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Thousand Barrels
Why TimBeeer SSalees ries ?
250
200
150
100
50
0 1998
1999
2000
2001
2002
2003
❖ Beer sales are highly seasonal
时间数列分析
Benefits and Uses of Time Series ❖ Benefits of time series Monitor sales performance over time… remove variation in monthly sales caused by calendar differences and seasonality that can conceal potential problems with sales
❖ A seasonal factor is computed and applied to the selling day adjusted sales
2020/6/23This factor, wheO:n/Netawoprkp/Paltihe/Fdile,nagmei.vppet s you monthly -7-
Improve decision making regarding sales and marketing actions
❖ Uses of time series
Assess current sales performance and evaluate the effectiveness of sales programs
2020p/6r/2o3 cedure for seasonal adjustments O:/Network/Path/Filename.ppt
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The X-11 procedure was developed by the U.S.
❖HAoswellidngodtaimy aedjussetmrieenst faacdtojrufsort esaachles ?
It ❖ 2020/6/23 is very difficult to evaluate O:/Network/Path/Filename.ppt monthly sales-5over time.
❖ MonHtholywvardiaotiotniminesasleesriisecsauwseodrbky?two
major factors
Seasonality Selling Days (calendar effects)
❖ Time Series technique statistically removes the effects of these two factors
❖ Time Series technique uses the X-11
Accurately determine the direction and rate of growth/decline in sales
Quickly identify changes in sales trends and correlate them to factors affecting sales… industry, company, competition
Determine underlying sales trend and project year end sales

Establish appropriate budgets for next year and estimate monthly
budget spreads
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Selling Days August 2003
SMTWT F S
August 2002 SMTWT F S
12
123
1.0 0.0
1.0 1.0 0.0
3456789
4 5 6 7 8 9 10
0.0 1.0 1.0 1.0 1.0 1.0 0.0
0.0 1.0 1.0 1.0 1.0 1.0 0.0
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Time series analysis is the primary sales analysis technique at A-B
❖ What isTTiimmeeSSereiersieAnsaAlysnisa?lysis
❖ How are Time Series plots developed? ❖ What are the advantages of Time Series
Analysis? ❖ What are Time Series used for?
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❖ TWimheasetriiessTainmalyesisSies raiestsatiAstnicaallysis ?
technique used to analyze and monitor sales volume over time.
10 11 12 13 14 15 16
11 12 13 14 15 16 17
0.0 1.0 1.0 1.0 1.0 1.0 0.0
0.0 1.0 1.0 1.0 1.0 1.0 0.0
17 18 19 20 21 22 23
18 19 20 21 22 23 24
0.0 1.0 1.0 1.0 1.0 1.0 0.0
month is computed and applied to the raw sales
This factor allows you to compare months as if they had the same number of selling days … e.g. accurately compare the June this year vs. June last year