Knowledge Management Implementation - The authors discuss the technology and guidance required to achieve good knowledge management in a biopharmaceutical company. - BioPharm International

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Knowledge Management Implementation
The authors discuss the technology and guidance required to achieve good knowledge management in a biopharmaceutical company.


BioPharm International
pp. 50-55

Phase 4: Classification of structured and unstructured assets

Data from various locations can be categorized as structured and unstructured assets. The structured assets are data that are stored in several database tables within specific applications according to the need of a particular business line. Typical examples are chromatography system software for storage of process information, chromatograms and reports of a particular chromatography process, or ERP systems for materials management. The data that are not stored in several database tables within specific applications are unstructured assets. Unstructured assets can be divided into documented and undocumented assets. Documented assets are unstructured assets stored in various process templates, or spreadsheets. Undocumented assets are unstructured assets which are not stored in anywhere in an enterprise. A typical example of an undocumented asset is expert knowledge that a process consultant stores in his brain.

Phase 5: Transformation of data and information into knowledge


Figure 3: Implementation of data access control strategy.
This phase deals with organizing the data and information and converting them to knowledge-rich information systems. An example of such an information system is an electronic document management system (EDMS). The EDMS manages electronic documents, scanned documents, pictures, tables, and other types of data. It enables efficient search, controlled storage, data security, data sharing, and data nonredundancy. Furthermore, these management systems enable secured access through different business lines. Consider a case as shown in Figure 3, where data is to be shared between quality control, R&D, and production managers. In this typical case the R&D manager can directly access the R&D data but can't access the production data. If he needs to consult any production data, he can access the data via access procedures through a production officer. A similar interaction can be described between a quality head and a production head.

Phase 6: Proposing the system structure


Figure 4: System structure of knowledge management.
This phase includes providing IT solution by creating a KM framework. This stage mainly deals with proposing the the system structure for KM. A typical example of such a framework is shown in Figure 4, where the user (e.g. R&D person, Finance officer etc.) interacts with a web-based interface through the internet or intranet. The Interface is designed in such a way that it is connected to all information management systems (e.g., enterprise resource planning, project management systems, learning and development modules, etc.) All information management systems, project management systems, learning and development modules, literature modules, and so forth, are connected to a database at the backend. This approach helps in effective data mining and prevents data redundancy and data overload.

Phase 7: Implementing the system structure

This phase includes the development of the system structure of KM. The development is carried out taking software development life cycle models in consideration. After development, the software is tested vigorously followed by maintenance. To implement the software solution of KM, various training sessions need to be conducted where people in the organization can understand the importance of KM, learn to implement KM through software solutions, and explore other issues regarding KM.


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