The Academy of Public administration under the President

The Academy of Public administration under the President of the Republic of Uzbekistan APPLICATION MODERN INFORMATION AND COMMUNICATION TECHNOLOGY IN DECISION MAKING IN PUBLIC ADMINISTRATION Bakoev Matyokub Chair of Decision making theory department

Managerial Decision Making A decision is defined as the choice of one among a number of alternatives The decision making process consists of three main stages: 1. Intelligence: Fact finding, problem and opportunity sensing, analysis, and exploration. 2. Design: Formulation of solutions, generation of alternatives, modeling and simulation. 3. Choice: Goal maximization, alternative selection , decision making, and implementation.

Need for decision-making support To be an effective top-level manager today, you need automated support. With change now the rule rather than the exception, more decisions must be made more quickly than ever before. The entire decision-making process, from problem recognition to policy implementation, has become so accelerated it's simply impossible to rely on human response alone. You need an automated system that will help you react and adapt to the constantly changing business environment you must relate to.

Role of a Decision Support System A DSS is intended for direct use by top managers to help them increase their effectiveness within their organizations. A DSS combines the human skills used in decision making with the power and capabilities of the computer to give you efficient management of large volumes of data, flexible reporting, analytical and modeling capabilities, and a variety of visual display alternatives.

Decision Support Systems (DSS) are a class of computerized information system that support decision-making activities. DSS are interactive computer-based systems and subsystems intended to help decision makers use communications technologies, data, documents, knowledge and/or models to complete decision process tasks. A decision support system may present information graphically and may include an expert system or artificial intelligence (AI). It may be aimed at business executives or some other group of knowledge workers

Component of decision support system Database management system (DBMS). It serves as a data bank for the DSS. It stores large quantities of data that are relevant to the class of problems for which the DSS has been designed and provides logical data structures with which the users interact. It should also be capable of informing the user of the types of data that are available and how to gain access to them. Model-base management system (MBMS). Its primary function is providing independence between specific models that are used in a DSS from the applications that use them. The purpose of an MBMS is to transform data from the DBMS into information that is useful in decision making. Dialog generation and management system (DGMS). The main product of an interaction with a DSS is insight. As their users are often managers who are not computertrained, DSSs need to be equipped with intuitive and easy-to-use interfaces. These interfaces aid in model An Output generator system (OGS). That provides the decision maker with easily interpretable results

Interaction among components of DSS

Types of decision support system Communication-driven Decision Support System: This supports more than one person working on a shared task. Data-driven Decision Support System: This emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data. Document-driven Decision Support System: This manages, retrieves, and manipulates unstructured information in a variety of electronic formats. Knowledge-driven Decision Support System: This provides specialized problem-solving expertise stored as facts, rules, procedures, or in similar structures. Model-driven Decision Support System: This emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model.

“Managerial Decision Making Models ”: Decision making under CERTAINTY Decision making under UNCERTAINTY Multicriteria Decision making under uncertainty • Optimistic approach • Conservative approach • Minimax Regret approach Optimization problems: • Production management • Marketing • Finance Network problems: • Transportation • Assignment • Production and Inventory Project Scheduling problems: • Time • Cost MDMM The Analytic Hierarchy Process: • Priority Ranking • Emlooyee Perfomance Evaluation Decision making under risk • Expected value approach • Risk minimization approach • High probability approach Decision making under conflict • Game theory • Multi player • Political decisions

Some computer software packages for decision making

Managerial Decision Support System -MDSS (in uzbek)

Models of MDSS Decision making under certainty Decision making under uncertainty Statistical methods of Decision making Multicriteria decision making

Decision making under uncertainty Ø Help Ø New problem Ø Examples

Interface of the model Decision methods Decision Summary decisions

Interface of notes for problems Statement of the problem Alternatives Note or comment States

Interface of decision tree Decision tree construction

CONCLUSION The role of information communication technology in decision making cannot be overemphasized. Effective decision making demands accurate, timely and relevant information. DSS provides accurate and timely information necessary to facilitate the decision-making process and enable the organizations planning, control, and operational functions to be carried out effectively. It is also used to generate the reports with the help of advanced technology having maximum characteristics of good information by which the decisions are to be taken related with the functionality of management decisions.

REFERENCE 1. Power, D. J. (2002). Decision support systems: concepts and resources for managers. Westport, Conn. , Quorum Books. 2. Marakas, G. M. (1999). Decision support systems in the twentyfirst century. Upper Saddle River, N. J. , Prentice Hall. 3. Marek J. Druzdzel and Roger R. Flynn (2002) Decision Support Systems

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