MANGT 421 CORRECT EXAM ANSWERS AND
QUESTIONS SET A+
✔✔Importance of forecasts for Capacity - ✔✔capacity shortages can result in
undependable delivery, loss of customers and market share
✔✔Realities of Forecasts - ✔✔- Forecasts are seldom perfect, unpredictable outside
factors may impact the forecast
- Most techniques assume an underlying stability in the system
- Product family and aggregated forecasts are more accurate than individual product
forecasts
✔✔Qualitative Forecasting (intuition, experience) - ✔✔permits the inclusion of soft
information such as human factors, personal opinions, hunches (difficult or impossible
to quantify)
✔✔Quantitative forecasting (mathematical techniques) - ✔✔either the projection of
historical data or the development of associative methods that attempt to use casual
variables to make a forecast (hard data)
✔✔Qualitative Methods - ✔✔1.) Jury of executive opinion
2.) Delphi method (panel of experts)
3.) Sales force composite
4.) Market Survey
✔✔Quantitative Methods - ✔✔1.) Naive approach
2.) Moving averages
3.) exponential smoothing
✔✔Naive Approach - ✔✔- assumes demand in the next period is the same as demand
in the most recent period
- sometimes cost effective/efficient
- good starting point
, ✔✔Moving Average - ✔✔used if little or no trend; provides overall impression of data
overtime
✔✔Weighted Moving Average - ✔✔some trend is present; based on experience and
intuition
✔✔Problems with moving average - ✔✔- Increasing n smooths the forecast but makes
it less sensitive to changes
- Does not forecast trends well
- Requires extensive historical data
✔✔Exponential Smoothing - ✔✔WMA where weights decline exponentially and most
recent data weighted most; requires smoothing constant (0 to 1); involves little record
keeping of past data
✔✔Focus Forecasting - ✔✔- uses historical data to test multiple forecasting models for
individual items
- lowest error used to forecast next demand
✔✔Service Forecasts - ✔✔unusual challenges:
- short term records
- needs differ for industry
- holidays/calendar events
✔✔Reactive Approach - ✔✔- view forecasts as probably future demand
- react to meet demand
✔✔Proactive Approach - ✔✔- seek to influence demand through advertising, pricing,
product/service
✔✔Product Life Cycle - ✔✔- may be any length from a few days to decade
- operations must be able to introduce new products
✔✔Traditionally for Product Development - ✔✔distinct departments
- duties/responsibilities defined
- difficult to foster forward thinking
✔✔A Champion - ✔✔- product manager drives the product through system and related
organization
✔✔Team Approach - ✔✔- cross-functional where representatives from all
disciplines/functions involved
- product development teams, manufacturability teams, value engineering teams
QUESTIONS SET A+
✔✔Importance of forecasts for Capacity - ✔✔capacity shortages can result in
undependable delivery, loss of customers and market share
✔✔Realities of Forecasts - ✔✔- Forecasts are seldom perfect, unpredictable outside
factors may impact the forecast
- Most techniques assume an underlying stability in the system
- Product family and aggregated forecasts are more accurate than individual product
forecasts
✔✔Qualitative Forecasting (intuition, experience) - ✔✔permits the inclusion of soft
information such as human factors, personal opinions, hunches (difficult or impossible
to quantify)
✔✔Quantitative forecasting (mathematical techniques) - ✔✔either the projection of
historical data or the development of associative methods that attempt to use casual
variables to make a forecast (hard data)
✔✔Qualitative Methods - ✔✔1.) Jury of executive opinion
2.) Delphi method (panel of experts)
3.) Sales force composite
4.) Market Survey
✔✔Quantitative Methods - ✔✔1.) Naive approach
2.) Moving averages
3.) exponential smoothing
✔✔Naive Approach - ✔✔- assumes demand in the next period is the same as demand
in the most recent period
- sometimes cost effective/efficient
- good starting point
, ✔✔Moving Average - ✔✔used if little or no trend; provides overall impression of data
overtime
✔✔Weighted Moving Average - ✔✔some trend is present; based on experience and
intuition
✔✔Problems with moving average - ✔✔- Increasing n smooths the forecast but makes
it less sensitive to changes
- Does not forecast trends well
- Requires extensive historical data
✔✔Exponential Smoothing - ✔✔WMA where weights decline exponentially and most
recent data weighted most; requires smoothing constant (0 to 1); involves little record
keeping of past data
✔✔Focus Forecasting - ✔✔- uses historical data to test multiple forecasting models for
individual items
- lowest error used to forecast next demand
✔✔Service Forecasts - ✔✔unusual challenges:
- short term records
- needs differ for industry
- holidays/calendar events
✔✔Reactive Approach - ✔✔- view forecasts as probably future demand
- react to meet demand
✔✔Proactive Approach - ✔✔- seek to influence demand through advertising, pricing,
product/service
✔✔Product Life Cycle - ✔✔- may be any length from a few days to decade
- operations must be able to introduce new products
✔✔Traditionally for Product Development - ✔✔distinct departments
- duties/responsibilities defined
- difficult to foster forward thinking
✔✔A Champion - ✔✔- product manager drives the product through system and related
organization
✔✔Team Approach - ✔✔- cross-functional where representatives from all
disciplines/functions involved
- product development teams, manufacturability teams, value engineering teams
