SCMG201 Week 7 DQ & DQR

3/19/23, 7:43 AM W7: Forecasting and Demand Planning - SCMG201 I001 Winter 2023

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W7: Forecasting and Demand Planning

SCMG201 I001 Winter 2023 LE

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Week 7 Discussion: Forecasting and Demand Planning

CO8: Evaluate the impact of the forecasting processes and demand planning on a supply chain's effectiveness.

Discussion Prompt:

In this week's Discussion chose a discussion topic from the following list (lifted from Sanders, p. 157):

1. Identify a nontraditional business event, such as forecasting demand for T- shirts following the Super Bowl, or the amount of relief aid needed following an earthquake. What do you think would be the best way to forecast such an event—qualitative or quantitative—and why? What are the implications of forecast error on supply chain management?

2. Think of a product you have recently purchased. How many different forecasts do you think the retailer had to make in order to decide how much product to stock? What are the consequences for that particular retailer if they had over-forecast versus under-forecast?

3. Imagine that you are starting an online retail business. What type of forecasting model would you use to decide how many different products you will be selling? Would you use the same forecasting model after you have been in business five years? Why or why not?

3/19/23, 7:43 AM W7: Forecasting and Demand Planning - SCMG201 I001 Winter 2023

https://myclassroom.apus.edu/d2l/le/78650/discussions/topics/683843/View 2/4

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4. Identify an example where large errors would be extremely costly. Which forecast error metric would be best for this environment?

5. Identify the differences between the two methods of collaboration discussed in the chapter: CPFR and S & OP. How are they similar, and how are they different? Explain the differences in the organizational objectives they are trying to achieve.

Sanders, Nada R. Supply Chain Management, 2nd Edition. Wiley, 2017-09-18. VitalBook file.

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3 - WEEK 7 DORIAN WALKER posted Mar 18, 2023 4:02 PM Subscribe

Imagine that you are starting an online retail business. What type of forecasting model would you use to decide how many different products you will be selling? Would you use the same forecasting model after you have been in business for five years? Why or why not?

A new business needs help trying to forecast off ambition. Therefore, if I were to start a business, I would resort to Qualitative forecasting. If there was some quantitative data available from similar businesses or partners, then there could be a chance to put that data to use. However, it is dangerous to go that route as the data needs to provide an authentic look into your business. So, utilizing some method of both Qualitative and Quantitative would be adequate. Assuming no data to evaluate on use, it would be wise to place e, effort into the Qualitative models. Based on the business plan and internal information, or sublimation, paired with cost analysis, one could infer how much inventory to carry. Knowing the market based on business models and research will also assist.

3/19/23, 7:43 AM W7: Forecasting and Demand Planning - SCMG201 I001 Winter 2023

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Last post yesterday at 6:06 PM

by Karl Kinkead

After several years, patterns may exist, and more market research will be conducted. Peaks and declines in sales will become more evident, and data will emerge in some abundance. With the trends in place, the Delphi method could be used to aid in the requisition of opinions about the products sold, aiding in the qualitative view. A time series and causal model should be used with more extrapolated data. With actual data trends, the business uses the past to determine plausible outcomes for the future. Coupled with current affairs, the best approach is to consider all avenues and use a multitude of models to estimate future sales. Above all, it is essential to have some semblance of forecasting. Start with what you know and record and measure sales and trends of each cycle. Eventually, there will be essential data to start working with. I would also research software that can assist; the return on investment could be higher if

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#3 Damian Hoffman posted Mar 3, 2023 3:45 AM

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If i was starting an online retail business, I would probably go with a time series forecasting

model. To predict future sales, this model relies on historical sales data and other factors,

like seasonality and marketing campaigns. Another popular model that can capture trends,

seasonality, and other patterns in the data is the Autoregressive Integrated Moving

Average (ARIMA) model. There are also various types of other forecasting models such as

causal models, and judgmental models.

However, the best model for a business depends on factors such as the products they are

selling, the size of the business, and the available data. It may be best to consult with

experts in data science or business analytics to determine the best model for your needs.

After five years of operating the business, the decision to use the same forecasting model

or not depends on the changes in the product mix and market conditions. If the business

remains the same, the same model could still be appropriate. However, if a lot of changes

have happened, you might need to update the model or consider a new one. You could also

consider using more advanced forecasting techniques as more data is collected over time.

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