Lena's number for 2026: It is January 2026. Lena and Marco sit down with last year's figures: the bakery took $1,600,000 in 2025, up from $1,430,000 in 2024.
| Their forecast for 2026 | Figure |
|---|---|
| Revenue | $1,840,000, a rise of 15% |
| The three shops | 1,200 loaves a day between them |
| Station Road, once it opens in September | Another 250 loaves a day |
On those numbers they will
- Fit out Station Road for $120,000.
- Buy a $45,000 oven.
- Hire two more bakers, so that Priti's night shift can bake 1,450 loaves a night.
Earlier in this topic you saw what a forecast is for: it lets a business plan staff, ovens, stock and money before the customers arrive. Now the other side.
A sales forecast is a prediction built from what has already happened. Every forecast quietly assumes that next year will behave like last year. That assumption is its biggest weakness (limitation), because the things that change sales most are often the things that have not happened yet.
Rivals move
- Crumbline plc, the fast-growing sandwich chain, opens a shop on the High Street in March
- Lunches grew 60% in 2025 partly because nobody nearby sold them. That growth is now at risk
- Goldcrust could cut the price of its loaves near Market Square again
The economy turns
- The town's biggest employer, a packaging factory, plans to cut 300 jobs in 2026
- Families with less to spend keep buying bread but cut cakes and lunches first
- Cake sales already fell 4% in 2025
Rules and tastes shift
- A new law, such as a tax on sugary food, can change prices overnight
- A trend, such as eating less white bread, can turn a growing line into a shrinking one
- None of these shows up in last year's figures
Right about the past, wrong about 2026: The bakery's forecast was made before Crumbline announced its High Street shop. Every figure in it was correct about 2024 and 2025, and it can still be wrong about 2026.
A forecast cannot allow for a change nobody knew about when it was made (external change). The bigger and more sudden the change, the further off the forecast will be.
So the first question to ask of any forecast is: what has changed, or might change, since the figures were collected? For Lena's Bakery the answer is a new rival for lunches, a cheaper loaf near Market Square and a town that may soon have less to spend.
It has happened before. Marco's forecast for Market Square in 2025 was 420 loaves a day. With Goldcrust's cheaper loaves two streets away, the shop sold 390.
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Marco asks a harder question. Not 'what might change?' but 'what is the $1,840,000 made of?' The answer is thinner than it looks.
The quality of a forecast can be no better than the figures it is built from (the data).
Four questions to ask of the data
How many years does it cover?
Lena's growth figure comes from one year: 2024 to 2025, up 11.9%. One year's rise is a single point, not a pattern. A trend needs several years before it can be trusted.
Was any year unusual?
Wholesale rose about 12% in 2025, most of it from one new hotel contract, and lunches jumped 60%. Jumps like these rarely repeat every year. A forecast that carries them forward comes out too high.
Is there any history at all?
Station Road has never sold a loaf. Its 250 loaves a day are borrowed from how the other shops sell, in other streets with other customers, and none of them has Crumbline selling coffee and a pastry for $3.50 at the station. A new shop has no figures of its own.
How far ahead does it reach?
Each year of a forecast is built on the year before it, so small errors grow. A 2026 figure can be checked by March; a 2028 figure is a guess built on two other guesses.
| Year | If sales grow 5% a year | If sales grow 15% a year | Gap |
|---|---|---|---|
| 2026 | $1,680,000 | $1,840,000 | $160,000 |
| 2027 | $1,764,000 | $2,116,000 | $352,000 |
| 2028 | $1,852,200 | $2,433,400 | $581,200 |
Two growth rates, far apart: Both growth rates are believable for a bakery opening a fourth shop. In 2026 they are $160,000 apart. By 2028 they are $581,200 apart, more than a third of the whole bakery's revenue in 2025.
Further ahead, less reliable: That is why a forecast is most useful for next month and least useful for three years ahead: the longer the period it covers (the time horizon), the less it can be trusted.
The same goes for the line of best fit from earlier in this topic. The line runs through the points you have and assumes the pattern carries on (extrapolation). With few points, or one odd year among them, the line can point the wrong way.
And two figures that rise together, such as lunch sales and the number of offices near the High Street, do not prove that one causes the other (correlation is not causation).
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Lena wants the shop: Lena has wanted a fourth shop for two years. Marco is less sure. The figure that says Station Road will sell 250 loaves a day is Lena's.
Optimism bias: People who want a plan to go ahead tend to believe the good numbers and explain away the bad ones (optimism bias). A forecast is numbers plus judgement, and judgement can lean.
Forecasting also takes time and money. Goldcrust plc has a team that forecasts every product in 400 bakeries every week. Lena's Bakery has Lena, on a Sunday evening, with a spreadsheet. The smaller the business, the rougher its forecast is likely to be.
Using a forecast that might be wrong
Forecast a range, not one number
$1,680,000 if sales grow only 5%, $1,840,000 if everything goes to plan. Two numbers show how sure the bakery really is.
Plan to survive the low case
Can the bakery still pay for Station Road and the oven if sales come in at $1,680,000? If yes, the plan is safe even when the forecast is wrong.
Check it every month
Real sales from the three shops arrive every day. Comparing them with the forecast each month shows early whether it was too high.
Ask the people who see the customers
Aisha, Kofi and Jonas see the queues. They will notice Crumbline's effect on lunches before any spreadsheet does.
Limits are not a reason to throw it away: A forecast with limits still beats no forecast. Without one, Lena could not plan the bakers, the oven or the money at all.
The skill is to use the forecast and know how far to trust it: close enough for next month, a rough guide for next year, a guess for three years out.
How this comes up: Sales forecasting comes up as a ten-mark discussion on a case, or as a two-mark explanation of one limitation or advantage.
| Question | Marks | What to do |
|---|---|---|
| Using the information in a case, discuss the benefits and limitations of sales forecasting for a business that is about to expand | 10 | Use the case: it gives you the forecast, the plan built on it, and the news that could upset it |
| Explain one limitation, or one advantage, of sales forecasting for a named business | 2 | The point, then what it means in the case |
The ten-mark pattern
- Benefits, from the case. What the forecast lets the business plan: capacity, staff, equipment, finance, stock. Use the case's numbers.
- Limitations of forecasting, from the case. What the forecast cannot see: the economy, a rival, a new law, a change in taste.
- Limitations of this data. How many years it covers, which years were unusual, what has no history, who made it, how far ahead it reaches. This is the step most answers miss.
- A judgement. How far the forecast can be trusted for this decision, and on what condition.
Two traps
- Discussing the plan, not the forecast. The question is about sales forecasting. Whether a fourth shop is a good idea is only the background; an answer about its rent and location is answering a different question.
- General limits only. 'Forecasts cannot predict the future' is true of every forecast. The strongest answers pick apart this forecast's data: one year of growth, a shop with no history, a figure set by the person who wants the shop.
Using the information in the case, discuss the benefits and limitations of sales forecasting for Lena's Bakery Ltd when deciding to open a fourth shop on Station Road.
Model answer plan
See the answer broken into clear points, with guidance on how each point earns marks.