From the market to forecast turnover

With 2,000 households in her potential customer base and two competitors, Inès could write that she will take a third of the market: 667 customers and €80,040 of turnover, and more customers than her workshop can serve. With a 20 % share, she states €48,000. With 18 %, €43,200, and her first financial year turns into a loss. Two points of market share separate a profitable project from a loss-making one: that is where the study must be at its strongest.

Four levels, from the market to customers

The most frequent trap is to confuse the market with the customer base. To avoid it, you name four levels and skip none of them. Each level reduces the previous one for a written reason, and each reduction is justified by a source or by an observation.

Between the last two sits the reachable customer base, defined in the first module. For Inès, location rules no one out: all potential customers live within twenty minutes. Capacity, however, sets a ceiling: her 1,100 jobs a year, worked out below, serve at most 550 households at two visits each.

In this course, a market share is always expressed on the potential customer base: 20 % of 2,000 households, or 400 customers. It must stay below the ceiling of the reachable base, 27.5 %. Beyond that, the stated turnover assumes customers the workshop could not serve.

Building turnover from demand

The formula is simple: captured customers × purchase frequency × average price excluding VAT. For Inès: 2,000 households × 20 % = 400 customers; her questionnaire records two repairs a year on average, giving 800 jobs; at an average price of €60 excluding VAT, first-year turnover reaches €48,000.

The official guidance asks for turnover to be entered for each element sold: goods bought for resale, goods produced, and services performed. If Inès also sells parts over the counter, that line is built separately, with its own customers, its own frequency and its own price.

All amounts are written excluding VAT. The value added tax collected is not income of the business: it is paid over. A price displayed including tax at a competitor must therefore be brought back to its pre-tax amount before entering the calculation, otherwise turnover is overstated from the very first line.

Checking against capacity

A figure built from demand must be compatible with what the business can produce. Based on her interviews with repairers in other towns, Inès estimates that one person working alone completes five jobs a day. Over 220 opening days, her capacity is 1,100 jobs a year.

The 800 jobs of the first year, 400 customers out of 550 reachable, take up about 73 % of her capacity. That leaves room for seasonal peaks. Had demand produced 1,500 jobs, turnover would have been capped by capacity, unless someone were hired, a cost the forecast would then have had to carry.

Capacity is calculated on the time actually available for production. A founder working alone also spends hours welcoming customers, ordering parts, keeping the books and answering messages. Five jobs a day assume that these tasks fit into the rest of the day; if they do not, the figure must come down, and the study must say so plainly.

Choosing a defensible market share

An equal split among competitors is a benchmark, not an assumption. A new entrant has neither the reputation nor the loyal customers of those already in place. Announcing a third of the market in year one amounts to assuming that customers will change their habits overnight.

A share is justified by observed facts, not by intentions. In Inès's fictitious survey, 12 of the 40 households concerned had their last repair done outside the area, which is 30 %. Neither of the two nearby workshops holds them: they are the least difficult customers to win.

Inès keeps 20 % for the first year: the gap with 30 % covers the time needed to become known and the households that will keep their habits. She did not ask households whether they would try a new workshop: as the previous module showed, the answer would mostly have been politeness.

The following years obey the same rule. Growth must have a cause: measured customer loyalty, a new service, a competitor leaving. Inès keeps 22 % in year two, then 25 % in year three, giving €52,800 then €60,000 of turnover excluding VAT.

Her cause is written down: first-year customers come back, and word of mouth widens the captured share as the workshop becomes known. A flat 10 % growth per year with no written cause is not an assumption: it is a setting, and nothing in the study can defend it.

Capacity then catches up with demand: 25 % of 2,000 households makes 500 customers and 1,000 jobs in year three, about 91 % of the 1,100 possible. The forecast must draw the consequence: beyond 550 customers, or 27.5 %, growth requires hiring or a second workstation, with their costs.

Comparing turnover with the break-even point

Turnover says nothing on its own: you need to know whether it covers costs. Inès plans €30,000 of fixed costs a year and parts amounting to 35 % of turnover. Her contribution margin is therefore 65 %, and her break-even point is €30,000 ÷ 65 %, or €46,153.85.

With €48,000 of turnover, the contribution margin reaches €31,200 and profit €1,200. The safety margin is only €1,846.15. The project holds, but only just: that is what the study must make visible, not hide.

The break-even calculator places the break-even date at around eleven and a half months. That date assumes steady activity, spread evenly over the year: it is the assumption the calculator states. Yet Inès's business is seasonal: her running sales total will cross the threshold earlier or later. The date shown is only an order of magnitude.

The calculation can be turned around to give the minimum number of customers: divide the break-even point by what one customer brings in over a year, and round up, since a customer cannot be divided. Compared with the potential base, that number gives the minimum share; this module's case study works it out for Inès.

The gap between the minimum share and the targeted share is the study's margin for error. That number, more than turnover itself, shows how accurate the study needs to be: the thinner the gap, the more solidly each customer assumption must be sourced.

Such a narrow margin calls for a written response in the study: cut fixed costs, raise the price if the comparison with competitors allows it, add a parts sales line, or plan enough starting cash to absorb a shortfall. A risk named in the study, with its remedy, is better than a risk discovered by whoever reads it.

Showing a cautious scenario next to the central one

Since the captured share is a choice, it is honest to show what becomes of the project if that choice proves too optimistic. Two columns are then presented: a central scenario, the one you defend, and a cautious scenario in which only the captured share falls. The other assumptions, being findings, stay unchanged.

Changing only one assumption at a time makes the reading immediate: the gap between the two columns has a single cause. Lowering everything at once, customers, frequency and price, produces a disaster scenario that says nothing useful, except about the author's ability to paint a table black.

The cautious scenario also says what the founder would do if it came true: cut opening hours, postpone an investment, draw on a cash reserve set aside for that purpose. Preparing for bad news shows that the project has an answer if it comes, and not merely the hope that it will not.

Rereading your figure before presenting it

• Is the area justified by a travel time, and linked to named municipalities?
• Does every number in the calculation point to a dated source or a described survey?
• Does the captured share stay below an equal split and below the reachable base, and is its value explained?
• Does the planned volume fit within production capacity?
• Are all amounts excluding VAT?
• Does turnover exceed the break-even point, and by how much?
• Does the growth in years 2 and 3 have a written cause?

A negative answer to any of these questions does not doom the project; it points to the page to rework before the meeting. It is far better to correct an assumption at home than to see it challenged during the meeting, with no figure at hand to answer.

Carrying the assumptions into the forecast

The official guidance describes the income statement as a table in which you enter your costs (expenses) and your income (receipts), and adds that if income exceeds costs the result is a profit, otherwise a loss. The three annual turnover figures built here form its first line.

ActioFin's forecast income statement calculator takes, for each year, this turnover excluding VAT and costs by type: purchases, overheads, taxes and duties, staff, depreciation. It also takes the loan's principal, rate and term. A year left blank carries over the amounts of the previous one.

It then works through contribution margin, gross operating surplus, operating profit, interest, corporation tax, net profit and cash flow. Under income tax, it calculates no tax at the level of the business. It proposes no market figure of its own: it calculates from those the study has established.

Seasonality is handled in the cash plan, not in the income statement. The guidance asks whether demand for your product is seasonal. If Inès's survey shows that repairs are concentrated in spring, the winter months will weigh on cash even when the year as a whole is profitable.

ActioFin's cash calculator does not model this seasonality: it works from average monthly turnover and purchases, constant from one month to the next. It reveals another trough, the start-up one, when payment terms leave the first months with no receipts. The seasonal trough has to be built separately, month by month.

For Inès, that means a twelve-column table in which the year's €48,000 is spread according to the calendar her survey describes, without changing the total. The calculator, for its part, takes the average of €4,000 a month: the two readings complement each other, one for the start-up, the other for the seasons.

The ratios obtained can be compared with those of the sector. INSEE's structural business statistics, produced by the Ésane system, describe the population of businesses and their characteristics each year. A variable cost rate far from the sector's is not necessarily wrong, but it must be explained.

Finally, the guidance recalls that forecast data must be updated every six months after the business is created. The first update compares the 400 customers expected with actual customers: if the gap is large, it is the captured share assumption that gets revised, and everyone knows where it is written.