impact of knowledge management system in enterprise architecture name john laskar – presenter phd...
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Impact of Knowledge Management System in Enterprise Architecture
Name John Laskar – PresenterPhD student at Engineering Management and Systems Engineering Department, George Washington University.
Other Authors – Dr. Tom Holzer Dr. Tim Eveleigh Dr. Shahryar Sarkani Engineering Management and Systems Engineering Department, George Washington University.
April 19, 2023
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Agenda
Introduction Problems Background Methodology Conclusion
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Introduction/ DefinitionsDefinitions of KM , KMS and EA
KM KMS EA
● Systematic Tools, Processes:
Knowledge - Acquire - Create - Understand - Use
● IT based Tools - Support KM
● Use Knowledge for: - Problem Solving ◦ Performance ◦ Process ● Knowledge Repository
- Retention - Future Use
● Business Process, IT Infrastructure ● EA builds: Organization’s - Processes - Systems - Technologies - Long Term Growth
● EA helps Projects: - Build Capabilities
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Purpose/Objective
Present the dissertation research Problem Assess impact of the research Receive feedback from the participating
INCOSE technical community Seek participants to fill out the Survey
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Research Question, Problem statement and Research Objective
Research Question 1: Do the critical barriers inhibit use of KMS in Enterprise Architecture?
Research Question 2: Does enterprise fail to leverage on KMS?
Problem Statement: Existing barriers of KMS, and enterprise’s failure to realize their benefits inhibit application of KMS in EA
Research Objective: Create a new technique for KMS application
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Problem● Problem 1: Enterprise fails to see KMS needs. Realizes only after spending significant amount of IT budget
•Problem Significance: Unprecedented Knowledge loss. Millions of Baby-boomers
retire this decade; only 25% of US companies has plans (according to INC)
•Hypotheses:There is urgent need to Preserve Tacit Knowledge, use of
KMS helps to solve this problem
• Productive technologies worth $115 Billion sit idle today in U.S. companies (Estimates of Technology transfer broker “BTG”). Hypotheses:
Enterprise need to use KMS to control IT waste
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Problem• Problem 2: Critical barriers inhibit KMS in an
enterprise Problem Significance:
Enterprise Information management problem is very serious Sarbanes- Oxley Act
• Requires executives to take responsibility for what happens within their companies.
Hypotheses:Organization culture, Management’s understanding of needs, IT investments , lack of performance measurements are barriers of using KMS
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Problem ● Problem 3: Best Practices and Lessons learned are not shared
•Problem Significance: Create Knowledge Gaps Redundant operations Excessive resource waste Increase expenses
• The Cost: $588 Billion per annum in the United States alone (A study by “Basex” 2005)
• Misuse of KM tools (i.e., e-mail, Web, instant messaging, social networking)
• Interrupt knowledge work• Significant downtime
Hypotheses: EA includes KMS to control IT waste
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Background
The Four KM Pillars by Stankosky/Baldanza and validated by Calabrese/Bixler)
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KM Pillars Pillar Deals with
Leadership/ Management
EnvironmentalStrategic, and enterprise-level decision-making processObjectivesKnowledge requirementsKnowledge sourcesPrioritization, and resource allocation of organization’s Knowledge assets
Organization Operational aspects of Knowledge assets including: - Functions - ProcessesOrganizational structuresControl measures and metricsProcess improvementBusiness process reengineering
Technology Various IT to supporting or enabling KM strategies and operations
Learning Organizational behavioral aspects and social engineeringEnsure that individuals collaborate and share knowledge to the maximum
Background (continued)
The Four KM Pillars by Stankosky/Baldanza and validated by Calabrese/Bixler
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Background (continued)
Successful KM program requires a more inclusive set of disciplines, elements, and processes, i.e., a KM framework model applicable to virtually all business domains (Stankosky, 2002)
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Background (continued)
(Stankosky, 2001)
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Possible Solutions Solution to Problem 1:
• To become thought leaders, KM-driven Enterprise need:– collaborative thought leadership– New visualization tools (John Lewis)
Solution to Problem 2:• Recognition of Knowledge-based economy• Knowledge is org.’s most critical resource (Liebowitz, Lynch)
Solution to Problem 3:• Leverage on Knowledge assets (Stankosky)
– Improve performance– Effectiveness– Innovation
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KM Lit. review
KM body of Knowledge
Stankosky KM Framework
Intellectual Capital, KM Tools
IT Innovation Knowledge Base
Enterprise Arch Lit. review
Essence of EA
CPIC
Best Practices FEA
EA KnowledgeRepository
OMB’s PerformanceImprovement Life Cycle
KM and EA Research Gap
Hypotheses
Survey
Methodology
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KnowledgeManagement(KM)
KM EAKMSarea
Key KM focus:•Systematic Process•Acquire knowledge assets•Organize knowledge assets•Communicate knowledge assets•Information Technology (IT)•Intelligence Capital (IP)•Organization efficiency•Innovation•Human development•Competitive business advantage•Organization Performance improvement
Enterprise Architecture(EA)
Key EA focus:•Manage change within organization•Achieve strategic initiatives•Systematic Process•Acquire knowledge assets•Organize knowledge assets•Communicate knowledge assets•Information Technology (IT)•Intelligence Capital (IP)•Organization efficiency•Innovation•Human development•Competitive business advantage•Organization Performance improvement
Key KMS focus:• KM toolkit, Technology•Managing Knowledge in an organization•Knowledge integration in virtual teams•Motivating Knowledge sharing•Measuring KM performance, KM metrics•Bridge between KM consultants and technologists
Methodology
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Two overarching research questions Literature review generates hypotheses Survey questions relating each hypotheses A survey Questionnaire designed that are
meaningful and relevant while also interesting, engaging, and quickly answered
Methodology – Status update
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Data Analysis method
4 BarriersDescriptive Statistics
4 Benefits Descriptive Statistics
Group Correlation
Governmentand
Private Manager
andK- worker
Largeand
Small
Productand
Service
Research Hypotheses: Literature review leads to 4 Barriers, 4 Benefits and 4 Groups
4 Barriers Govt. vs. Private : 4 Hypotheses Large vs. Small : 4 Hypotheses Management vs. K-worker : 4 Hypotheses Product vs. Service : 4 Hypotheses
4 Benefits Govt. vs. Private : 4 Hypotheses Large vs. Small : 4 Hypotheses Management vs. K-worker : 4 Hypotheses Product vs. Service : 4 Hypotheses
Total Number of Hypotheses: 16 + 16 = 32
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Research Question1(RQ1)
Research Question 2(RQ2)
KMS Barriers in EA
KMS Benefits In EA
H1- H16H1-
H4
H5- H8
H9- H12
H13- H16
H21-24
H17-20
H29-32
H25-28
H 17- H32
Theoretical Concept Diagram Large vs. SmallEnterprise
Government vs. PrivateEnterprise
Manager vs. K. workerEnterprise
Product vs. ServiceEnterprise
Large vs. SmallEnterprise
Government vs. PrivateEnterprise
Manager vs. K. workerEnterprise
Product vs. ServiceEnterprise
Part AQ1-Q19
Survey Question Numbers
Part AQ1-Q19
Part AQ1-Q19
Part AQ1-Q19
Part BQ1-Q11
Part BQ1-Q11
Part BQ1-Q11
Part BQ1-Q11
Survey Sample areas
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Data Collection/Analysis Survey 4 groups
• Government and non-Government• Large and Small enterprise• Product and Service enterprise• Executive Managers and Knowledge workers
Develop cross-correlation statistics among groups
Descriptive statistics, t-test hypotheses (using SPSS/minitab/Excel spread sheet)
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Conclusion
Identified 3 different problems Literature Review corresponds with initial
findings Survey Instrument “Questionnaire” Pilot
developed, Pre-tested, and finalized Survey in progress Data collection and Analysis preliminary stage
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References
• Tamara Schweitzer, INC. http://www.inc.com/news/articles/200703/boomers.html searched on April 23, 2012.
• John Lewis, The Explanation Age, Option Outlines, 2012• Liebowitz, 1999, Lynch, 2002 Organizational learning• M. Stankosky, L. Vandergriff, A. Green, In Search of Knowledge
Management: Pursuing Primary Principles, Emerald, 2010• J.W. Ross, P. Weill, D. C. Robertson, Enterprise Architecture As Strategy,
Harvard Business School Press, 2006• M. Franco, S. Mariano, Information Technology Repositories and
Knowledge Management Processes: A Qualitative analysis, VINE: The Journal of Information and Knowledge Management Systems,
• Vol. 37, No. 4, 2007, pp 440-451.
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Discussion
Do you have any questions? Will you Fill Out Survey?