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The demand for a product in the month of March turned out to be 20 units against an earlier made forecast of 20 units. The actual demand for April and May turned to be 25 and 26 units respectively. What will be the forecast for the month of June, using exponential smoothing method and taking smoothing constant α as 0.2?
- a)20 units
- b)22 units
- c)26 units
- d)28 units
Correct answer is option 'B'. Can you explain this answer?
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Exponential Smoothing Method
Exponential smoothing is a forecasting method that assigns exponentially decreasing weights to past observations. It is commonly used when there is a trend in the data and the most recent observations are considered more important than older ones.
The formula for exponential smoothing is given by:
Forecast for the next period = (1 - α) * Actual demand for the current period + α * Forecast for the previous period
Where:
- α (alpha) is the smoothing constant, which determines the weight given to the most recent observation. It is a value between 0 and 1.
Given Data
- Actual demand for March = 20 units
- Actual demand for April = 25 units
- Actual demand for May = 26 units
- Smoothing constant (α) = 0.2
Forecast for April
Using the exponential smoothing formula, we can calculate the forecast for April:
Forecast for April = (1 - α) * Actual demand for March + α * Forecast for March
= (1 - 0.2) * 20 + 0.2 * 20
= 0.8 * 20 + 0.2 * 20
= 16 + 4
= 20 units
Forecast for May
Using the same formula, we can calculate the forecast for May:
Forecast for May = (1 - α) * Actual demand for April + α * Forecast for April
= (1 - 0.2) * 25 + 0.2 * 20
= 0.8 * 25 + 0.2 * 20
= 20 + 4
= 24 units
Forecast for June
Finally, we can calculate the forecast for June using the same formula:
Forecast for June = (1 - α) * Actual demand for May + α * Forecast for May
= (1 - 0.2) * 26 + 0.2 * 24
= 0.8 * 26 + 0.2 * 24
= 20.8 + 4.8
= 25.6 units
Rounding this to the nearest whole number, the forecast for June is approximately 26 units.
Therefore, the correct answer is option c) 26 units.
Exponential smoothing is a forecasting method that assigns exponentially decreasing weights to past observations. It is commonly used when there is a trend in the data and the most recent observations are considered more important than older ones.
The formula for exponential smoothing is given by:
Forecast for the next period = (1 - α) * Actual demand for the current period + α * Forecast for the previous period
Where:
- α (alpha) is the smoothing constant, which determines the weight given to the most recent observation. It is a value between 0 and 1.
Given Data
- Actual demand for March = 20 units
- Actual demand for April = 25 units
- Actual demand for May = 26 units
- Smoothing constant (α) = 0.2
Forecast for April
Using the exponential smoothing formula, we can calculate the forecast for April:
Forecast for April = (1 - α) * Actual demand for March + α * Forecast for March
= (1 - 0.2) * 20 + 0.2 * 20
= 0.8 * 20 + 0.2 * 20
= 16 + 4
= 20 units
Forecast for May
Using the same formula, we can calculate the forecast for May:
Forecast for May = (1 - α) * Actual demand for April + α * Forecast for April
= (1 - 0.2) * 25 + 0.2 * 20
= 0.8 * 25 + 0.2 * 20
= 20 + 4
= 24 units
Forecast for June
Finally, we can calculate the forecast for June using the same formula:
Forecast for June = (1 - α) * Actual demand for May + α * Forecast for May
= (1 - 0.2) * 26 + 0.2 * 24
= 0.8 * 26 + 0.2 * 24
= 20.8 + 4.8
= 25.6 units
Rounding this to the nearest whole number, the forecast for June is approximately 26 units.
Therefore, the correct answer is option c) 26 units.
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The demand for a product in the month of March turned out to be 20 units against an earlier made forecast of 20 units. The actual demand for April and May turned to be 25 and 26 units respectively. What will be the forecast for the month of June, using exponential smoothing method and taking smoothing constant α as 0.2?a)20 units b)22 units c)26 units d)28 unitsCorrect answer is option 'B'. Can you explain this answer?
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