Knowledge Management Systems: Design, Implementation, Review Report
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This report provides a comprehensive overview of Knowledge Management Systems (KMS) and their significance in business development. It discusses the essential aspects of KMS, starting with an introduction that highlights the importance of information and knowledge management for organizatio...

Running head: KNOWLEDGE MANAGEMENT SYSTEMS
Knowledge Management Systems
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Knowledge Management Systems
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1KNOWLEDGE MANAGEMENT SYSTEMS
Table of Contents
Introduction......................................................................................................................................2
Discussion........................................................................................................................................2
Design..........................................................................................................................................2
Implementation............................................................................................................................3
Review.........................................................................................................................................3
Conclusion.......................................................................................................................................4
Reference List..................................................................................................................................5
Table of Contents
Introduction......................................................................................................................................2
Discussion........................................................................................................................................2
Design..........................................................................................................................................2
Implementation............................................................................................................................3
Review.........................................................................................................................................3
Conclusion.......................................................................................................................................4
Reference List..................................................................................................................................5

2KNOWLEDGE MANAGEMENT SYSTEMS
Introduction
Organizations need information and knowledge to develop their business and achieve
maximum growth. However, a huge amount of information often creates information overload.
A Knowledge Management System (KMS) is essential to manage such a large amount of
information (Dalkir & Beaulieu, 2017). This paper serves the purpose to summarize the use and
application of a KMS.
Discussion
KMS can be designed centered on the information requirement of the organization. The
levels and complexity of the system depends on the knowledge management process.
Design
There are four major processes involved while designing a KMS:
Data collection: The collection of data must be systematic to maximize the amount of
information inflow. Many organizations collect data by using customer surveys to
understand their buying preference. Some organizations like Amazon collect data from
the users Internet browsing history to generate product recommendations (Smith &
Linden, 2017).
Data storage: The collected data must be stored in the organizations’ servers for retrieval.
The data can thus be utilized for analysis to develop the required business plans.
Data indexing: The stored data must be indexed. Indexing means that the data is
categorized with respect to either its source or its use and then stored (Gani et al., 2016).
This increases the easiness of information retrieval.
Introduction
Organizations need information and knowledge to develop their business and achieve
maximum growth. However, a huge amount of information often creates information overload.
A Knowledge Management System (KMS) is essential to manage such a large amount of
information (Dalkir & Beaulieu, 2017). This paper serves the purpose to summarize the use and
application of a KMS.
Discussion
KMS can be designed centered on the information requirement of the organization. The
levels and complexity of the system depends on the knowledge management process.
Design
There are four major processes involved while designing a KMS:
Data collection: The collection of data must be systematic to maximize the amount of
information inflow. Many organizations collect data by using customer surveys to
understand their buying preference. Some organizations like Amazon collect data from
the users Internet browsing history to generate product recommendations (Smith &
Linden, 2017).
Data storage: The collected data must be stored in the organizations’ servers for retrieval.
The data can thus be utilized for analysis to develop the required business plans.
Data indexing: The stored data must be indexed. Indexing means that the data is
categorized with respect to either its source or its use and then stored (Gani et al., 2016).
This increases the easiness of information retrieval.
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3KNOWLEDGE MANAGEMENT SYSTEMS
Searchability: The interface for data searching must be easy to use. Searchability is a
continuation of the data indexing process. The indexed data can be searched using some
definite keywords related to the information stored (Jan & Contreras, 2016). The users
can thus easily access the data by entering the relevant keywords of the information they
are trying to acquire.
There is one more factor that must be considered while designing a knowledge
management system, the users who would use the system. The ability of each individual to
utilize the system to increase productivity must be considered.
Implementation
The designed system is now ready for implementation. The system can be initiated by
rolling out the data collection phase. Different data collection sources like surveys and
documents can be utilized. The collected information can then be indexed and stored. This type
of system is commonly implemented on the Intranets of different organizations. Thus, the users
of the system must be trained by experts to ensure that the system is used to its maximum
capabilities. Providing the necessary training is mandatory as some employees might not be
comfortable at using new technologies. International companies must also tend to the issue of
language barriers during the implementation of their knowledge system. Different branch offices
are located at various geographical locations. Thus, a common language must be used for
knowledge sharing purposes.
Review
There is no suitable metrics to measure the amount of information stored. However, the
progress of the organization after implementing such a system can be viewed and verified by
analyzing its growth.
Searchability: The interface for data searching must be easy to use. Searchability is a
continuation of the data indexing process. The indexed data can be searched using some
definite keywords related to the information stored (Jan & Contreras, 2016). The users
can thus easily access the data by entering the relevant keywords of the information they
are trying to acquire.
There is one more factor that must be considered while designing a knowledge
management system, the users who would use the system. The ability of each individual to
utilize the system to increase productivity must be considered.
Implementation
The designed system is now ready for implementation. The system can be initiated by
rolling out the data collection phase. Different data collection sources like surveys and
documents can be utilized. The collected information can then be indexed and stored. This type
of system is commonly implemented on the Intranets of different organizations. Thus, the users
of the system must be trained by experts to ensure that the system is used to its maximum
capabilities. Providing the necessary training is mandatory as some employees might not be
comfortable at using new technologies. International companies must also tend to the issue of
language barriers during the implementation of their knowledge system. Different branch offices
are located at various geographical locations. Thus, a common language must be used for
knowledge sharing purposes.
Review
There is no suitable metrics to measure the amount of information stored. However, the
progress of the organization after implementing such a system can be viewed and verified by
analyzing its growth.
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4KNOWLEDGE MANAGEMENT SYSTEMS
Conclusion
Thus, it can be concluded that knowledge management systems are essential to achieve
business development. These systems are hard to design and even harder to implement due
technological barriers. However, information is crucial for the success if any given process and
thus this system can be used to maximize productivity of any organization.
Conclusion
Thus, it can be concluded that knowledge management systems are essential to achieve
business development. These systems are hard to design and even harder to implement due
technological barriers. However, information is crucial for the success if any given process and
thus this system can be used to maximize productivity of any organization.

5KNOWLEDGE MANAGEMENT SYSTEMS
Reference List
Dalkir, K., & Beaulieu, M. (2017). Knowledge management in theory and practice. MIT press.
Gani, A., Siddiqa, A., Shamshirband, S., & Hanum, F. (2016). A survey on indexing techniques
for big data: taxonomy and performance evaluation. Knowledge and information
systems, 46(2), 241-284.
Jan, A. U., & Contreras, V. (2016). Success model for knowledge management systems used by
doctoral researchers. Computers in Human Behavior, 59, 258-264.
Smith, B., & Linden, G. (2017). Two decades of recommender systems at Amazon. com. IEEE
Internet Computing, 21(3), 12-18.
Reference List
Dalkir, K., & Beaulieu, M. (2017). Knowledge management in theory and practice. MIT press.
Gani, A., Siddiqa, A., Shamshirband, S., & Hanum, F. (2016). A survey on indexing techniques
for big data: taxonomy and performance evaluation. Knowledge and information
systems, 46(2), 241-284.
Jan, A. U., & Contreras, V. (2016). Success model for knowledge management systems used by
doctoral researchers. Computers in Human Behavior, 59, 258-264.
Smith, B., & Linden, G. (2017). Two decades of recommender systems at Amazon. com. IEEE
Internet Computing, 21(3), 12-18.
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