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Fundamental Information Systems Concepts and Principles

Fundamental Information Systems Concepts and Principles. Dr. Dwyer Fall 2012. Value of information. Does information have value? When is there a ‘market’ for information? (parties willing to pay) What are the critical qualities of information?. Information as a resource.

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Fundamental Information Systems Concepts and Principles

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  1. Fundamental Information Systems Concepts and Principles Dr. Dwyer Fall 2012

  2. Value of information • Does information have value? • When is there a ‘market’ for information? (parties willing to pay) • What are the critical qualities of information?

  3. Information as a resource • The success of an organization depends on its ability to collect and analyze relevant information to make strategic decisions to seize opportunities • The success of a professional depends on their ability to collect and analyze relevant data in order to recommend and implement strategic actions

  4. “Systems” perspective • Systems Theory - interaction between sub-systems (technology systems & organizational system/social system) • Derives from biological systems, where components interact with each other (predators v. prey) • Interacting components that affect each other • Dynamic (always changing) – non-deterministic

  5. Lee system interaction diagram

  6. Model of an IS

  7. Information Architecture • What technology (hardware/software) needs to be in place for this to work? • Response time? • Latency? • Down time?

  8. Technology innovation sppead up system evolution

  9. Information as a resource • Helps organizations make better decisions • The quality of the information is related to the quality of the decision • The ‘fit’ of the information is related to the quality of the decision

  10. Information quality • Relevance • Accuracy • Timeliness • Actionable • complexity

  11. Information <->Decisions • Nature of the problem • Identify possible solutions • Estimate the degree to which solution will solve the problem

  12. Thompson's Typology of Decision Processes • Where both preferences and cause/effect relations are clear, decision making is "computational". These decisions are often short term and information about the decision is fairly unambiguous. • Where outcome preferences are clear, but cause/effect relations are uncertain, Thompson suggest that "judgment" takes over and you make your best educated guess. These decisions are based on prior experience and are often qualitative in nature.

  13. Dec. Proc. Cont. • When the situation is reversed, and preferences are uncertain, then you rely on compromise between different groups. Political coalitions may be built which rely on negotiating and bargaining. • When neither preferences nor cause/effect relations are clear, then you rely on "inspirational" leadership. This is where the charismatic leader may step in and this type of decision often takes place in times of crisis.

  14. Daft & Lengel • “Why do organizations process information?” • in order to reduce uncertainty and equivocality. • Uncertainty is defined as “the difference between the amount of information required to perform the task and the amount of information already possessed by the organization.” • Equivocality is defined as ambiguity, or the existence of more than one possible interpretation or analysis of a situation.

  15. Information needs • Uncertainty is a simpler problem to solve, because the information does exist to ultimately answer any open questions. • Equivocality cannot be resolved by the collection of more information. Instead organizations can only work to reduce equivocality by pooling group opinion and expertise, and applying human judgment to make a decision. • Uncertainty and equivocality, drive the need for organizations to process information.

  16. IS analyst must • Understand information needs • Understand decision type and requirements

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