Information Technology Reference
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3.7 Future Research Directions and Conclusions
The objective of the chapter was to identify a model for developing an IT-based
KMS that would facilitate knowledge creation in an organization through the
exploitation of experimental data, with an emphasis on DOE. This chapter took
account of the types of knowledge required to conduct a DOE and the resulting
knowledge produced. We described an IT-based KMS that implemented Nonaka's
knowledge spiral in the DOE context.
A number of areas of improvement of the system can be identified that in turn
present opportunities for future research in this area. First, due to the nature of the
company, the socialization aspect of Nonaka's knowledge spiral was not included
here. However, this aspect may be addressed in a several ways.
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The use of e-mail to notify all stakeholders about the launch of new experiments.
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Additional capability to record and automatically synthesize information (and
insights) from brainstorming sessions into audio and video files. Rather than
codifying social tacit knowledge it merely records and hosts it, this can then
be available for all employees to listen to and reabsorb into their own cognitive
system for transfer to individual tacit knowledge.
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Discussion boards and forums have been researched as a form of socializa-
tion. Ruggles and Little's (1997) report proposed the use of weekly forums
with outside experts and internal employees - as this provides opportunities for
socialization both internal and external to the organization.
As outlined, graphical access to experimental findings would provide greater
insight into the relationship between different factors and also further build users'
tacit knowledge. Functionality that would allow employees to exploit the use of
graphical mediums to display experimental findings would most certainly facili-
tate the generation of internal tacit knowledge. Future research should examine the
impact of such IT-based features.
An additional feature where all employees synchronously interact with the find-
ings of experiments via IT and discuss different issues would also encourage the
socialization aspect of the knowledge spiral and present additional avenues for
future research. In addition, there may be greater potential to exploit experimen-
tal data beyond the capabilities of the DOE software. Currently, the system only
queries one experiment at a time; however, there is potential for the system to query
multiple experiments (based on similarities in product specifications or findings).
Furthermore, the IT system could highlight areas where knowledge is lacking and
make recommendations for additional experiments based on this. Such a feature
could be extended to address other areas of experimentation (i.e., outside the DOE
context).
Acquisition of explicit knowledge can be time consuming. Search engines such
as Google have capabilities that enable automating searches and features that inte-
grate those capabilities with the KMS would be highly beneficial. However, this
would require better understanding of the issues that underlie such knowledge
integration and indicate potential issues for future research.
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