Forecasting. Planning Forecast Customer Production Process Finished Goods Inputs.
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Transcript of Forecasting. Planning Forecast Customer Production Process Finished Goods Inputs.
ForecastingForecasting
Planning Forecast
Customer
ProductionProcess
FinishedGoods
Inputs
Forecasting
Marketing: forecasts sales for new and
existing products.
Production: uses sales forecasts to plan
production and operations; sometimes
involved in generating sales forecasts.
Characteristics of Forecasts
They are usually wrong A good forecast is usually more than a single
number Aggregate forecast are more accurate The longer the forecasting horizon, the less
accurate the forecasts will be Forecasts should not be used to the exclusion
of known information
Forecasting Horizon
Short term(inventory management, production plans..)
Intermediate term(sales patterns for product families..)
Long term(long term planning of capacity needs)
Forecasting Techniques
JudgmentalModels
Time SeriesMethods Causal Methods
ForecastingTechnique
DelphiMethod
MovingAverage
ExponentialSmoothing
RegressionAnalysis
SeasonalityModels
Types of forecasting Methods
Subjective methodsFREE HAND METHOD
Objective methodsSEMI AVERAGE
EVEN DATA ODD DATA
LEAST SQUARETREND MOMENT
FREE HAND METHOD
SEMI AVERAGEEVEN DATA
Y = a + bX
No. Year
Sales (Y-axis) Base time
(X-axis)
1 1988 1850 0 ∑ 1-6 = 11520
2 1989 1800 1 Y1 1920
3 1990 1900 2 X1 2.5
4 1991 2000 3
5 1992 1950 4
6 1993 2020 5 a= 3514.81 and b= 291.72
7 1994 1980 6 ∑ 7-12 = 11979
8 1995 1960 7 Y2 1996.5
9 1996 2000 8 X2 8.5
10 1997 2200 9
11 1998 2240 10
12 1999 2220 11
SEMI AVERAGEODD DATA
No. Year
Sales (Y-axis) Base time
(X-axis)
1 1988 1850 0 ∑ 1-5 = 9500
2 1989 1800 1 Y1 1900
3 1990 1900 2 X1 2
4 1991 2000 3
5 1992 1950 4
6 1993 2020 5 a= 1868 and b= 16
7 1994 1980 6 ∑ 7-11 = 9980
8 1995 1960 7 Y2 1996
9 1996 2000 8 X2 8
10 1997 2200 9
11 1998 2240 10
Y = a + bX
TREND MOMENT METHOD
LEAST SQUARE METHOD
EVEN DATA CASE