Living Lab’s first economic model was for the Singapore Grand Prix in 2012. In 2025 we became a software platform: government-grade intelligence for the visitor economy
Aviation route development starts with demand, not a comparator. Living Lab connects the airline’s network data, the airport’s traffic statistics, and the destination’s accommodation and event figures, so a route is assessed against the demand it would serve and the destination value it carries, not the demand a comparator route happens to show. Passenger forecasting standards are set out by ICAO.
Attributes what a route already delivered for the destination against the case that funded it: visitor spend, hotel nights, GVA, tax, and jobs, per route, on one method. Whether the incentive bought demand or paid for demand that would have flown anyway. Signal137 is the post-launch account, on the same evidence base used to plan the route.
Tests a route’s viability, frequency, or incentive case before the slot is committed. Whether the extra frequency is worth committing before demand has proven it, and what load-factor trigger should release it. Whether public co-funding demonstrably changes the outcome. Demand137 ties incentive funding to destination value delivered, not seats flown.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Is this route viable at launch, and at what frequency? | Demand vectorised by origin, timing, purpose, and price sensitivity for that specific city pair | The route sized to the demand that is there, not the comparator route's demand |
| Demand137 | When to grow, hold, or withdraw an existing route | Current performance against the vectorised demand case, not load factor alone | The network change timed to the evidence, not the review calendar |
| Demand137 | How much destination value does the route deliver? | Route demand connected to accommodation, event, and investment signals in the destination | Incentive funding tied to destination value, not passenger volume |
| Demand137 | Should we commit airport incentive or public co-funding? | A bounded case with a stated counterfactual and downside | Funding committed only where it demonstrably changes the outcome |
| Demand137 | Is the extra daily frequency worth committing now? | The daily case from month six, subject to a load-factor trigger, net of the added capacity cost | The frequency released on a trigger, not a hope |
| Demand137 | Can this work for a route with no comparator anywhere? | Built up from origin-market and destination-side signals, not borrowed from another city pair | No dependence on another route looking similar enough |
| Signal137 | What did the route we supported actually deliver? | Attributed destination value against the case that funded it | The renewal negotiated from evidence |
| Signal137 | Did the incentive buy anything? | The route's result set against the counterfactual of no support | Public money is not spent on demand the market would have delivered anyway |
| Both | Does this need airline booking data we cannot share? | No. Route demand vectorised from destination-side and market signals | The airline's data is not a precondition |
| Both | Who holds this, and where? | Model, data, and a trained team inside your jurisdiction | The capability survives the change of planner or official |
A hotel pipeline decision is usually made on an occupancy trend, extrapolated forward. That answers a different question from the one a planner, a developer, or an investor faces: is the market short of rooms overall, or short of rooms on the 18 nights a year when demand peaks?
A new route photographs well on launch day. Whether it is still flying in year three, without deep discounting, and still worth the airport incentive that started it, is a quieter question, and it is the one that comes up at renewal.
A race track, an arena, a stadium: each is built for a peak it reaches a few dozen times a year. The gap between peak and off-peak operational need is the commercial challenge behind every sports-anchored development, and the reason mixed use is the answer rather than the fashion.
Most destinations run near capacity for part of the year and well below it for the rest. A visitor added in the peak displaces one already there. A visitor added in the shoulder fills an empty room and is served by staff who would otherwise be idle. Almost no destination runs the calculation before fixing a date.
We turn messy event and tourism data into decisions that help communities grow. Bring curiosity and rigour. We will hand you questions nobody has answered yet.
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