Evaluate the usefulness of the moving average method to forecast sales of oil and gas to PGP.

Mark scheme

Marking points from the official mark scheme (May/June 2018). The mark or mark type is shown in brackets.

1. [Knowledge] Moving average based on past sales data
2. [Knowledge] Calculates an 8 period (usually) moving total and divides by 8; calculates seasonal and average seasonal variation; extrapolates trend and allows short term forecasts to be made; cyclical variations can be identified over periods longer than 1 year.
3. [Application] Some oil and gas products subject to seasonal variations in demand, e.g. heating oil.
4. [Application] Some products subject to cyclical demand driven by world economic booms/slump, e.g. fuel for cars/trucks and generating electricity.
5. [Analysis] Sales forecasts help in planning e.g. production/refinery capacity; workforce planning; inventory levels etc.
6. [Analysis] Accurate sales forecasting can help cut costs e.g. of unexpected
7. [Evaluation] Basing all forecasts on past data may mean that structural changes in demand are not taken account of e.g. rapidly changing trend towards renewable energy.
8. [Evaluation] Weather patterns in future may not be the same as those in the past - so relying on moving average method may be unwise.
9. [Evaluation] Should be used - but with caution and with use of other methods too e.g. market research to assess demand for new products such as lubricants for jet engines.
10. [Evaluation] Use as much past data as possible but most recent is most relevant.
11. [Evaluation] Adjust for trends that did not appear in past data.