Organisational implementation of storage area networks as a strategic knowledge managment tool
- Publication Type:
- Thesis
- Issue Date:
- 2008
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The growth of business data is proportional to growth in data storage systems. This
growth in turn has driven management to examine more closely more effective ways
of managing the functions of IT departments including the implementation of data
storage systems. One such system is Storage Area Networks (SAN) which are
complex and involve a vast array of different hardware, software, infrastructure setup
and vendors.
Given that, business operations in the twenty-first century are fast moving from
traditional methods to more sophisticated technology-based systems and tools. It is
arguable that successful implementation of new technologies is also dependent on
many factors such as the efficient management of resources including intellectual
and tangible assets. However these resources can be utilised much more efficiently
and effectively through the application of knowledge management tools such as SAN
systems which are well positioned to capture, store, use and re-use organisational
knowledge for the purpose of enhancing the competitive position of the company.
Some of the most important decisions facing organisations include: a) ongoing
shortening of the development cycle of new products and services, b) effective and
efficient communication with suppliers and experts from around the world, c)
receiving and responding to customer feedback, and d) accessing research and
development facilities around the world. However, in recent times, SAN systems as
Knowledge Management tools have been rapidly emerging as critical tools for
enhancing strategic advantage and for improving the organisation's standing.
The study provides knowledge on Critical (key) Success Factors or CSFs for
companies which have already implemented or plan to implement SAN in their
business operations. Furthermore, companies may benefit from the results by
utilising the assessment for planning and for strategic purposes. For example, as a
result of better utilisation and better understanding of the implementation of SAN
systems, cost savings and time savings may be achieved. In addition, simplifying
business processes and improving quality and efficiency of organisational digital
systems may lead to the additional benefits of improving the organisation's
competitive advantage.
Two separate focus groups were convened to assist the researcher by providing input
into the model, as well as questionnaires. Questionnaires were then mailed to a
randomly selected list of companies that have implemented SAN.
The following statistical steps and procedures were used to analyse the collected data
to develop the prediction model:
1) calculation of descriptive statistics;
2) examination of the non-response bias;
3) check of reliability and validity;
4) testing of the hypotheses; and
5) development of a prediction model
As a result of the statistical analysis, seven CSFs for SAN system implementation
success were identified. Some of the factors were identified to' make significant
contributions to the success of a SAN implementation as a strategic knowledge
management tool in organisations.
Accordingly, this thesis provides both theoretical and practical new insights into the
implementation of a SAN system and provides a framework for further development
of the SAN and the IS research field.
It is also believed that the findings of this thesis may help extend the existing
knowledge on SAN and implementation research.
The model used in this thesis is based on the industry conditions at the time and
place when the research was conducted.
The results of this research should be interpreted with caution, as this research is the
first of its kind and like any other research is subject to a number of limitations, some
due to the lack of information in the area of research as well as the limitations on the
survey data.
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