Managing Knowledge in the Digital Firm Chapter 12 Managing Knowledge in the Digital Firm

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm OBJECTIVES Assess the role of knowledge management and knowledge management programs in business Define and describe the types of systems used for enterprise-wide knowledge management and demonstrate how they provide value for organizations Define and describe the major types of knowledge work systems and assess how they provide value for firms

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm OBJECTIVES (Continued) Evaluate the business benefits of using intelligent techniques for knowledge management Identify the challenges posed by knowledge management systems and management solutions

Develop new business processes for document routing Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm Cott Corporation Case Challenge: Coordinating the flow of unstructured information and documents among multiple product development groups Solutions: Documentum eRoom software to manage product development documents Develop new business processes for document routing Illustrates the role of knowledge and document management systems for coordinating teams and achieving operational excellence

U.S Enterprise Knowledge Management Software Revenues 2001-2006 Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE U.S Enterprise Knowledge Management Software Revenues 2001-2006 Figure 12-1 Source: Based on the data in eMarketer, “Portals and Content Management Solutions,” June 2003.

Important Dimensions of Knowledge Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Important Dimensions of Knowledge Data: Flow of captured events or transactions Information: Data organized into categories of understanding Knowledge: Concepts, experience, and insight that provide a framework for creating, evaluating, and using information. Can be tacit (undocumented) or explicit (documented) Tacit : مفهوم ضمني

To transform information into knowledge, a firm must expend additional resources to discover patterns, rules, and contexts where the knowledge works.

Important Dimensions of Knowledge (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Important Dimensions of Knowledge (Continued) Wisdom: The collective and individual experience of applying knowledge to the solution of problem; knowing when, where, and how to apply knowledge Knowledge is a Firm Asset: Intangible asset Requires organizational resources Value increases as more people share it

Important Dimensions of Knowledge (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Important Dimensions of Knowledge (Continued) Knowledge has Different Forms: Tacit (not documented) or explicit (documented) Know-how, craft, and skill Knowing how to follow procedures; why things happen Knowledge has a Location: Cognitive event: involve in mental models and maps of individuals Social and individual bases of knowledge Sticky (hard to move), situated (enmeshed in a firm’s culture), contextual (works only in certain situations) Tacit:صامت Cognitive: معرفة، درايه Sticky :لزج situated:قائم على

Important Dimensions of Knowledge (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Important Dimensions of Knowledge (Continued) Knowledge is Situational: Conditional: knowing when to apply a procedure is just as important as knowing the procedure Contextual: We must know how to use a certain tool and under what circumstance.

Organizational Learning and Knowledge Management Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Organizational Learning and Knowledge Management Organizational learning: Adjusting business processes and patterns of decision making to reflect knowledge gained through information and experience gathered

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge management: set of business processes developed in an organization to create, store, transfer, and apply knowledge. Knowledge management increases the ability of the organization to learn from its environment and to incorporate knowledge into its business processes. Incorporate:يدمج

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge acquisition Knowledge storage Knowledge dissemination Knowledge application Building organizational and management capital: collaboration, communities of practice, and office environments

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Figure 12-2

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge acquisition The first knowledge management systems sought to build corporate libraries of documents, reports, presentations, and best practices and encouraged employees to create documents based on their experiences. Developing online expert networks so that employees can “find the expert” in the company who has the knowledge in his or her head.

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge acquisition Discovering patterns in corporate data or by using knowledge workstations where engineers can discover new knowledge. A coherent and organized knowledge system also requires systematic data from the firm’s transaction processing systems that track sales, payments, inventory, customers and other vital data as well as data form external sources such as news feeds, industry reports, legal opinions, scientific research, and government statistics. Coherent: متماسك، مترابط

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge storage Documents, patterns, and expert rules must be stored so they can be retrieved and used by employees. Management must support the development of planned knowledge storage system, encourage the development of corporate-wide schemas for indexing documents, and reward employees for taking the time to update and store documents properly.

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge Dissemination Documents, patterns, and expert rules must be Portal, e-mail, instant messaging, and search engine technologies have added to an existing array of groupware technologies and office systems for sharing calendars, documents, data, and graphics. Training programs, informal networks, and shared management experience communicated through a supportive culture help mangers focus their attention on the important knowledge and information.

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Knowledge Application Regardless of what type of knowledge management system is involved, knowledge that is not shared and applied to the practical problems facing firms and managers does not add business value. To provide a return on investment, organizational knowledge must become a systematic part of management decision making and become situated in existing and new decision support systems New knowledge must be built into a firm’s business process and key application systems.

The Knowledge Management Value Chain Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE The Knowledge Management Value Chain Building organizational and management capital: collaboration, communities of practice, and office environments Knowledge management is as much about building organizational and management capital as it is about technology. The role of mangers is to develop a knowledge culture, where the acquisition, discovery, and application of knowledge are esteemed and rewarded.

Enterprise wide knowledge management systems. Knowledge work systems. Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Types of Knowledge Management Systems Enterprise wide knowledge management systems. Knowledge work systems. Intelligent techniques.

Types of Knowledge Management Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Types of Knowledge Management Systems Figure 12-3

Types of Knowledge Management Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm THE KNOWLEDGE MANAGEMENT LANDSCAPE Types of Knowledge Management Systems Enterprise wide knowledge They are general-propose firm wide efforts to collect, store, distribute, and apply digital content and knowledge. They provide databases and tools for organizing and storing structured and unstructured documents and other knowledge objects, directories and tools for locating employees with expertise in a particular area, and increasingly, Web-based tools for collaborating and communication.

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Figure 12-4

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS include capabilities for storing both structured and unstructured data; tools for locating employee expertise within the firm; and capabilities for obtaining data and information from key transaction systems. They include supporting technologies such as portals, search engines, and collaboration tools to help employee search the corporate knowledge base, communicate ad collaborate with others inside and outside the firm, and apply the stored knowledge to new situations.

Semistructured knowledge Network (tacit) knowledge Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Categories of enterprise-wide knowledge management systems Structured knowledge Semistructured knowledge Network (tacit) knowledge Tacit: ضمني

Structured Knowledge System Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Structured Knowledge System It is explicit knowledge that exists n formal documents, as well as in formal rules that organizations derive by observing experts and their decision-making behaviors. The essential problems of structured knowledge are the creation of any appropriate database schema that can collect and organize the information into meaningful categories and the creation of a database that can be easily accessed by employees on variety of situations. Schema: مخطط

Structured Knowledge System Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Structured Knowledge System Once the schema is created, each document needs to be “tagged”, or the function of implementing the coding schema, interfacing with corporate databases where the document are stored, and creating an enterprise portal environment for employees to use when searching for corporate knowledge. Schema: مخطط

Structured Knowledge System Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Structured Knowledge System Knowledge repository for formal, structured text documents and reports or presentations Also known as content management system Require appropriate database schema and tagging of documents Examples: Database of case reports of consulting firms; tax law accounting databases of accounting firms Schema: مخطط

KWorld’s Knowledge Domains Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS KWorld’s Knowledge Domains Figure 12-5

KPMG Knowledge System Processes Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS KPMG Knowledge System Processes Figure 12-6 Commentary: تفسير

Semistructured Knowledge Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Semistructured Knowledge Systems It is all the digital information in a firm that does not exist a formal document or a formal report that was written by a designated author. It has been estimated that least 80 percent of an organization's business content is unstructured information in folders, messages, memos, proposals, e-mails, electronic slide presentations, and even videos created in different formats and stored in may locations. In many cases firms have no idea what Semistructured content has been created, where it is stored, or who is responsible for it. Designated:يظهر بوضح

Semistructured Knowledge Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Semistructured Knowledge Systems Knowledge repository for less-structured documents, such as e-mail, voicemail, chat room exchanges, videos, digital images, brochures, bulletin boards Also known as digital asset management systems Taxonomy: Scheme of classifying information and knowledge for easy retrieval (its like table of content in book) Tagging: Marking of documents according to knowledge taxonomy

Hummingbird’s Integrated Knowledge Management System Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Hummingbird’s Integrated Knowledge Management System Figure 12-7

Knowledge Network Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Knowledge Network Systems It address the problem that arises when the appropriate knowledge is not in the form of a digital document but instead resides in the memory of expert individuals in the firm. Knowledge network systems seek to turn tacit, unstructured, and undocumented knowledge into explicit knowledge that can be stored in database

Knowledge Network Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Knowledge Network Systems Solutions that are developed by experts and other in the firm are added to knowledge database. This new knowledge can be stored as recommended best business practices or as an answer in a database of frequently asked questions.

Knowledge Network Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Knowledge Network Systems Online directory of corporate experts, solutions developed by in-house experts, best practices, FAQs Document and organize “tacit” knowledge Also known as expertise location and management systems

Knowledge Network Systems (Continued) Key features can include: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Knowledge Network Systems (Continued) Key features can include: Knowledge exchange services Community of practice support Autoproofing capabilities Knowledge management services Autoproofing: اثبات، برهان

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Autoproofing: اثبات، برهان

The Problem of Distributed Knowledge Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS The Problem of Distributed Knowledge Figure 12-8

AskMe Enterprise Knowledge Network System Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS AskMe Enterprise Knowledge Network System Figure 12-9

Enterprise knowledge portals: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Supporting Technologies: Portals, Collaboration Tools, and Learning Management Systems Enterprise knowledge portals: Access to external sources of information Access to internal knowledge resources Capabilities for e-mail, chat, discussion groups, videoconferencing

Learning Management System (LMS): Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm ENTERPRISE-WIDE KNOWLEDGE MANAGEMENT SYSTEMS Learning Management System (LMS): Provides tools for the management, delivery, tracking, and assessment of various types of employee learning and training Integrates systems from human resources, accounting, sales in order to identify and quantify business impact of employee learning programs

Knowledge Workers and Knowledge Work Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Knowledge Workers and Knowledge Work Knowledge workers: Create knowledge and information for organization Knowledge workers key roles: Keeping the organization current in knowledge as it develops in the external world—in technology, science, social thought, and the arts

Knowledge Workers and Knowledge Work (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Knowledge Workers and Knowledge Work (Continued) Serving as internal consultants regarding the areas of their knowledge, the changes taking place, and opportunities Acting as change agents, evaluating, initiating, and promoting change projects

Requirements of Knowledge Work Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Requirements of Knowledge Work Systems It must give knowledge workers the specialized tools they need. Great computing power to handle the sophisticated graphics or complex calculation necessary for such knowledge workers. It must give the worker quick and easy access to external databases. User-friendly interface

Requirements of Knowledge Work Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Requirements of Knowledge Work Systems Figure 12-10

Examples of Knowledge Work Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Examples of Knowledge Work Systems Computer-Aided Design (CAD): Information system that automates the creation and revision of industrial and manufacturing designs using sophisticated graphics software Virtual Reality Systems: Interactive graphics software and hardware that create computer-generated simulations that emulate real-world activities or photorealistic simulations

Examples of Knowledge Work Systems (Continued) Investment Workstation: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm KNOWLEDGE WORK SYSTEMS Examples of Knowledge Work Systems (Continued) Investment Workstation: Powerful desktop computer for financial specialists, which is optimized to access and manipulate massive amounts of financial data

Knowledge Discovery: Artificial Intelligence (AI) technology: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Knowledge Discovery: Identification of underlying patterns, categories, and behaviors in large data sets, using techniques such as neural networks and data mining Artificial Intelligence (AI) technology: Computer-based systems based on human behavior, with the ability to learn languages, accomplish physical tasks, use a perceptual apparatus, and emulate human expertise and decision making

Capturing Knowledge: Expert Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Capturing Knowledge: Expert Systems expert system: Knowledge-intensive computer program that captures the expertise of a human in limited domains of knowledge. Expert systems capture the knowledge of skilled employees in the form of a set of rules. The set of rules in the expert system adds to the memory, or stored learning of the firm. An expert system can assist decision making by asking relevant questions and explaining the reasons for adopting certain actions

Capturing Knowledge: Expert Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Capturing Knowledge: Expert Systems Expert systems lack the breadth of knowledge and the understanding of fundamental principles of a human expert. They are quite narrow, shallow, and brittle. They typically perform very limited tasks that can be performed by professionals in a few minutes or hours

Capturing Knowledge: Expert Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Capturing Knowledge: Expert Systems Human knowledge must be modeled or represented in a way that a computer can process. The model of human knowledge used by expert systems is called the knowledge base. A standard structured programming construct is the IF–THEN construct, in which a condition is evaluated. If the condition is true, an action is taken.

Capturing Knowledge: Expert Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Capturing Knowledge: Expert Systems Expert system: An intelligent technique for capturing tacit knowledge in a very specific and limited domain of human expertise Knowledge base: Model of human knowledge that is used by expert systems Series of 200-10,000 IF-THEN rules to form a rule base AI shell: The programming environment of an expert system

How Expert Systems Work: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES How Expert Systems Work: Rules in an AI Program Figure 12-11

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Inference engine: The strategy used to search through the rule base in an expert system. Common strategies are forward chaining and backward chaining Forward chaining: A strategy for searching the rule base in an expert system that begins with the information entered by the user and searches the rule base to arrive at a conclusion

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Backward chaining: A strategy for searching the rule base in an expert system that acts like a problem solver by beginning with hypothesis and seeking out more information until the hypothesis is either proved or disproved Knowledge engineer: Elicits: يستخرج A specialist who elicits information and expertise from other professionals and translates it into a set of rules for an expert system

Inference Engines in Expert Systems Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Inference Engines in Expert Systems Figure 12-12

Example of Expert System Galeria Kaufhof, a German superstore chain, uses a rule-based system to help it manage over 110,000 deliveries of goods that it receives each day, ranging from clothing to complex electronics and fine china. Inspecting each delivery is time-consuming and expensive, but the company wants to make sure that it is receiving goods that are not damaged or defective. Kaufhof implemented a rule-based system that identifies high-risk deliveries and passes along lower-risk ones automatically.

The system scans delivery labels and identifies each delivery in terms of its size, type of product, whether the product is a new product, and the supplier’s past history of deliveries to Kaufhof. Deliveries of large numbers of complex products that are new or that have suppliers with unfavorable delivery histories are carefully inspected while other deliveries are passed on without inspection

Only certain classes of problems can be solved using expert systems Only certain classes of problems can be solved using expert systems. Virtually all successful expert systems deal with problems of classification in which there are relatively few alternative outcomes and in which these possible outcomes are all known in advance. Many expert systems require large, lengthy, and expensive development efforts.

Organizational Intelligence Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Organizational Intelligence Case-Based Reasoning (CBR): Knowledge system that represents knowledge as a database of cases and solutions Searches for stored cases with problem characteristics similar to the new case and applies solutions of the old case to the new case

Organizational Intelligence Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Organizational Intelligence In case-based reasoning (CBR), descriptions of past experiences of human specialists, represented as cases, are stored in a database for later retrieval when the user encounters a new case with similar parameters. The system searches for stored cases with problem characteristics similar to the new one, finds the closest fit, and applies the solutions of the old case to the new case. Successful solutions are tagged to the new case and both are stored together with the other cases in the knowledge base. Unsuccessful solutions also are appended to the case database along with explanations as to why the solutions did not work.

How Case-based Reasoning Works Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES How Case-based Reasoning Works Figure 12-13

Used for problems that are difficult to represent by IF-THEN rules Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Fuzzy Logic Systems Rule-based technology that can represent imprecise values or ranges of values by creating rules that use approximate or subjective values Used for problems that are difficult to represent by IF-THEN rules

Implementing Fuzzy Logic Rules in Hardware Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Implementing Fuzzy Logic Rules in Hardware Figure 12-14 Source: James M. Sibigtroth, “Implementing Fuzzy Expert Rules in Hardware,” Al Expert, April 1992. copyright 1992 Miller Freeman, Inc. Reprinted with permission.

Neural Networks Neural Network: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Neural Networks Neural Network: Hardware or software that emulates the processing patterns of the biological brain to discover patterns and relationships in massive amounts of data Use large numbers of sensing and processing nodes that interact with each other

Neural Networks (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Neural Networks (Continued) Uses rules it ‘learns” from patterns in data to construct a hidden layer of logic that can be applied to model new data Applications are found in medicine, science, and business They cannot always explain why they arrived at particular solution. They cannot always guarantee a completely certain solution, arrive at the same solution again with the same input data, or always guarantee the bet solution

How a Neural Network Works Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES How a Neural Network Works Figure 12-15 Source: Herb Edelstein, “Technology How-To: Mining Data Warehouses,” InformationWeek, January 8, 1996. Copyright 1996 CMP Media, Inc., 600 Community Drive, Manhasset, NY 12030. Reprinted with permission.

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Genetic Algorithms Adaptive computation that examines very large number of solutions for a problem to find optimal solution Programmed to “evolve” by changing and reorganizing component parts using processes such as reproduction, mutation, and natural selection: worst solutions are discarded and better ones survive to produce even better solutions

The Components of a Genetic Algorithm Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES The Components of a Genetic Algorithm Figure 12-16 Source: Dhar, Stein, SEVEN METHODS FOR TRANSFORMING CORPORATE DATA INTO BUSINESS INTELLIGENCE (Trade Version), 1st copyright 1997. Electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.

Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Hybrid AI system: Integration of multiple AI technologies (genetic algorithms, fuzzy logic, neural networks) into a single application to take advantage of the best features of these technologies Intelligent Agents: Software programs that work in the background without direct human intervention to carry out specific, repetitive, and predictable tasks for an individual user, business process, or software application

Intelligent Agents in P&G’s Supply Chain Network Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm INTELLIGENT TECHNIQUES Intelligent Agents in P&G’s Supply Chain Network Figure 12-17

Management Opportunities: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Management Opportunities: Proprietary knowledge can create an “invisible competitive advantage”

Management Challenges: Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Management Challenges: Insufficient resources are available to structure and update the content in repositories. Poor quality and high variability of content quality results from insufficient validating mechanisms. Content in repositories lacks context, making documents difficult to understand.

Management Challenges: (Continued) Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Management Challenges: (Continued) Individual employees are not rewarded for contributing content, and many fear sharing knowledge with others on the job. Search engines return too much information, reflecting lack of knowledge structure or taxonomy.

Choose a high-value business process Choose the right audience Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Solution Guidelines: Five important steps in developing a successful knowledge management project: Develop in stages Choose a high-value business process Choose the right audience Measure ROI during initial implementation Use the preliminary ROI to project enterprise-wide values

Implementing Knowledge Management Projects in Stages Management Information Systems Chapter 12 Managing Knowledge in the Digital Firm MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS Implementing Knowledge Management Projects in Stages Figure 12-18