Supply Chain Chapter 2

Cause-and-Effect Models can have multiple independent variables. A. True B. False

A. True

The Qualitative forecasting method is based on opinion & intuition A. True B. False

A. True

Forecasts are more accurate the farther out into the future that you forecast. A. True B. False

B. False

Independent Demand is demand for an item that is directly related to other items or finished products, such as a component or material used in making a finished product. A. True B. False

B. False

In the absence of any other information or visibility, individual supply chain participants can begin second-guessing what is happening with ordering patterns, and potentially start over-reacting. This is know as? a. Forecast Bias b. The Bullwhip Effect c. A Tracking Signal d. The Running Sum of Forecast Errors

B. The Bullwhip Effect

Five models of Time Series

Naive forecasting, simple moving average forecasting, weighted moving average, exponential smoothing, and linear trend

What are the five qualitative forecasting models?

Personal insight, Jury of executive opinion, delphi method, sales force estimation, and customer survey

What are the two basic forecasting techniques?

Qualitative and Quantitative

Two models of Cause and Effect

Simple regression and multiple regression

What are the types of quantitative forecasting?

Time Series and Cause and effect

Jury of executive opinion

forecast from people who know the most about the product and the marketplace that would likely form a jury to discuss and determine the demand

Personal Insight

forecast is based on the inside of the most experienced, most knowledgeable, or most senior person available

Sales force estimation

forecast performed specifically with a group of salespeople

Customer survey

forecast where customers are directly approached and asked to give their opinions about the particular product

Delphi Method

forecast where the input of each of the participants is collected separately so that people are not influenced by one another

Quantitative Forecasting

forecasting which uses mathematical models and historical data to make forecasts

Mean Squared Error (MSE)

magnifies the errors by squaring each one before adding them up and dividing by the number of forecast periods. MSE = ∑ (A-F) ² / n

Mean Absolute Percent Error (MAPE)

measures the size of the error in percentage terms. It is calculated as the average of the unsigned percentage error. MAPE = ∑ ((|A - F|)/ A) / n

Mean absolute deviation (MAD)

measures the size of the forecast error in units. It is calculated as the average of the unsigned, i.e., absolute, errors over a specified period of time. MAD = ∑(|A - F|) / n

Forecasting

the business function that estimates future demand for products so that they can be purchased or manufactured in appropriate quantities in advance of need

Demand

the need for a particular product or component

Demand Planning

the process of combining statistical forecasting techniques and judgement to construct demand estimates for products or services

When creating a quantitative forecast, data should be evaluated to detect for a repeating pattern of demand from year to year, or over some other time interval, with some periods of considerably higher demand than others. This is known as a? a. Trend Variation b. Random Variation c. Seasonal Variation d. Cyclical Variation

C. Seasonal Variation

Which one of the following is NOT a type of qualitative forecasting? a. Sales force composite b. Consumer survey c. Jury of executive opinion d. Naïve method

D. naive method

Qualitative Forecasting

Forecasting which is based on opinion and intuition

Forecast

an estimate of future demand

Cause and Effect

assumes that one or more factors predict future demand

What does the acronym CPFR represent? a. Coordinated Planning & Forecasting Relationships b. Collaborative Planning, Forecasting, & Replenishment c. Centralized Purchasing & Forecasting Relationships d. Collaborative Purchasing, Forecasting, & Receivables

b. Collaborative Planning, Forecasting, & Replenishment

Time Series

based on the assumption that the future is an extension of the past. Historical data is used to predict future demand ( most frequently used amount all the forecasting models)

Dependent Demand

demand for an item that is directly related to other items or finished products, such as a components or material used in making a finished product

Independent Demand

demand for an item that is unrelated to the demand for other items, such as finished product, a spare part, or a service part