OxfordAQA A-Level Business: Analysing future sales (9725) – Revision Notes

These notes condense section 3.3.5 Analysing future sales of the OxfordAQA International AS and A-level Business (9725) specification, Version 1.1, for International AS exams May/June 2027 onwards and International A-level exams May/June 2028 onwards. Sales forecasting belongs to the second-year (International A-level only) content and is examined through Unit 3: Business analysis. On the older 9625 specification? Revise from that document instead. The study guide has the full teaching and the longer examples.

Pair these notes with the practice questions. Course pages: 9725 hub and printable 9725 checklist. Not sure where your gaps are? Try the free diagnostics.

The six things the specification lists

1. Calculation and use of the three period moving average method to forecast sales.
2. The value of extrapolation.
3. Advantages and disadvantages of qualitative sales forecasting.
4. The value of sales forecasting.
5. Difficulties of sales forecasting.
6. The impact of sales forecasting on business decision-making.

Key definitions

• Sales forecast: an estimate of future sales volume or revenue for a stated period.
• Trend: the underlying direction of sales once short-term ups and downs are removed.
• Three period moving average: the mean of three consecutive periods of data, placed against the middle period, recalculated as the window moves on one period at a time.
• Extrapolation: extending a past trend into the future on the assumption that the pattern continues.
• Qualitative forecasting: forecasting based on judgement and opinion, not on past figures.
• Forecast error: the gap between actual and forecast sales, often shown as a percentage of the forecast.

Formulas and rules

What	How
Three period moving average	(period 1 + period 2 + period 3) ÷ 3, placed against period 2
Number of moving averages	number of data periods − 2
Average change in trend	(last moving average − first moving average) ÷ (number of moving averages − 1)
Forecast	last moving average + (periods ahead × average change)
Periods ahead	counted from the period of the last moving average, not the last actual figure
Forecast error (%)	(actual − forecast) ÷ forecast × 100

Method in steps: forecasting with moving averages

1. Add three consecutive periods; divide by 3; write the result against the middle period.
2. Slide the window on by one period and repeat to the end of the data.
3. Find the average change between consecutive moving averages.
4. Count how many periods the target lies beyond the last moving average.
5. Forecast = last moving average + (periods ahead × average change).
6. Round sensibly (whole units for products) and state the unit.

Small worked reminder: Pebblewick Café

Weekly orders for five weeks: 620, 710, 680, 770, 800.

Week 2: (620 + 710 + 680) ÷ 3 = 2,010 ÷ 3 = 670
Week 3: (710 + 680 + 770) ÷ 3 = 2,160 ÷ 3 = 720
Week 4: (680 + 770 + 800) ÷ 3 = 2,250 ÷ 3 = 750
Average change = (750 − 670) ÷ 2 = 40 orders per week
Week 6 is 2 weeks after week 4: 750 + (2 × 40) = 830 orders

The raw data fell in week 3, but every moving average rose: the trend is upward.

Small worked reminder: using the forecast

Each Pebblewick cook can prepare up to 140 orders a week. How many cooks does the week 6 forecast need?

830 ÷ 140 = 5.93 (2 d.p.)

Round up to 6 cooks: five would leave about 130 orders unmade. This is the “use” half of the specification point: a forecast only earns marks when you turn it into a decision. In an answer, add one line of caution, for example that five weeks of café data may include a holiday rush that will not repeat.

Evaluation checklist for forecasting questions

When a question asks you to evaluate a forecast or a decision based on one, test it against these five points:

• Data: how many periods is it based on, and are they typical?
• Market: is the market stable, or is something changing (new rival, economy, tastes)?
• Time horizon: is the forecast for next month or several years?
• Method: is it quantitative, qualitative or both, and does that suit the situation?
• Stakes: is the decision cheap to reverse (overtime) or costly and hard to reverse (a new site)?

Finish with a judgement: how far should the business rely on the forecast, and what else should it do?

Extrapolation: value in one box

For	Against
Quick and cheap: uses data already held	Assumes the past pattern continues
Objective and repeatable	Blind to new rivals, recessions, shifts in taste
Good for short-term forecasts in stable markets	Less reliable the further ahead it goes
A baseline that managers can adjust	Needs a run of past data, so weak for new products

One-line judgement: most useful short term in a stable market; least useful when the market is changing fast.

Qualitative forecasting

Examples: expert opinion; the Delphi technique (an anonymous expert panel answering in rounds until views converge); sales force composite (each salesperson estimates their area, then the estimates are totalled); hunch or intuition.

Advantages

• Works with no past data: new products, new markets, start-ups.
• Can anticipate changes that past figures cannot show.
• Uses the knowledge of staff who deal with customers every day.

Disadvantages

• Subjective, so open to optimism, pessimism or self-interest.
• Hard to check, and different panels may disagree.
• Formal panels take time and money.
• Staff whose bonus depends on beating a target may forecast low.

Value of sales forecasting

• Turns uncertainty into a planning figure.
• Starting point for budgets and cash flow forecasts.
• Co-ordinates functions around one set of numbers.
• Supports bids for loans or investment.
• Comparing forecast with actual gives early warning of change.

Difficulties of sales forecasting

• Changes in the external environment (economy, tastes, technology, regulation).
• Competitor moves.
• One-off events: weather, supply problems, publicity.
• No data for new products or markets.
• Longer time horizons mean wider error.
• Bias in judgement; gaps or errors in data.

Impact on decision-making

Function	Decisions that rest on the forecast
Operations	Capacity, production scheduling, inventory levels, supplier orders
Human resources	Recruitment, training, overtime, temporary staff, redundancies
Finance	Budgets, cash flow forecasts, need for external finance
Marketing	Promotion spending, pricing, distribution
Strategy	Whether to expand, enter new markets or invest in new capacity

Forecasting is also one of the ways to manage risk listed in section 3.4.6.

Must-know distinctions

• Moving average vs forecast. The moving average shows the trend in the past; the forecast extends it.
• Quantitative vs qualitative. Numbers from past data vs judgement and opinion.
• Trend vs actual. A month can fall while the trend still rises.
• Over-forecast vs under-forecast. Over-forecasting leaves surplus stock and idle staff; under-forecasting leads to lost sales and stockouts.

Quick self-test

1. Calculate the three period moving average of 35, 41 and 44.
2. Against which period is a three period moving average placed?
3. A set of data covers nine months. How many three period moving averages can be calculated?
4. Moving averages placed against periods 2 to 5 are 120, 126, 131 and 138. Data runs to period 6. Forecast period 7.
5. Define extrapolation.
6. Give one reason extrapolation is less reliable for a five-year forecast than for next month.
7. Name two qualitative forecasting methods.
8. Give one advantage of qualitative forecasting for a business launching a new product.
9. Give one disadvantage of a sales force composite.
10. A firm forecast 450 units and sold 414. Calculate the forecast error as a percentage of the forecast.
11. Which functional area uses the sales forecast to decide how many staff to recruit?
12. State one effect of over-forecasting sales on operations.

Answers

1. (35 + 41 + 44) ÷ 3 = 120 ÷ 3 = 40.
2. The middle period of the three.
3. 9 − 2 = 7.
4. Average change = (138 − 120) ÷ 3 = 6. Period 7 is 2 periods after period 5: 138 + (2 × 6) = 150.
5. Projecting a past trend into the future, assuming the pattern continues.
6. More time for the market to change: new rivals, economic shifts or new technology can break the trend.
7. Any two: expert opinion, the Delphi technique, sales force composite, hunch.
8. It can be used even though the product has no past sales data.
9. Salespeople may forecast low so their targets are easier to beat (or may be over-optimistic).
10. (414 − 450) ÷ 450 × 100 = −8% (sales were below forecast).
11. Human resources.
12. Surplus inventory, raising storage costs and tying up cash (or idle capacity).

Where marks are usually lost

• Writing a moving average against the last of its three periods.
• Dividing by the number of moving averages rather than the number of gaps between them.
• Counting periods ahead from the last actual figure.
• Leaving out units, or quoting a forecast to several decimal places of a scooter or a meal.
• Giving the forecast error without a sign, or dividing by actual instead of forecast when the question defines it the other way.
• Saying extrapolation is “inaccurate” without explaining which assumption fails in the case.
• Listing advantages of qualitative methods that are not linked to the business in the question.
• Describing the impact of a forecast on “the business” in general instead of on named functions.

Official syllabus

OxfordAQA International AS and A-level Business (9725) specification, Version 1.1, for International AS exams May/June 2027 onwards and International A-level exams May/June 2028 onwards. Published by OxfordAQA.