1. MBAA 607- Operations Analysis & Decision Support Systems Spring 2008 Tuesday 4:25-7:05 Dr. Linda Leon

2. Productivity = Output/Input where inputs include  labor  capital  materials  time  information  energy And output measures output produced, not necessarily sold

3. U. S Productivity Increases 1800-1973 productivity increased at average rate of 2.5% per year 1970s to mid-1980s productivity increased at only 1% to 1.5% per year due to quality problems Mid-1980s to 1995, the manufacturing sector increased its productivity rate by 2.5+% per year while the service sector lagged at 1- 1.5% per year 1995 to 2005 productivity rate increased by 5.6% per year as the result of decreasing labor input

4. Variables that Create Productivity Increases Labor Capital Management

5. Management Science A quantitative approach to decision making based on the scientific method of problem solving. Synonymous with operations research. Early roots in World War II; now flourishing in business and industry with the aid of computers.

6. Course Objectives To learn how to model operations management and decision-making problems using quantitative management science techniques To present various operations management and decision-making problems encountered in today’s business world

7. Quantitative Techniques Linear Programming Simulation Forecasting Decision Trees Project Management: PERT/ Critical Path Method (CPM)

8. Examples of Typical Operation Management Problems Resource Allocation Scheduling Demand Forecasting Revenue Management Planning Models Supply Chain Management Waiting Line Analysis Inventory Management Transportation & Location Analysis

9. Increasing Expected Productivity Assessing & Managing Operational Risk Forecasting & Planning Models Operations Analysis & DSS Tools Math Programming Simulation Models Decision Trees for Evaluating Alternatives Project Management

10. Course Objectives - Continued To develop analytical & computer modeling skills necessary to implement and analyze decision problems To learn how to integrate information provided by the use of quantitative techniques and computer models into the decision-making process and be aware of the limitations of the quantitative technique used