were collected for the 11 incidents. The nature of the uncommon problems varied in complexity. Eight technicians and the supervisor participated in the Fall, 2013 Critical Incident Analysis 111 interviews. Fifty percent of the technicians who participated were involved in 2 or more incidents. From the descriptive coding analysis of the sub-codes for each category of the knowledge life cycle (create, preserve, disseminate) it was revealed that SHD’s primary way of creating knowledge was through “going about connections” which included making deductions using heuristics, technical knowledge, and so on. Other means included consulting with other technicians, brainstorming on the whiteboard, searching online, and getting more information from the customer. The descriptive coding analysis also revealed that the primary means of preserving knowledge were through using the information sheet and the whiteboard. The primary means for disseminating knowledge was via “word of mouth” and the whiteboard. The close relationship between preservation and dissemination was the whiteboard ranked high for both categories.

SHD’s primary way of going through the knowledge life cycle was through making connections. With the technician being the unit, those connections may be internal, which refers to the cognitive steps of connecting prior experience and technical skills to solve a problem and/or external, which involves other technicians and other sources of information. The move from internal to external usually takes place by asking for or seeking for help as well as extending help. Asking for or seeking help is an action generated by the technician that is dealing with the problem and extending help is an action that is generated from another technician. Despite the method of connection, there is usually a process of making deductions that lead to the solution. These processes primarily describe the creation phase of the knowledge life cycle; however, the process was iterative and evidence was seen of new knowledge being built on old knowledge; in this case those connections were made primarily through dissemination of previous knowledge that was preserved in the “heads” of technicians that were around when the relevant knowledge was generated. On a bigger scale, with the organization being the unit, distinct phases of the knowledge life cycle were connected through various platforms. The whiteboard was the predominant one where knowledge was created, disseminated and preserved. When the whiteboard was not used, the office space acted as a connecting platform, but primarily for creation and dissemination. The wiki was used primarily for knowledge preservation with an intention for long term dissemination. Email and the website were primarily used to disseminate information to outsiders as deemed necessary and on some occasions to the technicians. Figure provides a visual representation of how the technicians went through the knowledge life cycle through making internal and external connections which were facilitated by various connecting platforms.

SHD’s driving forces may be divided into individual and environmental factors. Individual factors refer to the technicians’ knowledge, skills and capacity. The technicians had sufficient knowledge and skills to effectively solve uncommon problems; additional, they were intrinsically motivated to go through the knowledge life cycle processes. Environmental factors include SHD’s culture and mission, leadership, resources, tools, and processes. The mission of SHD is for all students to have technology they can use in class. Their motto, “to work on it until it’s fixed” supports the mission and dictates that students with complicated or uncommon problems will not be turned away during “rush”, thus triggering the creation phase of the knowledge life cycle. The culture of genuine interest in helping others is in alignment with SHD’s mission and not only refers to technicians helping students, but also helping each other which facilitated external connections with each other to solve a problem. With regards to leadership, having a supervisor for the office who was actively involved with the day to day operations drove the flow of knowledge along the knowledge life cycle, as knowledge was disseminated to him in many cases when it was not disseminated to anyone else. In addition, supervisor was the main person that added items to the wiki, so in this case, in the capacity of supervisor, he also acted as knowledge manager. The resources, tools, and processes drove the flow of knowledge along the knowledge life cycle as they acted as connecting platforms where knowledge could be created, preserved, and disseminated. Having a systemic way of going about the knowledge life cycle resulted in a shared understanding and thus increased the likelihood that the cyclic nature of the knowledge life cycle would occur.

SHD’s restraining forces to going through the knowledge life cycle during rush primarily fell under the category of environmental factors, with a lack of time and a fragmented system being major restraining forces. Time dictated the extent that the solution for a problem was pursued and it also influenced how the knowledge was disseminated and preserved, if at all. Although the whiteboard proved to be the most effective system for knowledge creation, dissemination, and to some extent preservation, it had limitations, in terms of space and organization. The whiteboard got full, sometimes the information was erased, and at other times it was hard to locate a specific issue. In addition, the whiteboard was mostly used for certain types of problems. The other KM systems included the information sheet and the wiki. These systems were primarily used for preservation, and had limitations as well. Since they were not easily accessible, and information was not easily retrieved, they were not used often by the technicians. At no point did these systems intersect, resulting in a fragmented system. The biggest challenge that the technicians reported was a lack of a system that documented what previous technicians did in a way that was easily retrievable.

Chapter 5: Conclusion

KM is indeed a complex issue for professionals who would like to make an impact as well as the organizations they work with. This study highlighted the value of studying knowledge in the context of an organization. Using the knowledge life cycle approach and the Theory of Organizational Knowledge Creation (Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, Toyama, et al., 2001) to guide the inquiry resulted in an in-depth understanding of the knowledge flow as it relates to critical incidents. The system/ tool that was most effective for SHD was the one that was most accessible and convenient. Importantly, the system/tool was also the one that was involved in the technicians’ core work process of finding solutions to problems, and facilitated their core method of making internal and external connections. This emphasizes the importance of integrating the KM system with the work processes of the organization, and ensuring that environmental constraints are accounted for, like a lack of time due to high demand for service. For SHD, KM challenges were seen with system restraints that were not accessible, and that did not effectively consolidate information from one source to another, with the biggest need being for a system that complements the core work process and links information that customers provide with the technicians’ knowledge solutions and troubleshooting processes. SHD did not seem to exhibit many of the cultural and organizational barriers that are seen in many organizations; however the fact that evidence was seen of where these factors acted as driving forces for the knowledge life cycle may provide examples to other organizations of how to develop an organizational environment that fosters knowledge flow, such as having a culture that encourages working together or “helping others”, a KM intention or vision, and hiring workers who are intrinsically motivated and value the mission of the organization. KM professionals can use these findings to inform solutions for similar environments. This study also acts as a model for similar studies that would like to investigate how knowledge flows within organizations.

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