OxfordAQA A-Level Business: Analysing future sales (9725) – Practice Questions

These are original questions written for Marlbridge, for revision and practice on this content. They are not reproduced past-paper questions, and they do not replicate the exam’s exact structure, question count or mark tariffs – examination boards hold copyright in their own papers. Use these alongside the official past papers from your board or school.

This set of questions tests section 3.3.5 Analysing future sales from 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 sits in the second-year (International A-level only) content and is examined through Unit 3: Business analysis. On the older 9625 specification? Practise from that document instead. Every business named is invented.

Before you start, the study guide teaches the method and the revision notes summarise it. Also useful: the 9725 course hub, the printable 9725 checklist and the free diagnostics.

Questions

1. Define the term extrapolation, as used in sales forecasting. [2]

2. Velloway Gym sold the following numbers of new memberships in five consecutive months: 84, 90, 99, 93, 108. Calculate the three period moving averages. [3]

3. Nimbrel Pet Supplies has calculated three period moving averages of its monthly unit sales. They are placed against months 2 to 6: 2,140; 2,180; 2,205; 2,250; 2,300. Its actual sales data runs to month 7. Calculate the sales forecast for month 8. [4]

4. State two advantages of qualitative sales forecasting. [2]

5. Ostravel Tiles plans to forecast sales of a new range of outdoor tiles by asking its sales representatives for estimates. Explain one disadvantage of this approach for Ostravel. [3]

6. Glasswell Bikes forecast sales of 1,250 bikes for the spring quarter. It actually sold 1,175.

(a) Calculate the forecast error as a percentage of the forecast. [2] (b) Explain one possible reason for the error. [2]

7. Larchfold Ceramics received the following orders in months 1 to 6: 1,530; 1,590; 1,620; 1,665; 1,650; 1,731. It can produce 1,760 orders a month. Using three period moving averages, forecast orders for month 8 and state whether Larchfold has enough capacity. [5]

8. Quennell Water supplies bottled water to offices, a market with stable demand. Explain two reasons why extrapolation may be of value to Quennell. [4]

9. Marrowdene Festivals runs outdoor music events. Explain two difficulties it may face in forecasting ticket sales. [4]

10. Tilsbury Kitchens has forecast a 20% rise in orders for fitted kitchens next year. Analyse how this forecast could affect decisions in its human resources and finance functions. [6]

11. Fothergale Organics delivers boxes of organic vegetables. Its weekly deliveries for weeks 1 to 7 were: 312, 327, 333, 330, 348, 357, 351. Its packing shed can handle 380 boxes a week. The owner, Morwenna Fothergale, is considering leasing a second packing site for three years. A national supermarket chain has announced it will launch its own vegetable box scheme in the region next year. A survey of Fothergale’s customers found that most would recommend the service to friends.

(a) Calculate the three period moving averages placed against week 2 and week 6. Use them to forecast deliveries for week 9. [4] (b) Evaluate whether Morwenna should rely on this forecast when deciding whether to lease the second packing site. [12]

Answers

1. Projecting a past trend in sales into the future [1], on the assumption that the past pattern will continue [1]. [2] Examiner insight: The assumption that the pattern continues is the part that gains the second mark; “using past data” alone describes most forecasting.

2. (84 + 90 + 99) ÷ 3 = 91 [1]; (90 + 99 + 93) ÷ 3 = 94 [1]; (99 + 93 + 108) ÷ 3 = 100 [1]. [3] Examiner insight: Show each three-month total; if one addition slips, visible working makes it clear the other averages are right.

3. Total change = 2,300 − 2,140 = 160 [1]. Average change = 160 ÷ 4 = 40 per month [1]. Month 8 is 2 months after month 6 [1]. Forecast = 2,300 + (2 × 40) = 2,380 units [1]. [4] Examiner insight: Five averages have four gaps; dividing by 5 is a common slip, and it changes the final figure.

4. Any two: it can be used where there is no past data, such as for a new product [1]; it can take account of expected changes that past figures cannot show, or it draws on the knowledge of staff close to customers [1]. [2] Examiner insight: Two distinct points are needed; “uses opinions” and “uses judgement” are the same idea.

5. Representatives may be paid a bonus for beating targets [1], so they may give low estimates to make targets easier to reach [1]. Ostravel could then under-produce the new range and lose sales in its first summer [1]. [3] Examiner insight: The third mark comes from the consequence for Ostravel; a general bias point with no effect on the business stops at two.

6. (a) (1,175 − 1,250) ÷ 1,250 × 100 [1] = −6% [1]. (b) A wet spring may have reduced demand for leisure cycling [1], so actual sales fell below a forecast built on past trends that did not expect it [1]. Examiner insight: Keep the minus sign or say “6% below forecast”; a bare “6%” leaves the direction unclear.

7. Moving averages: 4,740 ÷ 3 = 1,580; 4,875 ÷ 3 = 1,625; 4,935 ÷ 3 = 1,645; 5,046 ÷ 3 = 1,682 [1]. Average change = (1,682 − 1,580) ÷ 3 = 34 [1]. Month 8 is 3 months after month 5 [1]. Forecast = 1,682 + (3 × 34) = 1,784 orders [1]. This is 24 above capacity of 1,760, so Larchfold does not have enough capacity [1]. [5] Examiner insight: The last average sits against month 5, not month 6; counting two months ahead gives 1,750 and the wrong capacity conclusion.

8. Demand is stable, so the past trend is likely to continue [1], which makes an extrapolated forecast reasonably reliable for planning deliveries and stock [1]. It is quick and cheap because Quennell already holds its sales records [1], so managers can update the forecast often without paying for research [1]. [4] Examiner insight: Linking the value to Quennell’s stable market is what lifts this above a generic list.

9. Ticket sales depend heavily on the weather forecast close to each event [1], which cannot be known when the forecast is made months ahead [1]. Each festival may feature different headline acts, so past ticket sales are a weak guide to future events [1], making extrapolation unreliable [1]. [4] Examiner insight: Two separate difficulties, each explained in this context, are needed for full credit.

10. HR: Tilsbury may need more fitters and designers [1], so it must recruit and train early because skilled fitters take time to find [1]. If the forecast proves too high, it may have to make staff redundant, so it may use temporary contracts or overtime first [1]. Finance: the forecast feeds the budget and cash flow forecast [1]. More orders mean buying materials and paying wages before customers pay, so Tilsbury may need an overdraft or loan [1]. However, a 20% rise is large; finance may plan for a lower figure to protect cash if orders fall short [1]. [6] Examiner insight: Analysis credit comes from chains of cause and effect in each function; listing “recruit staff, get a loan” without the links earns little.

11. (a) Week 2: (312 + 327 + 333) ÷ 3 = 972 ÷ 3 = 324 [1]. Week 6: (348 + 357 + 351) ÷ 3 = 1,056 ÷ 3 = 352 [1]. Average change = (352 − 324) ÷ 4 = 7 boxes a week [1]. Week 9 is 3 weeks after week 6: 352 + (3 × 7) = 373 boxes [1]. (b) The forecast suggests a steady upward trend of about 7 boxes a week [1]. At that rate deliveries reach 380 by week 10, so the shed will soon be at full capacity [1], and without more space Morwenna would have to turn customers away [1]. The survey supports continued growth because satisfied customers recommend the service [1]. However, the forecast rests on only seven weeks of data [1], which may reflect a seasonal peak rather than long-term growth [1]. Extrapolating seven weeks of data across a three-year lease is a large step, and reliability falls the further ahead it goes [1]. The supermarket’s scheme is exactly the kind of external change extrapolation cannot see [1]; with its buying power and wide reach it could take customers and reverse the trend [1]. A three-year lease is hard to reverse and adds fixed costs [1], so an over-forecast could leave Fothergale paying for unused space [1]. Judgement: Morwenna should not rely on this forecast alone; she should gather a longer run of data or consider short-term options, such as extra shifts, until the effect of the supermarket’s scheme is clear [1]. Examiner insight: Strong evaluations use the calculated forecast and the case details (lease length, new rival, short data run) to reach a supported decision, rather than discussing forecasting in general.

Where marks are usually lost

• Placing a moving average against the third period instead of the middle period.
• Dividing the total change by the number of moving averages instead of the gaps between them.
• Counting periods ahead from the last actual figure instead of the last moving average.
• Dropping the sign on a forecast error, or not saying whether sales were above or below forecast.
• Leaving units off a forecast, or giving a fractional number of products.
• Explaining difficulties of forecasting in general with no link to the business in the case.
• Treating a forecast as a certainty when evaluating a large, hard-to-reverse decision.
• Ending an evaluation without a clear, justified judgement.

Next steps

• Go over the formulas again in the analysing future sales revision notes
• Reread the worked examples in the analysing future sales study guide
• Browse every 9725 page from the OxfordAQA A-level Business hub
• Tick off what you have covered on the printable 9725 checklist
• Spot weak topics: all free 10-minute diagnostics
• How to answer case-study questions: 9725 exam preparation guide
• Book a free trial class

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.