In: Statistics and Probability
Due to the ongoing COVID-19 pandemic, your employer closed down and retrenched all its employees. You decided to return to your hometown, a small town in the east coast of MARGATE. You noticed that there was no food delivery service business in the town and decided to start such a service using your cars. Your delivery riders would collect the orders from food outlets in the town and deliver the food to customers for a fee. However, you did not have sufficient funds to run the business. When you tried to obtain a business loan from a bank, the bank officer requested that you prepare a sales forecast for the proposed business.
i) Explain two main challenges in making the sales forecast as required by the bank.
ii) Describe which specific method is suitable for the sales forecast and provide the reasons why you choose this method.
c) After the bank approved your loan, you began operating delivery service company as described in 2(b).
The company recorded the following number of deliveries in the last 6 months:
Month |
Actual Deliveries |
January |
270 |
February |
280 |
March |
350 |
April |
250 |
May |
340 |
June |
320 |
Due to the expected increase in deliveries, you approached the bank again to obtain another business loan. This time, the bank officer asked for a forecast of the deliveries for the rest of the year based on your July forecast. You decided to use naive, 3month moving average and 6-month moving average forecast methods.
i) Calculate your forecast for July using the three methods stated.
ii) If actual deliveries for July are 309, which one among the three methods is the most accurate using absolute deviation calculation?
Naive Method:
Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | |
Period 1 | 270 | ||||||
Period 2 | 280 | 270 | 10 | 10 | 100 | 03.57% | |
Period 3 | 350 | 280 | 70 | 70 | 4900 | 20.00% | |
Period 4 | 250 | 350 | -100 | 100 | 10000 | 40.00% | |
Period 5 | 340 | 250 | 90 | 90 | 8100 | 26.47% | |
Period 6 | 320 | 340 | -20 | 20 | 400 | 06.25% | |
Total | 50 | 290 | 23500 | 96.29% | |||
Average | 10 | 58 | 4700 | 19.26% | |||
Bias | MAD | MSE | MAPE | ||||
SE | 88.50612 | ||||||
Next period | 320 |
3-month moving average:
Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | |
Period 1 | 270 | ||||||
Period 2 | 280 | ||||||
Period 3 | 350 | ||||||
Period 4 | 250 | 300 | -50 | 50 | 2500 | 20.00% | |
Period 5 | 340 | 293.3333 | 46.66667 | 46.66667 | 2177.778 | 13.73% | |
Period 6 | 320 | 313.3333 | 6.666667 | 6.666667 | 44.44444 | 02.08% | |
Total | 3.333333 | 103.3333 | 4722.222 | 0.3580882 | |||
Average | 1.111111 | 34.44444 | 1574.074 | 0.1193627 | |||
Bias | MAD | MSE | MAPE | ||||
SE | 68.71843 | ||||||
Next period | 303.333333 |
6-month moving average:
Not possible because there are only 6 data values.
3-month moving average is the most accurate using absolute deviation calculation.