Jay Liebowitz: Profiles in Knowledge

Originally published August 17, 2023

10 min readAug 18, 2023

Jay Liebowitz: Profiles in Knowledge

This is the 94th article in the Profiles in Knowledge series featuring thought leaders in knowledge management. Jay Liebowitz is a professor, consultant, author, and editor living in Washington, DC. His research interests include knowledge management, data analytics, intelligent systems, intuition-based decision making, IT management, expert systems, and artificial intelligence. He has lectured and consulted worldwide.

Background

Jay is Professor of Business Innovation and Industry Transformation at the Crummer Graduate School of Business at Rollins College. Previously he was the Visiting Distinguished Professor at the International School for Social and Business Studies in Slovenia. Jay was the Fulbright Visiting Research Chair in Business at Queen’s University for the Summer 2017 and a Fulbright Specialist at Dalarna University in Sweden in May 2019.

Jay served as the inaugural Executive-in-Residence for Public Service at Columbia University’s Data Science Institute. He was previously a Visiting Professor in the Stillman School of Business and the MS-Business Analytics Capstone & Co-Program Director (External Relations) at Seton Hall University. Jay previously served as the Distinguished Chair of Applied Business and Finance at Harrisburg University of Science and Technology. Before that, he was the Orkand Endowed Chair of Management and Technology in the Graduate School at the University of Maryland University College (UMUC). Jay served as a Full Professor in the Carey Business School at Johns Hopkins University.

At Johns Hopkins University, Jay was the founding Program Director for the Graduate Certificate in Competitive Intelligence and the Capstone Director of the MS-Information and Telecommunications Systems for Business Program, where he engaged over 30 organizations in industry, government, and not-for-profits in capstone projects.

Prior to joining Hopkins, Jay was the first Knowledge Management Officer at NASA Goddard Space Flight Center. Before NASA, he was the Robert W. Deutsch Distinguished Professor of Information Systems at the University of Maryland-Baltimore County, Professor of Management Science at George Washington University, and Chair of Artificial Intelligence at the U.S. Army War College.

Jay is the Founding Editor-in-Chief of Expert Systems With Applications: An International Journal. He was the Associate Editor of the international journal, Telematics and Informatics. He has published over 45 books and a myriad of journal articles on knowledge management, analytics, financial literacy, intelligent systems, and IT management. Jay served as the Editor-in-Chief of Procedia-CS (Elsevier). He is also the Series Book Editor of the Data Analytics Applications book series (Taylor & Francis), as well as the Series Book Editor of the new Digital Transformation: Accelerating Organizational Intelligence book series (World Scientific Publishing).

He was ranked one of the top 10 knowledge management researchers/practitioners out of 11,000 worldwide and was ranked #2 in KM Strategy worldwide according to the January 2010 Journal of Knowledge Management. He is a Fulbright Scholar, IEEE-USA Federal Communications Commission Executive Fellow, and Computer Educator of the Year (International Association for Computer Information Systems). In October 2011, the International Association for Computer Information Systems named the “Jay Liebowitz Outstanding Student Research Award” for the best student research paper at the IACIS Annual Conference. He is in the Top 2% of the top scientists in the world, according to a 2019 Stanford Study.

His recent books are Data Analytics and AI (Taylor & Francis, 2021), The Business of Pandemics: The COVID-19 Story (Taylor & Francis, 2021), A Research Agenda for Knowledge Management and Analytics (Elgar Publishers, 2021), Online Learning Analytics (Taylor & Francis, 2022), Digital Transformation for the University of the Future (World Scientific, 2022), Cryptocurrency Concepts, Technology, and Applications (Taylor & Francis, 2023), Pivoting Government through Digital Transformation (Auerbach Publications, 2023), and Developing the Intuitive Executive: Using Analytics and Intuition for Success (Auerbach Publications, 2023).

Education

George Washington University

Doctor of Science in system analysis and management/operations research, 1985
MBA in finance and investments, 1980
BBA in accounting, 1979

Profiles

Content

Articles

How to Make Knowledge Management More Rigorous

SMART (Strategize-Model-Act-Revise-Transfer) methodology for KM

Strategize:

Perform strategic planning
Determine key knowledge requirements (i.e., core competencies
Set knowledge management priorities
Perform business needs analysis
Identify business problem(s)
Establish metrics for success
Conduct cultural assessment and establish a motivate-and-reward structure to encourage knowledge sharing

Outputs from the strategize phase:

Business needs analysis document
Cultural assessment and incentives document

Model:

Perform conceptual modeling
Conduct a knowledge audit
Identify types and sources of knowledge (i.e., knowledge assets)
Determine competencies and weaknesses
Perform knowledge mapping to identify the organization and flow of knowledge
Perform gap analysis
Provide recommendations
Do knowledge planning
Plan knowledge management strategy
Build a supportive, knowledge sharing culture
Create and define knowledge management initiatives
Develop a cost-benefit analysis
Perform physical modeling
Develop the physical architecture
Develop the framework for access, input/update, storage and eventual distribution & use
Develop a high level meta-data design
Construct a visual prototype

Outputs from the model phase:

Knowledge audit document
Visual prototype (i.e., the knowledge map showing the taxonomy and flow of knowledge)
Knowledge management program plan
Requirements specifications document

Act:

Capture and secure knowledge
Collect and verify knowledge
Valuate the knowledge
Represent knowledge
Formalize how the knowledge is represented

Classify the knowledge

Encode the knowledge
Organize and store knowledge in the knowledge management system
Combine knowledge
Retrieve and integrate knowledge from the entire organization
Create knowledge
Have open discussion with customers and interested parties both internal and external to the organization
Perform exploration and discovery
Conduct experimentation (i.e., trial and error
Share knowledge
Distribute knowledge
Make knowledge easily accessible
Learn knowledge and loop back to Step 6

Outputs from the act phase:

Knowledge acquisition document
Design document
Visual and technical knowledge management system prototypes

Revise:

Pilot operational use of the knowledge management system;
Conduct knowledge review
Perform quality control
Review knowledge for validity and accuracy
Update knowledge
Perform relevance review
Prune knowledge and retain what is relevant, timely, and accurate and proven useful
Perform knowledge management system review
Test and evaluate achieved results
Revalidate/test against metrics

Outputs from the revise phase:

Evaluation methodology and results document
Knowledge management system pilot
User’s guide for the knowledge management system

Transfer:

Publish knowledge
Coordinate knowledge management activities and functions
Create integrated knowledge transfer programs
Notify where knowledge is located and what lessons were learned
Perform serious anecdote management (i.e., publicize testimonials of the benefits of the KMS)
Use knowledge to create value for the enterprise
Sell (e.g., package knowledgebases for sale)
Apply (e.g., knowledge management consulting services, apply methodology)
Use (e.g., improve customer satisfaction, employee support and training)
Monitor knowledge management activities via metrics
Conduct post-audit
Expand knowledge management initiatives
Continue to learn and loop back through the phases

Outputs from the transfer phase:

Maintenance document for the knowledge management system
Full production knowledge management system
Post-audit document
Lessons learned document

Articles by Others

DSI’s Inaugural Executive-in-Residence for Public Service is Helping the Federal Government Benefit from Data Science by The Data Science Institute at Columbia University
Forget Gen Y! Focus on the Disappearing Boomers by Mary Abraham
Review: What they didn’t tell you about KM by Andrea Japzon

SIKM Leaders Community

KMWorld Conference

KMWorld 2022

C303: Developing a KM Strategy & Framework: Lessons Learned & Shared — Slides (with Jack L Price and Ben Apple)

KMWorld Connect 2021

Modern KM Needs Both Man and Machine, KMWorld Connect Speakers Maintain

10 Rules of the road for Knowledge Management

You need to have a champion among senior leadership and alignment with corporate goals.
You need a well-designed KM implementation plan.
You need a formal knowledge retention strategy.
You need to incorporate KM as part of other strategies.
You need to be thoughtful in your application of KM.
You need to align KM to corporate culture.
You need to celebrate your successes.
You need to have the right metrics in place.
Don’t force-fit the technology.
Know that KM is just one part of strategic intelligence.

KMWorld 2012–2016

KMWorld 2016 Keynote Panel: Hacking KM
KMWorld 2013 B304: Content Challenges & Opportunities — Slides
KMWorld 2012 A106: Critical Success Factors in KM Initiatives — Slides

10 Keys to Success for Knowledge Management Initiatives

Top Ten Keys to Knowledge Management Success

Have A Senior Champion & Align Your KM Strategy With Your Organizational Strategies, Goals, and Objectives
Develop A Well-Designed KM Implementation (People, Process, and Technology)
Develop a Formal Knowledge Retention Strategy — Start from Day One of the Employee’s Life with the Organization
Incorporate KM as Part of Human Capital Strategy, Succession Planning, Workforce Development, and/or Quality Management
Be Thoughtful in Your Approach (Knowledge Audit, Social Network Analysis, etc.)
Align Your KM Approaches to Fit Your Organizational Culture
Celebrate the Successes, Then Bring in the Bittersweet Stories
Develop KM Metrics, Especially Outcome Measures
Don’t Force-Fit Technology (People/Culture/Process Are Where the Rubber Hits the Road
KM is Just One Part of Your “Strategic Intelligence”

Knowledge Sharing Tenets for Success

Enhance reward and recognition system to include learning and knowledge sharing competencies
Acquaint people with knowledge sharing and its benefits
Share the message that with creativity comes failure and we all benefit from talking about our successes and our failures
Integrate knowledge sharing into everyone’s job
Educate people about what types of knowledge are valuable and how they can be used
Make sure the technology works for people, not vice versa