Refer to the table in Appendix 1. Calculate: (i) seasonal variation in 2015 Quarter 1

Mark scheme

Marking points from the official mark scheme (May/June 2017). The mark or mark type is shown in brackets.

1. [1] $30m – 21.375 = $+8.625m
2. $m not required
3. [1] ($m(-1.375 – 1.125 – 1.875) / 3 = $–1.458 ($–1.46m 2 decimal places or – 1.5)
4. $m not required
5. [1] Predicted trend from inspection of graph: $23.8m (error margin 23.75 – 23.85)
6. [1] Add average seasonal variation: $-6.125m
7. [3] = $17.675m
8. Accept 17.68 or 17.7 (3 marks) (error margin 17.625 – 17.725)
9. $m not required
10. OFR
11. Up to 2 marks can be awarded for:
12. [1] Logical attempt to predict trend using the table (e.g. by considering the average of the Quarter 3s)
13. [1] Correct use of seasonal variation
14. Note to examiners: No reference to result from 2(b) limits AN and EVAL to L1
15. Answers could include:
16. Methods of forecasting sales
17. Sales forecasting using Time Series Analysis takes account of seasonal variations and gives a realistic prediction.
18. Forecasting enables planning, this method fits sales pattern well i.e.
19. PV faces clear seasonal variation and consistent past trends so it is reasonable to assume that the future will be similar, making forecasting valuable for planning.
20. Case indicates possible changes to the market – buyer's comments, change in buyers' requirements, increasingly fragmented relationships with buyers, possibility of direct selling, thus decreasing value of forecasting.
21. May be advisable to introduce an element of probability to the forecasts – what if analysis.
22. How forecasts contribute to market planning and production planning
23. If Pedro is certain the forecast indicates future success PV may not make the changes that other evidence indicates are necessary.
24. Application
25. Forecast only refers to export market, not 20% domestic sales
26. Multinational shoe retailer buyers, takeovers by larger shoe manufacturers
27. Possible more efficient working methods may lower costs
28. Possible effects of investment in new machinery
29. Use of graph to indicate changes in pattern (lower growth rate in 2016)
30. Forecast shows increased sales
31. PV faces clear seasonal variation and consistent past
32. Evaluation
33. More reliable than simple forecasting or just projecting a trend
34. Relies on future events behaving as in past patterns so may not be reliable
35. Other evidence needs to be taken into account e.g. prediction of competitors' behaviour, likely future government actions, and / or economic changes
36. Forecast only refers to exports, information on domestic market needed.