Valuing a show launch pipeline without paying twice for the same growth

The information memorandum runs to ninety pages and the five year plan sits on page forty one. Revenue climbs from 38.0 million to 47.5 million. Four of those years carry a launch, and each launch has a name, a hall and a target square metre figure. On page sixty three the adviser argues that the multiple should sit at the top of the range because the group has a proven launch capability.

Valuing a show launch pipeline is the part of the deal where the same growth gets sold to you twice, once inside the earnings you are paying a multiple on and once as a reason for that multiple to be higher. Neither the buyer nor the adviser is being dishonest. The two claims live in different sections of the same document and nobody reconciles them.

The fix is arithmetic rather than argument. Value the pipeline on its own, on stated assumptions, then go back and check what the base plan already contains.

Where the double count hides

A trade show group's plan usually mixes three sources of growth in one line: price and volume on the shows that already exist, revenue from shows acquired part way through a period, and revenue from launches. Listed groups are made to separate these. Informa's 2025 full year results reconcile reported revenue growth of 13.7 per cent into 6.3 per cent underlying, 1.3 per cent from phasing and other items, 8.0 per cent from acquisitions and disposals, and minus 1.9 per cent from currency. Once the decomposition is published, nobody can present the acquired 8.0 as evidence of organic momentum.

A private seller publishes no such reconciliation. The plan shows a single revenue line going up, and the launches are inside it. So when the adviser argues for a pipeline premium on top, the question to ask is whether the year five EBITDA the multiple is being applied to already includes the launch contribution. In most memoranda I have read, it does.

That is the whole double count, and it is worth stating plainly because it is easy to miss under time pressure. If year five EBITDA of 9.1 million includes 1.2 million of launch contribution, and you pay 9x on that number, you have already paid 10.8 million for launches that have not opened. A separate pipeline premium on top buys the same 1.2 million a second time.

What is a launch actually worth before it opens?

Very little, and the reason is compounding probability rather than pessimism about the concept.

A launch has to clear several gates in sequence. It has to sell enough space to run at all. It has to bring enough of the right buyers that exhibitors rebook. It has to survive the second edition, which is where most of the space sold on curiosity does not return. Then it has to reach a scale where the contribution covers the team time it consumes.

Blau, Pekny, Varma and Bunch set out the formal version of this in the Journal of Product Innovation Management in 2004, working on pharmaceutical development pipelines. Their case study runs nine interdependent candidates targeting three diseases, and the point that transfers cleanly to exhibitions is that candidates compete for the same scarce resources, so the value of the portfolio depends on the sequence you develop them in. Their optimised sequence produced an expected return 28 per cent higher than the conventional bubble chart ranking at almost the same level of risk. They evaluate the pipeline on expected net present value and report a risk measure they call the probability of losing money, which is a more useful pair of numbers for a launch portfolio than a single plan figure.

The exhibitions version needs three inputs per launch: the contribution at maturity, a cumulative probability of getting there, and the cash you burn on the way.

Probability weighting four launches, worked

Take the four launches in the memorandum. At maturity, defined as the fourth edition, the plan credits them with contribution of 900,000, 1,400,000, 600,000 and 1,100,000. That is 4,000,000 of mature contribution in total.

Now the survival probabilities. Build them as a chain rather than a single number, because the gates are sequential. Say the seller's own record shows 85 per cent of launches reach a second edition, 70 per cent of those reach a third, and 62 per cent of those reach a fourth with positive contribution. The cumulative probability is 0.85 multiplied by 0.70 multiplied by 0.62, which is 0.369.

Apply that to the mature contribution: 4,000,000 times 0.369 is 1,476,000 of probability weighted contribution, arriving in year four.

Discount it. At a 12 per cent deal discount rate, four years out, the factor is 1 divided by 1.12 to the fourth, which is 1 divided by 1.5735, or 0.6355. So 1,476,000 times 0.6355 is 938,000.

Then subtract the money you spend getting there. Each launch runs at a loss for its first three editions. Assume 240,000 of cumulative loss per launch, spread as 120,000, 80,000 and 40,000 across editions one to three. Across four launches that is 960,000 of nominal loss, and importantly it is spent whether the launch survives or not, so it does not get probability weighted the way the upside does. Discounted at 12 per cent, roughly 480,000 in year one, 320,000 in year two and 160,000 in year three gives 428,600 plus 255,100 plus 113,900, which is 797,600.

The pipeline is worth 938,000 less 797,600, which is 140,400. Against a plan that credits it with 4,000,000 of contribution.

Read that carefully. A pipeline of four unopened shows, on the seller's own survival record, carries about 140,000 of value today, and any price above that is paying for optimism. Launches can still be worth doing. This calculation prices the ones sitting in someone else's plan. The build against buy comparison is where you decide whether to fund launches at all. This calculation only prices the ones already in someone else's plan.

How do you check the base plan does not already contain it?

Ask for the plan with the launches stripped out, and read what happens to the growth rate.

If the seller can produce it in a day, they have modelled launches as a separate layer and the reconciliation is easy. If it takes two weeks and comes back with the same year five number, the launches were never a separate layer and the plan is a single trend line with names attached to it.

The test I use is a subtraction. Total plan growth over five years here is 47.5 million less 38.0 million, which is 9.5 million. The four launches contribute 4.0 million of that at maturity. So 5.5 million, or 58 per cent of the plan, comes from the existing shows, and 42 per cent comes from shows that do not exist. Then look at what the existing shows have actually done over the last three editions. If they have grown at 2 per cent a year and the plan has them at 5 per cent, the base is also carrying optimism, and the two effects stack.

Emerald Holding's 2025 results show what an honest decomposition looks like on the other side of the ledger. Full year revenue of 463.4 million dollars was up 64.6 million, made up of 66.4 million from acquisitions and 4.4 million of organic revenue growth, offset by a 6.2 million decrease from discontinued events. Organic growth of 4.4 million on a base of 392.6 million is 1.1 per cent. A buyer reading only the 16.2 per cent headline would form a very different view of the underlying business.

Structuring the price so the risk sits with the evidence

My preference is to refuse the pipeline premium and put the launch value into an earn out instead, defined on the launch itself rather than on group EBITDA.

Write it as a payment per launch that triggers when a named edition, usually the third or fourth, reports contribution above a stated floor, measured on a definition both sides sign at completion. Cap it. Set the total earn out somewhere near the probability weighted figure you computed, so the seller receives roughly the expected value if their survival record repeats and materially more if they beat it.

This does two useful things. It removes the argument about whose survival probability is correct, because the money follows the outcome. And it stops the seller from launching four weak shows in the year before completion to fatten the pipeline slide, since a launch that dies in edition two pays nothing.

The one place I would break my own rule is where a launch has already sold a meaningful share of its floor. A show with 60 per cent of target square metres contracted for an edition six months out has passed the hardest gate, and treating it at a 0.369 cumulative probability understates it badly. Price that one closer to a normal show with a short history, and use your own launch survival record only for the ones still on paper.

Where this stops

The survival chain is the weakest link in the whole calculation, and most groups cannot produce it honestly.

Getting 85, 70 and 62 per cent out of your own history needs a defensible list of every launch attempted, including the ones that were quietly folded into another show or renamed after a bad first edition. Those disappear from the record precisely because nobody wants to count them, and their absence biases the survival rate upward. A group that reports a 70 per cent launch survival rate has usually deleted the denominator rather than beaten the odds.

The second limit is that the discount rate does a lot of work here and it is genuinely arguable. At 12 per cent the pipeline came to 140,400. At 9 per cent the same numbers give a discounted upside of 1,045,600 against discounted losses of 833,300, so 212,300. At 15 per cent it goes to 843,900 less 764,600, or 79,300. The direction never changes, but anyone who wants a bigger number can find one inside a defensible range, which is why the assumption belongs on the page next to the answer rather than in a model tab.

None of this replaces the judgement about whether the sector supports another event, and it says nothing about what the existing shows are worth, which is set by the multiple the base business is priced on and belongs in a different conversation.

This week, take the last plan your own group approved and separate it into two lines: revenue from editions that have already run, and revenue from editions that have not. Then work out what share of next year's growth target depends on shows nobody has yet sold a square metre of. That share is your own pipeline exposure, and reading it against the synergy and portfolio view is a cheaper exercise than discovering it in someone else's data room.