4/10: Managing Knowledge & IS Tools for Decision-Making

1. 4/10: Managing Knowledge & IS Tools for Decision-Making • Knowledge Management • Office & document management systems • Knowledge work systems • Group collaboration systems, intranet knowledge environments • Artificial intelligence: Expert Systems, Case-based reasoning • Neural networks, Fuzzy logic, Genetic algorithms, Hybrid AI systems, Intelligent agents • Enhancing Management Decision-Making • Decision Support Systems (DSS) • Group DSS • Executive Support Systems (ESS)

2. Knowledge Management • “ The process of systematically and actively managing and leveraging the stores of knowledge in an organization.” • An organization’s knowledge base may include: • Structured internal knowledge • External knowledge • Informal internal knowledge (tacit knowledge)

3. Information Work • “Work that primarily consists of creating or processing information.” • Two types of workers: • Data workers: those who process & disseminateinformation & paperwork. • Knowledge workers: those who create knowledge; those who design products & services.

4. Office & Document Management Systems • 3 basic functions of an office: • Managing & coordinating the work of data & knowledge workers • Connecting the work of the local info workers with the larger organization • Connecting the organization to the external environment

5. Office Workers: Activities • Managing documents • Document creation, storage, retrieval, dissemination • Scheduling for individuals & groups • Communicating for individuals & groups • Voice,digital, & document-based communications • Managing data

6. Office Systems Help Office Workers • “Computer systems, such as word processing, voice mail, and imaging that are designed to increase productivity of office workers.” • Help with: • Document creation, dissemination, & retrieval • Collaboration • Scheduling • Etc.

7. Document Imaging Systems • Convert printed documents & images to digital form for storage & access by computer. • Not-often-used documents can be stored on a jukebox (optical disk system w/ multiple disks). • Alternative to DIS: Intranets • Workers publish documents to web-based form directly

8. Knowledge Work Systems • “Information systems that aid knowledge workers in the creation and integration of new knowledge in the organization.” • 3 key roles for knowledge workers: • Keeping the organization up to date with knowledge in external world • Serving as internal consultants in their areas of expertise • Acting as change agents to evaluate, initialize, & promote change.

9. Requirements for KWS • Specialized tools needed for particular task • User-friendly interface • Access to external databases • Examples of KWS: • CAD • Virtual reality systems, VRML systems • Investment workstations

10. CAD: Computer-Aided Design • Automates creation & modification of designs by using computers.

11. Virtual Reality, VRML Systems • Have visualization, rendering, and simulation capabilities beyond conventional CAD. • VRML: Virtual Reality Markup Language • Virtual reality designed for the Web

12. Group Collaboration Systems • Groupware • “Software that provides functions and services that support the collaborative activities of workgroups.” • Examples: • publishing: tracking multiple users’ edits to a document • replication: keeping identical data on multiple PCs • discussion tracking • security: preventing unauthorized access to data

13. Group Collaboration Systems • Intranet knowledge environments • An alternative to traditional groupware • Cheaper, easier to maintain for email, discussion groups, multimedia Web documents • Which to choose? • Groupware: projects requiring extensive coordination & management, editing on the fly, tracking revisions, greater security • Intranet: simple tasks like sharing documents, email, publishing documents, etc.

14. Artificial Intelligence • “The effort to develop computer-based systems that behave like humans.” (inc. hardware & software) • AI systems are based on human expertise, knowledge, and selected reasoning patterns, but do not exhibit human intelligence. • Why would businesses want this science-fiction idea? • to preserve expertise that may be lost • to store information in an active form • to create a mechanism invulnerable to human feelings • to eliminate boring & unsatisfying jobs • to enhance an organization’s knowledge base by providing interactivity.

15. Expert Systems • “Knowledge-intensive computer program that captures the expertise of a human in limited domains of knowledge.” • Narrow & brittle • Perform tasks that a professional could do in a few minutes or hours.

16. Expert Systems: Parts • Knowledge base: model of human knowledge used by ES. • Rule base: the part of the knowledge base that is contained in IF/THEN structures. • Knowledge frames: organizes knowledge into chunks of interrelated characteristics. • AI shell: programming environment of an ES. • Knowledge engineer: a systems analyst expert in converting human knowledge into an ES.

17. Case-based reasoning • “Artificial intelligence technology that represents knowledge as a database of cases and solutions.” • Each new case is compared with existing cases to suggest a solution. Each new case is added to the database of cases upon arriving at a satisfactory solution.

18. Other Intelligent Techniques • Neural networks • attempt to emulate the processing patterns of the biological brain; have a general capacity to learn. • Fuzzy logic • rule-based AI that tolerates imprecision using membership functions. • Genetic algorithms • Solution evolves through mutation, adaptation, and natural selection out of possible answers.

19. Intelligent agents • “Software that uses a built-in or learned knowledge base to carry out specific, repetitive, and predictible tasks for the user, business process, or other software application.” • Example uses: • wizards in MS Office • delete junk email • find cheapest airfare • search auctions for lowest price on item • Bots – http://www.mySimon.com

20. Enhancing Management Decision-Making • Decision Support Systems (DSS) • “Computer systems for management that combines data, analytical tools, and models to support semi-structured and unstructured decision-making. • MIS are predefined management reports, etc., not unstructured.

21. Two types of DSS • Model-driven DSS • “Primarily stand-alone system that uses a model to perform “what-if” analysis.” • Data-driven DSS • “A system that allows users to extract & analyze information in large databases.”

22. Data-driven DSS: Datamining • Associations: things linked to a single event. • Sequences: events linked over time. • Classification: patterns that describe a group, inferring a set of rules. • Clustering: like classification, but no defined group yet exists. • Forecasting: using a series of values to forecast what other values may be.

23. Parts of a DSS • Database: all the data • historical and/or current from various applications. • Software system • Software tools used for analysis. • Examples inc. web-based DSS

24. Examples of DSS • American Airlines: price & route selection • Frito-Lay: price, advertising, & promotion mix • Texas Oil & Gas: evaluation of drilling sites • General Accident Insurance: fraud detection

25. Group DSS • “An interactive computer-based system that facilitates solutions to unstructured problems by decision-makers working as a group.” • Parts: • Hardware: conference facility itself, PCs, overheads, etc. • Software tools: electronic questionnaires, brainstorming tools, voting tools, etc. • People

26. Executive Support Systems (ESS) • “Information systems for strategic-level unstructured decision-making in an organization through advanced graphics & communications.” • Drilling down: ability to move from summary data to lower and lower levels of detail.

27. Benefits of ESS • Easy to use; little training needed. • Ability to analyze, compare, and highlight trends. • Enhance quality of decision-making because of drill-down capability