Demand forecasting results in an estimate of future demand and gives an organization a basis for plann

 Demand forecasting results in an estimate of future demand and gives an organization a basis for planning and making sound business decisions. Since the future is unknown, it is expected that some errors between a forecast and actual demand will exist, so the goal of a good forecasting technique would be to minimize the difference between the forecast and the actual demand. Address the following requirements:

• Articulate the difference in short and long-term forecasts, forecasting techniques, and the benefits and challenges of each technique. 
• Create a forecast for a situation with which you are familiar (personal or professional) explaining the situation and why you chose the method of forecasting that you did.

Embed course material concepts, principles, and theories, which require supporting citations along with at least two scholarly, peer-reviewed references in supporting your answer. Keep in mind that these scholarly references can be found in the Saudi Digital Library by conducting an advanced search specific to scholarly references.You are required to reply to at least two peer discussion questions and post answers to this weekly discussion question and/or your instructor’s response to your posting. These post replies need to be substantial and constructive in nature. They should add to the content of the post and evaluate/analyze that post answer. Normal course dialogue doesn’t fulfill these two peer replies but is expected throughout the course. Answering all course questions is also required.
 

 Required: 

• Chapter 3 in Operations Management
• Chapter 3 PowerPoint slides – Operations Management Module 3 Chapter 3 PowerPoint slides – Alternative Formats
• Che-Jung CHANG, Guiping LI, Jianhong GUO, & Kun-Peng YU. (2020). Data-Driven Forecasting Model for Small Data Sets. Economic Computation & Economic Cybernetics Studies & Research, 54(4), 217–229. https://doi.org/10.24818/18423264/54.4.20.14
• Haresh Kumar Sharma, Kriti Kumari, & Samarjit Kar. (2020). A rough set approach for forecasting models. Decision Making: Applications in Management and Engineering, 3(1), 1–21. https://doi.org/10.31181/dmame2003001s
• Winkowski, C. (2019). Classification of forecasting methods in production engineering. Engineering Management in Production and Services. Volume 11: Issue 4.