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MIS Development

MIS Development. BBA-IT (Hons) 6 th Semester ( Decision Support Systems & Knowledge Management Systems ) By: Farhan Mir. Structured and Unstructured Problems. MANAGERS, DECISION MAKING, AND INFORMATION SYSTEMS. Decision Support Systems. an information system

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MIS Development

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  1. MIS Development BBA-IT (Hons) 6th Semester (Decision Support Systems & Knowledge Management Systems) By: Farhan Mir

  2. Structured and Unstructured Problems

  3. MANAGERS, DECISION MAKING, AND INFORMATION SYSTEMS

  4. Decision Support Systems • an information system • purpose to provide information for making informed decisions • interactive (needed for experimenting and prospecting)

  5. Decision Support Systems (DSSs) • Decision support systems (DSSs) are computer-based information systems that combine models and data in an attempt to solve semistructured and some unstructured problems with extensive user involvement.

  6. Working Definition • A DSS is: • computer based • model driven • management oriented • addresses non-structured problem • adaptive to user’s insights • supportive for a decision

  7. DSSs (Continued) • DSSs can examine numerous alternatives very quickly. • DSSs can provide a systematic risk analysis. • DSSs can be integrated with communications systems and databases. • DSSs can be used to support group work. • DSSs can perform these functions at relatively low cost.

  8. Characteristics and Capabilities of DSSs • Sensitivity analysis is the study of the impact that changes in one (or more) parts of a model have on other parts. • What-if analysis is the study of the impact of a change in the assumptions (input data) on the proposed solution. • Goal-seeking analysis is the study that attempts to find the value of the inputs necessary to achieve a desired level of output.

  9. DSS Components Model Management Data Management Data Some times (KM) Dialog Management User (manager)

  10. Question Type What is Why What will be What if Which is best/good enough How answer is provided raw data analysis representative models solutions solution choice Fundamental Questions Answered By DSS

  11. DSS Decision support systems couple the intellectual resources of individuals with the capabilities of the computer to improve the quality of decisions. It is a computer-based support system for management decision makers who deal with semi-structured problems. — Keen and Scott-Morton, 1978

  12. DSS A DSS is: • Flexible; • Adaptive; • Interactive; • GUI-based; • Iterative; and • Employs modeling.

  13. DSS Components • Data Management Subsystem (DMS) • Model Management Subsystem (MMS) • User Interface Subsystem (UIS) • Knowledge-based Management Subsystem (KMS) • The User

  14. User Interface Subsystem (UIS) • Covers all aspects of communication between a user and the DSS • It is the interface to the user and consists of a GUI that is typically displayed via a browser • Includes factors that deal with ease of use, accessibility, and human-machine interactions (which incorporate such things as Cognitive Style, Decision Style, and Display Preferences) • To most users, the user interface is the system

  15. DSS Process

  16. Model Management Subsystem (MMS) • Model base – contains a model library which stores different classes of models based on criteria such as decision types, user types, etc. • Model base management system (MBMS) – software to help create models, data manipulation in models, update models, and create new routines in models • Modeling language – for model building, could be text-based or graphical • Model directory – contains catalog of models, and model definitions (a range of models from Economics to Statistics like forecasting models)

  17. Knowledge-Based Management Subsystem (KMS) • Is the intelligence component incorporated into every subsystem of a DSS – thus, leading to intelligent DSS • Expert system or other intelligent systems provide the required expertise • Provides expertise for solving some or many aspects of complex unstructured and semi-structured problems • Provides knowledge that can enhance the operations of each subsystem of a DSS • All advanced DSS have KMS

  18. Group Decision Support Systems • Group of managers could also use a DSS as well on a common task or issue • To facilitate this a GDSS (Group Decision Support System) application is provided to multiple users on various computer and on multiple networks • Is the requirement in the organization that believe in team-based working environment

  19. The User (i.e., manager or decision-maker) • Two major classes – managers (users or decision makers) and intermediaries • Managers – look for more user-friendly systems that can do more general analysis and aid in decision-making • Intermediaries – are specialist staff who are trained in detailed-oriented system and are willing to use more complex system. They act as an intermediary between the manager and DSS. Examples are: Staff assistant, Expert tool user, Business (system) analyst, and GSS facilitator

  20. Knowledge Management Systems (Overview)

  21. What is Knowledge? • Data – collection of unprocessed facts • Information – organized or meaningful data • Knowledge – information that is contextual, relevant, and actionable • Strong experiential and reflective elements • Good leverage and increasing returns • Dynamic • Evolves over time with experience • Knowledge is also known as Intellectual Capital • The primary difference between the terms information and knowledge is in the level of understanding of their underlying organizational data

  22. Two major types of Knowledge • Explicit knowledge • Deals with objective, rational, and technical knowledge • Examples: policies, goals, strategies, papers, reports • Structured knowledge that is easy to codify • Easily manipulated, shared, taught or learned • Tacit knowledge • Unstructured knowledge – in the domain of subjective, cognitive, and experiential learning • Highly personal, hard to formalize and document • Cumulative store of the experiences, mental maps, insights, expertise, know-how, trade secrets, skills set, understanding, etc. • Involves a lot of human interpretation

  23. What is Knowledge Management? • Knowledge management(KM) is managing the organization’s knowledge (both explicit and tacit) through the process of creating, structuring, disseminating and applying knowledge to enhance organizational performance and create value • KM requires a major transformation in organizational culture to create a desire to share • Structuring enables problem-solving, dynamic learning, strategic planning, decision-making • Leverage value of intellectual capital through reuse

  24. KM Objectives • Create knowledge repositories • Improve knowledge access • Enhance the knowledge environment • Manage knowledge as an asset

  25. Knowledge Management System (KMS) • Knowledge management system (KMS) provides systematic and active management of ideas, information, and knowledge residing within organization’s employees • Why KMS? • Availability and use of technologies to manage knowledge • Used with turnover, change, downsizing • Provide consistent levels of service

  26. KM Initiatives • Knowledge creation • Generating new ideas, routines, insights • Modes include socialization, externalization, internalization, combination • Knowledge sharing • Willing explanation to another directly or through an intermediary • Knowledge seeking or elicitation • Knowledge sourcing • Knowledge use -- Leverage knowledge

  27. KM 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

  28. Components of KMS • Technologies • Communication • Access knowledge • Communicates with others • Collaboration • Perform groupwork • Same place/different place • Storage and retrieval • Capture, storing, retrieval, and management of both explicit and tacit knowledge through collaborative systems

  29. . . . . . KMS Architecture User Interface (Software installed on each user’s PC) Knowledge-enabling applications (customized applications, Expert Systems User Knowledge Acquisition The Knowledge Base Data warehousing (data cleansing, data mining) Groupware (document exchange, collaboration) Legacy applications (e.g., payroll) Databases

  30. AI & Expert Systems • One of the key promises of Knowledge Systems is that these could provide Artificial Intelligence (computer providing advice on problems like human intelligence) • Expert System is the application software that utilizes the mechanism of human intelligence of reasoning and therefore could provide decision makers with advice they would receive from such human experts

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