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BUS 355: CH 9: Forecasting
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Terms in this set (27)
forecasting
an estimate of the future level of some variable. common variables that are forecasted include demand levels, supply levels, and prices.
market level demand
us demand for hybrids to reach 5 million in 2014
firm level demand
what percentage will your firm capture? (in sales, components, spare parts, etc)
4 laws of forecasting
Law 1: Forecasts are almost always wrong (but they are still useful)
goal is to get a close estimate. can't get exact, too many factors.
Law 2: Forecast for the near term tend to be more accurate
(just like the weather). near term, less factors to affect forecast variable.
Law 3: Forecasts for groups of products or services tend to be more accurate
(total car sales vs. that of a particular color)groups easier and more accurate. demand, supply, or price of a specific item is usually affected by more factors.
Law 4: Forecasts are no substitute for calculated values
forecasts- should only be used when better approaches to determining the variable of interest are not available.
Law 1: Forecasts are almost always wrong (but they are still useful)
goal is to get a close estimate. can't get exact, too many factors.
Law 2: Forecast for the near term tend to be more accurate
(just like the weather). near term, less factors to affect forecast variable.
Law 3: Forecasts for groups of products or services tend to be more accurate
(total car sales vs. that of a particular color)groups easier and more accurate. demand, supply, or price of a specific item is usually affected by more factors.
Law 4: Forecasts are no substitute for calculated values
forecasts- should only be used when better approaches to determining the variable of interest are not available.
4 Laws of Forecasting
market surveys
build-up forecast
life-cycle analogy method
panel consensus forecasting
delphi method
5 types of qualitative forecasting methods
market surveys
a structured questionnaire submitted to potential customers, often to gauge potential demand.
(solicit opinions about products or potential products and often attempt to estimate likely demand. if structured well and administered to representative sample, can be quite effective. major drawback: expensive and time consuming to perform.)
build-up forecasts
a qualitative forecasting technique in which individuals familiar with specific market segments estimate the demand within these segments. these individual forecasts are then added up to get an overall forecast.
ex, company w/ sales offices in each of Japan's 47 prefectures might ask each regional sales manager to estimate per-prefecture sales. overall sales would then be calculated as the sum of these individual forecasts.
life-cycle analogy method
a qualitative forecasting technique that attempts to identify the time frames and demand levels for the introduction, growth, maturity, and decline life cycle stages of a new product or service.
often used w/ new items. base the forecast of the NEW off of the actual history of a similar product. major questions- how long will each stage last? how rapid will said growth be? how rapid will the decline be? how large will the overall demand be, especially during the maturity phase?
panel consensus forecasting
a qualitative forecasting technique that brings experts together to jointly discuss and develop a forecast.
delphi method
a qualitative forecasting technique in which experts work individually to develop forecasts. the individual forecasts are shared among the group, and then each participant is allowed to modify his or her forecast based on information from the experts. this process is repeated until consensus is reached.
experts work independently and then shared results.
quantitative forecasting methods
forecasting models that use measurable, historical data to generate forecasts. quantitative forecasting models can be divided into two major types: time series models and causal models.
qualitative forecasting techniques
forecasting techniques based on intuition or informed opinion. these techniques are used when data are scarce, not available, or irrelevant.
quantitative forecasting models
use statistical techniques and historical data to predict future levels. considered objective rather than subjective because they follow certain rules in calculating forecasting values. 2 main types of quantitative forecasting models are time series and causal models.
time series
a series of observations arranged in chronological order.
time series forecasting model
a quantitative forecasting model that uses a time series to develop forecasts. with a time series model, the chronology of the observations and their values are important in developing forecasts. (uses a series of observations in chronological order to develop forecasts).
causal forecasting models
models in which forecasts are modeled as a function of something other than time.
randomness
seasonality
trends
within time series forecasting models
randomness
in the context of forecasting, unpredictable movement from one time period to the next
seasonality
a repeated pattern of spikes or drops in a time series associated w/ certain times of the year.
moving average model
a time series forecasting model that derives a forecast by taking an average of recent demand values. less susceptible to random swings in demand.
weighted moving average model
a form of the moving average model that allows the actual weights applied to past observations to differ.
exponential smoothing model
a form of the moving average in which the forecast for the next period is calculated as the weighted average of the current period's actual value and forecast.
forecast accuracy
how do we know:
if a forecast model is "best"?
if a forecast model is still working?
what types of errors a particular forecasting model is prone to make?
... Need measures of forecast accuracy.
mean absolute deviation (MAD)
zero is a really good number!!! tracks the size of the error regardless of direction, a much better indicator.
mean absolute percentage error (MAPE)
=absolute value of the forecast errors.
collaborative planning, forecasting, and replenishment (CPFR)
a set of business processes, backed up by information technology, in which members agree to mutual business objectives and measures, develop joint sales and operational plans, and collaborate electronically to generate and update sales forecasts and replenishment plans.
what differentiates from traditional planning and forecasting approaches is the emphasis on collaboration.
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