1. Think of some of the leading indicators that could be used as a major input to causal forecasts in the economy. Discuss their use.

1. Think of some of the leading indicators that could be used as a major input to causal forecasts in the economy. Discuss their use. Oil and gasoline futures. Most of the commerce in the United States depends upon petroleum. Whether in shipping costs or the use of petroleum distillates the price of oil affects us. New housing starts – if people have the money they will want to improve their standard of living. Interest rates – what the Federal Reserve charges other banks for loans affects the consumer – housing loans, credit card rates and returns on money market and savings accounts. Durable goods – washers, dryers, refrigerators and other items that last more than three years. As people have more money to spend they will purchase these long-term use items. There will be others mentioned – this is just a few.

2. Which type of forecasts would most likely be used for Sales and Operations Planning (S&OP), and why are they the most appropriate? Quantitative and qualitative forecasts are the general types of forecasting used. The quantitative methods that seem to be the most appropriate are the time series and causal. These forecasts take into account “hard” data, giving a much more reliable model to predict. All forecasting methods contain errors, quantitative data tends to be more reliable.

3. What value does it bring to an operation if a forecasting method is used that only forecasts for families of products? Forecasts that look only at a type of product tend to be less accurate than a generalized forecast (convertibles vs. all cars) that looks at a family of products. To get a good look at particular market, looking at the family of products is more accurate.

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4. How should a company include information for their forecast that indicates the economy is headed for a recession? How, if at all, should that information impact time-series forecasting information? To include information that indicates a recession, I would use a seasonal or cyclical adjustment to my forecast. If hard data is available from the last recession, incorporate that data into the forecasting model. Opinion here may vary, using prime interest rates as one mechanism to account for inflation.