A(n) ____ network is a form of artificial intelligence in which a computer is programmed to mimic ...

Answer to #1

B

Answer to #2

The S&OP Benchmarking Consortium in the Center for Supply Chain Research adopted a five-step process in arriving at this consensus forecast. Step 1 (Run sales forecast reports) requires the development of a statistical forecast of future sales. This would be done using one or more forecasting techniques. Step 2 (Demand planning phase) requires the sales and/or marketing departments to review the forecast and make adjustments based on promotions of existing products, the introductions of new products, or the elimination of products. This revised forecast is usually stated in terms of both units and dollars since operations are concerned with units and finance is concerned with dollars. Step 3 (Supply planning phase) requires operations (manufacturing, warehousing, and transportation) to analyze the sales forecast to determine if existing capacity is adequate to handle the forecasted volumes. This requires analyzing not only the total volumes but also the timing of those volumes. Step 4 (Pre-S&OP meeting) asks individuals from sales, marketing, operations, and finance to attend a meeting that reviews the initial forecast and any capacity issues that might have emerged during Step 3 . Initial attempts will be made during this meeting to solve capacity issues by attempting to balance supply and demand. Alternative scenarios are usually developed to present at the executive S&OP meeting (Step 5) for consideration. These alternatives would identify potential lost sales and increased costs associated with balancing supply and demand. The sales forecast is also converted to dollars to see if the demand/supply plan meets the financial plan of the organization. Step 5 (Executive S&OP meeting) is where final decisions are made regarding sales forecasts and capacity issues. This is where the top executives from the various functional areas agree to the forecast and convert it into the operating plan for the organization.

Answer to #3

A

Answer to #4

The first type of forecast error measure is called the cumulative sum of forecast errors (CFE). It calculates the total forecast error for a set of data, taking into consideration both negative and positive errors. This is also referred to as bias. This gives an overall measure of forecast error. However, taking into consideration both negative and positive errors, this method can produce an overall low error total although individual period forecasts can either be much higher or much lower than actual demand.

The second measure of forecast error is mean squared error (MSE), which squares each period error so the negative and positive errors do not cancel each other out. MSE also provides a good indication of the average error per period over a set of demand data.

The third type is Mean Absolute Deviation (MAD) and is closely related to MSE. By taking the absolute value of each error, the negative and positive signs are removed and a good indication of average error per period is calculated. This measure is popular because it is easy to understand and provides a good indication of the accuracy of the forecast.

The final measure of forecast error is mean absolute percent error (MAPE), and it relates the forecast error to the level of demand so different types of forecasts can be compared.

Answer to #5

D

Answer to #6

Many organizations are faced with seasons that repeat themselves during a particular period. These seasons might be by time of day (for example, demand for hamburgers at a fast-food outlet), by day of the week (for example, the demand for gasoline), by week, by the month, or by some combination of these. Adjusting a forecast for seasons basically uses a combination of seasonal factors and average demand to arrive at an adjusted forecast.

Answer to #7

C

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