How Web 2.0 technologies are transforming collaborative knowledge management systems

Knowledge Management

Literature Review of Knowledge Management

Relationship between Data, Information, and Knowledge

Evaluating the Types of Knowledge and Knowledge Management Systems

Power of Knowledge to Transform Organizations

Web 2.0 Meme Map

The re-orienting of knowledge management from rigid, functionally driven, ontological data structures to more collaborative approaches to capturing, classifying, analyzing data and creating knowledge is occurring at a rapid pace today. The combining of Web 2.0 technologies (O'Reilly, 2006) and social networking are transforming the area of knowledge management, making the field more mercurial and rapid in its change. As a result of these fundamentally different approach to knowledge management including greater collaboration-based workflows that are capitalizing on the lessons learned from social networking (Parise, 2009) while at the same time finding that real-time data and system integration (Dadzie, Lanfranchi, Petrelli, 2009) can yield significantly greater knowledge generation. The net effect of this fundamental reordering of knowledge management systems that capitalize more on the collaborative nature of how organizations, groups, teams and individuals work with each other (Baldi, Heier, 2009). This reorientation of knowledge management to align more closely with how collaborative process workflows in modem organizations has also been shown to increase an organization's competitiveness (Massa, Testa, 2009). The greater the level of knowledge propagation and collaborative use, the greater the agility of organizations to respond to turbulent economic conditions as well (Kiessling, Richey, Meng, Dabic, 2009). The intention of this literature review is to explain how knowledge management is transforming organizations.

Relationship between Data, Information, and Knowledge

The progression of data to knowledge is one that is also being re-ordered by the more process-centric and highly collaboratively-driven approach to knowledge management. Ontologically-based relationships between data elements are today creating entirely new data models that were not available in previous generation systems given the constraints of their technology (Sicilia, Sicilia, Sanchez-Alonso, Garcia-Barriocanal, Pontikaki, 2009).

The sources of knowledge within an organization continue to expand in proportion of the ability of companies to capture it. From the suppliers, network of channel partners, resellers, dealers, distributors and service providers to the sales, marketing and pricing teams, there is knowledge being generated continually within organizations. There is a massive amount of knowledge generated within manufacturing and service provider organizations, as the most optimal approaches to generating results is continually pursued. In short, each department within an organization generates knowledge. What varies is the extent of the structure of the data, from highly structured to unstructured, from data that is highly granular in nature to those data sets which are full records of quantitative data which need to be analyzed. The ability to gain insights from the knowledge within organizations is directly dependent on the rigidity or agility of taxonomies that support its capture and use (Ardichvili, Yoon, 2009).

Data then continues to be a more active element or component than the traditional, hierarchical and often rigid definition of this element of a knowledge management system from the past. Data now has itself become more collaborative within enterprises and serves as the catalyst of significantly redefining how knowledge management systems within the enterprise are created (McAfee, 2006). The combining of SOA platforms, the integration of Web Services, and the growth of XML as the means for interconnecting and integrating these systems and processes together has taken data would otherwise not have been as valuable and put it into a more productive context. Web 2.0 design objectives' impact on the design, development and continued fine-tuning of knowledge management applications is creating more contexts into which data can be applied, thereby increasing its value. In conjunction with the socially-driven, more collaborative aspects of how Web 2.0 is transforming knowledge management, this technical aspect is also increasing the value of data, its context in broader, more strategic knowledge management initiatives, and assisting in putting more into context.

Many of the evaluation frameworks of knowledge management (Nevo, Furneaux, Wand, 2008) include the core concepts of the Five C. Model (Ardichvili, Yoon, 2009). The Five C. Model is comprised of the process areas of Conduit; functional and process areas of Content; all process, functional areas and development areas of collaboration, often called the Conversation; Context; and the ability to manage of the many forms of content, often called Control. The Five C. Model is more attuned to the structure of knowledge management systems as repositories of data, often with taxonomies that are long-standing and rarely changing. Given the rapid growth of social networking based on the collaborative design objectives of Web 2.0 technologies (O'Reilly, 2006), taxonomies are becoming more role- and process-based, aligning more effectively to the needs of organizations. In conjunction with this change from rigid, static taxonomies to more role- and process-based ones, there is a corresponding shift to content that is contextual in scope (Baldi, Heier, 2009). The impact of the highly collaborative platforms of social networking has in fact created contextual content that is suitable for roles in an organization and the processes they support. This approach to using contextual content is also changing the nature, depth, and quality of Conversation within the Five C. Model as well. The Conduit and Control aspects of this model are also going through a transformation as a result of the adoption of more collaborative approaches to generating, sharing, analyzing and using knowledge as well. In short, Web 2.0 design principles are acting as an accelerator in the context of the Five C. Model, forcing each of the components to work more closely integrated with each other, making the entire ecosystem the model represents more focused on velocity and less on the areas of rigid, static and often limiting taxonomies that had dominated knowledge management systems in the past (Ardichvili, Yoon, 2009). In summary, Web 2.0 technologies in general and social networking specifically have created an accelerator effect driven by greater levels of collaboration and information sharing, all predicated on more agile, role- and process-based knowledge management system architectures (Parise, 2009). The advent of Web Services within knowledge management systems driven by Web 2.0 design principles brings the multiplicity of needs of users more into the actual structure of taxonomies and design requirements (Ardichvili, Yoon, 2009). In addition to serving as the catalyst of greater acceleration of the Five C. Model, Web 2.0 design requirements are making knowledge management more closely align with the precise needs of users. This is significant as a development in knowledge management systems, as in previous-generation architectures this type of alignment would take multiple iterations, or changes; to a given knowledge management system to achieve the level of alignment of system design to user needs (Baldi, Heier, 2009). The uses of XML as an integration technology and AJAX as a rapid prototyping application and thin Web-based client have further served as catalysts to the rapid increases in performance of knowledge management systems. In addition to all of these factors the rapid adoption of the Software-as-a-Service (SaaS) platform which supports multi-tenancy and the ability to scale to support thousands of users of knowledge management systems, and the full implications of Web 2.0 and its many development, design and performance gains can be seen.

Evaluating the Types of Knowledge and Knowledge Management Systems

Knowledge management systems have historically excelled in the areas of structured content that emanates from the traditional enterprise content management (ECM) and in some companies, their Enterprise Resource Planning (ERP) systems (Ardichvili, Yoon, 2009). The use of structured content in the context of traditional knowledge management systems led to the development of structured, often rigidly defined reports that over time became irrelevant in their use as business' need for knowledge shifted drastically over time. These initial knowledge management systems were more hierarchical, structured with silos of databases and integrated through the use of Search functions and on high-end systems, a reliance on Enterprise Application Integration (EAI) approaches to bridging the gaps between systems. Report writing software and knowledge-based analytics applications became increasingly in demand to meet the changing requirements for users of these systems to gain new insights from the knowledge included within them.

As these systems over time began to prove to be too rigid to meet the needs of users, a shift was occurring in the structure of knowledge management systems as well (Ardichvili, Yoon, 2009). More efficient, streamlined integration technologies including XML and its many variants, the growth of AJAX as a thin-client-based programming language, the development of relational databases, and the growth of the SOA platform in conjunction with Web Services have all come together to create more agile knowledge management systems (Baldi, Heier, 2009). All of these factors have also been accelerated by the importance of collaboration as a design objective for Web 2.0 (O'Reilly, 2006) which has had a corresponding effect on all applications, knowledge management being one of the most influenced due to the many users of these systems (Ardichvili, Yoon, 2009).

Due to the rapid development of Web 2.0-based knowledge management systems, there also has been a corresponding increase in their importance within organizations as well. From the many tactical roles that knowledge management fulfilled within organizations across all industries, given how collaboration and new technologies are acting as accelerators, knowledge management as a strategic resource has arrived, especially in highly regulated industries where advanced knowledge are critical to process execution (Sicilia, Sicilia, Sanchez-Alonso, Garcia-Barriocanal, Pontikaki, 2009). The strategic role of knowledge management has also been augmented by the roles- and process-based approach that companies can now use to selectively deliver the most relevant knowledge to those that need it. The strategic role of knowledge management to transform organizations is proven as companies are able today to construct learning ecosystems throughout their entire supply chains (Dyer, Nobeoka, 2000)

Power of Knowledge to Transform Organizations

The global economic recession has shown that to the extent there is integration between the knowledge management systems throughout an organization is the extent to which they can gain greater insights into how to compete more effectively (Kiessling, Richey, Meng, Dabic, 2009). Having progressed from being focused purely on knowledge that was easily captured and therefore rigid and difficult to use in a multitude of scenarios, knowledge management systems have rapidly progressed to a strategic asset. The use of knowledge management specifically in the area of pricing management and optimization is a case in point. The impact of knowledge management in pricing systems continues to provide consumer packaged goods companies including food producers with much greater levels of insight into price elasticity (Massa, Testa, 2009). This has given many food companies the ability to stay financially viable in the midst of the current recession.

Conclusion

Knowledge management's contributions continue to accelerate based on the rapid growth of Web 2.0 design principles (O'Reilly, 2006) applied to enterprise-level knowledge needs, creating the foundation of Enterprise 2.0 (McAfee, 2006). Social networking's impact on knowledge management continues (Parise, 2009) as the design objectives of greater collaboration and sharing of information across processes and roles accelerates. Compounding this is the growth of XML and AJAX as strategic technologies in the development of knowledge management systems (Ardichvili, Yoon, 2009). All of these factors are combining to create a more strategic role for knowledge management within organizations which will only accelerate over the coming years.