An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | }
\hline \text { Year } & \text { \# Sald } \
\hline 4 \text { years ago } & 10,000 \
\hline 3 \text { years ago } & 12,000 \
\hline \text { 2 years ago } & 18,000 \
\hline \text { Last year } & 20,000 \
\hline
\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.2, if the forecast for last year was 15,000?
A) 20,000
B) 19,000
C) 17,500
D) 16,000
E) 15,000

Question

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } 
\hline \text { Year } & \text { \# Sald } \
\hline 4 \text { years ago } & 10,000 \
\hline 3 \text { years ago } & 12,000 \
\hline \text { 2 years ago } & 18,000 \
\hline \text { Last year } & 20,000 \
\hline
\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.2, if the forecast for last year was 15,000?
A) 20,000
B) 19,000
C) 17,500
D) 16,000
E) 15,000

Quizplus · Accepted Answer

Exponential smoothing forecast formula is $F_{t+1} = \alpha \cdot A_t + (1 - \alpha) \cdot F_t$, where $F_{t+1}$ is the forecast for the next period, $A_t$ is the actual demand in the current period, $F_t$ is the forecast for the current period, and $\alpha$ is the smoothing constant. Plugging in the values: $F_{t+1} = 0.2 \cdot 20,000 + 0.8 \cdot 15,000 = 4,000 + 12,000 = 16,000$.

An Operation Analyst Is Forecasting This Year's Demand for One