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

Agenda

Introduction Problems Background Methodology Conclusion

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

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

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

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

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

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

Background

The Four KM Pillars by Stankosky/Baldanza and validated by Calabrese/Bixler)

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

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)

Background (continued)

(Stankosky, 2001)

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

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

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

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

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

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

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)

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

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.

Discussion

Do you have any questions? Will you Fill Out Survey?