francis k. andoh-baidoo state university of new york at brockport jon blue university of delaware
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Organizational Memory and Knowledge Systems (OMKS): An Integrated Approach to Building Modern Decision Support Systems. Francis K. Andoh-Baidoo State University of New York at Brockport Jon Blue University of Delaware SIG-DSS Pre-ICIS 2006 Research Workshop December 10, 2006 Milwaukee, WI. - PowerPoint PPT PresentationTRANSCRIPT
Organizational Memory and Knowledge Systems (OMKS): An Integrated Approach to Building Modern Decision Support Systems
Francis K. Andoh-BaidooState University of New York at BrockportJon BlueUniversity of Delaware
SIG-DSS Pre-ICIS 2006 Research WorkshopDecember 10, 2006Milwaukee, WI
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Agenda Problem Statement Theoretical Framework
Decision Making and Decision Support Systems (DSS) Data Warehouse Knowledge Management System Organizational Memory Information System (OMIS) Knowledge Spiral (Nonaka & Takeuchi, 1995)
Proposed Modern Decision Support System Approach - OMKS Knowledge Conversion in OMKS Implications for Research and Practice Conclusions
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Problem Statement Researchers have recommended that
organizations eliminate their silo systems by consolidating their data, information, and knowledge repositories to enable effective and efficient decision making. Unfortunately, most organizations have not realized this end
The acquisition, storage, and utilization of tacit knowledge is difficult
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Theoretical Framework Decision Making and Decision Support
Systems (DSS) Modern DSS are commissioned to support all
four phase of the decision making process: intelligence, design, choice, and implementation (Simon, 1955)
Data Warehouses, Knowledge Systems, and Organizational Memory Information Systems support decision making
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Theoretical Framework (con’t.) Data Warehouse
Defined as “…a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of management’s decision-making process” (Inmon, p. 1)
Typically, On-Line Analytical Processing (OLAP), Data Mining, and Knowledge Discovery tools are used to support decision making processes
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Theoretical Framework (con’t.) Knowledge Management System
Repository for explicit & tacit knowledge Explicit knowledge – systematic and can be expressed
formally as language, rules, objects, symbols, or equations
Tacit knowledge – includes beliefs, perspectives, and mental models ingrained in a person’s mind Tacit knowledge can be articulated, captured, and
represented (Nonaka, Takeuchi, & Umemoto, 1996; Polyshyn, 1981)
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Theoretical Framework (con’t.) Organizational Memory Information Systems
(OMIS) Integrated knowledge based IS with culture,
history, business processes, and human memory attributes (Hackbarth, 1998)
Facilitate Organizational Learning: Individual learning, learning through direct communication, and learning using a knowledge repository (Heijst et al., 1997)
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Theoretical Framework (con’t.)
Knowledge Spiral (Nonaka & Takeuchi, 1995)
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Proposed Modern DSS Approach Scenarios Ontology Metadata Data / Knowledge Repositories Knowledge Conversion
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A Scenario is a sequence of hypothetical (but mimicking real) situations encountered by a domain expert, together with the intermediate responses/actions (Yu-N & Abidi, 2000)
Ontology is a common and shared understanding of some domain that is capable of being communicated across people and systems (Benjamins et al., 1998)
Scenarios/Ontology/Metadata
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Scenarios/Ontology/Metadata (con’t).
Ontology can be used with Scenarios to standardize the acquisition of tacit knowledge (Yu-N & Abidi, 2000)
Ontology-based metadata represents a common global metadata
Ontology-based metadata addresses the issues of data and semantic heterogeneity
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Organization’sIndividuals
Admin ToolsDevelopment
Tools
Tools to Access DataEdit/Query Interface/Browser
Analysis Tools
ProposedOrganizational Memory and Knowledge System
Data
Warehouse
Knowledge
Repository
OntologicalMetadata
Marketing
Manufacturing
Sales
Human
Resources
Organization’s/External Databases
Knowledge
SummarizedData
AggregatedData
Scenarios/ Organizational Ontology
To Capture Tacit Knowledge
Knowledge Conversion
Knowledge Source
Supports Decision Making
ETL + OrganizationalOntology
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Knowledge Conversion in OMKS
Externalization (tacit to explicit) Scenario based acquisition Facilitates tacit to explicit knowledge by using
mathematical models (Nemati et al., 2002) Stored as explicit mathematical inequalities Canonical model formulations with links to relational
tables in the DSS
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Knowledge Conversion in OMKS (con’t).
Socialization (tacit to tacit) Ontology facilitates the common vocabulary for
knowledge worker communication Storage of digitized films of physical
demonstration for viewing by any organization members (with verbal explanations that explain the process)
Kinematics - individual sited with probes and a system records the movements of the person (Nemati et al., 2002)
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Knowledge Conversion in OMKS (con’t).
Combination (explicit to explicit) Explicit knowledge is reconfigured
Valid knowledge can be used to modify existing knowledge
AI-based data mining on the output from brainstorming sessions
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Knowledge Conversion in OMKS (con’t).
Internalization (explicit to tacit) Knowledge workers improve their work activities
through the shared knowledge (modification of the mental model)
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Implications Research
More design science research needed on how to develop modern DSS using the proposed approach
Theory based behavioral research needed on the organizational impact of the proposed approach
Further research needs an integrated team of DSS, OMIS, and Data Warehousing scholars
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Implications (con’t.) Practice
Organizations may benefit from the exploration of integrating existing Data Warehousing and Organizational Memory Information System
Organizations using the proposed framework can enhance decision making and organizational learning
Consultants may be called upon to study the problems with integrating systems in the proposed framework
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Conclusion Researchers have suggested that integrating
knowledge management and decision support systems can enhance decision making
We have proposed a framework for developing modern DSS that combines functional features of data warehousing and organizational memory information systems
Framework uses scenarios to capture tacit knowledge and ontology for standardization Such an approach has the potential to enhance decision
making and organizational learning
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References Benjamins, V.R., Fensel, D., & Perez, A.G. (1998). Knowledge Management through Ontologies.
In Proceedings of the Second International Conference of Practical Aspects of Knowledge Management (PAKM 98), October 29-30.
Hackbarth, G. (1998). The Impact of Organizational Memory on IT Systems, In Proceedings of the Fourth Americase Conference on Information Systems, E. Hoadley and I. Benbasat (eds)., pp. 588-590.
Heijst, G., Spek, R., & Kruizinga, E. (1997). Corporate memories as a tool for knowledge management. Expert Systems With Applications, 13(1), 41–54.
Inmon, W. (1995). What is a Data Warehouse? Prism Tech Topic, Vol.1, No. 1. Nemati, H.R., Steiger, D.M., Iyer, L.S., & Hershel, R.T. (2002). Knowledge warehouse: an
architectural integration of knowledge management, decision support, artificial intelligence and data warehousing, Decision Support Systems, Volume 33, Issue 2, June, 143-161.
Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company, How Japanese companies manage the dynamics of innovation, Oxford University Press, New York.
Nonaka, I., Takeuchi, H., & Umemoto K. (1996). A theory of organizational knowledge creation, International Journal of Technology Management, 11(7/8), 833 – 845.
Polanyi, M. (1966). The Tacit Dimension. Routledge and Kegan Paul, London, UK, 1966. Simon, H.A. (1955). A Behavioral Model of Rational choice. Quarterly Journal of Economics,
Vol. 69, pp. 99-118. Yu-N, C., Abidi, S.S.R. (2000). A Scenarios Mediated Approach for Tacit Knowledge Acquisition
and Crystallisation: Towards Higher Return-On-Knowledge and Experience, In Proceedings of the Third International Conference on Practical Aspects of Knowledge Management (PAKM2000) Basel, Switzerland, 30-31 Oct. 2000.