Refer to the table in Appendix 1. Calculate:

Mark scheme

Marking points from the official mark scheme (May/June 2019). The mark or mark type is shown in brackets.

1. 4(a)(i) 4 period MA = 8 period moving total/8 (1 mark if no calculation)
2. 4(a)(i) = (23 + 36 + 50 + 36 + 36 + 50 + 36 + 25)/8 (1)
3. 4(a)(i) = 292/8 (2)
4. 4(a)(i) = 36 500 litres or 36.5 thousand litres (3)
5. 4(a)(i) Allow full marks for 36.5 thousand or 36 500
6. 4(a)(i) OFR
7. 4(a)(ii) Sales - 4 period moving average trend (1)
8. 4(a)(ii) = 40 – 30 (1)
9. 4(a)(ii) = 10000 litres (2) Allow full marks for 10 or 10 000
10. 4(a)(ii) Note: -10 or -10 000 is no marks (wrong equation)
11. 4(b) Predicted trend from inspection of graph: 40.8 (1) Allow ±0.2 i.e. 40.6 – 41
12. 4(b) Add average seasonal variation Q3 = 11.97(1)
13. 4(b) Forecast = 52.77 thousand litres or 527 700 litres (3)
14. 4(b) Allow 52.57 – 52.97 thousand litres (3)
15. 4(b) Correct units must be indicated for full marks
16. 4(b) 52.57 - 52.97 or 527 570 – 527 970 (2)
17. 4(b) OFR
18. 4(c) Methods of forecasting sales: TSA, Delphi etc
19. 4(c) TSA based on extrapolating from past sales data
20. 4(c) Delphi technique based estimates of a panel of experts
21. 4(c) Sales forecasting using Time Series Analysis takes account of seasonal variations and gives a realistic prediction.
22. 4(c) Marketing decisions relate to marketing strategy / marketing mix
23. 4(c) Operational decisions relate to production e.g. stock control, capacity utilisation. May include reference to numbers of workers / types of contract
24. 4(c) Trend clearly shows that sales of ice cream are increasing
25. 4(c) Reference to usefulness of data in Table 1 e.g. change in milk sales by volume etc
26. 4(c) Forecasting enables planning, this method fits ice cream sales pattern well i.e. SWF 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. E.g. Volume of milk required to meet production requirements
27. 4(c) Combined forecasting sales of milk and milk products will inform decisions regarding purchase of animal feed, herd size required – this requires relatively long term planning as herd size may take time to alter.
28. 4(c) Case indicates possible changes to the market; demographic change and change in tastes will impact accuracy of forecasts based on past data
29. 4(c) Not all products sold by SWF will demonstrate seasonal patterns of demand e.g. milk thus using 4 period moving average not necessary.
30. 4(c) Helps ensure efficient use of labour and machinery helping to control costs of production and therefore ensure profitability
31. 4(c) Marketing decisions regarding pricing will be influenced by many other factors such as PED and costs of production
32. 4(c) Advertising likely to be influenced by overall sales so foresting important but will also be influenced by competitor actions
33. 4(c) Objectives will influence decisions – e.g. if SWF wishes to increase profits may need to cut costs of operations
34. 4(c) How forecasts contribute to market planning and production planning
35. 4(c) More reliable than simple forecasting or just projecting a trend
36. 4(c) Relies on future events behaving as in past so may not be reliable
37. 4(c) Extent to which it is or isn't useful
38. 4(c) Other evidence needs to be taken into account e.g. prediction of competitors’ behaviour, likely future government actions, and/or economic changes
39. 4(c) May be advisable to introduce an element of probability to the forecasts – what if analysis?
40. 4(c) Note: Limit to L1 AN & EVAL if only marketing or operational decisions considered.
41. 4(c) Note: Limit to L1 AN & EVAL if no reference to trend shown from 4(b)/Appendix 1
42. 4(c) OFR for answer to 4(b)