1. Information Systems for Managerial Decision Support  Introduction  Information, Decisions, and Management  Decision Support Technologies  OLAP and DSS  DSS Applications in Corporate Functional Management  Practitioners of Management Science

2. Achieving Success with Analytics $ROI Raw Data Standard Reports Ad Hoc Reports and OLAP Descriptive Modeling Predictive Modeling Data Information Intelligence Optimization Modeling Decision Support What happened? What will happen? What is the best that could happen? Decision Guidance Why did it happen?

3. Where are we? 3 The Web Databases SQL Data HTML or XML Data Automated Data Acquisition using VBA Decision Modeling with Excel HTTP Request DataModels

4. Changes in the Analytical Landscape Analytical Modelers Management IT Ops Data Integrators Business Governance STAKEHOLDERS Now… Customer Service Retail Logistics Promotions OPERATIONS TARGET Customers Stockholders

7. Introduction u Management –A process by which organizational goals are achieved through the use of resources u Resources: Inputs u Goal Attainment: Output u Measuring Success: Productivity = Outputs / Inputs

8. Introduction cont. uManagement is decision making uThe manager is a decision maker uNow fast changing, complex environment uFactors affecting decision making oTechnology/Information/Computers oStructural Complexity/Competition oInternational Markets/Political Stability oConsumerism/Changes, Fluctuations

9. Information, Decisions, and Management u Information oType of information required is directly related to the level of management and the amount of structure in the decision situation u Levels of managerial decision-making oStrategic Management oTactical Management oOperational Management

10. Strategic Management u Monitor the strategic performance of the organization and its overall direction in the political, economic, and competitive business environment u Unstructured Decisions oNot possible to specify in advance most of the decision procedures to follow oDecision maker must provide judgement, evaluation and insights to a novel, important and nonroutine-type decision u Require more summarized, ad hoc, unscheduled reports, forecasts, and external intelligence to support their more unstructured planning and policy-making responsibilities

11. Tactical Management u Allocate resources and monitor the performance of their organizational subunits, including departments, divisions, process teams, and other workgroups u Semistructured Decisions oSome decision procedures can be prespecified, but not enough to lead to a definite recommended decision oOnly part of the decision has a clear-cut answer provided by an accepted procedure u Require information from both the operational level and the strategic level to support their semistructured decision making responsibilities

12. Operational Management u Direct the use of resources and the performance of tasks according to procedures and established budgets and schedules u Structured Decisions oThe procedures to follow when a decision is needed can be specified in advance oInvolves a repetitive and routine-type decision where there is a definite procedure to follow u Require more prespecified internal reports emphasizing detailed current and historical data comparisons that support day-to-day operations

13. Decision Support Technologies u Management Information Systems (MIS) u Decision Support Systems (DSS) u Enterprise (Executive) Information Systems (EIS) u Enterprise Resource Planning (ERP) and Supply- Chain Management (SCM) u Knowledge Management Systems u Expert Systems (ES) u Artificial Neural Networks (ANN)

14. OLAP u Online Analytical Processing (OLAP) oA capability of management, decision support, and executive information systems that enables managers and analysts to interactively examine and manipulate large amounts of detailed and consolidated data from many perspectives u Basic analytical operations include oConsolidation: aggregation of data oDrill-Down: display detail data oSlicing & Dicing: produce different views from database

15. Decision Support Systems u Computer-based information systems that provide interactive information support to managers during the decision-making process u DSS use: oAnalytical models oSpecialized databases oDecision makers’ own insights and judgements oInteractive, computer-based modeling processes to support the making of semistructured and unstructured decisions by individual managers oData mining  analysis of large pools of data to find patterns and rules that can be used to guide decision making and predict future behavior

16. Decision Support Systems u Using a DSS involves four basic types of modeling activities: oWhat-if Analysis  an end user makes changes to variables, or relationships among variables, and observes the resulting changes in the value of other variables oSensitivitiy Analysis  a special case of what-if analysis—the value of only one variable is changed repeatedly, and the resulting changes on other variables are observed. oGoal Seeking Analysis  sets a target value for a variable and then repeatedly changes other variables until the target value is achieved oOptimization Analysis  the goal is to find the optimum value for one or more target variables, given certain constraints

17. DSS Applications According to a recent survey, computer-based DSS are widely applied in both profit making and non-profit organizations. In corporate functional management fields, production and operations management contain the largest number of application articles, followed by management information systems, marketing, finance, strategic management and multifunctional areas. The following website list some of the important application examples from the survey. http://cstl-hcb.semo.edu/eom/ORINSIHT.HTM

18. Management Science The Problem Solving Process Identify Problem Formulate & Implement Model Analyze Model Test Results Implement Solution unsatisfactory results A field of study that uses computers, statistics, and mathematics to analyze and solve business problems Computer Model: A set of mathematical relationships and logical assumptions implemented in a computer as an abstract representation of a real-world object or phenomenon

19. A Generic Mathematical Model Y = f (X 1, X 2, …, X k ) Y = dependent variable (a bottom line performance measure) X i = independent variables (inputs having an impact on Y) f (. ) = function defining the relationship between the X i and Y Where:

20. Categories of Mathematical Models Prescriptiveknown,known or underLP, Networks, IP, well-defineddecision maker’sCPM, EOQ, NLP, controlGP, MOLP Predictiveunknown,known or underRegression Analysis, ill-defineddecision maker’sTime Series Analysis, control Discriminant Analysis Descriptiveknown,unknown orSimulation, PERT, well-defineduncertain Queueing, Inventory Models ModelIndependent OR/MS CategoryForm of f (. )Variables Techniques