Chap 3: Forecasting

Question 1

It is a statement about the future value of a variable such as demand.

Answer 1

forecast

Question 2

It is the art and science of predicting future events.

Answer 2

Forecasting

Question 3

Elements of Good Forecast

Answer 3

 Should be timely
 Should be accurate
 Should be reliable
 Should be expressed in meaningful units
 Should be in writing
 Should be simple to understand and use
 Should be cost effective

Question 4

Steps in the Forecasting Process

Answer 4

1. Determine the purpose of the forecast.
2. Establish a time horizon
3. Select a forecasting technique.
4. Obtain, clean, and analyze appropriate data.
5. Make the forecast.
6. Monitor the forecast.

Question 5

APPROACHES TO FORECASTING

Answer 5

-QUALITATIVE APPROACHES
-QUANTITATIVE APPROACHES

Question 6

OVERVIEW OF QUALITATIVE METHODS

Answer 6

1. Jury of executive opinion.
2. Delphi Method.
3. Sales force composite.
4. Consumer market survey.

Question 7

OVERVIEW OF QUANTITATIVE METHODS

Answer 7

I. Time-Series Models
II. Associative Model

Question 8

Decomposition of a Time Series

Answer 8

1. Trend
2. Seasonality
3. Cycles
4. Random variations

Question 9

Random Variations includes…

Answer 9

a. Naïve approach
b. Moving averages
c. Weighted Moving Average
d. Exponential Smoothing

Question 10

MEASURING FORECAST ERROR

Answer 10

-MEAN ABSOLUTE DEVIATION (MAD)
-MEAN SQUARED ERROR (MSE)
-MEAN ABSOLUTE PERCENTAGE ERROR (MAPE)

Question 11

Associative Model includes…

Answer 11

a. Trend projection
b. Associative Forecasting Methods: Regression and Correlational Analysis

Question 12

Trend Projection includes…

Answer 12

-SEASONAL VARIATIONS IN DATA
-CYCLICAL VARIATIONS IN DATA

Question 13

Under this method, the opinions of a group of high level experts or managers, often in combination with statistical models, are pooled to arrive at a group estimate of demand.

Answer 13

Jury of executive opinion

Question 14

Three different types of Delphi Method patrticipants

Answer 14

-Decision Makers
-Staff Personnel
-Respondents

Question 15

usually consists of a group of 5 to 10 experts who will be making the actual
forecast

Answer 15

Decision makers

Question 16

assist decision makers by preparing, distributing, collecting, and summarizing a series of questionnaires and survey results.

Answer 16

Staff personnel

Question 17

are a group of people, often located in different places, whose
judgments are valued.

Answer 17

Respondents

Question 18

In this approach, each salesperson estimates what sales will be in his or her region. These forecasts are then reviewed to ensure that they are realistic. Then they are combined at the district and national levels to reach an overall forecast.

Answer 18

Sales force composite

Question 19

This method solicits input from customers or potential customers regarding future purchasing plans. It can help not only in preparing a forecast but also in improving product design and planning for new products.

Answer 19

Consumer market survey

Question 20

It is based on a sequence of evenly spaced (weekly, monthly,
quarterly, and so on) data points.

Answer 20

Time-Series Models

Question 21

It is the gradual upward or downward movement of the data over time.
Changes in income, population, age distribution, or cultural views may
account for movement in trend.

Answer 21

Trend

Question 22

It is a data pattern that repeats itself after a period of days, weeks, months, or quarters. There are six common seasonality patterns

Answer 22

Seasonality

Question 23

Patterns in the data that occur every several years. They are usually tied into the business cycle and

Answer 23

Cycles

Question 24

Are “blips” in the data caused by chance and unusual situations. They follow no discernible pattern, so they cannot be predicted.

Answer 24

Random variations

Question 25

The simplest way to forecast is to assume that demand in the next period will be equal to demand in the most recent period.

Answer 25

Naïve approach

Question 26

Uses a number of historical actual data values to generate a forecast. It is useful if we can assume that market demands will stay fairly steady over time.

Answer 26

Moving averages

Question 27

When a detectable trend or pattern is present, weights can be used to place more emphasis on recent values. This practice makes forecasting techniques more responsive to changes because more recent periods may be more heavily weighted.

Answer 27

Weighted Moving Average –

Question 28

It is a sophisticated weighted-moving average forecasting method that is still fairly easy to use. It involves very little record keeping of past data.

Answer 28

Exponential Smoothing

Question 29

This value is computed by taking the sum of the absolute values of the individual forecast errors (deviations) and dividing by the number of periods of data (n)

Answer 29

MEAN ABSOLUTE DEVIATION (MAD)

Question 30

The average of the squared differences between the forecasts and observed values

Answer 30

MEAN SQUARED ERROR (MSE)

Question 31

This is computed as the average of the absolute difference between the forecasted and actual values, expressed as percentage of the actual values.

Answer 31

MEAN ABSOLUTE PERCENTAGE error (MAPE)

Question 32

This technique fits a trend line to a series of historical data points and then projects the line into the future for medium to long-range forecasts.

Answer 32

Trend Projection

Question 33

Are regular up and down movements in a time series that relate to recurring events such as weather of holidays. Demand for coal and fuel oil, for example, peaks during cold winter months. Demand for golf clubs or sunscreen may be highest in summer.

Answer 33

SEASONAL VARIATIONS IN DATA

Question 34

Are like seasonal variations in data but occur every several years, not weeks, months or quarters.

Answer 34

CYCLICAL VARIATIONS IN DATA

Question 35

Unlike time-series forecasting, this models usually consider several variables that are related to the quantity being predicted. Once these related variables have been found, a statistical model is built and used to forecast the item of interest. T

Answer 35

ASSOCIATIVE FORECASTING METHODS