Key Idea: Topic 4.3 is HL-only and focuses on forecasting future sales using data, trends and judgement. HL students are expected not just to use forecasting methods, but also to evaluate how reliable they are and what could make them wrong.
⏱️ Short-term: **Short-term forecasts —** more accurate. **Used for —** staffing, ordering stock, short-term planning. **Lower uncertainty**.
📅 Long-term: **Long-term forecasts —** less accurate. **Used for —** strategy, budgets, investment and expansion. **Higher uncertainty**.
📐 Moving averages: **Moving averages —** smooth out short-term fluctuations. **Useful for —** showing the underlying trend. **More periods —** smoother but slower to react.
➡️ Extrapolation: **Extrapolation —** extends a trend into the future. **Useful for —** simple projections when conditions stay similar. **Risky if the market is changing quickly**.
🛡️ Managing uncertainty: **Good forecasting practice —** use several methods. **Update forecasts regularly**. **Build in safety margins**. **Prepare best-case, worst-case and most likely scenarios**.
⚠️ Why forecasts go wrong: **Forecasts can fail because —** markets change. **Competitors act unexpectedly**. **Customer tastes shift**. **External shocks disrupt patterns**.
HL exam tip: If a question shows a graph or time series, identify the overall trend first, then comment on seasonal or unusual movements. Do not jump straight to a conclusion without reading the pattern carefully.
A strong HL answer explains both the usefulness and the limitation of the method. For example, moving averages may reveal trend more clearly, but they can hide sudden changes and still rely on past data.
Past-paper-style answers score better when they acknowledge uncertainty. A forecast is a guide for decision-making, not a guarantee that sales will happen exactly as predicted.
Example: A strong answer: Extrapolation may help the business predict future sales quickly by extending the trend line. However, it assumes past patterns will continue, so it may become unreliable if competition, consumer tastes or economic conditions change.
Important: Common triggers: explain sales forecasting, distinguish short-term and long-term forecasts, interpret time series patterns, calculate or explain moving averages, analyse extrapolation, or evaluate forecasting limitations.
- Identify the forecasting method or data pattern
- Explain how it works
- Apply it to the business context
- State what it suggests about future sales
- Add at least one limitation
- For HL, judge reliability rather than treating the forecast as certain