Read through the Case Study entitled “Highline Financial Services, Ltd.” in Chapter 3 of your textbook. Examine the historical trends this company has experienced for the three products (A, B, C) discussed over the 2 years shown.Address the following requirements:
Prepare demand forecasts for the next four quarters for all three products, describe the forecasting method you chose and explain why that forecasting method is best suited to the scenario.
Explain why you did, or did not, choose the same forecasting method for each product.
What are the benefits of using a formalized approach to forecasting these products?
Required to be four to five pages in length, which does not include the title page and reference pages, which are never a part of the content minimum requirements.
Support your submission with course material concepts, principles, and theories from the textbook and at least three scholarly, peer-reviewed journal articles.
Use APA style guidelines.
It is strongly encouraged that you submit all assignments into Turnitin prior to submitting them to your instructor for grading. If you are unsure how to submit an assignment into the Originality Check tool, review the Turnitin – Student Guide for step-by-step instructions.
Review Chapter 3 in Operations Management
Review Chapter 3 PowerPoint slides – Operations Management Module 4 Chapter 3 PowerPoint slides – Alternative Formats
Sharma, H. K., Kumari, K., & Kar, S. (2020). A rough set approach for forecasting models. Decision Making: Applications in Management and Engineering, 3(1), 1–21.
Delli Gatti, D., & Grazzini, J. (2020). Rising to the challenge: Bayesian estimation and forecasting techniques for macroeconomic Agent Based Models. Journal of Economic Behavior and Organization, 178, 875–902. https://doi.org/10.1016/j.jebo.2020.07.023
Bourdeau, M., Zhai, X. qiang, Nefzaoui, E., Guo, X., & Chatellier, P. (2019). Modeling and forecasting building energy consumption: A review of data-driven techniques. Sustainable Cities and Society, 48. https://doi.org/10.1016/j.scs.2019.101533
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