There is an old adage that says that what gets measured gets managed (or, conversely that what does not get measured does not get managed). It seems then that in order to manage knowledge, one must be able to measure it. Furthermore, following Bose (2004), to be able to show the value of a knolwedge management system, it is imperative that this value be demostrated through metrics, if not straightforwardly through monetary value then, at least, throgh formally established anecdotal evidence. In fact, this is why measuring knolwedge (management) is not the same as measuring typical ROI, it refers to intangible assets that supplement financial measures. Bose collects several lists of metrics that can be employed to build intellectual capital indicators, for example: number of patents, customes and employee satisfaction, IT investment and literacy, training expense per employee, emplyee turnover, leadership, motvation, etc. While some of those are relatively easy to determine (it is just a matter of counting number of patents, for instance) some others are qualitative / subjective in nature and must be treated carefully, especially when they are turned into numeric values. For example, if an employee is asked to rate his satisfaction on a scale from 1 to 10, he or she might say 9 on a good day and 5 on a bady day... Moreover, it is not just a question of gathering metrics from a list, the key is to build indicators that make sense according to the (knowledge management) strategy. Bose propose a top-down way to go about building intellectual capital indicators: (1) defining the business concept or strategy; (2) identifying critical succes factors; (3) Selecting corresponding performance indicators; (4) assigning weights (priority, importance) to those indicators; (5) consolidating metrics (in a hierarchy); (6) generating a single intellectual capital index; and (7) using the index to guide management. Regardless of whether this may be too linear or rigid, it still points at two key aspects that must be accounted for. One, measuring is the result of a strategic purpose and the resulting measures should be used to guide (correct, improve, learn) the organization towards set goals. Two, the act of defining metrics, indicators, indexes and critical succes factors is a way to materialize and clarify the strategy and as such is full of (inter-subjective) value judgments and should be understood as a means, not an end in itself.
In terms of specific methods or frameworks for measuring knowledge management, Bose mention the Balanced Scorecard (BSC), the Skandia Navigator and Economic Value Added (EVA). Let's focus on the BSC. Kaplan and Norton introduced the BSC in the early 90s as way for companies to focus on (measuring) their intangible assets. After some use, in the late 90s, the BSC began being used as a strategic management system, which as mentioned above, would help translate the vision and strategy into specific goals and metrics at the department or individual level (Kaplan & Norton, 1996). The focus on intangible assets meant categorizing metrics into four perspectives: financial (traditional, tangible), internal business processes, customers, and learning and growth. This last one in particular is evidently tied to intellectual capital and meant that in the 2000s the BSC sarted being used for measuring knowledge management as well. For example, in Fairchild (2002) a porposal is made for leveraging KM through the BSC by mapping the BSC perspectives to intellectual capital (IC) perspectives as follows: the financial perspective would correspond to IC as such, for instance through the Skandia Navigator; the customer perpesctive would correspond to social capital (as we know, social capital has much to do with how customers perceive the company - reputation, trust, etc.); the internal perspective would corespond to strucural aspects (in this case related to KM processes, skills and technology); and the learning and growth perspective would be mapped to human capital (e.g. training and satisfaction).
However, Voepel et al. (2006) raise a warning with respect to using the BSC from the point of view of innovation. They argue that the BSC is too rigid (having a predefined set of perspectives may not work for all types of organizations or organizational designs). It may also be too static because it places too much emphasis on uniform and hierarchical objectives (whereas innovation should be much more flexible). It is also mostly internal: despite having a customer perspective, it still refects only on the organization and not on its competition or partners which we have already seen as critical in an innovation mindset. It has a rather formal understanding of learning which may be equated to the STI-mode of learning discussed earlier in this course, which implies neglecting the DUI-mode (though Voelpel et al do not frame it this way). And, finally, it is too mechanistic (even bureaucratic). This last issue, however, could be said of any formal use of metrics or performance indicators and is perhaps the most difficutl challenge. How do we enable rigorous and traceable managament, without going against the flexibility required of knowledge managament aimed at dynamic capabilities and innovation? How do we use the measurements as an evolutionary improvement strategy and not as a end in itself where the quantitative results are more important than the creation of new knolwedge, products, services, etc?
miércoles, 31 de agosto de 2011
martes, 23 de agosto de 2011
Intra and Inter-organizational Networks (aug. 23)
Throughout the course we have emphasized the networked character of knolwedge management, under the premise that knolwedge sharing both within and between firms holds the key to tap resources in order to be able to produce more significant and sustained innovations. On the one hand, intra-organizational networks (between members of the same organization) stimulate knolwedge sharing as well as enabling more localized decision-making. Galbraith et al. (2002) call these, the lateral capabilties of an organization to highlight the fact that they overcome the rigidity of hierarchies. Since network structures emerge naturally (from the bottom-up), it is idfficult to provide specific institutional designs, let alone guarantee that they will actually emerge in an effective manner. Nonetheless, Galbraith et al. do provide certain mechanisms or tols that should catalyze or nurture such emergence. Given that Galbraith is pioneer of the "information-processing view of organizations" (owing much to Herbert Simon) it is only natural that they would suggest information technology as one such mechanism (and here one must think of knowledge manegement technologies in particular). But we should keep in mind that IT may create information processing capabilities as well as generating additional iformation processing needs (by, for example providing local decision-makers with more information than what they are used to handling). Additional mechanisms include: communities or pracice, annual retreats, and personnel co-location, among others.
Moving beyind the organization we then go into inter-organizational networs (connected to literature on business networks, virtual organizations, clusters, districts, etc.). This new level steps aside from the traditional "resource-based view of organizations" where the focus is on a firm's resources and capabilities, to a focus on network resources. Through Toyota's experience when entering the US in the 90s, Dyer and Hatch (2006) illustrate the competitive advantage that one organization can create out of identifying and supporting relation-specific capabilities, in this case between Toyota and its US suppliers. Since Toyota's strategy and IT are aligned in order to enhance the capabalities of their suppliers, one could rightly expect that such capabilities might also be exploited by Toyota's competition (given that they share the same suppliers). However, such capabilities are tied to a knowledge-sharing strategy which is difficult to replicate and which in effect neithr GM nor Ford, for example, were able to benefit from. The specificity of the relation between Toyota and its suppliers, coupled to replication barriers (the existence of rigid processes or lack of absorbtive capacity) actually implies that Toyota was able to gain sustained advantage from their knolwedge transfer without the risk of it being copied. Since resources are tied to the capability to exploit them, it was not possible for other manufacturers to use the knolwedge that Toyota shared with its suppliers, since they would also have had to redesign their associated processes, systems, standards, or even trivial but rigid elements such as the size of boxes. This supports the notion that knowledge sharing is a key source of competitive advantage, rather than the belief that knolwedge protection is more strategic. Nonetheless, this needs to be a continued effort, because despite the lengthy or costly learning curves and transofmration processes, it will still be the case that best practices will eventually be copied and the firm must always be developing new ones.
Moving beyind the organization we then go into inter-organizational networs (connected to literature on business networks, virtual organizations, clusters, districts, etc.). This new level steps aside from the traditional "resource-based view of organizations" where the focus is on a firm's resources and capabilities, to a focus on network resources. Through Toyota's experience when entering the US in the 90s, Dyer and Hatch (2006) illustrate the competitive advantage that one organization can create out of identifying and supporting relation-specific capabilities, in this case between Toyota and its US suppliers. Since Toyota's strategy and IT are aligned in order to enhance the capabalities of their suppliers, one could rightly expect that such capabilities might also be exploited by Toyota's competition (given that they share the same suppliers). However, such capabilities are tied to a knowledge-sharing strategy which is difficult to replicate and which in effect neithr GM nor Ford, for example, were able to benefit from. The specificity of the relation between Toyota and its suppliers, coupled to replication barriers (the existence of rigid processes or lack of absorbtive capacity) actually implies that Toyota was able to gain sustained advantage from their knolwedge transfer without the risk of it being copied. Since resources are tied to the capability to exploit them, it was not possible for other manufacturers to use the knolwedge that Toyota shared with its suppliers, since they would also have had to redesign their associated processes, systems, standards, or even trivial but rigid elements such as the size of boxes. This supports the notion that knowledge sharing is a key source of competitive advantage, rather than the belief that knolwedge protection is more strategic. Nonetheless, this needs to be a continued effort, because despite the lengthy or costly learning curves and transofmration processes, it will still be the case that best practices will eventually be copied and the firm must always be developing new ones.
martes, 16 de agosto de 2011
Organizational Learning and Dynamic Capabilities (aug. 16)
Dynamic capabilities, according to Sher and Lee (2004) refer to the organization's way of responding in a rapidly changing environment, where a capability is understood as the adoption, integration and reconfiguration of skills, resources and functions to meet change. In order for dynamic capabiities to develop, Sher and Lee argue that an organization must take into consideration: (1) path-dependence (future decisions are influenced by past decisions); (2) double-loop learning (where single-loop learning referes to doing things better, double-loop is about doing better things); and (3) meta-routines (routines to learn routines). In sum, it is about knolwedge management of both exogeneous knolwedge (clients, suppliers, competition) and endogeneous knolwedge. Information technology then acts as a mediating variable between knowledge management and dynamic capabilities, enabling the transition from knolwedge and learning to being able to react adequately. However, in their study, Sher and Lee found that only ERPs and Data Warehouses were indeed influential factors in this relationship, while e-mail, document managemrnt and online search capabilities were not. This suggests that IT does not have a deterministic effect on this relationship and will in fact be dependent on the way in which specific organizations employ it to leverage knowledge management.
A different understanding of dynamic capabiltiies allows for a broader definition, where they refer to a learned and stable pattern of collective activity through which the organization systematically generates and modifies its routines in pursuit of improved effectiveness (Zollo and Winter, 2002). In this view, the envinroment need not be rapidly changing for the orgrnization to adapt to it, the key is rather in the formal and persistent way in which the organization goes about this adaptation (an ad hoc cerative adaptation is not a dynamic capability). Dynamic capabilities are related to learning mechanisms, which can be (1) through experience and routines; (2) through articulating (implicit) knolwedge; or (3) through codifying (explicit) knolwedge. As a process, Zollo and Winter propose an evolutionary approach where dynamic capabilities emerge from a cycle going from variation (of explicit knolwedge), to selection (explicit), to replication (of tacit knolwedge) and finally to retention (tacit) and then back to variation. Along the way, it is a key factor that individuals and the organization as a whole be able to explicitly identify the connection between decisions /actions and performance.
It then becomes clear that the relationship between knolwedge management and dynamic capabilities is learning-oriented. In fact, a combination of organizational learning and knowledge sharing is what enables improved firm effectiveness (Yang, 2007). In particular, it is an effort aimed at preventing knowledge depreciation (out of employee turnover, obsolescenece, incomplete knolwedge transfer or difficult access). However, until recently most literature on organizational larning has focused on procedural (know -how) and declarative knowledge (know-what) while negelecting relational knolwedge (know-who), as claimed by Borgatti and Cross (2003). This is obviosuly changing in the context of a networked, knowledeg-based society where the Internet and social networking have become familiar interaction spaces. In this new environment, social ties may be weak (in which case they may help in finding a job, advancing professionally or distributing ideas) or strong (in which case they may foster knolwedeg transfer, especially when such knolwedge is tacit and complex). It has already been recognized for some time that such ties are more likely to emerge when there is homophily (kinship in terms of race, gender, age, education) or physical proximity. However, Borgatti and Cross also find that it all starts with the decision to seek information in the network and this depends on: knowing (who knows what), value (how much do I value the other's knolwedge), access (how easy is it to access the other's knolwedge) and cost (how costly is it to access the other's knowledge). Empirically, however, cost seems less important perhaps becase it is overshadowed by the urgency of the information need.
In summary: in order for an organization to develop dyamic capabiltiies that will enable it to stay in the game and improve its effectieveness, an adequate organizational learning strategy must be in place, with an emphasis on relational knowledge. Furthermore, this connection is enabled both srategically and technologically by knowledge management
A different understanding of dynamic capabiltiies allows for a broader definition, where they refer to a learned and stable pattern of collective activity through which the organization systematically generates and modifies its routines in pursuit of improved effectiveness (Zollo and Winter, 2002). In this view, the envinroment need not be rapidly changing for the orgrnization to adapt to it, the key is rather in the formal and persistent way in which the organization goes about this adaptation (an ad hoc cerative adaptation is not a dynamic capability). Dynamic capabilities are related to learning mechanisms, which can be (1) through experience and routines; (2) through articulating (implicit) knolwedge; or (3) through codifying (explicit) knolwedge. As a process, Zollo and Winter propose an evolutionary approach where dynamic capabilities emerge from a cycle going from variation (of explicit knolwedge), to selection (explicit), to replication (of tacit knolwedge) and finally to retention (tacit) and then back to variation. Along the way, it is a key factor that individuals and the organization as a whole be able to explicitly identify the connection between decisions /actions and performance.
It then becomes clear that the relationship between knolwedge management and dynamic capabilities is learning-oriented. In fact, a combination of organizational learning and knowledge sharing is what enables improved firm effectiveness (Yang, 2007). In particular, it is an effort aimed at preventing knowledge depreciation (out of employee turnover, obsolescenece, incomplete knolwedge transfer or difficult access). However, until recently most literature on organizational larning has focused on procedural (know -how) and declarative knowledge (know-what) while negelecting relational knolwedge (know-who), as claimed by Borgatti and Cross (2003). This is obviosuly changing in the context of a networked, knowledeg-based society where the Internet and social networking have become familiar interaction spaces. In this new environment, social ties may be weak (in which case they may help in finding a job, advancing professionally or distributing ideas) or strong (in which case they may foster knolwedeg transfer, especially when such knolwedge is tacit and complex). It has already been recognized for some time that such ties are more likely to emerge when there is homophily (kinship in terms of race, gender, age, education) or physical proximity. However, Borgatti and Cross also find that it all starts with the decision to seek information in the network and this depends on: knowing (who knows what), value (how much do I value the other's knolwedge), access (how easy is it to access the other's knolwedge) and cost (how costly is it to access the other's knowledge). Empirically, however, cost seems less important perhaps becase it is overshadowed by the urgency of the information need.
In summary: in order for an organization to develop dyamic capabiltiies that will enable it to stay in the game and improve its effectieveness, an adequate organizational learning strategy must be in place, with an emphasis on relational knowledge. Furthermore, this connection is enabled both srategically and technologically by knowledge management
martes, 2 de agosto de 2011
Business Intelligence and KM (Aug. 2)
There is a clear and growing relationship between business intelligence (BI) and knowledge management (KM). In Herschel and Yermish (2009) the view is that BI focuses on identifying trends or patterns in (typically large) explicit data warehouses. The aim is to aid in decision-making or in planning of corrective actions when the trend deviates from organizational goals. BI usually employs explicit quantitative data, which may imply an (excessive) emphasis in the technological tools and methods employed to analyze data, such as data mining and online analytical processing - OLAP). Accordingly, Herschel and Yermish argue that BI by itself is insufficient for generating value. Since we have already discussed the value creation emphasis of KM, then the idea is that BI be viewed as a subset of KM in order to make the technological capabilities useful and value-adding. For instance, an organization might place their BI activities and support tools in the context of a KM strategy led by learning objectives, using Nonaka and Takeuchi's SECI model for example.Also, since KM encompasses both explicit and tacit knowledge, a KM process should make knowledge explicit prior to employing BI techniques. One way in which this can be achieved is employing so-called knowledge exchange protocols. These offer a template and a structure for sharing knowledge, thereby stimulating and facilitating entry of new knowledge (from individuals into the system) as well as consumption of existing knowledge (from system to individual). An example protocol is presented by Herschel and Yermish: the SOAP protocol (not to be confused with service-oriented jargon) includes Subjective, Objective, Assessment and Plan categories. This template is applicable to different domains and enables an explicit categorization of tacit knowledge via text.
A different take on the relationship between KM and BI is offered by Cody et al. (2002). Out of their work at IBM research, the authors contend that the main difference between BI and KM is that the first is centered on (quantitative) explicit data analysis, while the latter is focused on tacit textual information. As such, the point is to move towards a single BIKM system in which it is possible to associate text with data. Often, the presence of meta-data will be enough to componentize text and link it to data, but in other cases there will be no meta-data or the link will not be explicit beforehand, requiring more preparation steps. In the end a single model with shared dimensions will integrate both text and data in order to improve the quality of business decisions (enriching the analyses offered by only using data).
A different take on the relationship between KM and BI is offered by Cody et al. (2002). Out of their work at IBM research, the authors contend that the main difference between BI and KM is that the first is centered on (quantitative) explicit data analysis, while the latter is focused on tacit textual information. As such, the point is to move towards a single BIKM system in which it is possible to associate text with data. Often, the presence of meta-data will be enough to componentize text and link it to data, but in other cases there will be no meta-data or the link will not be explicit beforehand, requiring more preparation steps. In the end a single model with shared dimensions will integrate both text and data in order to improve the quality of business decisions (enriching the analyses offered by only using data).
miércoles, 27 de julio de 2011
Creating knolwedge-based value (Jul. 26)
According to Vorakulpipat & Rezgui (2008), knowledge management (KM) has gone through three distinct generations. The first generation focused on sharing knowledge, where KM would support the transmission and absorption required for effective knowledge transfer. The second generation, the present one, emphasizes the creation of knowledge as a recognition that sharing is not enough and that in order for an organization to learn and evolve it must also generate new knowledge. The third generation, the future, should be about creating value: sharing and generating knowledge are not enough unless the actually deliver some added value to a product or service. It should be noted that "value" does not necessarily mean profit; as we have discussed previously it may be value embedded in social capital or in the capability to innovate.
Vorakulpipat & Rezgui (2008) follow by stating that up until now, KM has been understood from three different dimensions. (1) A socio-technical dimension in which ICT is seen as a necessary but not sufficient component of KM. Actually, the socio-technical approach has been around for decades in information systems to address the human (social) aspects which are crucial for the development and use of any such system. (2) A socio-organizational dimension in which ICT is not even a key element and where the focus is on the organizational culture, seen as a network of conversations (cf. Winograd & Flores, 1987) where issues such as motivation, satisfaction and trust are required for effective KM. (3) A learning process dimension addresses the fact that KM is all about dynamic capabilities enabled by a continuous learning cycle (e.g. through Nonaka and Takeuchi's SECI model).
Adding value through KM is then a matter or striking the right balance between human networks, social capital, intellectual capital, technology and change management. All these are important, but a particular KM strategy will determine where the most value might be obtained. Specific value might take the form of: trust, respect, understanding, employee satisfaction and, of course, profit obtained through innovations. But such innovations, need not only be based on knowledge but be also client-centered and service-driven, because this is where value is materialized in the end.
In order to illustrate this relationship, we discussed some of the opportunities for KM in each of the specific project groups and the way that value could be created in them. The following figure shows the summary of our discussion.
Vorakulpipat & Rezgui (2008) follow by stating that up until now, KM has been understood from three different dimensions. (1) A socio-technical dimension in which ICT is seen as a necessary but not sufficient component of KM. Actually, the socio-technical approach has been around for decades in information systems to address the human (social) aspects which are crucial for the development and use of any such system. (2) A socio-organizational dimension in which ICT is not even a key element and where the focus is on the organizational culture, seen as a network of conversations (cf. Winograd & Flores, 1987) where issues such as motivation, satisfaction and trust are required for effective KM. (3) A learning process dimension addresses the fact that KM is all about dynamic capabilities enabled by a continuous learning cycle (e.g. through Nonaka and Takeuchi's SECI model).
Adding value through KM is then a matter or striking the right balance between human networks, social capital, intellectual capital, technology and change management. All these are important, but a particular KM strategy will determine where the most value might be obtained. Specific value might take the form of: trust, respect, understanding, employee satisfaction and, of course, profit obtained through innovations. But such innovations, need not only be based on knowledge but be also client-centered and service-driven, because this is where value is materialized in the end.
In order to illustrate this relationship, we discussed some of the opportunities for KM in each of the specific project groups and the way that value could be created in them. The following figure shows the summary of our discussion.
miércoles, 20 de julio de 2011
Knowledge managament and innovation (Jul. 19)
Innovation is a generic and sometimes confusing concept. There may be industrial, social, cultural, incremental, radical as well as being the result of an explicit aim (such as in R&D) or an emergent (sometimes unexpected) result of a learning process. Some place the weight of innovation on the fact that the new product or service is actually introduced successfully into the market, as opposed to just a new idea that is never marketed. Some emphasize the novelty behind an innovation, while others admit knowledge or technology transfer as a potential source of innovation. For example, the same product or service may be introduced into a new context or market implying a new innovation (since there is no guarantee that it will have the same success it has had elsewhere). In any case, the role of knowledge and knowledge management as pillars of innovation is long recognized and empirically demonstrated.
With respect to the modes of learning and innovation, Jensen et al. (2007) make a distinction between the Science, Technology and Innovation, or STI-mode, and the Doing, Using and Interacting, or DUI-mode. STI is borne out of formal, science and technology-based codified knowledge, emphasizing so-called know-why type of knowledge. In addition, STI usually implies a formal documentation of the whole learning and innovation process, which often results in the generation of new global knowledge, despite having a local, problem-based origin. Because it is formal, STI has widely used (standardized) measures for assessing its presence and strength in firms (e.g. investment in R&D, scientifically trained personnel, cooperation with universities or research centers). DUI, on the other hand is much less formal and is akin to organizational learning in that it stems from experience-based relational learning. as such, DUI focuses on know-how and know-who types of knowledge and is made possible in flexible organizations that foster knowledge sharing especially across disciplines and organizational units. While the presence of either STI or DUI enable a firm to be more innovative, it is a combination of both which is usually behind firms that excel in innovation. as a consequence, knowledge management may be used to propel the integration between STI and DUI-modes by enabling shared access to codified knowledge, as well as supporting knowledge-based interaction within the firm and across its boundaries (clients, partners, market in general).
The role of knowledge management for innovation is not new, but the focus has shifted as organizations move towards a service-based paradigm, as argued by Darroch (2005). Rather than seeing resources as the main assets of the organization, the key are the services those resources actually deliver. And in order for a resource to deliver a service, it must be coupled to a capability (skills or experience which enable exploiting a particular resource). Seen this way, knowledge is a resource and knowledge management is a coordination mechanism which supports its transformation into a capability, specifically the capability to innovate. A study of New Zealand firms shows that this is the case for all three phases of knowledge management. Acquisition, Dissemination and Responsiveness to Knowledge all contribute to innovation (or rather, innovative firms usually support these three KM functions).
With respect to the modes of learning and innovation, Jensen et al. (2007) make a distinction between the Science, Technology and Innovation, or STI-mode, and the Doing, Using and Interacting, or DUI-mode. STI is borne out of formal, science and technology-based codified knowledge, emphasizing so-called know-why type of knowledge. In addition, STI usually implies a formal documentation of the whole learning and innovation process, which often results in the generation of new global knowledge, despite having a local, problem-based origin. Because it is formal, STI has widely used (standardized) measures for assessing its presence and strength in firms (e.g. investment in R&D, scientifically trained personnel, cooperation with universities or research centers). DUI, on the other hand is much less formal and is akin to organizational learning in that it stems from experience-based relational learning. as such, DUI focuses on know-how and know-who types of knowledge and is made possible in flexible organizations that foster knowledge sharing especially across disciplines and organizational units. While the presence of either STI or DUI enable a firm to be more innovative, it is a combination of both which is usually behind firms that excel in innovation. as a consequence, knowledge management may be used to propel the integration between STI and DUI-modes by enabling shared access to codified knowledge, as well as supporting knowledge-based interaction within the firm and across its boundaries (clients, partners, market in general).
The role of knowledge management for innovation is not new, but the focus has shifted as organizations move towards a service-based paradigm, as argued by Darroch (2005). Rather than seeing resources as the main assets of the organization, the key are the services those resources actually deliver. And in order for a resource to deliver a service, it must be coupled to a capability (skills or experience which enable exploiting a particular resource). Seen this way, knowledge is a resource and knowledge management is a coordination mechanism which supports its transformation into a capability, specifically the capability to innovate. A study of New Zealand firms shows that this is the case for all three phases of knowledge management. Acquisition, Dissemination and Responsiveness to Knowledge all contribute to innovation (or rather, innovative firms usually support these three KM functions).
viernes, 8 de julio de 2011
No hay clase Julio 12
Olvidé decurles que debido a un compromiso adquirido antes del inicio del curso, este martes 12 de julio no habrá clase. La idea es reponerla después, pero por ahora significa que la lectura para el 12 es ahora para el 19. Nos vemos entonces.
Knowledge management in Colombia (Jul. 5)
Knowledge management (KM), we have seen, is a rich, multi-disciplinary field. But it should be noted that the various theories that inform KM have mostly been borne within developed countries and it is worth reflecting upon their applicability in different contexts, such as the Colombian one. We have discussed the need for KM in an information / knowledge / networked society where globalized capitalism dominates; however, this generalization of the whole of society under a single market-based understanding is problematic and risky. In Colombia, the idea of a networked nation ("nación-en-red") has been around for some time without emphasizing the economic dimension of the network, but rather its emergence out of a self-organization of our inherent diversity in geographic, economic, ethnic, cultural and socio-historical terms (Fals-Borda, 2003: 19). This implies, for instance, that the strengthening of a networked nation should lead us to our own vernacular roots, more authentic within our context, without the need for xenophobic attitudes. It is a matter of protecting our endogenous knowledge, preventing it from being given away to "the North" only to be fed back after having been transformed by foreigners according to their logic and interests (ibid.: 25-26), such as when traditional medicine is appropriated by multi-national pharmaceuticals or when our artists are reshaped by corporations who transform their identity to cater to an international commercial pre-fabricated taste. The challenge is thus to look inwards without loosing a global perspective, through the development of alternative and contextualized scientific, cultural and political paradigms useful for our own vital needs (ibid.: 82).
It is in our own best interest to understand and accept the fact that knowledge transfer (or the introduction of foreign innovations or products) alone does not always result appropriate for problems generated within our context. Even if this knowledge is amazingly sophisticated, novel and of proven utility in different environments, it may end up generating chaos while at the same time weakening the creation of local knowledge (ibid.: 87). Again, the idea is not to isolate ourselves from the external intellectual world but to accumulate knowledge ("suma de saberes") congruent with out growth and progress and linked to locally developed knowledge (ibid.:92). As a consequence, the activity of knowledge management in Colombia should (1) foster the creation and sharing of locally developed knowledge, and (2) be supported by KM theories and instruments that have been contextualized and linked to local scientific theories and culture.
In that sense, it is worthwhile to consider the state of current knowledge management in the country, as well as some of the specific challenges and opportunities it has raised. In a 2007 survey paper, Baquero and Schulte explore KM practices in 50 Colombian organizations. While the study shows that there is an increasing interest in developing KM programs, departments and systems (around half of the organizations surveyed were planning to develop KM strategies at that time), it also shows the worrying fact that very few organizations actually believe that their value systems and culture facilitate KM practices. Despite these limitations and the fact that most efforts are weakly supported by underlying KM systems (i.e. ICT), the results have mostly been effective, including: increased knowledge sharing, higher productivity, better customer relationships, improved organizational memory, increased innovation and more employee involvement. Some of the challenges and shortcommings identified are: the lack of measurement of KM effectiveness, the difficulty in capturing tacit knowledge, the tendency to see KM as theoretical (generating resistance to KM), the lack of resources, the fact that sharing knowledge is often seen as loosing power and low overall adoption. This means that there are strong opportunities in terms of consulting, research and development of contextualized theories and systems for KM in Colombia.
It is in our own best interest to understand and accept the fact that knowledge transfer (or the introduction of foreign innovations or products) alone does not always result appropriate for problems generated within our context. Even if this knowledge is amazingly sophisticated, novel and of proven utility in different environments, it may end up generating chaos while at the same time weakening the creation of local knowledge (ibid.: 87). Again, the idea is not to isolate ourselves from the external intellectual world but to accumulate knowledge ("suma de saberes") congruent with out growth and progress and linked to locally developed knowledge (ibid.:92). As a consequence, the activity of knowledge management in Colombia should (1) foster the creation and sharing of locally developed knowledge, and (2) be supported by KM theories and instruments that have been contextualized and linked to local scientific theories and culture.
In that sense, it is worthwhile to consider the state of current knowledge management in the country, as well as some of the specific challenges and opportunities it has raised. In a 2007 survey paper, Baquero and Schulte explore KM practices in 50 Colombian organizations. While the study shows that there is an increasing interest in developing KM programs, departments and systems (around half of the organizations surveyed were planning to develop KM strategies at that time), it also shows the worrying fact that very few organizations actually believe that their value systems and culture facilitate KM practices. Despite these limitations and the fact that most efforts are weakly supported by underlying KM systems (i.e. ICT), the results have mostly been effective, including: increased knowledge sharing, higher productivity, better customer relationships, improved organizational memory, increased innovation and more employee involvement. Some of the challenges and shortcommings identified are: the lack of measurement of KM effectiveness, the difficulty in capturing tacit knowledge, the tendency to see KM as theoretical (generating resistance to KM), the lack of resources, the fact that sharing knowledge is often seen as loosing power and low overall adoption. This means that there are strong opportunities in terms of consulting, research and development of contextualized theories and systems for KM in Colombia.
miércoles, 29 de junio de 2011
Social and intellectual capital (Jun. 28)
The fact that we live within a market-based globalized capitalist society renders traditional hierarchical, mechanistic organizations obsolete. Thus, we have been told that in a post-industrial economy, intangible assets, knowledge-based organizations and social capital are the way forward, as expressed in Manning (2010). Indeed, the very notion of capitalism has changed within neo-capital theories, according to which the market is subordinated by social and political realities. While classic capitalism underlines returns on investments and profit-maximizing as an organizational goal, neo-capital theories couple financial goals to social-based objectives such as sociability, acceptance, status and power. Furthermore, the concept of capital is shifted or extended to include human and intellectual capital. As such, the concept of social capital was introduced as an umbrella concept for social sciences emphasizing the positive effects of sociability for organizations. In addition, this movement offers the use of analytical tools based on social relations (e.g. social network analysis) in order to design and evaluate knowledge management strategies to foster and develop social capital.
But, as Manning argues, social capital is not just about creating or modelling social relations, it is about the reciprocity, norms and beliefs that should be coupled to those relations in order for real value or wealth to be generated. For a strong social fabric to emerge, expectations and trustworthiness must be part of the social network and effective information channels must be in place. Those conditions are typically only possible within closed networks with clear norms that enforce a behavior that strikes the right balance between individual self-interest and group-wide goals. This balance is hard to achieve because norms can either foster or restrict behavior, resulting in conflicting trade-offs. In addition, while the closure of the network prevents easy entry or exit (which results in less commitment or identity) it may also render the network less able to adapt to the dynamics of the globalized capitalist market. If social capital building initiatives are not built strategically with an eye on long-term impact, further negative outcomes may include: discrimination, "old boys club" effect, conflicts around the legitimacy of knowledge ownership and potential threats to privacy.
But, as Manning argues, social capital is not just about creating or modelling social relations, it is about the reciprocity, norms and beliefs that should be coupled to those relations in order for real value or wealth to be generated. For a strong social fabric to emerge, expectations and trustworthiness must be part of the social network and effective information channels must be in place. Those conditions are typically only possible within closed networks with clear norms that enforce a behavior that strikes the right balance between individual self-interest and group-wide goals. This balance is hard to achieve because norms can either foster or restrict behavior, resulting in conflicting trade-offs. In addition, while the closure of the network prevents easy entry or exit (which results in less commitment or identity) it may also render the network less able to adapt to the dynamics of the globalized capitalist market. If social capital building initiatives are not built strategically with an eye on long-term impact, further negative outcomes may include: discrimination, "old boys club" effect, conflicts around the legitimacy of knowledge ownership and potential threats to privacy.
jueves, 23 de junio de 2011
A multi-discipinary, multi-technological field (Jun. 21)
Knowledge management (KM) is a multi-disciplinary, multi-technological field. Not just because knowledge itself is at the heart of every discipline (and as such, has many definitions, contexts and interests surrounding it) but because the management of it is founded on a number of different theories. Baskerville and Dulipovici (2006), for instance, provide an account of the theoretical foundations which covers many different aspects from different points of view. In order to present an introductory tour around the foundations, the auhtors structure it around a specific taxonomy. They devise three main purposes related to KM: the rationale behind the terminology and the use of KM, the process definition through which KM is achieved and technologically supported, and the evaluation of KM efforts.
The rationale of KM has been informed mainly by information economics and strategic management, indicating the organizational and strategic philosophy behind KM. This has resulted in some of the "classic" concepts behind KM, such as intellectual capital and dynamic capabilities. Specific concepts or theories that have been developed out of this tradition for KM include: knowledge networks, continuity management, knolwedge marketplaces and knowledge capabilities. In a way, this tradition sees many authors relating knowledge to other classic organizational resources or assets in order to use them in a strategic way, either by enabling a firm to create value out of the production and sharing of knolwedge, or pushing the firm to establish knolwedge-based alliances with other partners.
With respect to the process definition, we see a variety of disciplines required to develop a particular KM strategy, favoring a knowledge culture and using information and communication technology (ICT) in order to support this strategy with an eye on creating value and fostering innovation within an organization. Accordingly, Baskerville and Dulipovici, include many different theories related to this KM dimension based on four foundations: organizational culture, structure and behavior, as well as artificial intelligence. Through this foundations, research has contributed an array of concepts and frameworks to develop a knowledge culture through a specific knowledge structure and with a specific KM process (i.e. creation, codification and transfer / use). This organizational design is typically supported by a knolwedge infrastructure which is supported on knolwedge-based systems and data mining techniques in order to exploit ICT for KM purposes.
Regarding evaluation, the taxonomy proposes quality management and organizational performance as the foundations that lead to specific ways in which knolwedge and knowledge management can be assessed in a firm. Aside from financial measures (which try to pin down KM to the bottom-line in terms of cost and benefit), more qualitative frameworks are also avaialble.
In sum, KM is structured around economics, organizational theory, management science and an ICT component which is usually supported by artifical intelligence techniques and tools. In fact, in a different paper Liao (2003) offers another taxonomy for KM focusing on the technoologies and applications that are part of the KM catalogue. This results in a review of knolwedge-based systems, data mining, basic ICT (information processing and networking), expert systems, databases and systems modelling approaches which have all been applied in the field of KM. It can be thus gathered that there is nos single approach to KM nor a well-defined set of technologies that should be implemented to support it. Rather, it is a task for each organization to determine their own KM strategy (obviously aligned with the general organizational goals and context), process and supporting ICT infrastructure. This is much the same case as with information systems in general, where the resulting system is defined by the interaction between the organization (the structure and processes), the people (users, managers, stakeholders) and the technology (ICT systems, models and methods).
Accordigly, it makes sense to approach KM with a design science research in information systems perspective (Hevner et al., 2004). On the one hand, we have the environment in which the organizational context resides and from which requirements (opportunities, needs, gaps) are identified. On the other hand, we have the knolwedge base (concepts, models, methods and artifacts) which offers applicable knolwedge to satisfy those requirements (out of published material along with prior experience). In the core, there is a design process (itearting between construction and evaluation) which merges the requirements and the applicable knolwedge into the design of a specific artifact that solves a problem in the defined context. Indeed, design is problem-solving and problem-solving is seen as changing existing situations into desired ones (following Herbert Simon's tradition).
Overall, this offers the introductory strategy and material for the course and for developing each group project around a KM problem in a real-world organization. The result should be an artifact that potentially solves the problem using the knolwedge offered in the course and does so in a creative way. We will continue to explore in more detail some of the most imporant concepts, models and technologies while at the same time carrying out the problem-solving design. Each participant should go through the presentation of technologies (see the course documents link on the right of this blog) and explore the different web-based examples as a way to potentially inspire their own design or be used as a component of their resulting artifact.
The rationale of KM has been informed mainly by information economics and strategic management, indicating the organizational and strategic philosophy behind KM. This has resulted in some of the "classic" concepts behind KM, such as intellectual capital and dynamic capabilities. Specific concepts or theories that have been developed out of this tradition for KM include: knowledge networks, continuity management, knolwedge marketplaces and knowledge capabilities. In a way, this tradition sees many authors relating knowledge to other classic organizational resources or assets in order to use them in a strategic way, either by enabling a firm to create value out of the production and sharing of knolwedge, or pushing the firm to establish knolwedge-based alliances with other partners.
With respect to the process definition, we see a variety of disciplines required to develop a particular KM strategy, favoring a knowledge culture and using information and communication technology (ICT) in order to support this strategy with an eye on creating value and fostering innovation within an organization. Accordingly, Baskerville and Dulipovici, include many different theories related to this KM dimension based on four foundations: organizational culture, structure and behavior, as well as artificial intelligence. Through this foundations, research has contributed an array of concepts and frameworks to develop a knowledge culture through a specific knowledge structure and with a specific KM process (i.e. creation, codification and transfer / use). This organizational design is typically supported by a knolwedge infrastructure which is supported on knolwedge-based systems and data mining techniques in order to exploit ICT for KM purposes.
Regarding evaluation, the taxonomy proposes quality management and organizational performance as the foundations that lead to specific ways in which knolwedge and knowledge management can be assessed in a firm. Aside from financial measures (which try to pin down KM to the bottom-line in terms of cost and benefit), more qualitative frameworks are also avaialble.
In sum, KM is structured around economics, organizational theory, management science and an ICT component which is usually supported by artifical intelligence techniques and tools. In fact, in a different paper Liao (2003) offers another taxonomy for KM focusing on the technoologies and applications that are part of the KM catalogue. This results in a review of knolwedge-based systems, data mining, basic ICT (information processing and networking), expert systems, databases and systems modelling approaches which have all been applied in the field of KM. It can be thus gathered that there is nos single approach to KM nor a well-defined set of technologies that should be implemented to support it. Rather, it is a task for each organization to determine their own KM strategy (obviously aligned with the general organizational goals and context), process and supporting ICT infrastructure. This is much the same case as with information systems in general, where the resulting system is defined by the interaction between the organization (the structure and processes), the people (users, managers, stakeholders) and the technology (ICT systems, models and methods).
Accordigly, it makes sense to approach KM with a design science research in information systems perspective (Hevner et al., 2004). On the one hand, we have the environment in which the organizational context resides and from which requirements (opportunities, needs, gaps) are identified. On the other hand, we have the knolwedge base (concepts, models, methods and artifacts) which offers applicable knolwedge to satisfy those requirements (out of published material along with prior experience). In the core, there is a design process (itearting between construction and evaluation) which merges the requirements and the applicable knolwedge into the design of a specific artifact that solves a problem in the defined context. Indeed, design is problem-solving and problem-solving is seen as changing existing situations into desired ones (following Herbert Simon's tradition).
Overall, this offers the introductory strategy and material for the course and for developing each group project around a KM problem in a real-world organization. The result should be an artifact that potentially solves the problem using the knolwedge offered in the course and does so in a creative way. We will continue to explore in more detail some of the most imporant concepts, models and technologies while at the same time carrying out the problem-solving design. Each participant should go through the presentation of technologies (see the course documents link on the right of this blog) and explore the different web-based examples as a way to potentially inspire their own design or be used as a component of their resulting artifact.
martes, 14 de junio de 2011
Programa del Curso (Especialización GT)
Justificación |
El tipo de sociedad en la que vivimos (o hacia la que vamos) ha sido caracterizado como sociedad de la información, sociedad del conocimiento, sociedad en red o sociedad post-industrial. Esto es un reconocimiento de que el mundo cultural, económico y socio-político está inmerso dentro de un cambio cuyos efectos ya son generales y que están conectados a la ubicuidad de un modelo de capitalismo globalizado frente al cual individuos y empresas deben estar preparados. Por ello se ha venido haciendo énfasis en los trabajadores del conocimiento o las empresas basadas en el conocimiento como una prerrequisito para la supervivencia en un entorno dinámico y altamente competitivo. Sin embargo, el conocimiento no es un recurso en el sentido tradicional: emerge a partir de la interacción entre dichos trabajadores y entre empresas de diversa índole. La gestión del conocimiento y las herramientas tecnológicas que lo soporten buscan precisamente facilitar el proceso de generación y compartición de conocimiento, de manera que pueda ser el motor para la innovación y la sostenibilidad de empresas, comunidades y países enteros. |
Objetivos |
El objetivo general del curso es identificar y describir los enfoques contemporáneos para el estudio de la gestión del conocimiento, el desarrollo de sistemas de gestión del conocimiento y su administración con miras a generar valor agregado estratégico en organizaciones reales. Al final del curso, el estudiante debe ser capaz de vincular los procesos de negocios con la gestión de conocimiento. Adicionalmente, debe haber adquirido la habilidad de liderar el desarrollo estratégico y tecnológico de sistemas de gestión del conocimiento en una organización en busca de una cultura innovadora. |
Contenidos Temáticos |
Módulo 1: Fundamentos de la gestión del conocimiento 1.1.Fundamentos teóricos de la gestión del conocimiento 1.2.TI para la gestión del conocimiento 1.3.Capital intelectual y capital social 1.4.Gestión del conocimiento en Colombia Módulo 2: La gestión del conocimiento y la innovación 2.1. Innovación basada en el conocimiento 2.2. Gestión del conocimiento, estrategia y creación de valor 2.3. Inteligencia del negocio y gestión del conocimiento 2.4. Capacidades dinámicas y gestión del conocimiento Módulo 3: La gestión del conocimiento organizacional: aprendizaje, redes y medición 3.1. Gestión del conocimiento y aprendizaje organizacional 3.2. Redes sociales y redes de negocios 3.3. La medición del conocimiento |
Estrategias Pedagógicas |
El desarrollo de las actividades ligadas a las estrategias descritas a continuación se apoyará mediante la creación de foros, blogs y otras herramientas virtuales. - Aprendizaje Directivo: En los encuentros presenciales, se llevarán a cabo presentaciones y talleres dirigidos por el profesor en torno a cada uno de los módulos del curso. - Autoaprendizaje y Proyección: Se promoverá dentro de los estudiantes el desarrollo de competencias de investigación autónoma, a través de la consecución, lectura y análisis de artículos científicos y estudios de casos relacionados con los temas asociados a la asignatura. El trabajo se desarrollará sobre la exigencia de que el estudiante prepare los temas señalados, utilizando para esto la bibliografía del curso y los artículos recientes publicados en el tema de trabajo. En la clase, los estudiantes socializarán el resultado del análisis realizado, generando una discusión abierta en la clase, en la cual el profesor se concentrará en la resolución de dudas, contribuirá con explicaciones complementarias y el análisis de los impactos en los contextos de aplicación. - Proyecto de Apropiación Práctica: El curso se estructura alrededor de un proyecto que tiene por objeto lograr que el estudiante profundice y apropie los conceptos mediante la solución de un problema práctico. El proyecto pretende que los estudiantes: profundicen el estado del arte, identifiquen problemas en los cuales los conocimientos del curso se pueden aplicar, apliquen los conceptos, realicen un proceso riguroso de desarrollo del proyecto, apliquen elementos metodológicos apropiados, analicen los impactos sobre el entorno, generen un informe con el suficiente formalismo y obtengan un mayor conocimiento de las herramientas disponibles. - Resolución de Problemas: Se llevarán al aula de clase, problemas de aplicación y casos de estudio; los cuales se trabajaran por medio de talleres. Los estudiantes presentarán ante la clase los análisis realizados y las posibles soluciones propuestas relacionándolas con los conocimientos dados en clase. Este análisis debe tener un sustento conceptual y teórico; además, esta presentación debe ser realizada utilizando el formalismo y rigor adecuado. Las soluciones propuestas, en la medida de lo posible, no deben limitarse a una propuesta puramente técnica, sino que también deben tener en cuenta factores del contexto de aplicación y uso. |
Evaluación |
Proyecto: 40% (Entrega 30% y presentación pública 10%) Actidades Independientes: 30% (lecturas, investigaciones, evaluaciones, participación) Talleres grupales en clase: 30% |
Bibliografía |
|
Programa Detallado | |||
Semana | Fecha | Tema | Referencias |
1. Fundamentos de la Gestión del Conocimiento | |||
1 | Fundamentos teóricos de la gestión del conocimiento | (Baskerville & Dulipovici, 2006) | |
2 | TI para la gestión del conocimiento | (Liao, 2003) | |
3 | Capital intelectual y capital social | (Manning, 2010) | |
4 | Gestión del conocimiento en Colombia | (Baquero & Schulte, 2007) | |
2. La gestión del conocimiento y la innovación | |||
5 | Innovación basada en el conocimiento | (Darroch, 2005; Jensen, Johnson, Lorenz, & Lundvall, 2007) | |
6 | Gestión del conocimiento, estrategia y creación de valor | (Vorakulpipat & Rezgui, 2008) | |
7 | Inteligencia del negocio y gestión del conocimiento | (Cody, Kreulen, Krishna, & Spangler, 2002; Herschel & Yermish, 2009) | |
8 | Capacidades dinámicas y gestión del conocimiento | (Sher & Lee, 2004; Zollo & Winter, 2002) | |
3. La gestión del conocimiento organizacional: aprendizaje, redes y medición | |||
9 | Gestión del conocimiento y aprendizaje organizacional | (Borgatti & Cross, 2003; Yang, 2007) | |
10 | Redes sociales y redes de negocios | (Dyer & Hatch, 2006; Galbraith, Downey, & Kates, 2002) | |
11 | La medición del conocimiento | (Bose, 2004; Kaplan & Norton, 2007) | |
12 | Presentaciones y entrega final | ||
jueves, 10 de febrero de 2011
Artículo resultado del curso es aceptado en conferencia internacional
El artículo generado en el curso Gestión del Conocimiento el semestre pasado por los estudiantes Juan Carlos Guevara, José Luis Lara y Carlos Moque fue aceptado en el evento ED-MEDIA 2011--World Conference on Educational Multimedia, Hypermedia & Telecommunications. El título del artículo aceptado para presentación y publicación es: " Knowledge Management Systems to support the research groups’ activities." Felicitaciones a los tres; es un buen ejemplo de cómo se puede generar conocimiento a partir del trabajo orientado a proyectos académicos en los cursos de MISyC de la Javeriana.
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