Decision Support and Expert Systems

1. Decision Support and Expert Systems Chapter 10 – Oz (5th ed)

2. Decision Making in Business • Organization’s success depends on quality of managers’ decisions • When decisions involve large amounts of data and complex processing, a DSS is a valuable tool • When decision making involves many uncertainties and/or lots of alternatives a DSS is needed

3. Simon’s Stages of Decision Making • Intelligence - the individual collects information to identify problems occurring • Design - the individual conceives of possible alternative solutions to the problem • Choice - the individual selects among the various solution alternatives • Implementation - the individual puts the decision into effect and reports on the progressof the solution

4. The Decision Making Process Is Not Linear Intelligence Is there a problem? Design What are the alternatives? Choice Which should you choose? Implementation Is the choice working?

5. Typical Activities in the Stages of Decision-Making

6. Figure 12.2 Business problems vary from structured to unstructured. Many fall between the two extremes and are considered semistructured. Structured and Unstructured Problems

7. Types of Decisions • Structured decisions are repetitive, routine, and involve a definite procedure for handling • Unstructured decisions are nonroutine decisions in which the decision maker must provide judgment, evaluation, and insights; there is no agreed-upon procedure for making the decision • Semistructured decisions are ones where only part of the problem has a clear-cut answer provided by an acceptable procedure

8. Example of a Structured and Semistructured Problem • Structured problem: How much will I earn after two years if I invest $100,000 in municipal bonds that pay 4 percent per annum tax free? • Semistructured problem: If I invest $100,000 in stock XYZ and sell the stock in two years, how much money will I make? • How are these problems different?

9. Examples of Structured and Semistructured Problems

10. A Definition of a DSS • A DSS is a computer system that combines data, sophisticated analytical models, and user-friendly software to support semi-structured and unstructured decision making. • Examples • Some DSS are very sophisticated and built by experts to improve firm performance (e.g., in trucking, models are developed to minimize total mileage and maximize truck loads while maintaining satisfactory delivery times) • Other DSS are built for individual managers to assist in daily decision making tasks (e.g., Mrs. Fields Cookies provides managers with a DSS that assists in decisions related to which cookies to make, how many to make based on prior sales)

11. Characteristics of a DSS • DSS offer users flexibility, adaptability, and a quick response (usually interactive) • DSS allow users to initiate and control the input and output • DSS operate with little or no assistance from professional programmers (e.g., personal and CDSS) • DSS provide support for decisions and problems whose solutions cannot be specified in advance • DSS use sophisticated analysis and modeling tools

12. How a DSS Can Improve Managerial Decision Making • In the intelligence phase • produce more timely data • increase the use of quantitative data • make more data available • In the design phase • generate more alternatives • generate more accurate alternatives • In the choice phase • make faster decisions • sometimes rank the choices

13. Components of a DSS • Data management module • consists of current or historical data and possibly some external data; data warehouse • Capabilities to manipulate the data • Model management module • collection of mathematical models (statistical models, linear programming, forecasting, sensitivity analysis models) available for the user • May also include OLAP or datamining tools • Dialog management module • Interface between user and other modules • Displays the analysis of results

14. Typical Features of Commercial DSS • Easy to use graphical user interface (Windows like) • Drill down capacity • On-demand financial analysis (ratios or indicators) • Access to external (outside the firm) databases • Statistical analysis tools • Tools to navigate in a database or data warehouse • Ability to perform ad hoc queries or what-if analysis • Ability to solve diverse business problems

15. Web Sites With DSS Products • Examples of DSS software http://cdss.state.co.us/ http://www.vanguardsw.com DecisionScript enables you to build Web-based DSS or CDSS DecisionPro can be downloaded for free 15-day trial Examples of EIS • http://visualmining.com • Look at dashboards and specific examples • http://www.meditech.com/productbriefs/pages/ProductBriefsCSESS.htm • Drill down, customized views, individualized reporting

16. Types of DSS (one way of classifying) • Model-driven DSS are primarily standalone systems that use some type of quantitative model to perform “what-if” or other types of analysis. • Data-driven DSS are systems that analyze large pools of data that are (usually) stored in a data warehouse; these systems permit managers to extract useful relationships that exist in the data (datamining). • Web-based DSS exist for both types (customer decision support systems; Vanguard;, Rainbird irrigation systems), Home Depot (deck projects)

17. Other Types of DSS • Geographic Information Systems (GIS) • Customer DSS (CDSS)

18. Geographic Information Systems (GIS) • A GIS is a DSS for decision aid for map-related decisions • Typical GIS contains • Database of quantitative and qualitative data • Database of maps • Program to display information on maps • Applications of GIS • Identifying the best site to locate a branch office • Targeting pockets of potential customers • Repositioning promotions and advertising • Tracking the spread of disease or crime

19. Web Sites for GIS • HUD environmental maps http://198.102.62.140/emaps/SearchFrame.asp • A major GIS vendor • http://maps.esri.com • An example of how a state can use a GIS • http://www.state.ma.us/mgis/muniapps.htm • An example of how Charlotte, NC uses a GIS • http://meckcama.co.mecklenburg.nc.us/relookup// • http://gischamber.co.mecklenburg.nc.us/website/chamber/Default.aspx • An example from San Francisco, CA • http://www.sfgov.org/site/gis_index.asp • Use APN #8719003 in SFprospector; demographic and business report for Mission Bay South location • An example from York County, SC • http://www.yorkcountygov.com

20. Customer DSS (CDSS) • A CDSS is a special type of DSS designed to support the buying decisions of an existing or potential customer. Most current CDSS are Web based • Support exists for both the individual consumer (B2C) and businesses (B2B) • Complexity of products and sophistication of the buyer often determine the nature of a CDSS

21. Examples of CDSS • BusinessWeek (www.businessweek.com/bschools) • PriceGrabber ( www.pricegrabber.com) • BankRate (http://www.bankrate.com/) • HomeDepot (http://www.homedepot.com) • Design tools and calculators for various projects • Automobile tires (http://www.tirerack.com) • Assistance for choosing tires for an automobile • Vanguard (Vanguard - Investing for retirement - Determine how much to save#early#early) • Retirement planning tool

22. Manager and Consumer Decision Making

23. The Electronic Spreadsheet: A DSS Tool • Most widely used tool for decision support because it is widely accessible to both experienced and inexperienced users • Features of spreadsheets that support DSS construction • Preprogrammed functions enable the use of many mathematical models • Built in IF-THEN function • Ability to use Visual Basic for Applications • Charts, pivot tables, what-if tables, scenario management

24. Ethical and Societal IssuesDecisions by Machines • To what extent should businesses use computer-based decisions that can affect individuals. • Mortgage companies, credit card companies, employers, banks, etc. • Distinctions between US and European approaches • Pros for automated decisions – efficiency (cost, time, speed) • Cons – injustices due to errors, awareness, and finality of decision

25. Model Types • A model is an abstraction of an object or activity (entity) • Model types • Physical models like a scale model of a building • Narrative models provide spoken or written descriptions • Graphic models that use lines, symbols and shapes (ER diagram) • Mathematical models employ equations and(or) inequalities

26. Mathematical Models • A system of mathematical expressions usually equations that describe relationships between variables in order to better understand or describe a real world situation or process. • Mathematical models usually contain input and output variables. Input variables are variables that are systematically varied (plugged into the equations). The results from the equations are the output variables. • Types of models • Dynamic versus static • Stochastic (probabilistic) versus deterministic • Linear versus nonlinear

27. Accounting breakeven analysis tax computations depreciation methods Finance cash flow return on investment after-tax yield Marketing product demand forecast pricing strategies Sales performance Production product-mix inventory level (EOQ) quality control production schedule Sample Models by Functional Area

28. Uses of Models • Description • Understanding • Prediction • Simulation • Optimization • Models typically do more than one of the above