Princeton Presentations: Beyond Risk Modeling to Uncertainty Management
AI-ML Risk Management Analytics beyond Prediction to 'Anticipation of Surprise'™

Latest Research: AI & Machine Learning for Risk & Uncertainty Management
AI-Algorithms-Machine Learning: 63 SSRN Top-10 Rankings, Top-2% Authors
Princeton University Presentations Pioneering Model Risk Arbitrage

CIO Magazine      Fortune Magazine      Inc. Magazine

Frank Knight in Risk, Uncertainty & Profit

'"It is this true uncertainty, and not risk, as has been argued, which forms the basis of a valid theory of profit and accounts for the divergence between actual and theoretical competition... It is a world of change in which we live, and a world of uncertainty...If we are to understand the workings of the economic system we must examine the meaning and significance of uncertainty; and to this end some inquiry into the nature and function of knowledge itself is necessary."


 

Princeton University MIT Sloan School of Management Artificial Intelligence (AI) & Machine Learning Management and LeadershipExecutive Education MIT Computer Science & ArtificialIntelligence Laboratory CSAIL Artificial Intelligence (AI) & Machine Learning Management and LeadershipExecutive Education
'Knight Reconsidered':
Risk, Uncertainty, & Profit
for the Cyber Era


CIO Magazine      Risk, Uncertainty, and Profit: Frank Knight

     

“The new business model of the Information Age, however, is marked by fundamental, not incremental, change. Businesses can't plan long-term; instead, they must shift to a more flexible "anticipation-of-surprise" model.”
-- Yogesh Malhotra, CIO Magazine, 1999.
[Decade later, Wall Street CFOs know so.]

 

 

*Goldman Sachs: How to Anticipate Risk?
25 Years: Model Risk Management Program

"The future is moving so quickly that you can’t anticipate it… We have put a tremendous emphasis on quick response instead of planning. We will continue to be surprised, but we won't be surprised that we are surprised. We will anticipate the surprise."

Yogesh Malhotra says his vision is to fill the gaps between business and technology, data and knowledge, and, theory and practice...” -- in Fortune Interview, June 1998.


"KM is obsoleting what you know before others obsolete it and profit by creating the challenges and opportunities others haven't even thought about” - Dr. Yogesh Malhotra, in Inc. Technology Interview, 1999"
- U.S. Office of the Under Secretary of Defense (Comptroller) &
Defense Information Systems Agency (DISA)
.

 

Princeton Quant & FinTech Presentations
MIT AI-Machine Learning Executive Guide

2016 Princeton Quant Trading Conference    /MITSloan&CSAILAIMachineLearningExecutiveGuide

 

2018 Princeton FinTech & Quant Conference   2016 Princeton Quant Trading Conference

2016 New York State CyberSecurity Conference 2015 Princeton Quant Trading Conference

 

Download Research: The Model Risk Management Research Program (1993-Current):
Artificial Intelligence, Algorithms, Machine Learning, Deep Learning:
Risk Management Analytics beyond 'Prediction' to 'Anticipation of Surprise'™


Model Risk Management program that anticipated needs of OCC and Wall Street CROs to “anticipate risk” over a decade before they said we must anticipate risk: with research advancing execution of Model Risk Management (see, e.g., US Fed & OCC SR11-7 & OCC2011-12) such as 'anticipation of risks' by 'effective challenge of models'.


120+ SSRN Top-10 Research Rankings: Top-3 % SSRN Authors:
Artificial Intelligence, Algorithms, Machine Learning, Deep Learning:
Recent Research Papers, Expert Papers, Keynotes, and Presentations
.
Capital Markets, Computational Techniques, Corporate Governance, Cyberlaw, Decision-Making under Risk & Uncertainty, Econometric & Statistical Methods, Econometric Modeling, Econometrics, Hedging & Derivatives, Information Systems & Economics, Mathematical Methods & Programming, Microeconomics, Operations Research, Risk Management, Risk Management Controls, Risk Modeling, Stochastic Models, Systemic Risk, Uncertainty & Risk Modeling, and, VaR Value-at-Risk.

2017-2018 MIT AI-Machine Learning Executive Guide including RPA:
Crypto-Quantum-FinTech: Machine Learning-Internet of Things:
Cyber-Finance-Trust: Offensive Cybersecurity and Model Risk Arbitrage

2018Princeton FinTech & Quant Conference, 2018, April 21 .

2018 Princeton Quant Trading Conference: Post-FinTech Model Risk Arbitrage :
Crypto-Quantum-FinTech: Machine Learning-Internet of Things:
Cyber-Finance-Trust: Offensive Cybersecurity and Model Risk Arbitrage

2018Princeton FinTech & Quant Conference, 2018, April 21 .
Sponsored by Princeton University, SIG.

2016 Princeton Quant Trading Conference: Post-FinTech Model Risk Arbitrage :
Crypto-Quantum-FinTech: Machine Learning-Internet of Things:
Cyber-Finance-Trust: Offensive Cybersecurity and Model Risk Arbitrage

2016 Princeton Quant Trading Conference, 2016, April 16 .
Sponsored by Princeton University, Goldman Sachs, Citadel.

2015 Princeton Quant Trading Conference: Post-HFT Model Risk Management:
Cyber-Quantum-FinTech: Machine Learning, Bayesian Inference, Quantum Crypto
Cyber-Finance-Trust: Defensive Cybersecurity and Model Risk Management
2015 Princeton Quant Trading Conference, 2015, April 04.
Sponsored by Princeton University Bendheim Center & ORFE, Citadel, KCG.

Model Risk Management and Model Risk Arbitrage for Quantitative Finance & Cyber Risk Insurance:
- Risk, Uncertainty, and, Profit for the Cyber Era: 'Knight Reconsidered' and 'Knight Reconsidered Again'
Post-2008 & Post-Cyber Quantitative Finance Model Risk Management Post Doc Research, 2015-2016.

‘Bayesian vs. VaR’ to Model Risk Management for Multi-Asset Portfolios
Advanced Practice beyond MIT Sloan Management Review's Post-Crisis 'MRM Dilemma', 2014 Dec.

Markov Chain Monte Carlo Models for High-Dimension Stochastics
Advanced Statistical Computing Algorithms for Model Risk Management of Systemic Risks, 2014 May.

Cybersecurity & Cyber-Finance Risk Management: Understanding Vulnerabilities, Threats, & Risk Mitigation
CSO-CxO Plenary Keynote, National Cybersecurity Summit, Virginia, 2015 Sep.

Bridging Networks, Systems, and, Controls Frameworks for Cybersecurity Standards Development 
New York Cyber Security and Engineering Technology Association (NYSETA) Conference, 2015 Oct.

Quantitative Modeling of Trust Protocols for Mobile Wireless Networks
Quantitative Models of Trust Frameworks for Mobile Wi-Fi Social Networks, 2014 Dec.

Penetration Testing Frameworks for Stress Testing Banking VoIP Networks
Stress Testing Frameworks for Emerging Quantitative Finance Cyber Risk Concerns, 2014 May.

Hong Kong Institute of CPAs Interview on the Future of Bitcoin
Preceded Multiple Predicted Global Regulatory Developments on Bitcoin, 2014 Jan.

Bitcoin Protocol, ‘Cryptographic Proof’, &, Transaction Block Chain
First Technical Research Report on Bitcoin's Cryptographic ‘Proof of Work’, 2013 Dec.

Number Field Sieve Cryptanalysis Algorithms for Breaking Encryption
Preceded Google's Public Announcement of Switch from 1024- to 2048-bit RSA, 2013 May.

JP Morgan Multi-Asset Portfolio Liquidity Assessment Framework
Presentation to JP Morgan Senior Leaders, Managing Directors, Portfolio Managers, 2012 Jun .

Measuring Financial Risks with Improved Alternatives Beyond VaR
Preceded Risk Magazine Report about Basel Moving Beyond VaR, 2012 Jan.

AACSB Reports Impact of Research on Model Risk Management Practices
AACSB International, 2008 Feb.

Structural Equation Models of Digital Consumer Behavior
JMIS, Ranked among Top-2 Peer Reviewed Academic Research Journals, 2008.

Interview: World's Leading Management Thinkers on Corporate Strategy
Business Standard (India), 2007 Jan.

Systems & Decision Models for Black Swans in Wicked Environments
Computer Society of India Communications: Invited Reprint of 1997 ACIS Article, 2006 Jul.

UK Management Press: IT & Knowledge Management Pioneer Interview
Emerald Group Publishing, UK Management Publisher, 2005.

Designing Real Time Enterprise Decision Models & Business Processes
Journal of Knowledge Management, 2005 Apr .

Multivariate Regression Models of Digital Consumer Behaviors
JMIS, Ranked among Top-2 Peer Reviewed Academic Research Journals, 2005.

Why Knowledge Management Systems Fail? Why Models Fail?
American Society for Information Science and Technology, 2004.

Modeling ‘Human Factors’ Seen in Model Risk Management Guidance
Communications of the ACM, Association for Computing Machinery (ACM), 2004.

PCA Models of Consumer Behavior for CRM Process Automation
Americas Conference In Information Systems, 2004 Aug .

CIO Insight Interview: Next Gen Enterprise Risk Management Systems
CIO Insight, 2004 Jul.

‘Effective Challenge of Models’, ‘Professional Skepticism’ & ‘Human Factor’
CIO Insight: The Original Interview Focused on Model Risk Management, 2004 Jul.

United Nations Global Economists Expert Panel Modeling Expert Paper
United Nations, 2003 Sep.

United Nations Global Economists Expert Panel Modeling Expert Keynote
United Nations, 2003 Sep.

Europe Interview: Systems and Models for Black Swans & Extreme Events
Business Management Europe, 2003 Sep.

Asia Interview: Systems and Models for Black Swans & Extreme Events
Business Management Europe, 2003 Sep.

Regression Models of Motivation & Commitment in Knowledge Work
IEEE, 2003 Jan.

Designing Digital Exchanges, Social Networks, & Electronic Communities
Information Strategy: The Executive's Journal, 2002.

Designing Systems for the Digital World of Black Swans & Extreme Events
United Nations - UNESCO Encyclopedia of Life Support Systems (EOLSS), 2002.

When Best [Practices] Becomes Worst: On Managing Model Risk
Momentum: The Quality Magazine of Australasia [Quality Society of Australasia], 2002 Sep.

Risk Management and Controls for Emerging Business Environments
Knowledge Management, 2001 Jul.

Intel Expert Paper: Enabling Next Generation Digital ERM Architectures
Intel Corporation, 2001 Jul.

Machine Learning vs. Human Factor for “Effective Challenge of Models”
Expert Systems with Applications Journal, 2001 Jan.: Top Ranked Research Paper

Risk Management and Controls for Digital Business Model Innovation
Knowledge Management and Business Model Innovation, 2001.

BOOK: Knowledge Management and Business Model Innovation
Genesis of Knowledge Management for Business Model Innovation, 2000.

Modeling & Measuring Digital Assets & Capital for Knowledge Economies
Journal of Global Information Management, 2000 Sep.

Designing Digital Enterprises with Insourcing, Outsourcing, Self-Sourcing
Information and Management, 2000.

Advancing Digital e-Business Information Strategy to "Internet Time"
Information Strategy: The Executive’s Journal, 2000.

Innovative 'Loose-Tight' Systems for Agile Digital Business Models
Information Resources Management Journal, 2000 Mar.

Preventing Model Risks in Digital Business Models & Decision Models
Knowledge Management for the Information Professional, 2000.

BOOK: Knowledge Management and Virtual Organizations
Genesis of Knowledge Management for Virtual Organizations, 2000.


Modeling How Human Information-Processing Guides Meaning & Behavior
Journal of High Technology Management Research, 1999 Oct .


CIO Magazine Interview: Does KM=IT? Does 'Reality' = 'Model'?
CIO Magazine, 1999 Sep.


Advancing Beyond Model Risks in Knowledge Management Systems
Knowledge Management (UK), 1999 Mar.


Multivariate Regression Models of Social Influences in Social Networks
IEEE, 1999 Jan.


Systems & Decision Models for Black Swans in Wicked Environments
Americas Conference in Information Systems, 1997 Aug .


Academy of Management Best Reviewer Award: Quantitative Analytics
100+ Quantitative Statistical Modeling Reviews for 40+ Research Publishers.


National Science Foundation Cybercomputing-Cybersecurity Expert Panels
32 National Science Foundation Computer Scientists SBIR/STTR Expert Panels.


Google Scholar: Decision Models, Risk Models, Uncertainty Management
20-Year Research Program: Global Impact on Worldwide Firms & Governments.


Other Computational Quantitative Finance & Risk Analytics Publications
1993-Current .

Other Computational Quantitative Finance & Risk Analytics Projects

AWS Partner: Silicon Valley-Wall Street-Pentagon-Global Digital CEO Practices Pioneer: MIT-Princeton AI-Quantum Faculty-SME: R&D Impact Among Nobel Laureates

 Amazon AWS Web ServicesMIT Sloan School of Management Artificial Intelligence (AI) & Machine Learning Management and LeadershipExecutive Education MIT Computer Science & ArtificialIntelligence Laboratory CSAIL Artificial Intelligence (AI) & Machine Learning Management and LeadershipExecutive Education    Princeton University   Goldman Sachs JP Morgan Asset Management


*Pentagon Joint Chiefs: C4I-Cyber™: Beyond AI-Quantum Supremacy: Command-Control Supremacy™.
*US Air Force: AIMLExchange™: Invited Interviews: Top USAF Chief Scientist Pentagon Role.
*GIBC Digital Welcomes Leading Machine Learning & AI Expert to Lead $Billion AI-ML Data Center.
*Block Chain-Cloud Computing Pioneer: AI-Crypto Expert On Asia-Australia CEO Global Road Shows.
*MIT Computer Science & AI Lab AI-ML Executive Guide: MIT-Princeton AI-Quantum Faculty-SME.
*Princeton University Quant Trading-FinTech Crypto Presentations: Sponsors: Goldman Sachs, Citadel.

*2021 R&D Leading Worldwide Digital Practices: AI-ML-DL-Cyber-Crypto-Quantum-Risk-Computing
*2021 Joint Chiefs Of Staff: Beyond ABMS JADC2 to Quantum Uncertainty and Time-Space Complexity
*2020 Joint Chiefs Of Staff: AI-Quantum Autonomy in Space: Quantum PhD-Engineers Expert Keynote
*2021 Silicon Valley-Wall Street-Pentagon Digital Pioneer: Digital Startups to Trillion Dollar Enterprises
*2020 Making Quantum Computing Real for JADC2 With Qiskit: Quantum Communication & Networking
*2020 Beyond Data Protection to Command and Control (C2) Sustainability: U.S. Data Protection Act
*2019 Innovation Community (UK): Dr. Yogesh Malhotra: Future of AI-ML - Data Science, BlockChain
*2019 Journal of Financial Transformation: Capital Markets-Risks: AI Augmentation-Risk Management.
*2019 New York State Cyber Security Conference: AI-ML-GANs-DeepFakes: Cyber Risk of Deep Fakes.
*2016 New York State Cyber Security Conference: Beyond Predictive to Anticipatory Risk Analytics.
*2018 CFA Society Keynote: JP Morgan-Goldman Sachs Cases: Model Risk Management AutoML.
*2018 AFCEA C4I Cyber Conference: AI-ML-Cybersecurity Risk & Uncertainty Management Controls.
*2018 MIT Sloan-Computer Sc. & AI Lab AI-ML Executive Guide including RPA & Cognitive Automation
*2018 Princeton FinTech & Quant Conference: Invited Research Presentation: AI-ML-DL MRM.
*2016 Princeton Quant Trading Presentation: Beyond Model Risk Management to Model Risk Arbitrage.
*2015 Princeton Quant Presentation: Future of Finance Beyond 'Flash Boys': Managing Uncertainty.
*2018 Journal of Operational Risk: Toward 'Cyber-Finance’ Cyber Risk Management Frameworks.
*2017 National Association of Insurance Commissioners, Cyber Risk Insurance beyond VaR Models.
*2017 IUP Journal of Computer Sciences, April, Quantitative Modeling of Trust Management Protocols.
*Stress Testing for Cyber Risks: Cyber Risk Insurance Models beyond VaR: Risk, Uncertainty, & Profit.
*Integrated Enterprise Risk Management, Model Risk Management & Cyber-Finance Risk Management.
*Bridging Networks, Systems, Controls Frameworks: Cybersecurity Curricula & Standards Development.
*Advancing Cognitive Analytics Using Quantum Computing for Next Generation Encryption.
*Invited Princeton Quant Trading Presentations: 'Rethinking Finance' for Global Networked DeFi.
*Cybersecurity & Cyber-Finance Risk Management: Strategies, Tactics, Operations, Intelligence.

*Risk Management Framework: Penetration Testing: Banking-Finance Network VoIP Protocols.
*CyberFinance: Cybersecurity Risk Analytics Must Evolve to Survive Emerging Cyber Financial Threats.
*Beyond 'Bayesian vs. VaR' Dilemma: Managing Risk After Risk Management Failed for Hedge Funds.
*Measuring & Managing Financial Risks with Improved Alternatives Beyond Value-at-Risk (VaR).

*Markov Chain Monte Carlo Models for High-Dimensionality Complex Network Security Problems.
*Risk, Uncertainty, Profit: 'Knight Reconsidered': Model Risk Management in Cyber Risk Insurance.
*Cyber-Finance Risk Management: Strategies, Tactics, Operations, Intelligence: ERM to MRM.
*Number Field Sieve Cryptanalytic Algorithms for Efficient Prime Factorization on Composites.
*Bitcoin & Statistical Probabilistic Quant Methods: Financial Regulation: Hong Kong CPAs.
*Bitcoin Protocol & Block Chain: Model of 'Cryptographic Proof' Crypto-Currency Payment Systems.
*2015-2023 120+ SSRN Top-10 Rankings: AI-ML-Quant-Cyber-Crypto-Quantum-Risk Computing.
*2008 AACSB International Impact of Research Report: Among Finance Nobel Laureates Black-Scholes

Top Wall Street Investment Banks Quantitative Finance Projects & FinTech Ventures

US Air Force HQ AI-Machine Learning Commercial Exchange: Pioneering AGI To Save the World
AFRL Commercialization Academy: Building the Future of AGI: Griffiss Cyberspace & Drone™.
MIT Computer Science & AI Lab AI-Machine Learning Executive Guide: AI, ML, DL, NLP, RPA.
Princeton: Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance.

Journal of Financial Transformation:Capital Markets: AI Augmentation Cyber Risk Management.
New York State Cyber Security Conference: AI-ML-GANs-DeepFakes: Cyber Risk of Deep Fakes.
CFA Society Keynote: JP Morgan-Goldman Sachs Practices: Model Risk Management with AutoML.
AFCEA C4I Cyber Conference: AI-ML-Cybersecurity Risk & Uncertainty Management Controls.
MIT Sloan-Computer Sc. & AI Lab AI-ML Executive Guide including RPA & Cognitive Automation
Princeton FinTech Quant Conference: Research Presentation: AI-ML-Deep Learning MRM.
Journal of Operational Risk: 'Cyber-Finance’ Cyber Risk Management Frameworks of Practice.
National Association of Insurance Commissioners: Expert Paper: Cyber Risk Insurance Modeling
Princeton Quant Trading Presentation: Beyond Model Risk Management to Model Risk Arbitrage.
Princeton Quant Trading Presentation: Future of Finance Beyond 'Flash Boys': Uncertainty.
Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects
Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'
Quantitative Finance Risk Analytics, Econometric Analytics, Numerical Programming Models
Quantitative Finance Model Risk Management for Systemic-Tail Risks in Cyber Risk Insurance
JP Morgan Portfolio Optimization, VaR & Stress Testing: 17-Asset Class Portfolio
JP Morgan Portfolio Liquidity Risk Modeling Framework for $500-600Bn Portfolio
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Goldman Sachs Alumnus Asset Manager Large-Scale Data High Freq Econometric Models
Quantitative Finance, Risk Modeling, Econometric Modeling, Numerical Programming
Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management
Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing
Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing
Impact: Quantitative Finance, Quantitative Risk Analytics & Risk Management Projects
Digital Social Enterprise Ventures Creating Trillion $ Practices for Hundreds of Millions

Named among FinTech Finance & IT Nobel laureates for Real World Impact of Research
FinTech Innovations: Model Risk Arbitrage, Open Systems Finance, Cyber Finance, Cyber Insurance
AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe
Research Impact Recognized among Finance & Information Technology Nobel laureates
120+ SSRN Top-10 Rankings: AI-Machine Learning; Cybersecurity; Computer Science, Quant Trading
FinTech Innovations: Model Risk Arbitrage, Cyber Finance, Cyber Risk Insurance Modeling
Computational Quantitative Finance Modeling & Risk Management Research Publications
Model Risk Management of Cyber Risk Insurance Models & Quantitative Finance Analytics
Thesis on Ongoing Convergence of Financial Risk Management & Cyber Risk Management
U.S. Federal Reserve & Office of the Comptroller of the Currency Model Risk Guidance
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Markov Chain Monte Carlo Models & Algorithms to Enable Bayesian Inference Modeling
OCC Notes Cybersecurity Risk & Cyber Attacks as Key Contributor to Banks' Financial Risk
Future of Bitcoin & Statistical Probabilistic Quantitative Methods: Global Financial Regulation
Models Validation Expert Panels: IT, Operations Research, Economics, Computer Science

Global, National, & Enterprise CxO Level FinTech-Cyber-Risk Analytics Ventures
CxO Think Tank that pioneered 'Digital' Management of Risk, Uncertainty, & Complexity
CxO Consulting: Global, National & Corporate Risk Management Practices Leadership
CxO Guidance: Cyber Defense & Finance-IT-Risk Management: Uncertainty & Risk
CxO Keynotes: Conference Board, Silicon Valley, UN, World Economy: Uncertainty & Risk
The Future of Finance Project Leading Quantitative Finance Practices at Elite Conferences
The Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research
UN Quantitative Economics Expert Paper & Keynote on Global Economists Expert Panel
National Science Foundation Cybersecurity & Cybercomputing National Expert Panels
Digital Social Enterprise Innovation Ventures Pioneering the Future of Risk and Quant
Global Footprint of Worldwide World-Leading CxO Risk Management Ventures & Practices

Digital Transformation - Artificial Intelligence: ML-DL-NLP-RPA - Cyber-Crypto Computing - Post AI-Quantum Computing

30-Years as World-Leading AI-Cyber-Global Digital Transformation Networks Pioneer: Post-WWW to Post AI-Quantum Computing

"There are many definitions of knowledge management. It has been described as "a systematic process for capturing and communicating knowledge people can use." Others have said it is "understanding what your knowledge assets are and how to profit from them." Or the flip side of that: "to obsolete what you know before others obsolete it." (Malhotra) "
- U.S. Department of Defense, Office of the Under Secretary of Defense (Comptroller)

"KM is obsoleting what you know before others obsolete it and profit by creating the challenges and opportunities others haven't even thought about -- Dr. Yogesh Malhotra, Inc. Technology"
- U.S. Defense Information Systems Agency Interoperability Directorate

"If you spend some time at [the digital research lab] founded by Dr. Malhotra you will be blessed by some of the world's most astute thinking on the nature of knowledge and its value."
- U.S. Army Knowledge Symposium, Theme: "Knowledge Dominance: Transforming the Army...from Tooth to Tail", Department of Defense, United States Army.

"We are observing diminishing credibility of information technologists. A key reason for this is an urgent need to understand how technologies, people and processes together combine to influence enterprise performance. Today's effective CIO doesn't deliver IT. He delivers business transformation services."
- Yogesh Malhotra, Journal of Knowledge Management, 2005
- United States Air Force Research Lab CIO Col. Tom Hamilton
in presentation to the Armed Forces Communications Electronics Association titled 'Enterprise IT Solutions Are Tough But They're Tougher If You're Stupid', July 21, 2005.

"Knowledge Management refers to the critical issues of organizational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." -- Yogesh Malhotra
- United States Department of Navy

"Dr. Yogesh Malhotra, PhD, drawing upon numerous sources, proposes several theories as to how IT can be used to drive the change of organizations. As environments become more turbulent, organizations must adapt at the same rate to maintain its advantage. Among his theories are that the turbulent environments (in this case, business, but can translate to the turbulent military conflict environment) drive organizations to use IT for empowering workers at all levels, increasing span of control, and increasing lateral communications."
- United States Marine Corps, Reorganization Of The Marine Air Command And Control System To Meet 21St Century Doctrine And Technology, Thesis, September 2001.

"The self-organizing capacity of dynamically adaptive systems is amazing. They tend to eliminate redundancy, minimize connections, and establish priorities--all without outside direction. When something is organized, we tend to believe that someone organized it, some outside influence. But that's not necessarily so. Self-organization is a process in which the organization of a system occurs spontaneously based on the action of its members, without this process being controlled by an external system. The richness of possible behavior increases rapidly with the number of interconnections and the level of feedback. (Malhotra) "
- U.S. Army War College Quarterly

"Dr. Malhotra argues in Business Process Redesign that reengineering is the notion of discontinuous thinking -- recognizing and breaking away from outdated rules and fundamental assumptions. He suggests that reengineering principles are organized around outcomes, and that people who use the output should perform the process. This links parallel activities instead of integrating results, and puts the decision point where the work is performed (Malhotra, 1996). Integrating the DPW processes further into the installation staff can achieve these outcomes. Seventy percent of Business Process Redesigns (BPR) fail because of business focus on cost-cutting and narrow technical approaches (Malhotra, 1996). The installation commanders should decide how DPWs could best serve the community. They should have the opportunity to focus on efficient output and not on restructuring to cut cost. Developing the Corps as the primary service provider narrows the commander's options and does not solve the problem, merely the symptoms. The ultimate success of BPR depends on the experience of people who execute it and how well they apply their creativity to redesigning the processes."
- U.S. Army Management Staff College

"These activities are often described as "knowledge management." See Knowledge Management, in the World Wide Web Virtual Library, edited by Yogesh Malhotra. (Accessed June 16, 1998)....The terms "marshalling" and "mobilization" are intended here to represent two major activities of knowledge management in U.S. national security decisionmaking. Although others may describe and classify basic knowledge-building activities differently, "knowledge management" has been accepted as an umbrella term. See. for example, TheWorld Wide Web Virtual Library on Knowledge Management, edited by Yogesh Malhotra, (Accessed June 16, 1998)..."
- U.S. Air Force Colonel Roc A. Myers, Colonel (s), Harvard University Air Force National Defense Fellow with the Program in 1997-98. Strategic Knowledgecraft: Operational Art for the Twenty-First Century, Roc A. Myers, Prepared while an Air Force National Defense Fellow with the Program in 1997-98 (September 2000).

"Seventy percent of BPR projects fail. Three primary obstacles inhibit the success of reengineering projects: Lack of sustained management commitment and leadership -- It is critical that senior leadership not only support BPR but also be a vocal advocate. Unrealistic scope and expectations -- It is important to manage expectations. BPR is not a panacea that will cure all ills. Resistance to change -- The world is changing all the time and the pace of change continues to accelerate. It will continue to change whether we participate or not. We must change with it or be left behind. AIT provides AIS program managers the opportunity to completely reexamine and reengineer their entire business process, because it offers capabilities not previously available in terms of timeliness and accuracy of data capture. During the operational prototype, the Air Force provided an excellent example of a reengineered business process as a result of AIT. The Supply Asset Tracking System (SATS) is a front-end server that integrates AIT with the supply AIS, the Standard Base Supply System (SBSS). SATS uses linear bar codes for tracking and inventory purposes and smart cards for personal identification to verify receipt and establish personal accountability of property. (Malhotra) "
- U.S. Department of Defense Logistics Implementation Plan

"Knowledge Management caters to the critical issues of organisational adaption, survival and competence in the face of increasingly discontinuous environmental change ... Essentially, it embodies organisational process that seek synergistic combination of data and information processing capacity of information technologies and the creative and innovative capacity of human beings." - Yogesh Malhotra
- Royal Australian Air Force (RAAF) AIRCDRE John Blackburn, Director General Policy and Planning - Air Force (DGPP-AF), Royal Australian Air Force (RAAF), in Air Power Conference 2000.

"First intangible assets are defined in relation to core competencies of the firm. Each core competence is a combination of intangible assets such as knowledge and skills, standards and values, explicit know-how and technology, management processes and assets, and endowments such as image, relationships, and networks. Knowledge creation is the core competence of any firm (Malhotra, 2000)."
- Government of UK, Ministry of Defence

"Malhotra noted the importance of Information Systems for organizational learning, mentioning a series of techniques, methods and tools that can foster organizational learning at many steps of the process: knowledge acquisition, creation and distribution [Malhotra, 1996]."
- Canadian Department of National Defence, Canada, Defence R&D Canada

"Knowledge Management caters to the critical issues of organisational adaption, survival and competence in the face of increasingly discontinuous environmental change. Essentially, it embodies organisational process that seek synergistic combination of data and information processing capacity of information technologies and the creative and innovative capacity of human beings. -- Yogesh Malhotra"
- Air Force, Australia, Director General Policy and Planning

"According to Malhotra, KM ensures that right knowledge is applied at the right place and time and it is about doing the right thing instead of doing things right. Its application to R&D will avoid unnecessary duplication of research. It can help support both individual and organizational learning from past successes and failures while guiding future actions and changes."
- International Atomic Energy Agency

"The Knowledge Management (KM) area has become so diverse over the past ten years as researchers have begun to investigate not only the mechanics of knowledge creation and transfer but also of social and cultural issues that are of importance in understanding this topic. KM is the process of leveraging and utilizing the vast, untapped potential of both implied and documented knowledge to achieve optimal performance, both are equally important for improving performance. Knowledge Management enables businesses to exchange and optimize the knowledge and experience. "Knowledge Management caters for the critical issues of organisational adoption, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings" (Dr. Yogesh Malhotra 1997)."
- IBM

"In his latest book, Knowledge Management and Virtual Organisations, KM luminary, Dr. Yogesh Malhotra, offers some cautionary advice. He exposes three myths often associated with KM solutions. The first of these is that knowledge management technologies can deliver the right information to the right person at the right time. This assumes businesses will develop incrementally in stable markets. However as Malhotra says, "the new business model in the Information Age is marked by fundamental, not incremental change. Businesses can't plan long-term; instead, they must shift to a more flexible 'anticipation of surprise' model. Thus it is impossible to build a system that predicts who the right person at the right time even is, let alone what constitutes the right information."
- Microsoft Corporation

"All can be used to further the goal of keeping the channels of communication open to allow for the exchange of issues and ideas within an organization. According to BRINT Institute chairman and CKO Dr. Yogesh Malhotra, "The key issue is not about the latest information technologies, but whether those technologies are used within, and for facilitating, a culture of information sharing, relationship building and trust." With communication and trust, set within the solid framework of a component architecture, your business can harness that elusive ability to get the right information to the right people at the right time for the right business purposes."
- Cisco Systems, Inc.

"According to Yogesh Malhotra, Knowledge Management practitioner and web author, "Knowledge Management is a brand new field emerging at the confluence of organization theory, management strategy, and management information systems." Breaking apart this definition, Knowledge Management can be defined as an internal, corporate strategy. Knowledge Management can also stand alone as a separate, Information Technology program. Malhotra is right on target when he states that Knowledge Management is a brand new field. Knowledge Management began receiving airplay in 1996. At that time, Tom Davenport wrote in CIO Magazine that a chief knowledge officer "captures and leverages structured knowledge, with information technology as a key enabler." Expanding upon Malhotra and Davenport's definitions, Knowledge Management within NCR Corporation can be defined via a business objective (strategic), a method of Knowledge Management delivery (the management information system), and a role within the organization. NCR's objective is to create, capture, and disseminate knowledge."
- NCR Corporation

"Institutionalization of 'best practices' by embedding them in information technology might facilitate efficient handling of routine, 'linear,' and predictable situations during stable or incrementally changing environments. However, when this change is discontinuous, there is a persistent need for continuous renewal of the basic premises underlying the 'best practices' stored in organizational knowledge bases. -- Yogesh Malhotra in Knowledge Management in Inquiring Organizations"
- Vice President, SAP, North America in SAP Portals ASUG Meeting

"Often used synonymously, the terms knowledge and information, are actually different. Information facilitates knowledge, and can exist without knowledge. Knowledge, however, cannot exist without information. To simplify the concept, Dr. Yogesh Malhotra, renowned scholar on Knowledge Management, defines "Knowledge" as potential for action that has an immediate link to performance. This definition suggests that a person's response or action, or contextual consideration for future action, based on information, is knowledge."
- VeriSign Inc.

"It is generally agreed that the greatest challenges to knowledge management initiatives are resistance to change in both an organization's information-sharing culture and the business processes that occur as a result. K.M. Malhotra defined the problem as follows: Culture is the most difficult component of KM to define, quantify, measure and influence. However, the success or failure of an effective KM program is almost solely dependant upon whether an organization's culture encourages or hinders sharing and transferring knowledge freely within the organization's structure. One thing is certain: an organization's cultural predisposition toward the free transfer of knowledge is largely reflective of the proactive stance demonstrated by the organization's leadership."
- Northrop Grumman

"Il Knowledge Management essenzialmente coinvolge processi organizzativi che cercano di realizzare una combinazione tra le capacità di elaborazione di dati e informazioni e le capacità creative e innovative degli esseri umani. (fonte: Yogesh Malhotra, Ph.D., Knowledge Management for the New World of Business...)"
- Microsoft, Italy

"Knowledge Management refers to the critical issues of organisational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organisational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings. This definition proposed by Dr. Yogesh Malhotra summarises a key issue for e-learning strategies and the way they will impact professional training and companies' organisation policies."
- European Commission

"In the Committee's view, definitions that treat the area as a discipline rather than a mere collection of technologies best encapsulate what knowledge management means. For example, Malhotra says:, "Knowledge Management caters to the critical issue of organisational adaptation, survival and competence in the face of increasingly discontinuous environmental change..."
- Parliament of Victoria, Australia

"It is therefore impossible to typify the roles of Knowledge Management workers other than the CKO, and indeed these roles themselves are in a constant state of change. Dr. Yogesh Malhotra defines this as follows: Given the need for autonomy in learning and decision making, such knowledge workers would also need to be comfortable with self-control and self-learning."
- Government of UK

"We are facing "permanent white-waters" which demands strategies for adaptation to uncertainty in contrast to the conventional emphasis on optimisation based on prediction (Malhotra 1999). To quote a decision-maker in a large multinational firm; "The future is moving so quickly that you can't anticipate it. We have put a tremendous emphasis on quick response instead of planning. We will continue to be surprised, but we won't be surprised that we are surprised. We will anticipate the surprise." (Malhotra 1999)."
- Government of Sweden

"It is difficult, not to say impossible, to replace the significance of individual or collective face-to-face interactions in the sharing of tacit knowledge and articulating it as explicit in an organization, even if rapid development of interactive multimedia applications combining text, image and sound offers increasingly advanced communication potential. Virtual forms of working and work organization might at best supplement, but never totally replace, self-managing teams with close physical and social contacts, for instance, as a forum for learning. (Malhotra) "
- Government of Finland

"A key feature of knowledge management is the sharing of knowledge as opposed to simply the dissemination of information. Knowledge has a different quality to information. Knowledge includes human experience and the ability to make complex judgments based on past experience. Information is more about mere data whereas knowledge is 'potential for action'. (Malhotra)
- Government of Australia

"Ich glaube die Technology ist der leichtere Teil des Ganzen. Die wirkliche Herausforderung stecken doch darin wie die Geschäfts-Prozessen und die darauf aufbauenden Geschäfts- Modelle in Einklang gehalten werden mit den radikalen änderungen in der Geschäftswelt und dem Berufsbild der "Knowledge Worker."[Malhotra, 1993]."
- Government of Austria

"Knowledge management refers to the critical issues of organizational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings," says Dr. Yogesh Malhotra, founding chairman and chief knowledge architect of the BRINT Institute, in an interview with Alistair Craven. Widely recognized as a knowledge management pioneer, Malhotra adds, "Knowledge management is more about the pragmatic and thoughtful application of any concept or definition, as it is not in the definition but in real world execution where opportunities and challenges lie. Any definition therefore must be understood within the specific context of expected performance outcomes and value propositions that answer the question 'Why' about relevance of KM.""
- U.S. Embassy, American Center, New Delhi, India

"Knowledge management, which is a new field emerging from the confluence of organisation theory, management strategy and management information systems, is viewed as an essential driver for innovation. According to Malhotra "Knowledge Management caters to the critical issues of organisational adaption, survival and competence in face of increasingly discontinuous change. Essentially it embodies organisational processes that seek a synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings"."
- Government of South Africa

"Estes ativos do conhecimento aumentam com o uso e daí a importância de as empresas identificarem o que sabem e manterem todo o esforço para desenvolverem área de gestão do conhecimento. A gestão do conhecimento, segundo Malhotra é a capacidade de catalizar os aspectos críticos de adaptação, sobrevivência e competência, buscando uma combinação sinérgica da capacidade de processar informações e conhecimento com a capacidade criativa e inovativa dos seres humanos. (MALHOTRA, 1999)."
- Government of Brazil

"Esta enumeración no implica que algún factor no pueda ocupar a la vez distintas posiciones. La principal característica del nuevo entorno de las organizaciones es su alto nivel de incertidumbre. Por incertidumbre entendemos "la diferencia entre la cantidad de información requerida para realizar una tarea y la cantidad de información ya en poder de la organización" YOGESH, Malhotra.""
- Government of Argentina

"The disconnect between IT expenditures and the firms' organizational performance could be attributed to an economic transition from an era of competitive advantage based on information to one based on knowledge creation." - Yogesh Malhotra
- Government of Mauritius

"The focus of knowledge management is on 'doing the right thing' instead of doing things right’, (Yogesh Malhotra, 2001). The emphasize is that that knowledge management provides framework within which the organization views all processes of the activities to sustain the business and/or ensuring the business survival. Within the army organization, there is no difference. The army needs to keep pace with the technology advancement preparing for the increasingly dynamic and unpredictable regional and world environment."
- Royal Military Police Directorate, Army HQ, Malaysia

"Knowledge Management embodies organnizational processes that seek synergistic combinations of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." -- Yogesh Malhotra, Ph.D."
- Government of Malta

"Dr. Yogesh Malhotra, one of the experts and founder contributor in the development of concept of KM has defined the KM as under : "Knowledge Management caters to the critical issues of organizational adaptation, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings". As it is clear from this definition that objective of Knowledge Management as a crucial management function is not only to survive under changing environment but also to make the organisation adaptable and competitive. The same is particularly applicable for Banks in India, since they are now operating under such a dynamic business environment."
- Indian Banks' Association, India

"Dr. Yogesh Malhotra, the Founder and Chief Knowledge Architect of BRINT, and a well-known expert in the field of K-economy, opines: "The challenges facing us as we enter the 21st Century are formidable. Globalization, Information Technology and Shareholders' Values are transforming the world. To meet these challenges is to become a knowledge-creating or knowledge intensive organization"."
- Indian Banks' Association, India

"Knowledge Management has structural and functional basis in the IM (Information Management or IRM. The main difference is the high degree of dynamic activity involved in the KM system. To summarize in the words of Dr. Malhotra, (10) 'use of the information and control systems and compliance with pre-defined goals, objectives and best practices may not necessarily achieve long-term organizational competence. This is the world of 're-use,' 're-engineering', 're-cycling' etc, which challenges the assumptions underlying the 'accepted way of doing things.' This world needs the capability to understand the problems afresh given the changing environmental conditions. Knowledge management focuses on 'doing the right thing' instead of 'doing things right.'"
- Indian Statistical Institute, Bangalore, India

"Knowledge Management caters to the critical issues of organizational adaption, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings."
- National Academy of Psychology (NAOP), India

"Finally, all who are concerned with IT security issues should understand -- and appreciate -- the difference between information and knowledge. Information, writes Yogesh Malhotra, PhD, is embedded in a computer -- while knowledge is embedded in people. "Information generated by a computer is not a very rich carrier of human interpretation for potential action," he writes. "Computer are merely tools, however great their information-processing capabilities may be."
- Chairman of the Board, The Institute of Internal Auditors

"Leadership Quote of the Week: The focus of knowledge management is on doing the right thing instead of doing things right... Yogesh Malhotra"
- Chartered Management Institute, UK

"Dr. Yogesh Malhotra, founder of the Brint Institute and a pioneer in knowledge management, posits that "the basic premise is that you can predict how and what you'll need to do and that IS can simplify this and do it efficiently". However, the new business model, he says, is marked by fundamental, not incremental, change and businesses can't plan long-term. Instead, they must shift to a more flexible "anticipation of surprise" model, making it impossible to build a system that can predict what is the right information to be delivered to the right person at the right time. This is not to say that information technology has been displaced from the knowledge management equation; its place has been preserved by a growing realisation among developers that software alone cannot automatically be seen as the solution."
- National President of the Australian Computer Society, Australia

"Yogesh Malhotra, founding chairman and chief knowledge officer for the BRINT Institute in Syracuse, New York, believes that the fundamental distinction between data and knowledge plays a major role in whether a system is designed for adaptation and quick response to change. "Dynamic and radically changing environments overwhelm the deterministic logic of a structured model, resulting in a 70 percent failure rate that has characterized implementations of knowledge management models" says Malhotra. Recounting his visit to a Silicon Valley hi-tech consulting firm, Malhotra attributes most failed corporate intranet initiatives to the above fallacy... Malhotra says that once routinized for efficiency and optimization, knowledge-harvesting processes may be delegated to others. However, supply managers need to be more proactively involved in knowledge-creation and knowledge-renewal processes..."
- Institute for Supply Management (ISM)

"Yogesh Malhotra, founding Chairman and Chief Knowledge Architect of the BRINT Institute states: "Knowledge management software is not a canned solution; "Knowledge management technologies cannot always deliver the right information to the right person at the right time; "Information technologies cannot store human intelligence and experience; "Knowledge management systems do not account for renewal of existing knowledge and creation of new knowledge; "Greater incentives are needed for workers to contribute quality content to KMS." Improper use of KMS databases can waste resources if an organization does not really know what knowledge assets it possesses and fails to capitalize on potential new initiatives."
- National Association of Realtors

"Similarly, Dr. Yogesh Malhotra, the famous "Knowledge Architect", wrote a cautionary article on "When Best [Practices] Becomes Worst", Momentum: the Quality Magazine of Australasia, Quality Society of Australasia, NSW (Australia, 2002). In fact, the conditions for producing and utilizing knowledge workers are not a question of the persons concerned merely acquiring subject-matter expertise, problem-solving competency and communication skills. It is essential to provide an environment where such persons can operate and flourish. In the same vein, one of Malhotra's recent books (monograph) for UNESCO discusses knowledge work taking place in "hyper turbulent organizational environments.""
- International Labour Office (ILO)

"Knowledge Management - Discipline that seeks to improve the performance of individual organizations by maintaining and leveraging present and future value of knowledge assets, encompassing both human and automated activities. " Knowledge Management caters to the critical issues of organizational adaption, survival and competence in face of increasingly discontinuous environmental change.... Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." - Dr. Yogesh Malhotra"
- U.S. Department of Health & Human Services

"The mechanistic model of information processing and control based upon compliance is not only limited to the computational machinery, but extends to specification of goals, tasks, best practices and institutionalized procedures to achieve the pre-specified outcomes." -- Yogesh Malhotra
- European Health Management Association, Ireland

"KM has become an increasingly important management discipline in recent years. Nevertheless, some say the phrase KM is unhelpful because 'knowledge is not a "thing" that can be "managed"1. They challenge the 'dominance and control model' that often underlies traditional views of knowledge and organisational management and development. They assert instead the notion that knowledge is largely cognitive, tacit and highly personal. They champion the fundamental role of people and the social interactive basis of knowledge sharing and creation. (Malhotra, Y..) "
- UK Department of Health

"Knowledge management is viewed as an essentialdriver for innovation. According to Malhotra, "Knowledge Management caters to the critical issuesof organisational adaptation, survival and competencein the face of increasingly discontinuous change.Essentially it embodies organisational processes thatseek a synergistic combination of the data andinformation processing capacity of informationtechnologies, and the creative and innovative capacityof human beings"."
- United Nations Development Program (UNDP), Geneva, Switzerland

"Adaptive Learning (See: Double Loop Learning): "Adaptive learning, or, single-loop learning, focuses on solving problems in the present without examining the appropriateness of current learning behaviors." -- Malhotra, Y., Organizational learning and learning organizations: an overview."
- World Health Organization (WHO)

"Dr. Yogesh Malhotra is regarded among the world's most influential practitioners and thought leaders on knowledge management. Widely recognized as a knowledge management pioneer, in this extensive interview read what Dr. Malhotra has to say about knowledge, information, technology and chasing success in this field."
- Emerald Group Publishing Ltd (UK)

"Dr. Yogesh Malhotra in the US is a leader in the knowledge management field. In a recent article written for the US Journal for Quality & Participation, he has pointed to a problem in relation to organisations investing heavily in information technology but not realising gains in terms of knowledge creation."
- Irish Times, Ireland

"Be that as it may, there is no doubt that domestic enterprises, faced by a complete bankruptcy of knowledge and ideas, will, some day, understand the value of the knowledge held by their employees. In the meantime, they would do well to study the writings of Dr. Yogesh Malhotra, an authority on technology and innovation management, business performance, and corporate strategy issues related to information systems, knowledge management, e-business and electronic commerce, business decision models, and new organisation forms."
- The Hindu, A Major National Daily Newspaper, India

"Professor Yogesh Malhotra of Syracuse University, New York, and expert in this field, has recently argued that one of the reasons for this failure is that more often than not knowledge management is practiced in isolation and does not take into account the dynamism of the external environment."
- Malaysian Business, Malaysia
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