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Decision support tools

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  1. Decision support tools Lecture 13: Managing Decision Support Tools

  2. Module structure • Management Decision-Making • OLAP & Data Mining • Group Support Systems • Executive Support Systems • Model-based Decision Support Systems • Intelligent Systems • Expert Systems • Managing Decision Support Tools

  3. What needs to be managed? • Selecting appropriate tools • What decisions need support? • Cost justification • System implementation and maintenance • Information requirements • Knowledge capture • Updating models and knowledge • Catering for changing business needs • And also – People! • Participation, trust, accountability, frontline support

  4. Remember this slide? A key to good decision making is to explore and compare many relevant alternatives. The more alternatives that exist, the more computer-assisted searching and comparison is needed. Typically, decisions must be made under time pressure. Frequently it is not possible to manually process the needed information fast enough to be effective. Decision makers can be in different locations and so is the information. Bringing them all together quickly and inexpensively may be a difficult task. It is often necessary to conduct sophisticated mathematical analysis in order to make a good decision. Such analysis requires the use of modeling.

  5. Selecting decision support tools P R O D U C T I O N F I N A N C E M A R K E T I NG

  6. Factors to consider • Types of decision that are made • Structured / unstructured • Type of support that is needed • e.g. strategic, group • Existing IT infrastructure • Integrated internal data sources • External communications • Availability of models and knowledge

  7. Cost justification • May be expensive to implement • Value of benefit is difficult to quantify • Time saved on information gathering • Better evaluation of alternatives • Uncertain value of outcome (better decisions?) • Time delay until results are visible • Long term investment • Maintenance costs

  8. DST implementation • At the organisational level • Access to data • Availability of models • Knowledge capture • Modifying business processes • User training • Maintenance and updating • Personal DST applications • End-user development issues of quality and control • Distraction from core business responsibilities

  9. People issues • Reliance on technology • Suspension of personal judgement • Failure of technology • Consequences of an incorrect decision • Accountability • Identification and rewarding of knowledge sources • Expert systems • Impact on employment • Change management • Integrating decision-making within business processes • Frontline decision support

  10. See you again on 14 April Overview of Prac 3 (case study analysis)