To forecast the demand for the third quarter of this year (July, August, and September) using a three-quarter moving average, we need to take the average demand of the previous three quarters (1st quarter, 2nd quarter, and 4th quarter of last year) to project the demand for the 3rd quarter of this year.

Here's a breakdown of the steps:

Data Given:

• Last Year:

  • 1st Quarter: Jan = 125, Feb = 145, Mar = 155
  • 2nd Quarter: Apr = 195, May = 205, Jun = 225
  • 3rd Quarter: Jul = 170, Aug = 160, Sep = 150
  • 4th Quarter: Oct = 225, Nov = 250, Dec = 265

• This Year:

  • 1st Quarter: Jan = 145, Feb = 155, Mar = 140
  • 2nd Quarter: Apr = 215, May = 230, Jun = 220
  • 3rd Quarter: Jul = (forecast), Aug = (forecast), Sep = (forecast)

Step 1: Calculate the Total Demand for Each Quarter

• Last Year 1st Quarter: $125 + 145 + 155 = 425$

• Last Year 2nd Quarter: $195 + 205 + 225 = 625$

• Last Year 4th Quarter: $225 + 250 + 265 = 740$

• This Year 1st Quarter: $145 + 155 + 140 = 440$

• This Year 2nd Quarter: $215 + 230 + 220 = 665$

Step 2: Calculate the Three-Quarter Moving Average

For the forecast of the 3rd quarter of this year, we use the total demand from the last three quarters (i.e., 1st and 2nd quarters of this year, and 4th quarter of last year):

$\text{Three-quarter Moving Average} = \frac{440 + 665 + 740}{3} = \frac{1845}{3} = 615$

Step 3: Forecast for the 3rd Quarter of This Year

The forecasted demand for the 3rd quarter of this year is 615 units.

Would you like more details or clarification on any part of this process?

Here are some related questions you might find helpful:

1. How does the choice of different moving averages (e.g., two-quarter, four-quarter) affect the forecast?
2. What are the advantages of using a moving average for forecasting demand?
3. How could seasonality adjustments improve the accuracy of this forecast?
4. Can other methods like exponential smoothing be more effective in certain forecasting scenarios?
5. How would you forecast demand for future quarters using this method?

Tip: Moving averages work well when there's no strong trend or seasonal pattern in the data, but may lag in detecting sudden changes.