© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-1 Chapter 9 Knowledge Management Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-2 Learning Objectives Define knowledge. Learn the characteristics of knowledge management. Describe organizational learning. Understand the knowledge management cycle. Understand knowledge management system technology and how it is implemented. Learn knowledge management approaches. Understand the activities of the CKO and knowledge workers. Describe the role of knowledge management in the organization. Be able to evaluate intellectual capital. Understand knowledge management systems implementation. Illustrate the role of technology, people, and management with regards to knowledge management. Understand the benefits and problems of knowledge management initiatives. Learn how knowledge management can change organizations.

The Knowledge Economy The new source of wealth is knowledge, and not labor, land, or financial capital. It is the intangible, intellectual assets that must be managed. The key challenge of the knowledge- based economy is to foster innovation.

The Knowledge Economy For several decades the world's best- known forecasters of societal change have predicted the emergence of a new economy in which brainpower, not machine power, is the critical resource. But the future has already turned into the present, and the era of knowledge has arrived. --"The Learning Organization," Economist Intelligence Unit

Knowledge Management Is a process that helps organizations identify, select, organize, disseminate and transfer important information and expertise that are part of organization's memory and that typically reside within the organization in an unstructured manner. In simple language KM is the systematic and active managing of ideas, information and knowledge in an organization's employees. It's important to note that the definition says nothing about technology; while KM is often facilitated by IT, technology by itself is not KM. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-5

Intellectual capital Often used as a synonym for "Knowledge" implies that there is a financial value to knowledge. For example, in 2000 the value of the intellectual capital of the property- casualty insurance industry has been estimated to be between $270 billion to $33o billion (Mooney, 2000). © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-6

Organizational Learning Learning Organization Refers to an organization's capability of learning from its past experience ( DiBelle, 1995). Organizational Learning Is the development of new knowledge and insights that have the potential to influence an organization's behavior. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-7

Knowledge Mgmt The goal is to capture, store, maintain, and deliver useful knowledge in a meaningful form to anyone who needs it anyplace and anytime within an org. Knowledge = Intellectual Capital © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-8

Jessica Chen- Burger Why KM ? A company's intellectual capital represents its ability to change in the face of adversity. Develop new products. Cut research and develop time. Provide quality customer service. Share knowledge with employees, partners and customers. Source: Orbital Software

Some well known KM Definitions "If only HP knew what it knows it would make three times more profit tomorrow" Lew Platt, ex CEO Hewlett Packard © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-10

"We recognize that our most important asset is people and their knowledge. We understand Knowledge Management (KM) as the cultivation of an environment within which people are willing to share, learn and collaborate together leading to improvement". Care Services Improvement Partnership (CSIP) © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-11

Growth of KM: 1000% Increase Over the past 7 Years (In Annual Investment $) : 1998:  $776 Million Total US Spending (for all uses) 2005  $600 Billion Public K-12 & Higher Education  $70 Billion Corporate and Govt. Training

Chief Knowledge Officer (CKO) The CKO's role are to maximize the firm's knowledge assets, design and implement knowledge management strategies, effectively exchange knowledge assets internally and externally, and promote system use. The CKO is responsible for creating an infrastructure and cultural environment for knowledge sharing. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-13

Goal of Knowledge Mgmt:

The Importance of Managing Knowledge Intellectual capital is appreciable assets, most assets depreciate. Knowledge work is increasing in importance as much as the increase in service economy. Employees with the most intellectual capital have become volunteers. Most managers ignore intellectual capital and lose out on the benefits of its use. Employees with the most intellectual capital are often the least appreciated. Knowledge mismanagement. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-15

Encourage Knowledge SHARING Discouragement due to org. cultural or technical barriers. Educate people on the value of knowledge. Refurbish reward and recognition system. Act as a role model for sharing. Make it a job requirement. Make the tech. work for people; don’t expect the people to work for the tech. Educate people about the value in the know. It is OK to make mistakes, “No one is perfect” © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-16

Why people do not share KNOWLWDGE It can cripple an org. As people refuse to share what they know, a situation created by Org. Culture Barriers. Why people hoard (hide away) their knowledge. Knowledge as a source of power and will guarantee job security. People wont get credit for sharing knowledge. People don’t have time, or know how to share. People don’t knowthe value or how much they know. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-17

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-18 Siemens Knows What It Knows Through Knowledge Management Knowledge management –Community of interest Repositories (storehouse) Communities of practice Informal knowledge-sharing techniques –Employee initiated Created ShareNet –Easy to share knowledge –Incentives for posting –Internal evangelists responsible for training, monitoring, and assisting users –Top management support

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-19 Knowledge Management Process to help organization identify, select, organize, disseminate, transfer information Structuring enables problem-solving, dynamic learning, strategic planning, decision-making and reduce redundancy Leverage value of intellectual capital through reuse The age of knowledge worker.

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Knowledge Data = collection of facts, measurements, statistics Information = organized data Knowledge = contextual, relevant, actionable info. –Strong experiential and reflective elements –Good leverage and increasing returns –Dynamic –Branches and fragments with growth –Knowledge is valuable when it is shared. –Uncertain value in sharing –Evolves over time with experience

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-21 Knowledge Explicit (Leaky) knowledge –Objective, rational, technical –Policies, goals, strategies, papers, reports –Codified –Leaky knowledge Tacit (sticky) knowledge –Subjective, cognitive, experiential learning –Highly personalized –Difficult to formalize –Cumulative store of the experiences. –Within the brain of individuals or embedded in the group interaction.

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-22 Knowledge Management Systematic and active management of ideas, information, and knowledge residing within organization’s employees Knowledge management systems –Use of technologies to manage knowledge –Used with turnover, change, downsizing –Provide consistent levels of service

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Organizational Learning Learning organization –Ability to learn from past –To improve, organization must learn –3 Issues: Meaning, Management, Measurement –5 Activities: Problem-solving, Creative experimentation, learning from past, learning from acknowledged best practices, transfer of knowledge within organization -, Organizational memory way to save and share. Must have organizational memory to have a learning Org. Categories ( Wells) 1- Individual 2-information 3-Culture 4-Transformation 5-Structural

“Generally when a technology project fails, it is because the technology doesn’t match the organization’s culture” Organizational learning –Develop new knowledge that have the potential to influence behavior. –Corporate memory is critical for success. –Org. Learning Process: Know. Acquisition. Know. Sharing. Know. Utilization. Organizational culture –Pattern of shared basic assumptions –Can cause KM success or failure. –Difficult to measure the impact of culture on org. (Strong culture produce strong results(ROI, Net income, increase in stock price) KSF To create an enterprise with a culture of continuous change where employees are not threatened by change bur are encouraged by it because they believe it will improve their quality of life. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-24

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-25 Knowledge Management Initiatives Aims –Make knowledge visible –Develop knowledge intensive culture –Build knowledge infrastructure Surrounding processes –Creation of knowledge –Sharing of knowledge –Seeking out knowledge –Using knowledge

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-26 Knowledge Management Initiatives Knowledge creation –Generating new ideas, routines, insights –Modes Socialization, externalization, internalization, combination Knowledge sharing –Willing explanation to another directly or through an intermediary Knowledge seeking –Knowledge sourcing

Core competency linked to Tacit and Explicit Knowledge Core Competencies of the organization Explicit Knowledge Policies, Patents, Decisions, strategies Tacit Knowledge Expertise, Know- how, Org. Culture, Values © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-27 Process of explication may generate tacit knowledge Convert tacit know. To measurable Explicit knowledge

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-28 Approaches to Knowledge Management Process Approach –Codifies knowledge Formalized controls, approaches, technologies Fails to capture most tacit knowledge Practice Approach –Assumes that most knowledge is tacit Informal systems –Social events, communities of practice, person-to- person contacts Challenge to make tacit knowledge explicit, capture it, add to it, transfer it

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-29 Approaches to Knowledge Management Hybrid Approach –Practice approach initially used to store explicit knowledge –Tacit knowledge primarily stored as contact information –Best practices captured and managed Best practices –Methods that effective organizations use to operate and manage functions Knowledge repository –Place for capture and storage of knowledge –Different storage mechanisms depending upon data captured

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-30 Knowledge Management System Cycle Creates knowledge through new ways of doing things Identifies and captures new knowledge Places knowledge into context so it is usable Stores knowledge in repository Reviews for accuracy and relevance Makes knowledge available at all times to anyone Disseminate

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-31 Components of Knowledge Management Systems Technologies –Communication Access knowledge Communicates with others –Collaboration Perform group work Synchronous or asynchronous Same place/different place –Storage and retrieval Capture, storing, retrieval, and management of both explicit and tacit knowledge through collaborative systems

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-32 Components of Knowledge Management Systems Supporting technologies –Artificial intelligence KM is a systems often have AI methods embedded in them Expert systems, neural networks, fuzzy logic, intelligent agents –Intelligent agents Systems that learn how users work and provide assistance –Knowledge discovery in databases Process used to search for and extract information –Internal = data and document mining –External = model marts and model warehouses –XML Extensible Markup Language Enables standardized representations of data Better collaboration and communication through portals

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-33 Knowledge Management System Implementation Challenge to identify and integrate components –Early systems developed with networks, groupware, databases Knowware –Technology tools that support knowledge management Collaborative computing tools –Groupware Knowledge servers Enterprise knowledge portals Document management systems –Content management systems Knowledge harvesting tools Search engines Knowledge management suites –Complete out-of-the-box solutions

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-34 Knowledge Management System Implementation Implementation –Software packages available Include one or more tools –Consulting firms –Outsourcing Application Service Providers

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-35 Knowledge Management System Integration Integration with enterprise and information systems DSS/BI –Integrates models and activates them for specific problem Artificial Intelligence –Expert system = if-then-else rules –Natural language processing = understanding searches –Artificial neural networks = understanding text –Artificial intelligence based tools = identify and classify expertise

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-36 Knowledge Management System Integration Database –Knowledge discovery in databases CRM –Provide tacit knowledge to users Supply chain management systems –Can access combined tacit and explicit knowledge Corporate intranets and extranets –Knowledge flows more freely in both directions –Capture knowledge directly with little user involvement –Deliver knowledge when system thinks it is needed

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-37 Human Resources Chief knowledge officer –Senior level –Sets strategic priorities –Defines area of knowledge based on organization mission and goals –Creates infrastructure –Identifies knowledge champions –Manages content produced by groups –Adds to knowledge base CEO –Champion knowledge management Upper management –Ensures availability of resources to CKO Communities of practice Knowledge management system developers –Team members that develop system Knowledge management system staff –Catalog and manage knowledge

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-38 Knowledge Management Valuation Asset-based approaches –Identifies intellectual assets –Focuses on increasing value Knowledge linked to applications and business benefits approaches –Balanced scorecard –Economic value added –Inclusive valuation methodology –Return on management ratio –Knowledge capital measure Estimated sale price approach

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-39 Metrics Financial –ROI –Perceptual, rather than absolute –Intellectual capital not considered an asset Non-financial –Value of intangibles External relationship linkages capital Structural capital Human capital Social capital Environmental capital

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 9-40 Factors Leading to Success and Failure of Systems Success –Companies must assess need –System needs technical and organizational infrastructure to build on –System must have economic value to organization –Senior management support –Organization needs multiple channels for knowledge transfer –Appropriate organizational culture Failure –System does not meet organization’s needs –Lack of commitment –No incentive to use system –Lack of integration