Decision support systems
- 2. WHAT IS DECISION MAKING? • A selection process, concerned with selecting the best type of alternative • The thought process of selecting a logical choice from the available options • The process by which managers respond to opportunities and threats • It leads to commitment. The commitment depends upon the nature of the decision whether short term or long term.
- 3. MANAGERS AND DECISION MAKING • It is very difficult for managers to make good decisions without valid, timely and relevant information: Number of alternatives to be considered is increasing Many decisions are made under time pressure
- 4. DECISION PROCESS • Decision makers go through a fairly systematic process: Act on it Review It Define the “Process or Problem” Develop Alternative Courses of Action Select The “Best” One
- 5. THE NATURE OF DECISIONS • Information systems can support decision-making levels. • These include the three levels of management activity. Strategic management Tactical management Operational management
- 6. INFORMATION REQUIREMENTS BY MANAGEMENT LEVEL Strategic Management Tactical Management Operational Management
- 7. TYPES OF DECISIONS • The decision fall into one of the following categories: Structured Decisions Unstructured Semi-Structured
- 8. STRUCTURED DECISIONS • Structured decisions are repetitive and routine problems for which standard solutions exist • Ex: finding an appropriate inventory level, finding an optimal investment strategy
- 9. UNSTRUCTURED DECISIONS • Unstructured decisions are non-routine and complex. • We cannot specify some procedures to make a decision • Ex: expanding the business, moving operations to foreign countries. • IS must provide a wide range of information products to support these types of decisions at all levels of the organization
- 10. SEMI-STRUCTURED DECISIONS • Semi-structured decisions fall between structured and unstructured decisions • It requires a combination of standard procedures and individual judgment. • Ex: annual evaluation of employees, trading bonds, setting marketing budgets for consumer products.
- 11. WHAT IS DSS? • A decision support system is a computer application that analyzes business data and presents it so that users can make business decisions more easily. • It is an informational application. • Typical information that a decision support application might gather and present would be: Comparative sales figures between one week and the next Projected revenue figures based on new product sales assumptions The consequences of different decision alternatives, given past experience in a context that is described
- 12. DSS ARCHITECTURE • Three fundamental components of a DSS architecture are: • the database (or knowledge base), • the model (i.e., the decision context and user criteria), and • the user interface The users themselves are also important components of the architecture.
- 13. TYPES OF MODELS • DSS software is a collection of software tools that are used for data analysis or a collection of mathematical and analytical models. • There can be 3 different types of modeling software for DSSs: Statistical models Optimization models Forecasting models
- 14. STATISTICAL MODELING • Statistical modeling software can be used to help establish relationships such as relating product sales to differences in age, income or other factors between communities. • Ex: SPSS.
- 15. OPTIMIZATION MODELS • Optimization models often using Linear Programming (LP) determine the proper mix of products within a given market to maximize profit.
- 16. FORECASTING MODELS • The user of this type of model might supply a range of historical data to project future conditions and sales that might result from those conditions. • Companies often use this software to predict the action of competitors.
- 17. CAPABILITIES OF DSS • Using a DSS involves 4 basic types of analytical modeling activities: What-if analysis Sensitivity analysis Goal-seeking analysis Optimization analysis
- 18. WHAT-IF ANALYSIS • What-If analysis is used to determine what some of the possible changes could be on a theoretical solution. • Observing how changes to selected variables affect the other variables. • E.g. What if we cut advertising by 10%?What would happen to sales?
- 19. SENSITIVITY ANALYSIS • Sensitivity analysis is the study of how different variables effect one and other, when change occurs. • Observing how repeated changes to a single variables affect other variables. • E.g: Let's cut advertising by $1000 repeatedly so we can see its relationship to sales.
- 20. GOAL-SEEKING ANALYSIS • Compiles all of the given data and determines what inputs are required to reach specific goals. • Making repeated changes to selected variables until a chosen variable reaches to a target value. • E.g. Let's try increase in advertising until sales reach to target
- 21. OPTIMIZATION ANALYSIS • To find the optimum value for one or more target variables, given certain constraints. • Finding an optimum value for selected variables, given certain constraints. • E.g. What's the best amount of advertising to have, our budget and choice of media?
- 22. CHARACTERISTICS OF DSS • Improved decision making through better understanding of the businesses • An increased number of decision alternatives examined • The ability to implement ad hoc analysis • Faster response • Improved communication • More effective teamwork • Better control • Time and costs savings
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