OM - GB335 - Chapter 4

Question 1

Forecasting

Answer 1

Process of predicting a future event, and is the underlying basis of all business decisions

Question 2

Forecasting Time Horizons

Answer 2

• Short-Range
• Medium-Range
• Long-Range

is influenced by the product life cycle. Into and growth require longer forecasts than maturity and decline.

Question 3

Types of Forecasts

Answer 3

• Economic
• Technological
• Demand

Question 4

Stategic Importance of Forecasting

Answer 4

• Human Resources
• Capacity
• Supply-Chain Management

Question 5

7 Steps in Forecasting

Answer 5

1. Determine the use of the forecast
2. select the items to be forecasted
3. Determine the time horizon of the forecast
4. select the forecasting model(s)
5. gather the data
6. Make the forecast
7. Validate and implement results

Question 6

Forecasting Approaches: Quantitative

Answer 6

Used when situation is stable and historical data exist, and involves mathematical techniques

Question 7

Forecasting Approaches: Qualitative

Answer 7

Used when situation is vague and little data exists, and involves intuition, experience

Question 8

Forecasting Approaches: Qualitative Methods

Answer 8

1. Jury of executive Opinion (pool opinions of high-level experts)
2. Delphi Method (panel of experts, queried iteratively)
3. Sales force composite
4. Consumer Market Survey

Question 9

Forecasting Approaches: Quantitative Methods

Answer 9

Time Series Models
1. Naive Approach
2. Moving Averages
3. Exponential Smoothing
4. Trend Projection
Associative Model
5. Linear Regression

Question 10

Naive Approach

Answer 10

Assumes demand in the next period is the same as demand in most recent period

can be cost-effective, and can be a good starting point

Question 11

Moving Average Method

Answer 11

is a series of arithmetic means, used often for smoothing and provides an overall impression of data over time

Question 12

Exponential Smoothing

Answer 12

a form of weighted moving average, qhich requires smoothing constant and involves little record keeping of past data

Question 13

Trend Projections

Answer 13

Fitting a trend line to historical data points to project into the medium to long-range

Question 14

Time Series Forecasting

Answer 14

set of evenly spaced numerical data obtained by observing response variable at regular time periods
forecast based on only past values, no other variables important, assumes that factors influencing past and present will continue influence in future

Question 15

Time Series Components

Answer 15

• Trend
• Cyclical
• Seasonal
• Random

Question 16

Time Series Components: Trend

Answer 16

• persistent, overall upward or downward pattern
• changes due to population, technology, etc.
• Typically several years duration

Question 17

Time Series Components: seasonal

Answer 17

• Regular pattern of up and down fluctuations
• Due to weather, customs, etc.
• Occurs within a single year

Question 18

Time Series Components: Cyclical

Answer 18

• Repeating up and down movements
• Affected by business cycle, political, and economic factors
• Multiple years duration
• Often causal or associative relationships

Question 19

Time Series Components: Random

Answer 19

Erratic, unsystematic, residual fluctuations

• due to random variation or unforeseen events
• short duration and nonrepeating

Question 20

Associative Forecasting

Answer 20

used when changes in one or more independent variables can be used to predict the changes in the dependent variable

Question 21

Adaptive Forecasting

Answer 21

its possible to use the computer to continually monitor forecast error and adjust the values used in exponential soothing to continually minimize forecast error ( adaptive smoothing )

Question 22

Focus Forecasting

Answer 22

Based on two principles:

1. sophisticated forecasting models are not always better than simple ones
2. there is no single technique that should be used for all products or services

• this approach uses historical data to test multiple forecasting models for individual items
• The forecasting model with the lowest error is then used to forecast the next demand

Question 23

Forecasting in the Service Sector

Answer 23

Presents unusual challenges

• special need for short-term records
• needs differ greatly as function of industry and product
• Holidays and other calendar events
• unusual events