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.
miércoles, 29 de junio de 2011
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 | ||
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