1. Decision Support Systems Management Information Systems BUS 391 Barry Floyd

2. Agenda Excel Examples Definition Fundamentals Conclusion

3. Tax Computation Given certain assumptions, earnings, and savings goals, how much should John and Sue pay in estimated quarterly taxes?

4. Tax Computation Save 5% of total income in a tax deductible retirement account, up to a maximum of $3,000 Entitled to personal exemption of $3,100 each Standard deduction for joint tax filers is $8,000 Tax brackets 15% for up to $48,000 and 26% for $48,001 to $115,000 How much estimated taxes should they pay each quarter?

5. Parameters

6. Input area

7. Tax Computation

8. Breakeven Analysis Determine Total Revenue Fixed Cost Total Variable Cost Total Cost Profit

9. Known Parameters

10. Input

11. Results

12. What is a DSS? An interactive information system that provides information, models, and data manipulation tools to help make decisions in semi-structured and unstructured situations where no one know exactly how the decision should be made.

13. Steps involved in Decision Modeling Formulation Defining the problem Developing a model Acquiring Input data Solution Developing a solution Testing the solution Interpretation Analyzing the results and sensitivity analysis Implementing the results

14. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Develop a clear, concise statement of the problem. Go beyond symptoms, look for cause! Find measurable objectives.

15. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Develop a model … for decisions modeling, this is a mathematical model. Decision variable is controllable, a parameter is an inherent measurable quantity.

16. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Get data from reports or interviews or sampling, etc. (e.g., time to manufacture a widget).

17. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Manipulate model to arrive at the best (or optimal) solution to the problem.

18. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Test completely. Use known data, comparison data, etc.

19. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Determine implications of solution. What happens if results are implemented? How sensitive is the solution to fluctuations?

20. Steps involved in Decision Modeling Formulation –Defining the problem –Developing a model –Acquiring Input data Solution –Developing a solution –Testing the solution Interpretation –Analyzing the results and sensitivity analysis –Implementing the results Can be the most difficult part …

21. Different flavors of DSS Simulation and optimization OLAP and Data Mining Expert Systems Neural Networks Fuzzy Logic Case-based Reasoning Intelligent Agents

22. Simulation and optimization Simulation – calculates outcomes based on some abstraction (typically mathematical) of the situation Optimization – calculates the ‘best’ answer given certain sets of constraints (e.g., which set of fixed and variable costs given a range of potential sales would provide the most profit).

23. OLAP and Data Mining OLAP – Online analytical processing Explores large volumes of transaction data Data Mining Explores large volumes of data looking for patterns that help managers understand critical relationships  Eg if someone buys cake mix, do they also buy frosting?  What drives paint sales? Not new home purchases, but sales of existing homes.

24. Expert Systems Builds on ‘knowledge’ typically extracted from an expert (e.g., a medical specialist on cancer) Knowledge must be ‘captured’ and represented within the system  Typically done with If-Then rules Data about particular case Inference engine applies rules to data to derive an outcome

25. Neural Networks Statistical method for finding and representing patterns in data Neural represents the way researchers believe the brain works A neural network is an information system that recognizes objects or patterns based on examples that have been used to train it.

26. Fuzzy Logic Fuzzy logic is a form of reasoning that makes it possible to combine imprecise conditions stated in a form similar to the types of descriptive categories people use. Don’t use either/or logic, allow categories to be somewhat vague and potentially overlapping: Very profitable, somewhat profitable, slightly profitable categories. Use multiple rules and build a system that combines the rules in a meaningful manner.

27. Case Based Reasoning A DSS method based on the idea of finding past cases most similar to the current situation in which a decision must be made. Must maintain a Database of cases and a means of searching the cases to match the problem at hand. Must have a means of ‘categorizing’ cases and limiting structure to a manageable set.

28. Intelligent Agents An autonomous, goal-directed computerized process that can be launched into a computer system/network to do background work Shopbots, email agents, news agents.  Shopbot – find best price for X  Email – scan email messages as they arrive and determine if user should be interrupted  News Agent – scan news sources to put together a customized newspaper.

29. Conclusion DSS is decided different than TPS and MIS We’ll employ Excel as our modeling/DSS environment

30. Data Table and Scenario Management Barry Floyd

31. Data Tables and Scenario Management Data Table Displays results of multiple what-if analyses  One variable Data Table Specify one input cell and any number of result cells  Two variable Data Table Specify two input cells and one result cell Scenario Allows you to define a set of input cells and result cells and to then view the results in a systematic fashion

32. One Variable Data Table One or more result cells One input cell

33. One Variable Data Table Steps Create row of output formulas Define column of input values Highlight formulas and input values Select data, table Indicate the 'input' cell - note we have a column of values and so choose column

34. Two Variable Tables Variable 1 values in first row Variable 2 values in first Column Result values displayed in table

35. Two variable tables Steps in creating a two variable data table Create column of variable costs Create row of number of units Place "RESULT CELL" reference in the upper left hand corner Format cell to show a label rather than the formula Add a label Highlight table area Select data, select table Assign B4 to row input cell, B9 to column input cell Format table to currency

36. Scenario Manager Used to perform ‘what-if’ analyses given more than two variables Identify key variables whose values are important for characterizing the ‘scene’ High quality  Fixed costs are higher, variable costs are higher, Selling price is higher Low quality  Fixed costs lower, variable costs are medium, selling price is low Mid quality  Fixed costs mid, variable costs are medium, selling price is medium

37. Values HighMediumLow Selling Price $50$30$10 Fixed Costs $5000$2500$1000 Variable Costs $20$10$3

38. Steps Select tools, scenarios Create a scenario Add values to attributes Repeat for each scenario Click on a scenario, click show Or click on summary

39. Output results

40. Summary Use the power of excel to analyze data in an interactive format. Do ‘what-if’ analyses on a one variable, two variable and multi-variable format. Very powerful, relatively easy to use.