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Decision support systems

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Aneel Ahmed

Decision support systems (DSS) are computer applications that analyze business data and present it in a way to help users make business decisions more easily. A DSS has three main components - a database or knowledge base, a model representing the decision context and user criteria, and a user interface. It allows managers to perform what-if analysis, sensitivity analysis, goal-seeking analysis, and optimization analysis to evaluate different decisions and scenarios. The goal of a DSS is to improve decision making by providing a better understanding of the business and allowing more alternatives to be considered more quickly and effectively.

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DECISION SUPPORT SYSTEMS
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.
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
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
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
INFORMATION REQUIREMENTS BY MANAGEMENT LEVEL Strategic Management Tactical Management Operational Management
TYPES OF DECISIONS The decision fall into one of the following categories: Structured Decisions Unstructured Semi-Structured
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
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
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.
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
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.
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
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.
OPTIMIZATION MODELS Optimization models often using Linear Programming (LP) determine the proper mix of products within a given market to maximize profit.
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.
CAPABILITIES OF DSS Using a DSS involves 4 basic types of analytical modeling activities: What-if analysis Sensitivity analysis Goal-seeking analysis Optimization analysis
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?
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.
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
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?
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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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