Sales forecasting and time-series
Введено| English | Значение |
|---|---|
| sales forecasting/seɪlz ˈfɔːkæstɪŋ/ | Прогнозирование продаж |
| time series/taɪm ˈsɪəriːz/ | Временной ряд |
| trend/trend/ | Тренд |
| seasonal/ˈsiːzənl/ | Сезонность |
| moving average/ˈmuːvɪŋ ˈævrɪdʒ/ | Движущее среднее |
| extrapolation/ekˈstræpəleɪʃn/ | Экстраполяция |
Predicting next quarter's sales
- How many units should the factory make next quarter? Order too much and stock piles up; too little and you lose sales.
- Sales forecasting 销售预测 uses past data to predict the future.
Sales forecast lab
sales = trend + seasonal effect
Move along a sales trend and see how forecast and actual can separate.
A time series is data that is:
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A time series records a variable over regular periods.
The long-run underlying direction of a time series is its ______.
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The trend is what moving averages reveal.
Time-series 时间序列 analysis
- A time series is data recorded over regular intervals (e.g. quarterly sales).
- It splits into a long-run trend 趋势, seasonal 季节性 variation, and random noise.
Sales wobble seasonally around an underlying upward trend.
Sales over four quarters are 30, 34, 28, 32. What is the 4-quarter moving average?
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(30 + 34 + 28 + 32) ÷ 4 = 124 ÷ 4 = 31.
The main purpose of a moving average is to:
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It smooths the data so the trend stands out.
Moving averages 移动平均
- A moving average smooths out short-term ups and downs to reveal the trend.
- A 4-quarter moving average averages each set of four consecutive quarters.
Worked example. Sales of 20, 24, 18, 26 over four quarters average to (20+24+18+26) ÷ 4 = 22 — the smoothed trend value, with the seasonal swings averaged out.
Sales wobble seasonally around a smooth underlying trend
Extrapolation gives reliable forecasts even when market conditions change sharply.
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False. Extrapolation assumes the future will follow the past trend. That assumption fails when conditions change, for example after a new competitor or a recession.
Extrapolation 外推 and its limits
- Extrapolation extends the past trend into the future to forecast.
- It assumes the future behaves like the past — risky if conditions change (a new rival, a recession).
Forecasts are not facts. Extrapolation only works while the trend holds. A sudden shock — new competitor, technology, downturn — can make a confident forecast badly wrong.
You've got it
- a time series splits into trend, seasonal variation and noise
- a moving average smooths data to reveal the underlying trend
- extrapolation projects the trend forward — risky if conditions change
Write from a moving average of 23
- Sales over four quarters are 20, 24, 22 and 26.
- Find the 4-quarter moving average.
Sales over four quarters are 20, 24, 22 and 26. What is the 4-quarter moving average?
92 divided by 4 is 23.
What is the 4-quarter moving average?
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The four quarters sum to 92, and 92 divided by 4 is 23. Other options — 31 (the lesson average); 26 (the last quarter used as the average).