DSS defined:

1. DSS defined: • It is a system which provides tools to managers to assist them in solving semi structured problem in their own personalized way. DSS is not intended to make decisions for managers rather to provide mangers with the set of capabilities that enable them to generate information that they require to make decisions. • Note: DSS support human decision making process rather than a means to replace it. The DSS which replace the human decision making process completely rather than to support it is known as Programmed Decision System.

2. Difference between Structured and Unstructured Decisions • Structure decisions are made easily from a given set of decisions • Issue reminder for payment • Semi/Unstructured Decision • These are decisions for which information obtained from comp system is only portion of tot knowledge required to make decisions.

3. Properties of DSS: • Support for semi structured and unstructured decision making • Flexibility in specifying output requirements. • Fast response • Ease of use • Developed for non computer professionals. • Tactical and strategic management focus • Focus managerial effectiveness rather efficiency.

4. Tasks performed by DSS: • Information retrieval • Data reconfiguration ( the process of displaying/presenting the data into forms other than the way it is logically represented in the computer system) • Data reconfigurations tasks are sort, exchange fields, join data and presentation graphics. • Computing activities • Data analysis

5. Facilities in DSS: • Query language • Statistical analysis • Graphics presentation • Model creation facility • Decision making data storage facility • Components of DSS: • DSS Hardware • DSS Software • DSS Data

6. DSS output/Information Generated by DSS: • Screen based Interactive inquiries and responses • The format for the information is adhoc and flexible • DSS Analytical modeling activities: • What if analysis (observing how changes to selected variables affect other variables) • Sensibility analysis (how repeated changes to a single variable affect other var) • Goal seeking analysis (making repeated changes to selected variable reach a target variable) • Optimization analysis (finding an optimum value for selected variable given certain constraints)

7. DSS functions performed by a spreadsheet: • Graphic and charts (Chart wizard) • Calculating activities (formula and Functions) • What if analysis (Goal seek) • Data analysis ( Pivot tables and charts) • Querying (data filtering ) • Scenario analysis • Building the models

8. EIS (ESS): • EIS is referred to as ESS (Executive Support System ) which is the used to meet the special informational needs of top level management. • EIS pools data from internal and external sources and manipulate it to produce information and makes information available to strategic mangers for making decisions on unstructured issues in an easy to use form. • In EIS some features of MIS and DSS are combined. The first goal of EIS is to provide strategic mangers with immediate and easy access to critical success factors. This is also known as the enterprise information system. • Users of EIS: Executive Managers

9. EIS Features • Lack of structure • High degree of uncertainty • Future Orientation • It capture the information from informal sources

10. EIS Capabilities • Strategic Planning support • External environment focus • Broad based computing facilities • Customization • Exceptional ease of learning

11. EIS Benefits: • EIS provides easy access to key internal and external information to the strategic mangers. • EIS provides summarized and strategically critical information drawn from MIS & DSS • EIS also use data from external sources information for the production of summarized and strategically critical information

12. Application of EIS: • 1. Provision of information about organizational performance. This information includes the actual, budgeted and forecasted figures for sales, production and profitability • 2. Provision of information for internal communication. It includes storage and retrieval of personal correspondence, minutes of meetings, financial reports. • 3. Provision of external environment information (information about political and economic environment)

13. Commercial Available EIS • Commander EIS ( Comshare Inc.) • Command Centre (Pilot Executive Software) • Executive Edge ( Execucom System Corp.) • Express EIS ( Information Resources Inc.)

14. EIS as a tool for strategic planning: • An EIS can be considered as a tool for strategic planning for the following reasons • 1. It supports all the major responsibilities and activities of senior executives and can also be considered means of tracking critical business needs for saving the organizational future. • 2. Most of company executives want to have EIS in order to • access information faster than at present • access a broader range of information at present • extract selected information in more focused way • display information in graphical form • 3. It will improve the performance of executives and reduce time wasted in information search activity

15. Critical Success Factors of EIS • A committed and informed sponsor • An operating sponsor • A clear link to business objective • The use of proper technology • Finding the data problems • Managing organizational resistance • Managing and system evolution

16. Expert System: • It is an information system (an application of AI) that captures and store the knowledge of human expert and imitate human reasoning and decision making process for those who have less expertise. • Artificial Intelligence: AI is development of computer based systems designed to behave as human. AI is application of human intelligence to computers. AI systems are based on human expertise, knowledge and reasoning patterns. AI has a variety of capabilities like speech recognition, logical reasoning and creative responses

17. AI applications: • Expert system • Neural network • Robotics • Natural languages • Vision system

18. ES Applications: • Diagnosis ( recognizing diseases based on symptoms) • Repair • Instruction ( providing individualized training in a specific field) • Interpretation ( analyzing data and determining its significance) • Prediction ( taking educated guesses at possible outcomes of observable situations) • Designing and planning • Monitoring and control • Legal advice • Tax advice • Forecasting

19. ES development languages: ES shell as ES builder, Prolog, LISP • Advantages of ES: • AI and expertise is permanent, whereas human experts may leave the business. • AI is easily copied. • AI is consistent, whereas human experts and decision makers not be. • AI can be documented. The reasoning behind an expert recommendation produced by a computer will be recorded. Depending on the task the computer may be much faster than the human being.

20. Components of ES: • knowledge base • Inference rules • Working memory • Inference Engine • Knowledge acquisition program

21. KNOWLEDGE BASE KNOWGE ACQ PROG EXPLN PRG INFER ENGIN WORKING MEMORY

22. 1. Knowledge base: It is the combined subject knowledge (facts) and experience of human exp (rules). • 2. Inference rules: These are a set of logical judgments applied to the knowledge base each time user describes a situation to the expert system. • 3. Working memory: it store facts and rules being used by the current enquiry and information given to it by the user. • 4. Inference engine: software that executes reasoning • 5. Knowledge acquisition Program: it enables the expert system to incorporate new knowledge and rules

23. Disadvantages of ES: • Systems are expensive. • The technology is still relatively new. Systems will probably need extensive testing and debugging. • People are naturally more creative. • Systems have a very narrow focus.