Forecasting and its Applications in Hospitality Management
Forecasting applications exist everywhere in hospitality management including budgeting, staffing and scheduling, inventory management, demand forecasting, and financial proformas, to name a few. There are numerous examples of bad forecasts resulting in significant monetary losses in firms. This course focuses on the state-of-the-art in forecasting techniques. Because the course covers a wide range of forecasting situations, participants will gain ideas on how to improve their forecasts by seeing techniques and approaches used in other areas. The course examines how to measure forecast accuracy, the cost of inaccurate forecasts, why forecasts are often inaccurate, and whether it is better to over- or under-forecast. The class will consider actions to respond to inaccurate forecasts and also examine the effectiveness of quantitative and judgmental methods of forecasting. This class is most appropriate for decision-makers with responsibility for forecasting. However, managers who use forecasts developed by others will also find significant value in the course. The course format includes lectures, hands-on use of forecasting software, and in-class discussions of readings, assignments, and personal experiences. Intermediary Excel® skills are a required for this course.
Course participants will come away with the knowledge and tools to help them develop better forecasts for their organizations and to avoid the bad forecasts that decrease profitability.
How should forecast accuracy be measured
What is the cost of inaccurate forecasts
Why are forecasts often inaccurate
What should be done when forecasts are inaccurate
What are judgmental forecasting methods so common
What are the requirements for good forecasting practice
What are blended forecasts and how can they improve forecast accuracy
What forecasting approaches work best for short-, medium-, and long-term forecasts
What are the state-of-the-art forecasting techniques
What are the participants’ key challenges in forecasting
What are the participants’ key forecasting successes