Impact of Knowledge Management System in Enterprise Architecture

Impact of Knowledge Management System in Enterprise Architecture Name John Laskar – Presenter Ph. D 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. 25 September 2020

Agenda § § § Introduction Problems Background Methodology Conclusion

Introduction/ Definitions of KM , KMS and EA KM KMS EA ● Systematic Tools, Processes: ● IT based Tools - Support KM ● Business Process, IT Infrastructure Knowledge - Acquire - Create - Understand - Use ● Use Knowledge for: - Problem Solving ◦ Performance ◦ Process ● EA builds: Organization’s - Processes - Systems - Technologies - Long Term Growth ● Knowledge Repository - Retention - Future Use ● 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 3: Best Practices and Lessons learned are not shared ● • Problem Significance: q q 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

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

Background (continued) KM Pillars Pillar Deals with Leadership/ Management Environmental Strategic, and enterprise-level decision-making process Objectives Knowledge requirements Knowledge sources Prioritization, and resource allocation of organization’s Knowledge assets Organization Operational aspects of Knowledge assets including: - Functions - Processes Organizational structures Control measures and metrics Process improvement Business process reengineering Technology Various IT to supporting or enabling KM strategies and operations Learning Organizational behavioral aspects and social engineering Ensure that individuals collaborate and share knowledge to the maximum 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

Methodology KM Lit. review Enterprise Arch Lit. review Best Practices Essence of EA FEA KM body of Knowledge Stankosky KM Framework CPIC EA Knowledge Repository Intellectual Capital, KM Tools OMB’s Performance Improvement Life Cycle IT Innovation Knowledge Base KM and EA Research Gap Hypotheses Survey

Methodology 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 Knowledge Management (KM) KM Enterprise Architecture (EA) KMS area 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 EA 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 – Status update § § 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

Data Analysis method 4 Barriers Descriptive Statistics 4 Benefits Descriptive Statistics Group Correlation Government and Private Product and Service Large and Small Manager and K- worker § Research Hypotheses: Literature review leads to 4 Barriers, 4 Benefits and 4 Groups § 4 Barriers ü Govt. vs. Private : 4 Hypotheses ü Large vs. Small : 4 Hypotheses ü Management vs. K-worker : 4 Hypotheses ü Product vs. Service : 4 Hypotheses § 4 Benefits ü Govt. vs. Private : 4 Hypotheses ü Large vs. Small : 4 Hypotheses ü Management vs. K-worker : 4 Hypotheses ü Product vs. Service : 4 Hypotheses § Total Number of Hypotheses: 16 + 16 = 32

Theoretical Concept Diagram Survey Sample areas Research Question 1 (RQ 1) H 1 - H 16 4 -H H 1 H 5 - H 8 H 9 - H 12 H 1 3 - H KMS Barriers in EA KMS Benefits In EA 16 H 1 7 -2 0 Survey Question Numbers Part A Q 1 -Q 19 Government vs. Private Enterprise Part A Q 1 -Q 19 Manager vs. K. worker Enterprise Part A Q 1 -Q 19 Product vs. Service Enterprise Part A Q 1 -Q 19 Large vs. Small Enterprise Part B Q 1 -Q 11 Government vs. Private Enterprise Part B Q 1 -Q 11 Manager vs. K. worker Enterprise Part B Q 1 -Q 11 Product vs. Service Enterprise Part B Q 1 -Q 11 4 2 1 - H 2 Large vs. Small Enterprise 8 5 -2 H 2 Research Question 2 (RQ 2) H 17 - H 32 H 29 -32

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?