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
Hotel supply and demand analysis. Living Lab connects the tourism board’s forecast, the hotel association’s occupancy report, the short-term rental listing count, and the route data that usually sit on separate schedules, so a new route, a major event, or a rival’s price move is traced through to hotel demand. Reference data is published by UN Tourism.
Attributes what the last approval did to the market: whether the new rooms were filled by demand or by discounting, whether short-term rental listings absorbed the overflow, whether the peak the case was built on recurred. Signal137 shows the committee what the pipeline actually delivered, so the next approval is sized on evidence.
Tests the pipeline before it is approved: no new supply, demand grows with no response, new supply at the proposed scale. The peak-night gap beside the average-night occupancy, so the committee sees whether the development solves the actual problem or adds average-night competition. Demand137 sequences keys so each opening is absorbed before the next.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Whether to approve new room supply, and at what scale and class | Demand vectorised by origin, purpose, timing, and price sensitivity, not an occupancy trend alone | Supply sized and phased against the demand pattern, not the headline trend |
| Demand137 | Where and when will compression nights concentrate? | Event calendar, route capacity, and comparable-market seasonality, linked | Pricing, inventory, and staffing matched to the modelled compression window |
| Demand137 | Can existing stock, short-term rentals included, absorb demand without new build? | Total effective supply, not licensed hotel stock alone | Approvals right-sized against real, not partial, capacity |
| Demand137 | How many short-term rental licences to release, or withdraw? | The yield, displacement, and fiscal effect of each licensing level | Licences move with hotel supply, not against it |
| Demand137 | In what order should the keys open? | Absorption by location and by year, so each opening is filled before the next | Rooms approved that demand will fill, sequenced so none sit empty |
| Demand137 | Can this tell us not to build? | Yes. If the gap is covered by existing and informal supply, or the peak is too short, that is the result | The proposal is not the answer the model was built to give |
| Signal137 | Did the last approval fill with demand or with discounting? | Occupancy and rate for the new stock set against the counterfactual | The next approval sized on what the last one did |
| Signal137 | Did the peak we built for recur? | The strong season separated from the underlying trend | The pipeline is sized to the trend, not the memory |
| Both | What is the difference between this and capacity, pricing, and market pressure? | This decides whether and where new supply is warranted; that page covers the operational response once supply is fixed | Buyers use this first, at the planning or investment stage |
| Both | Who holds this, and where? | Model, data, and a trained team inside your jurisdiction | The capability survives the change of official or consultant |
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.
On 13 June 2026 Scotland played Haiti at Gillette Stadium. Around 50,000 Scottish supporters travelled. Boston’s bars sold beer at roughly four times the volume of a Fourth of July weekend, and some ran dry. Every signal that would have warned them was visible weeks ahead.
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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