Luận văn A systems based theory of organizational information

of much hands-on experience played the role of information or ‘I’. Moreover, our model resolved three remaining points or shortcomings above in Weick’s model in a consistent and clear cut way. Organizational information (nearly the same as meanings), data (as frameworks), and knowledge (as sensemaking) were formed in a Peircean semiotic triad. The formulation process was defined by an integration of the Peircean perceptual judgment and inquiry process through both inference and insight from human action. The phenomena of information, knowledge, and data could be distinguished by the time indicators and epistemic status. Finally, getting back to Weick’s suggestions of four sources of resilience in organizations, especially under sudden changes, it could be found that they were in line with our model of organizational information formulation, and hence, rooted in the same foundation of semiotic triad. One, it was improvisation and bricolage, with its 178 main theme as creativity (p.639). This was reflected very obviously in phase one of inquiry process through abductive activities for knowledge creation in our model. Two, it was virtual role systems. This was for reforming the group or organization in the old or new role structure, or alternatively, helped each person literally becomes a group (p.640). In our model, it was on methods of belief fixation that were employed or implied by community or group to reach information. Three, it was wisdom, which reflected experience but embodied doubt, and adaptation to novelties. This was clearly crossing both the stage of information use (for factual surprise by human experiencing the real world) and the first stage of information formulation (for genuine doubt by both insight and inference from factual surprise). Hence, it might be a combination of both data and knowledge. Four, it was a respectful interaction that was showed by “a good life with others as trust, honesty, and self-respect in moment-to-moment interaction” (p.643). This was reflected in the whole of organizational information formulation and use (from action, perception, cognition, to conception or behavior) to get the factual surprise, genuine doubt, and firm belief, but especially in the final stage of the inquiry process with methods of belief fixation inside a community of inquiry. Hence, instead of Weick’s four principles, which were somewhat arbitrary theoretically, we might propose a semiotic triad of three categories and respective relations for organizational designs for changes. At this point, our model attempted to show a little bit more its theoretically comprehensive and concise way to explain organizational phenomena. The existing case study 2. Organizational creativity in context: learning from a failing attempt to introduce IT-support for creativity. The paper written by Stenmark, published in International journal of technology and human interaction in 2005, was a research paper on creativity management. Its author employed an empirical data on Mindpool, an intranet 179 electronic brainstorming system, in Volvo information technology (IT) headquarter in Sweden, a member of the world-wide Volvo group. At the time of the research, Volvo IT company had about 900 employees and served the group other companies as its only customers. The case discussed about the failure of installation and deployment of Mindpool as a replacement of the traditional box-on-the-wall suggestion system of Volvo IT. The latter supported employees “to submit ideas and suggestions for improvement to a proposal-handling committee (PHC), which would honour the proposer of a good idea with a financial remuneration” (p.84). Meanwhile, Mindpool, following both principles of brainstorming and suggestion system, was a hybrid system and featured three outstanding designs: asynchronicity, anonymity, and accessibility (p. 86), all of which are to increase the number and diversity of submissions of new ideas over the corporate. However, after three week test period, “the creativity-boosting effect was less than anticipated, and even though the prototype worked well technically we considered usage a failure” (p.89). Reconsidering empirical results from employee interviews as presented in the paper, and coding Volvo IT Mindpool usage as its organizational information, we argued that Mindpool operation failure resulting from the fact that Volvo IT organizational information could not be formulated successfully. The key reasons for this were: (i) data (D) not yet available adequately; and (ii) methods of belief fixation (M) of communities of inquiry not also yet specified. The former was supported with informant ideas of the needs of such an online brainstorming system: “Creativity can cause problems, too. In a production environment that has to work… well, if it is working, you’d better leave it alone and not try to fix it up, because then you create problems”, or “You don’t have time to speculate, or be creative in a general sort of way” (p.90). That Volvo employees actually were in no need using Mindpool indicated no data for formulation of organizational information as Mindpool deployment. The 180 latter was evident in the following comments of Volvo IT respondents: “If you have a good idea, why post it here [in Mindpool] instead of submitting it to the PHC? There you might get a reward and you know you’ll get a response. In this system [Mindpool] you just post things and you’ll never know whether someone uses it” (p.92), or “There should be someone to make sure that there is some order to it and that the suggestions are serious. You know - weed out the crap […]. That person could perhaps also direct certain ideas to the right place in the organization…” (p.91). The fact that Volvo employees hesitantly participated in the new system revealed that they were not persuaded strong enough about Mindpool benefits in gathering and transferring their new business ideas, or alternatively, methods of belief fixation of the involved communities were not made clear. Getting back to our testing propositions of the resultant grounded theory, we found that the three propositions of P1, P2, and P3 held true indirectly. With P3, no new data (D) formed because Mindpool was just in the test period, no real life benefits of using the new system recorded. As a result, P2 went right too: no use of Mindpool or no data, no new ways of using Mindpool or no knowledge gained. For P1, due to missing some methods of belief fixation (M) of the whole organization as a community of inquiry, no organizational information (I) could be formulated regardless of the states of data (D) and knowledge (K). Finally, we believed that our model, in comparison with Stenmark’s, offered a more fundamental and consistent way to explain the phenomena of organizational creativity. Basically, both explanations seemingly had the same root of organizational factors, which was organizational information formulation as our part and was contextual factors as Stenmark’s. However, Stenmark’s three suggestions inspired by Volvo empirical evidences might need to be reconsidered with care. One, he emphasized extrinsic motivation in financial compensation for increasing the system use. This was evident but his reasoning was seemingly a bit inconsistent when he stated 181 both focus on the reward and an employee needs to interact with her colleagues. According to him, the former discouraged employees to share thoughts and ideas with their peers but the latter strikingly was also true because “the employee may never arrive at the groundbreaking conclusion on her own, without interaction and dialogue with other humans” (p.96). Two, he tried to seek a balance between anonymity and the request of IT tools “must make salient who contributes to the system” (p.96), both of which did belong to work climate, autonomy and settings that in some situations required instead increased accountability (p.94). Hence, for such specific settings, his explanations may rather be limited somehow. Three, he proposed an employee time redundancy for bootstrapping organizational creativity. However, his explanatory factor was only applicable into goal oriented organizations but not in activity-oriented ones (p.95). In short, Volvo empirical data showed the new technology was insufficient to support organizational creativity. The contextual factors were necessarily invoked for better explanations. Although Stenmark’s accounts on social psychology provided a fit in Mindpool evidence, ours on organizational information might offer a more generic yet parsimonious and consistent explanatory way for the relevant literature. The existing case study 3. What is organizational knowledge - Knowledge practices within Panafon’s customer care department. The paper written by Tsoukas and Vladimirou, published in Journal of Management Studies in 2001, was a research paper on the nature of organizational knowledge. Its authors employed an empirical investigation on customer queries at a call centre in Panafon, the leading mobile phone company in Greece. We adopted the existing case for the reason that our research and Tsoukas and Vladimirou’s have the same object of study, which is the nature of organizational information or knowledge. Such a comparison with minimal variations between two theoretical models of the 182 same research question shall be significant for evaluation of theoretical levels of the two. Panafon Customer Care Department (CCD) at the time of Tsoukas and Vladimirou’s report had 4 call centers in total, and received 60,000 calls a day on average from more than 2 million subscribers. CCD’s mission was to provide information services for Panafon subscribers, both contract and pre-paid customers, ranging from directory inquiries, directory assistance, secretarial messaging services, voice mail inquiries to general information on the company’s services like tariffs, or network coverage and to general information about mobile phones (p.984). CCD’s operations spanned 24 hours a day and relied on 250 employees taking the role of customer care operators those who have been well trained, formally and on the job, about the company products and services as well as techniques of supporting customers (p.984). Assuming that the operators were responsible for answering customer calls in an efficient, courteous, and helpful way according to their experience and training, Tsoukas and Vladimirou observed that “providing customer support is not as easy a job as it might first appear” (p.986) and conceptualized handling customer queries as knowledge practice in CCD (p.985). For answering customer queries, the operators often relied on information provided by Panafon, which is both printed and electronic format, and both recorded for some time and just up-to-the-minute, for example computerized databases and printed company manuals. Formal company information system was insufficient, however, for supports of high quality (e.g. speedy) to subscribers (p.985). Tsoukas and Vladimirou identified from their field data that the operators also need to draw upon their “work experience” built over time, which could be considered as an informal memory system, both individual and collective level. The former level was “the individual stocks of experience held by each operator”, and the latter level was “the stories shared in their community” (p.985), or “informal collective stock of 183 knowledge” (p.986), which is quite important, valuable source (p.986), and crucially shaped by the overall company culture (p.987). Next, the operators by themselves also developed a set of diagnostic skills to help them think quickly and serve customers speedily, which become instrumentalized, or tacit (p.987). Tsoukas and Vladimirou analyzed “over time, operators learn to dwell in these skills, feed them as extensions of their own body and thus gradually become subsidiarily aware of them, which enables operators to focus on the task at hand” (p.987). It should be noted that diagnostic skills, according to Tsoukas and Vladimirou, broadly covered perceptual ones. These two authors also argued that by their tacit, or heuristic (p.988) knowledge, the operators could specially handle particular problems of customer queries. And to explain handling customer queries more effective than expected for some operators, the strategy of improvisation (Orlikowski, 1996; Weick, 1998; 1993a) was cited and borrowed. Following that, drawing on findings from case data, Tsoukas and Vladimirou proposed the links between individual knowledge, organizational knowledge, and human action in organizations as follows. First, data referred to discrete items (for example, “address, and phone numbers”, p.988), and information included generic propositions in the form if-then statements (for example, “if this problem appears, then look at this or that”, p.988). Both data and information were present in formal company information system, including computerized databases and printed manuals. For information to be transformed into personal knowledge (personal and individual knowledge was used interchangeably in their paper), the operators themselves, relying on contexts of their conversations with callers as well as on behavioral frameworks, general principles, or rules, which was abstracted as theory (p.979), made their judgments or drawn their distinctions on specific customer queries and acted accordingly. Note that, according to Tsoukas and Vladimirou, knowledge was understood as both outcome and process (p.974), hence both operator capability to 184 draw distinctions and distinctions drawn could refer to knowledge. Next, for knowledge to be organizational, it was stressed that the operators need to draw and act upon the company rules (p.979). Then, from knowledge to action, an improvisational element was inescapable (p.988). We reexamined CCD operator supports for customer queries as organizational business activities coded as organizational information in our study as follows. Customer queries played the role of providing data (D) for operator, which was for example: “When asking for information, several customers tended to provide plenty of contextual details while describing their query. Often such contextual information was, strictly speaking, redundant and actually tended to blur, to some extent, the point of their query”, or “the primary task for the operator is to dispel the ambiguity surrounding customer calls and understand what the problem really is, and how, consequently, it ought to be solved. Even seemingly simple problems require diagnostic skills on the part of operators” (p.986). However, it should be noted that, customer queries would be considered as having data (D) only when they made operator surprise. In other words, for the major of usual queries, data (D) could not be created. A piece of evidence was for example as follows: “Answers to 95 per cent of the questions we are asked exist somewhere in the computer system, or in the manuals, or somewhere”. Such situations asked operator to act in a habitual way, accurately, quickly and efficiently (pp. 985-8). At this point, the testing proposition P3 held. Next, the operator’s knowledge (K) was referred to only when data (D) created by the operator’s perceptual skills that were accumulated over time (pp. 986-7). At this time, the official company information system and her past work experience (i.e. individual stock of experience and shared stories in her community) could really not help to deal with customer calls, or the speed of answering customers was in question (p.985). As mentioned earlier, the diagnostic skills that were also developed 185 on the job helped the operator to examine all possibilities, to make finer distinctions, and to reach conclusion (pp.986-7). We weighted this capability as the operator’s knowledge (K), and noted that the operator did it by herself. The further question might be in what ways this happened. Our model took abduction (Peirce, 1958) as a generic strategy for all diagnostic activities with note that abduction is both insight and inference as mentioned previously. This was in line with our findings of business consulting case that comprises expert’s diagnosis as a central knowledge ingredient. The testing proposition P2 was also confirmed. Then organizational information (I) was formulated evidently: “Although operators did make use of the information systems provided by the company, they did so in a manner whose distinguishing features were, on the one hand, the exercise of the operators’ judgment in diagnosing problems, while, on the other hand, the way in which the operators’ judgment was exercised had been crucially shaped by the overall company culture” (p.987). It was clear that the latter was more crucial on high quality service (p.987) and it was also what we called methods (M) of belief fixation of community or organization under investigation. In other words, symbolically, M that was embodied in company culture played the decisive role to shape I from K. Another evidence showed a process of organizational information formulation as well as the significance of inter-subjectivity formed by community or organization: “Narrating work-related episodes to one another about, for example, awkward customers and uncommon questions tackled creates an environment in which the ties of community are reinforced, collective memory is enriched, and individual knowledge is enhanced” (p.986). At this point, we also found that with work practice just gained, the operator could handle next customer queries in a different way (hopefully, much better), which was symbolically an information use process that might result in new facts or surprise. A next round of organizational information formulation (and use) might be start again. The testing proposition P3 also held. 186 Now we proceeded to make some connections between our model with Tsoukas and Vladimirou’s. We first agreed simply that to answer customer queries was a human action. To act so, the operators needed to rely on something that we termed organizational information, which was neither organizational knowledge nor personal knowledge as Tsoukas and Vladimirou did. It should be noted that for our model, organizational information or personal information could be distinguished only in a weak sense that is the former was formulated by more than one individual in the organization. To be more precise, in our model, no personal information was possible because information must be formulated by any community in which individual was a participant or member. Getting back to the case data, we found that operators in the bottom line literally relied on the company information, which was understood as both printed and electronic materials provided by the company, on the informal collective stock of knowledge or the stories shared in their community, and on the individual stock of experience (pp.985-6). It was obvious that the two formers (i.e. company information and collective stories), which, on part of our model, were belonging to our theoretical construct of organizational information, whereas on Tsoukas and Vladimirou’s model, were organizational knowledge. The latter (i.e. individual stock of experience) was analyzed by Tsoukas and Vladimirou as diagnostic skills to help the operator to think and act quickly, and as perceptual skills to help the operator to recognize customer behavior and act accordingly (p.987), both of which was abstracted as the operator’s tacit knowledge that was developed as a result of operator repeatedly coping with particular problems and solutions. We made four points here about operator’s knowledge and organizational knowledge. One, the tacitness of the operator’s knowledge was seemingly invoked and presented only for handling a particular problem in a particular way (p.987). The question was for the major of normal problems, if there is any knowledge in need for the operator to work with her customers. Two, there was seemingly overlap or no clear cut between personal 187 knowledge and tacit knowledge (p.987) in CCD case data. The case data did not show any evidence about personal but non-tacit knowledge. Three, there was seemingly organizational knowledge that was always explicit because it was just personal knowledge constrained by company rules, or “casting into propositional statements” (p.988). Following that, it turned to be contradictory because (i) organizational knowledge was in both individual minds and in shared stories, hence organizational knowledge became the same as heuristic knowledge (p.988), (ii) heuristic knowledge was always alongside formal organizational knowledge, and could be turned into organizational knowledge (p.988). Four, it seemed very hard to arrive at a fuse between the personal character of knowledge and the collective essence of knowledge as Tsoukas and Vladimirou sought (p.973). Last, heuristic knowledge was assumed that it was emerged from the operator’s improvisation; how about where personal knowledge did come from? Getting back to our model, we developed knowledge as always personal, and hence tacit, or a cognitive status or process, or alternatively, no organizational knowledge at all. Meanwhile, information in our model was always organizational (e.g. communal), and hence explicit (in a sense, without tacitness), or a behavioral guideline. In addition, our model also suggested a view of context, which was supported from CCD data but not found in Tsoukas and Vladimirou’s work. First we sought that there were three groups of stakeholders in CCD setting: subscribers, operators, and call center itself (e.g. CCD supervisors, Panafon). CCD knowledge practice described by Tsoukas and Vladimirou was, to subscribers, customer queries that we abstracted in a context of inquiry, to operators, answering calls that we put in a context of action, to call center itself, providing customer care services to maintain and attract Panafon subscribers (p.984), which we typified in a context of habit. The two former contexts were self-explanatory as simultaneously evidenced: “Answers to 95 188 per cent of the questions we are asked exist somewhere in the computer system, or in the manuals, or somewhere. Most likely the subscriber will be given the information he wants” (p.985). Next, the context of habit seemed to be undercurrent but really crucial for linking the two remaining contexts and more importantly, for theoretical explanation of CCD operation as a whole. Tsoukas and Vladimirou analyzed such linking: “Operators must be able to continuously provide efficient, courteous and helpful customer support services to subscribers – at least that is the official company policy” (p.986), or the way that operators exercised their judgments in handling customer calls was “shaped by the overall company culture” (p.987). In specific for context of inquiry viewed by subscribers, it was also pointed out that the quality of customer care (i.e. customer queries), which was identified as CCD’s mission, was a determinant for customers to choose their service providers (e.g. Panafon) (p.983). At this point, we found a support for our argument that context of habit played the role of organizing. Without such a context of habit, there were no benchmark or ground rules for context of action; that is, some operators’ answers might be better or worse, depending on criteria of assessments or views of stakeholders. Following that, the same might be said on customers’ calls, or context of habit showed the significance of context of inquiry, or alternatively context of inquiry might not justify itself. A final note was about the distinction of habitual behavior between context of action and context of habit. At the first sight, the operators in their context of action also accommodated their habits. That was true but it should be noted two points. One, for the context of action, the dominant factor was action itself, or more abstractly, a particular or person; for example, the operator needed to spend her best efforts (e.g. improvisation, tacitness) to answer her customer calls in any concrete situation: “The tacitness of operators’ knowledge was manifested when they were asked to describe how a