Chapter 12staff.uob.edu.bh/files/820500720_files/chapter_12.pdf© 2006 by Prentice Hall Chapter 12 ... Semistructured Knowledge System 3. ... © 2006 by Prentice Hall All the major

12.1 Modified by N Alsalman

© 2006 by Prentice Hall

12 Chapter

Managing Knowledge in the Digital Firm

Managing Knowledge Managing Knowledge in the Digital Firm in the Digital Firm



• Assess the role of knowledge management and knowledge management programs in business

• Define and describe the types of systems used for enterprisewide 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 Management Information Systems Chapter 12 Chapter 12 Managing Knowledge in the Digital Firm Managing Knowledge in the Digital Firm

OBJECTIVES



• Evaluate the business benefits of using intelligent techniques for knowledge management

• Identify the challenges posed by knowledge management systems and management solutions

OBJECTIVES (Continued)




• 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


Cott Corporation Case



Important Dimensions of Knowledge Important Dimensions of Knowledge

• Data: Flow of captured events or transactions captured by and organisation’s system that by it self is useful only for transacting.

• Information: Data organized into categories of understanding such us monthly yearly regional.

• Knowledge: Concepts, experience, and insight that provide a framework for creating, evaluating, and using information. Can be tacit (undocumented) or explicit (documented)


THE KNOWLEDGE MANAGEMENT LANDSCAPE



Knowledge is a Firm Asset:

• Intangible asset

• Requires organizational resources

• Value increases as more people share it


• Wisdom: The collective and individual experience of applying knowledge to the solution of problem; knowing when, where, and how to apply knowledge


Important Dimensions of Knowledge (Continued)



• Tacit or explicit

• Involves Knowhow, craft, and skill

• Knowing how to follow procedures; why things happen not only when things happen

Knowledge has a Location:

• Cognitive event takes place in peoples mind or a specific business process

• There is both Collective (social) and individual bases of knowledge

• Sticky ( hard to move) and not universally applicable , situated ( trapped in a firm’s culture), relative to a situation ( works only in certain situations) .



Knowledge has Different Forms: Important Dimensions of Knowledge (Continued)



• Conditional : Know when to apply a procedure is as important as knowing the procedure

• Contextual: you need to know how to use a tool and under what circumstances.

We must recognise that organisation’s knowledge based core competencies ( 2 or 3 things that org. does best) are key org. assets and can not be

duplicated easily.



Knowledge is Situational:

Important Dimensions of Knowledge (Continued)



• Organizational learning: Adjusting business processes and patterns of decision making to reflect knowledge gained through:

• information and experience gathering

• Careful measurement of planned activities

• Trail and error ( experience )

• Feedback from customers

Organizational Learning and Knowledge Management






U.S Enterprise Knowledge Management Software Revenues 20012006

Figure 121


Source: Based on the data in eMarketer, “Portals and Content Management Solutions,” June 2003.



Knowledge Management

• • Set of processes Set of processesdeveloped in an organisation developed in an organisation to to create create, store, , store, transfer transfer , and , and apply apply knowledge knowledge. .

• • It is an enabler for organisational learning It is an enabler for organisational learning

• • There are value adding steps in the knowledge There are value adding steps in the knowledge management chain each step adds value to raw management chain each step adds value to raw data and information as they are transformed into data and information as they are transformed into knowledge . knowledge .





The Knowledge Management Value Chain

Figure 122





• • The management and organisational The management and organisational activities represent the investment in activities represent the investment in organisational capital ( set of business organisational capital ( set of business processes, culture and behaviour required processes, culture and behaviour required to obtain value from investment in IS) to obtain value from investment in IS) required to obtain substantial return on required to obtain substantial return on the IT investments. the IT investments.

• • Effective KW management is 80% Effective KW management is 80% Managerial and organisational and 20% Managerial and organisational and 20% Technology Technology





1. Knowledge acquisition 1. Build Corporate libraries of documents, reports,

presentations and best practises including unstructured documents such as email

2. Developing online expert networks to find experts who have knowledge in their heads.

3. Discovering patterns in corporate data by using KW workstations


The Knowledge Management Value Chain




2. Knowledge storage 1. Once they discover the above they need to store it

in a database called KW management system that digitise, index and tag documents.

2. Communities of expertise and expert systems help org. to preserve knowledge.

3. Management must support the development of planned KW Man agent system, encourage the development of corporate wide schemas for indexing by rewarding employees for submitting information.


The Knowledge Management Value Chain(Continued)




3. Knowledge dissemination 1. Portals, email IM and search engines has resulted in

an explosion of KW and information dissemination.

2. Groupware and Office Systems

3. Management and organization activities play a critical role in helping employees discovering in a sea of information and KW what is really important to them by providing training programmes and sharing management experiences to provide supportive culture.






4. Knowledge application 1. Whatever system an organisation have it is useless if

they do not apply it in solving problems to add value to the org.

2. To provide ROI KW Management systems must be part of decision making.

3. New KW must be built into org. business process and key corporate systems.

4. Management should support the above by creating new products, services and new markets based on new KW.






5. Building organizational and management capital: collaboration, communities of practice, and office environments.

1. Develop KW Culture

2. Develop new KW Management roles such as CKO Chief Knowledge Officer.

3. Help in developing Communities of Practice Informal social networks of professionals and employees within and outside the org. who have similar work related activities so they can exchange day to day experiences and knowledge






Types of Knowledge Management Systems

Figure 123



Intelligent Techniques



ENTERPRISEWIDE KNOWLEDGE MANAGEMENT SYSTEMS

Figure 124


It also includes supporting technologies

such as

This system includes:

1. Capabilities for storing both structured and unstructured data

2. Tools for locating employee expertise within the firm

3. Capabilities for obtaining data from key TPSs



• There are three types of Enterprise Knowledge Systems 1. Structured Knowledge System 2. Semistructured Knowledge System 3. Network Knowledge System ( Tacit)





• Knowledge repository for formal, structured text documents and reports or presentations (Explicit knowledge)

• Also known as content management system

• Require appropriate database schema and tagging of documents for easy access in a variety situations

• Each document needs to be tagged or coded for retrieval by search engines.

Structured Knowledge System





• Structured Knowledge Systems perform the functions of : 1. Implementing the coding.

2. Interfacing with the firm’s databases where the documents are stored.

3. Creating an enterprise portal environment for employees to use when searching for knowledge.






All the major accounting and consulting firms have developed structured document ( casebased) repositories of reports from consultants who are

working with particular clients after the consulting is completed in some companies these are called best

practices.

Examples: Database of case reports of consulting firms; tax law accounting databases of accounting firms






KWorld’s Knowledge Domains


Figure 125


KPMG International tax and accounting firm with:

•95000 professionals serving clients through

•1100 offices and 820 cities

•150 countries

Very large global base of employees and clients they will have a problem of sharing knowledge disseminating best

practices

What do they need

Structured Knowledge Repository



KPMG Knowledge System Processes


Figure 126




• Knowledge repository for lessstructured documents, such as email, voicemail, chat room exchanges, videos, digital images, brochures, bulletin boards

• Also known as digital asset management systems • One of the first challenges face a company when building knowledge repository is identifying the correct categories to use when classifying documents.

WHAT IS THE SOULUTION

Semistructured Knowledge Systems





• Taxonomy: Scheme of classifying information and knowledge for easy retrieval it is like a table of contents of a book or like a library’s logical categories the more precise the taxonomy the more relevant search results are. Once a knowledge taxonomy is produced documents are all tagged.

• Tagging: Marking of documents according to the proper knowledge taxonomy ( Class)

Semistructured Knowledge Systems





Hummingbird’s Integrated Knowledge Management System


Figure 127


This solution combines

•Documents Management

•Knowledge Management

•Business Intelligence

•Portal technologies

•It is used for managing structured and semistructured knowledge




• Online directory of corporate experts, solutions developed by inhouse experts, best practices, FAQs

• Document and organize “tacit” knowledge

• Also known as expertise location and management systems

Knowledge Network Systems






Knowledge Network Systems (Continued)



The Problem of Distributed Knowledge


Figure 128


The problem of distributed knowledge is finding the right person who knows failing that will result in

rediscovering effort which can cost companies a lot.

An IDC ( International Data Cooperation ) estimate that

the average cost of redundant effort in Fortune 500 companies exceeds 60

million $ per year



AskMe Enterprise Knowledge Network System






Supporting Technologies: Portals, Collaboration Tools, Supporting Technologies: Portals, Collaboration Tools, and Learning Management Systems and Learning Management Systems

Enterprise knowledge portals:

• Access to external sources of information

• Access to internal knowledge resources

• Capabilities for email, chat, discussion groups, videoconferencing




An Enterprise Information Portal




• 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

Learning Management System (LMS):




KNOWLEDGE WORK SYSTEMS

Knowledge Workers and Knowledge Work Knowledge Workers and Knowledge Work

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: Create knowledge and information for organization





• 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


Knowledge Workers and Knowledge Work (Continued)



Requirements of Knowledge Work Systems

Figure 1210





Examples of Knowledge Work Systems Examples of Knowledge Work Systems

• Information system that automates the creation and revision of industrial and manufacturing designs using sophisticated graphics software

ComputerAided Design (CAD):

• Interactive graphics software and hardware that create computergenerated simulations that emulate realworld activities or photorealistic simulations. If it is used on the Internet it uses Virtual Reality Modelling Language ( VRML)

Virtual Reality Systems:





• Powerful desktop computer for financial specialists, which is optimized to access and manipulate massive amounts of financial data

Investment Workstation:



Examples of Knowledge Work Systems (Continued)



INTELLIGENT TECHNIQUES

• Identification of underlying patterns, categories, and behaviors in large data sets, using techniques such as neural networks and data mining

Knowledge Discovery:

• Computerbased 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

Artificial Intelligence (AI) technology:




Capturing Knowledge: Expert Systems 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 20010,000 IFTHEN rules to form a rule base



AI shell: The programming environment of an expert system



How Expert Systems Work: How Expert Systems Work: Rules in an AI Program

Figure 1211





• The strategy used to search through the rule base in an expert system. Common strategies are forward chaining and backward chaining

Inference engine:



• 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

Forward 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

Backward chaining:


• A specialist who elicits information and expertise from other professionals and translates it into a set of rules for an expert system

Knowledge engineer:



Inference Engines in Expert Systems


Figure 1212




Organizational Intelligence Organizational Intelligence

• 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

CaseBased Reasoning (CBR):





How Casebased Reasoning Works


Figure 1213




• Proprietary knowledge can create an “invisible competitive advantage”

Management Opportunities:

MANAGEMENT OPPORTUNITIES, CHALLENGES AND SOLUTIONS




• 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:





• 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.



Management Challenges: (Continued)



• Develop in stages

• Choose a highvalue business process

• Choose the right audience

• Measure ROI during initial implementation

• Use the preliminary ROI to project enterprisewide values

Solution Guidelines:



Five important steps in developing a successful knowledge management project:



Implementing Knowledge Management Projects in Stages

Figure 1218

