LumiBite (LB) produces chilled ready meals for supermarkets. Its marketing manager is preparing estimates of expected sales for the next six months before negotiating production capacity with suppliers.
Define the term sales forecasting.
NordTrail (NT) sells outdoor clothing through its website. The business has three years of monthly sales records. Sales usually rise sharply before winter and fall in early summer. NT’s operations manager wants to use these records when ordering inventory from overseas suppliers with long lead times.
Explain one benefit and one limitation for NT of using sales forecasting.
PulsePlay (PP) develops mobile fitness apps. The product manager has monthly subscription data, but several months include sales spikes caused by one-off influencer promotions. PP is considering using a moving average before making its next sales forecast.
Outline why PP might use a moving average in sales forecasting.
Apex Scoops (AS) operates ice cream kiosks in a coastal city. The finance manager compares actual monthly sales with a smoothed sales trend. She notices that sales are regularly higher than trend in July and August, but one unusually low month occurred after a major storm damaged the seafront.

Explain the difference between seasonal variation and random variation for AS.
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HarbourFit (HF) is a small chain of gyms. Membership sales increase every January and September. The human resources manager uses sales forecasts when planning personal trainer contracts, while the finance manager uses them when preparing the cash flow forecast.
Explain how sales forecasting could support workforce planning and financial planning at HF.
NovaScoops (NS) is a small manufacturer of frozen yoghurt sold to supermarkets. NS uses monthly sales forecasts to plan production and staffing. The marketing manager is concerned that recent weather changes have made forecasts less accurate.
Sales data for one product range:
Month | Forecast sales volume / tubs | Actual sales volume / tubs |
|---|---|---|
April | 4200 | 4100 |
May | 4600 | 4980 |
June | 7000 | 6300 |
Calculate the percentage forecast error for June using: forecast error = . Show all your working.
Comment on one limitation of sales forecasting for NS using your answer to part (a).
Kuppa (KP) sells reusable coffee cups online. KP uses sales forecasts to plan digital advertising expenditure and expected profit. The finance manager wants to check whether the September forecast justifies a campaign.
Forecast data:
Item | Figure |
|---|---|
Forecast sales volume for July / cups | 1200 |
Forecast sales volume for August / cups | 1400 |
Forecast sales volume for September / cups | 1600 |
Selling price per cup / USD | 12 |
Variable cost per cup / USD | 5 |
Fixed digital marketing cost for September / USD | 3000 |
Calculate the forecast total contribution for September. Show all your working.
Calculate the forecast profit for September after the fixed digital marketing cost. Show all your working.
Comment on one benefit of using sales forecasting for KP's financial planning.
UrbanBite (UB) operates a food truck near office buildings. UB uses daily sales forecasts to decide how many meals to prepare. The owner records unusual events to help identify possible random variation.
Daily sales data:
Day | Forecast meals | Actual meals | Event noted by owner |
|---|---|---|---|
Monday | 300 | 280 | Normal trading |
Tuesday | 320 | 315 | Normal trading |
Wednesday | 310 | 330 | Positive social media review |
Thursday | 340 | 260 | Heavy rain all lunch hour |
Friday | 500 | 520 | Normal trading |
Calculate the total weekly forecast variance in meals, using actual sales minus forecast sales. Show all your working.
Comment on whether the weekly shortfall is more likely to be random variation or seasonal variation.
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VitaPods (VP) sells refillable coffee capsules through supermarkets. Sales rose steadily for two years, so the marketing director used extrapolation to forecast further growth. A new environmental regulation has now reduced the use of some capsule materials, and a large competitor has launched a cheaper refillable product.
Explain two limitations for VP of using extrapolation for sales forecasting.
GlowGrow (GG) manufactures indoor plant-growing lamps. It has five years of quarterly sales data showing a clear upward trend and higher sales in winter. GG is considering expanding its production line, but recent energy price increases and several negative online reviews about product reliability may affect future demand.
Year | Quarter | Sales volume (units) |
|---|---|---|
Year 1 | Q1 | 150 |
Year 1 | Q2 | 110 |
Year 1 | Q3 | 90 |
Year 1 | Q4 | 130 |
Year 2 | Q1 | 160 |
Year 2 | Q2 | 120 |
Year 2 | Q3 | 100 |
Year 2 | Q4 | 140 |
Year 3 | Q1 | 170 |
Year 3 | Q2 | 130 |
Year 3 | Q3 | 110 |
Year 3 | Q4 | 150 |
Year 4 | Q1 | 185 |
Year 4 | Q2 | 140 |
Year 4 | Q3 | 120 |
Year 4 | Q4 | 165 |
Year 5 | Q1 | 200 |
Year 5 | Q2 | 150 |
Year 5 | Q3 | 130 |
Year 5 | Q4 | 180 |
Analyse the usefulness of sales forecasting to GG when deciding whether to expand production.
PedalPeak (PP) manufactures electric bicycles for urban commuters. PP has experienced increasing sales and wants to use extrapolation to estimate next year's sales volume before deciding whether to expand its factory.
Annual sales volume:
Year | Sales volume / bicycles |
|---|---|
2021 | 1800 |
2022 | 2300 |
2023 | 2700 |
2024 | 3300 |
Calculate the forecast sales volume for 2025 by extrapolating the average annual increase from 2021 to 2024. Show all your working.
Explain one benefit to PP of using this sales forecast when deciding whether to expand its factory.
HarbourStay (HS) operates a coastal hotel. HS uses time series analysis because demand for rooms changes during the year. The manager uses an additive seasonal model, in which seasonal variation is calculated as actual sales minus trend value.
Room-night data:
Period | Actual room nights sold | Trend value (room nights) |
|---|---|---|
Spring 2024 | 4800 | 4500 |
Summer 2024 | 6900 | 5600 |
Autumn 2024 | 5100 | 5300 |
Summer 2025 forecast trend value | — | 5900 |
Calculate the seasonal variation for Summer 2024. Show all your working.
Using your answer to part (a), calculate the forecast room nights sold for Summer 2025. Show all your working.
Comment on one limitation of using this forecast for HS.
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FitMeal (FM) sells monthly healthy meal-plan subscriptions. FM uses past subscription numbers to forecast future sales revenue, but a new competitor is expected to enter the market.
Subscription data:
| Year | Number of subscribers at year end / subscribers |
|---|---|
| 2021 | 900 |
| 2022 | 1200 |
| 2023 | 1450 |
| 2024 | 1750 |
The monthly subscription price is USD 30.
Year | Number of subscribers at year end / subscribers | Monthly subscription price / USD |
|---|---|---|
2021 | 900 | 30 |
2022 | 1200 | 30 |
2023 | 1450 | 30 |
2024 | 1750 | 30 |
Calculate the forecast number of subscribers at the end of 2025 by extrapolating the average annual increase from 2021 to 2024. Show all your working.
Using your answer to part (a), calculate the forecast annual sales revenue for 2025. Assume that the forecast number of subscribers applies in each month of 2025. Use the unrounded forecast from part (a) in your calculation and state your answer in USD. Show all your working.
State one limitation of FM using past sales data to forecast 2025 subscriptions.
MangoBike (MB) rents electric bicycles to tourists and commuters. During its first year, the booking system recorded some walk-in rentals incorrectly and the business did not separate tourist rentals from commuter rentals. The marketing director wants to base next year’s pricing, promotion and inventory decisions on the first year’s sales forecast.
Analyse the importance of data quality when MB uses sales forecasting for marketing decisions.
EcoGlow (EG) makes solar garden lamps. EG's marketing manager compares forecast and actual sales weekly to decide whether the forecasting method is reliable enough for stock control.
Weekly sales data:
Week | Forecast sales volume (lamps) | Actual sales volume (lamps) |
|---|---|---|
1 | 800 | 760 |
2 | 900 | 990 |
3 | 950 | 920 |
4 | 1000 | 1100 |
Calculate the mean absolute forecast error in units for the four weeks. Show all your working.
Comment on whether EG's sales forecasts appear reliable enough for stock control.
LumaSkin (LS) produces sunscreen. LS uses monthly sales forecasts to decide inventory levels. For July, LS planned available inventory equal to the forecast demand plus a safety stock of . A heatwave increased actual demand.
Forecast and inventory data:
Month | Forecast demand (units) | Actual demand (units) |
|---|---|---|
May | 5000 | 5300 |
June | 8500 | 8200 |
July | 12000 | 14500 |
Calculate LS's July stock shortfall or surplus, assuming planned available inventory was forecast demand plus safety stock. Show all your working.
Comment on the usefulness of sales forecasting for LS's operations planning.
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Solaro (SO) installs home battery storage systems for households with solar panels. SO’s sales team has recorded monthly enquiries and completed installations for four years. Sales usually increase after government announcements about energy prices and in months when electricity bills are sent to households. SO uses moving averages to smooth monthly sales data and to forecast installation bookings.
SO is considering whether to base its next marketing plan mainly on these sales forecasts. The marketing director wants to use the forecast to decide the timing of online advertising, promotional discounts and recruitment of temporary installation teams. The managing director is concerned that future sales may depend more on external factors than past sales: a possible change in government subsidies, new safety regulations, changes in interest rates and negative media coverage of battery fires in another country.

Using information from the stimulus and appropriate business concepts, discuss whether SO should base its marketing plan mainly on sales forecasts.
FreshLoop (FL) delivers weekly boxes of locally grown vegetables to households in one large city. FL is considering expanding into a second city. The marketing director has prepared a forecast for the first year in the new city by using sales patterns from the existing city. She believes the forecast should guide FL’s pricing, promotion and staffing decisions.
FL’s existing city has high brand awareness and many repeat customers. The second city has a younger population, more apartment living and two established competitors offering similar delivery services. FL has not previously traded there.
Selected data from FL’s existing city:
| Quarter | Actual boxes sold in existing city | Forecast boxes for new city | Forecast average revenue per box / USD |
|---|---|---|---|
| Q1 | 42000 | 18000 | 24 |
| Q2 | 47500 | 21000 | 24 |
| Q3 | 39000 | 16500 | 23 |
| Q4 | 52000 | 24000 | 25 |
Estimated additional fixed marketing cost for the new city in year 1: USD 160000.
Quarter | Actual boxes sold in existing city | Forecast boxes for new city | Forecast average revenue per box (USD) | Additional fixed marketing cost (USD) |
|---|---|---|---|---|
Q1 | 42000 | 18000 | 24 | |
Q2 | 47500 | 21000 | 24 | |
Q3 | 39000 | 16500 | 23 | |
Q4 | 52000 | 24000 | 25 | |
Year 1 fixed marketing cost | 160000 |
Using the data provided, to what extent should FL rely on sales forecasting when planning its expansion into the second city?
BeanRoot (BR) manufactures plant-based ready-to-drink coffee in recyclable cartons. BR sells mainly through independent cafes and university shops. Sales have grown over the last three years, but the pattern is uneven: demand rises strongly at the start of university terms and falls during vacation periods. BR’s marketing manager has prepared a quarterly sales forecast using time series analysis and extrapolation of the trend. The forecast suggests that BR could justify investing in a second production line and signing a two-year supply contract with a national supermarket chain.
However, BR’s operations director is cautious. A recent increase in milk-alternative prices may raise BR’s selling price, and two large competitors have launched similar products. BR also had one unusually successful quarter after a celebrity posted about its products on social media. The finance director argues that, despite these uncertainties, a sales forecast is needed to prepare cash flow forecasts, plan inventory and coordinate marketing with production.
Quarter | Actual sales volume ('000 cartons) | Smoothed trend ('000 cartons) | Seasonal variation ('000 cartons) | Forecast sales volume ('000 cartons) |
|---|---|---|---|---|
2022 Q1 | 55 | 50 | +6 | — |
2022 Q2 | 43 | 51 | -8 | — |
2022 Q3 | 40 | 52 | -12 | — |
2022 Q4 | 57 | 53 | +4 | — |
2023 Q1 | 60 | 54 | +6 | — |
2023 Q2 | 47 | 55 | -8 | — |
2023 Q3 | 67 | 56 | -12 | — |
2023 Q4 | 62 | 57 | +4 | — |
2024 Q1 | 64 | 58 | +6 | — |
2024 Q2 | 51 | 59 | -8 | — |
2024 Q3 | 50 | 60 | -12 | — |
2024 Q4 | 66 | 61 | +4 | — |
2025 Q1 | — | 62 | +6 | 68 |
2025 Q2 | — | 63 | -8 | 55 |
2025 Q3 | — | 64 | -12 | 52 |
2025 Q4 | — | 65 | +4 | 69 |
Evaluate the usefulness of sales forecasting to BR when deciding whether to invest in a second production line.
DriftWear (DW) manufactures waterproof jackets made from recycled materials. DW sells mainly through outdoor retailers. The operations director wants to invest in an automated cutting machine that would increase annual capacity by 40%. The investment would require a long-term loan and would only be profitable if sales continue to grow.
DW’s marketing manager has used past sales data to prepare a sales forecast. She argues that sales forecasting will reduce uncertainty before the investment decision is made. However, a large sportswear brand has recently launched a lower-priced recycled jacket range.
Selected sales data for DW:
Year | Actual sales volume / jackets | Forecast sales volume / jackets | Average selling price / USD |
|---|---|---|---|
2022 | 18000 | 17500 | 95 |
2023 | 21500 | 21000 | 96 |
2024 | 26000 | 24500 | 98 |
2025 | 28600 | 31000 | 98 |
2026 forecast | 34500 | 99 |
Using the data provided, evaluate the usefulness of sales forecasting to DW when deciding whether to invest in the automated cutting machine.
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AeroCharge (AC) sells portable phone chargers at music festivals and through its website. Demand is highly seasonal because most festival sales occur between May and August. AC’s marketing manager has used time series analysis to forecast sales for the next festival season. She recommends increasing inventory and hiring temporary sales staff.
The operations manager is concerned that the forecast may be unreliable. Several major festivals are moving to cashless payment systems that rent chargers to customers on-site. AC is also planning a new premium charger with a higher selling price but limited past sales data.
Selected sales information for AC:
| Period | Actual sales volume / chargers | Trend value / chargers | Forecast sales volume for next comparable period / chargers |
|---|---|---|---|
| Spring 2025 | 8200 | 9000 | 9100 |
| Summer 2025 | 24600 | 18500 | 25200 |
| Autumn 2025 | 9600 | 10800 | 10100 |
| Winter 2025 | 7200 | 8500 | 7600 |
Expected temporary staffing cost for Summer 2026: USD 38000.
Period | Actual sales volume / chargers | Trend value / chargers | Forecast sales volume for next comparable period / chargers | Expected temporary staffing cost for Summer 2026 / USD |
|---|---|---|---|---|
Spring 2025 | 8200 | 9000 | 9100 | — |
Summer 2025 | 24600 | 18500 | 25200 | — |
Autumn 2025 | 9600 | 10800 | 10100 | — |
Winter 2025 | 7200 | 8500 | 7600 | — |
Summer 2026 staffing cost | — | — | — | 38000 |
Using the data provided, recommend whether AC should base its Summer 2026 marketing and operations plans mainly on the sales forecast.
Read the resources and answer the questions that follow.
RRB collects donated textbooks, refurbishes them and sells low-cost exam revision packs to schools. Surpluses fund free reading clubs for children in low-income areas. RRB’s founder, Nia, stated: “If we forecast demand badly, either pupils miss out because we have no packs left, or cash is tied up in books no school wants.” RRB wants to open three temporary pop-up stalls near examination centres next year.
RRB’s current workshop capacity is 4500 packs per quarter without overtime, or 6500 packs per quarter with overtime and extra volunteer shifts. Unsold packs become less useful when examination syllabuses change. Some donated books arrive in poor condition and cannot be used.
RRB has 82 000 social-media followers, but posts reach between 8% and 35% of followers depending on the platform algorithm. Two schools have asked RRB to guarantee minimum stock levels before signing supply agreements.
Quarter | Forecast sales volume / packs | Actual sales volume / packs | Notes recorded by RRB |
|---|---|---|---|
Q1 | 2400 | 2600 | Normal trading |
Q2 | 5200 | 7100 | One large school tender and a viral student video |
Q3 | 3100 | 2800 | Supplier shortage of science textbooks |
Q4 | 6100 | 5400 | Competitor donation campaign |
Describe one benefit to RRB of using sales forecasting for operations planning.
Using Resource 2 and Resource 3, explain two limitations of RRB relying on past sales data to forecast demand.
Using all the resources provided and your knowledge of business management tools and theories, recommend a plan of action for RRB to use sales forecasting to support the proposed pop-up stalls while maintaining its social mission.
Read the resources and answer the questions that follow.
WW refurbishes used smart thermostats and installs them at a discount in homes affected by fuel poverty. Full-price online sales to environmentally conscious customers help finance the discounted installations. WW’s mission statement is: “Lower energy bills, less waste and warmer homes.” WW is considering a major winter campaign and may lease a larger workshop for two years.
WW has cash reserves equal to two months of expenses. The lease on the larger workshop would increase fixed costs but allow WW to refurbish 800 more thermostats per quarter. Components are imported with a 12-week lead time.
WW has 36 000 email subscribers and partnerships with four local councils. A new low-priced competitor has entered the online market. WW’s operations manager said: “Our past sales figures tell us a lot, but energy prices, weather and government grants can change demand very quickly.”
Period | Forecast sales volume / thermostats | Actual sales volume / thermostats | Main external factor |
|---|---|---|---|
Winter 2024 | 1800 | 2300 | Sharp rise in energy prices |
Spring 2025 | 1200 | 1150 | Normal demand |
Summer 2025 | 900 | 760 | Warmer than average weather |
Autumn 2025 | 1500 | 2050 | Temporary government energy-efficiency grant |
Describe one benefit to WW of using sales forecasting for financial planning.
Using Resource 2 and Resource 4, analyse the usefulness of time series analysis for WW.
Using all the resources provided and your knowledge of business management tools and theories, recommend a plan of action for WW to improve its sales forecasting before deciding whether to lease the larger workshop.
Koru Kidswear (KK) designs and sells premium school backpacks through its website and selected department stores. KK has experienced unpredictable sales. Some demand is seasonal because parents buy backpacks before the school year begins, but online sales also change quickly after influencer reviews and competitor promotions. KK has only recently entered overseas markets, where the school year starts at different times.
KK’s directors are considering three actions for the next 12 months:
The operations manager supports this plan, arguing that stock shortages last year damaged KK’s reputation. The marketing manager opposes reducing market research, arguing that overseas customers may have different preferences and that competitor promotions can quickly change demand. KK’s finance manager says the business cannot afford both high inventory levels and extensive market research unless the forecast is reliable.
Recommend whether KK should rely on sales forecasting when planning inventory and market research for the next 12 months.
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Read the resources and answer the questions that follow.
FBK turns surplus food from supermarkets into frozen meals and employs people who have been long-term unemployed. It sells meals through community shops and a small subscription service. Surpluses are reinvested in free cookery training. FBK is considering launching a new range of ready-to-cook family meal kits in two nearby cities.
FBK has only ten months of reliable subscription data. Until March, its sales system did not separate paid trial boxes from free sample boxes. The supply of surplus vegetables changes weekly. Meal kits would require new packaging, recipe cards and more accurate demand planning than frozen meals.
A social-media video about FBK received 150 000 views, but FBK does not know how many viewers became paying customers. A charity partner said: “Expansion could create jobs, but only if FBK avoids wasting food and cash on products customers do not buy.”
Month | Forecast sales volume (meal boxes) | Actual sales volume (meal boxes) | Notes recorded by FBK |
|---|---|---|---|
January | 900 | 880 | Normal trading |
February | 950 | 1100 | Local news report about food waste |
March | 1000 | 910 | Several delivery delays |
April | 1050 | 1240 | Partner gym promoted FBK online |
Outline one limitation for FBK of using sales forecasting for the proposed new meal kits.
Using Resource 2 and Resource 3, explain two benefits to FBK of using sales forecasting when planning the new meal kits.
Using all the resources provided and your knowledge of business management tools and theories, recommend a plan of action for FBK to use sales forecasting when deciding whether to launch the new meal kits in two nearby cities.