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Making Decisions Using Decision Support Systems


If we break down decision making to its core components, it is a process of selecting between two or more alternatives. We need a process to manage the evalation of each option, and the probability that it will resolve the dilemna of the decision. A Decision Support System [DSS] assists decision making based on the estimated values of alternatives.

Most decision support systems are support the solution of non-structured management problems for improved decision making, and are highly interactive, flexible, and adaptable.

As we automate more of our decision making, our business processes speed up, decision ROI increases and consistency increases across the business. This has a direct impact on productivity and profit. More importantly, this translates to better outcomes for our customers, clients and patients.

Decision support helps to filter out inaccurate experiential recall and biases around personal judgements. This is particularly important in medical and judicial decisions, where a wrong decision has life impacting consequences. In such circumstances, it is important to recognize that DSS is a decision SUPPORT system, not a decision MAKING system.

Doctors, Judges and Corporate Executives all suffer high stress levels around decision making, especially when issues are complex and the outcome of the decision has signfiicant consequences. Thus DSS is particular valuable in situations that have:

  • Time constraints on delivery
  • High Stakes
  • Complexity - numerous ambiguities
  • Expert involvement - who cling to their iintuitive decision making rather than structured approaches

Decision-making methodology is programmed into the DSS to replicate a real-world process around distinct scenarios. These scenarios are stored as a set of facts, rules and procedures.

Key DSS characteristics and capabilities include support for:

  • Semistructured and unstructured problems
  • Decision makers of all levels
  • Individuals and groups
  • Interdependent or sequential decisions
  • Intelligence, design, choice, and implementation
  • Multuple decision processes and styles
  • Adaptability and flexibility of scenarios
  • Interactive and easy to use
  • Positive ROI - benefits exceed cost
  • Complete control by decision-makers
  • Easy adaptability to support changing needs
  • Modeling and analysis

 

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