A hotel, resort, or mixed-use scheme is a bet on the demand a site can reach. Living Lab shows what the location’s routes, calendar, and origin markets can deliver across the year. It sizes the scheme to that demand, on the same numbers.
One model of the demand around the site: every route in and its seat capacity, the drive-time catchment, the hotel supply and rate in the market, every event on the calendar, and the search interest and sentiment in each origin market. Signal137 measures what a delivered phase actually produced against the case. Demand137 shows what demand exists at this location by origin, season, and purpose, with the access ceiling as the cap. The feasibility study covers this site.
What a delivered phase produced against what was forecast: rate, occupancy, and spend attributed to the events, routes, and markets that drove them. Where the case held and what it leaned on. What the opening did to the surrounding market and the city, in GVA, tax, and jobs. Displacement and counterfactual stated. The evidence for the next phase and the refinancing, on one method.
What the site can physically reach: seats on the routes, the drive-time catchment, the last mile. Phasing tested against the calendar and the supply pipeline. Base and downside cases with the interval stated. Every number marked observed, derived, or inferred.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | What scale can the site's demand sustain? | Demand vectorised across several cycles, not the single peak year used to size the massing plan | Unit count, room count, or footprint set against a tested range |
| Demand137 | Which phase first, and how fast to release the next? | A phased demand curve with the lead indicators that signal when a phase is ready | Phasing sequenced against demand as it arrives, not a fixed construction calendar |
| Demand137 | Does the scheme depend on infrastructure not yet secured? | The route, road, venue, or utility the demand case assumes, mapped and dated | Go or no-go, or phasing, conditioned on the dependency being secured first |
| Demand137 | Can local capacity absorb the scheme without stalling consent? | Labour, planning throughput, and existing visitor pressure in the catchment | A scale and phasing a planning committee can approve |
| Demand137 | How do we size and pace the scheme to what the demand supports? | The range shows it, with the assumptions stated | A lender can test the range because the assumptions are stated |
| Signal137 | Did phase one absorb as the case said it would? | Occupancy, rate, and absorption against the forecast, with the driver attributed | Phase two released on evidence |
| Signal137 | Was last season the trend, or the peak? | The strong season separated from the underlying demand, per property | The next phase is sized to the trend |
| Signal137 | What did the opening do to the surrounding market? | Displacement and new demand around the site, measured | The cannibalisation question answered before the next release |
| Both | Can this go into a planning application or a lender's technical report? | Every scenario states its assumptions, counterfactual, and uncertainty range | A planning officer or technical adviser can retrace it rather than take it on trust |
| Both | Do you need our scheme financials or land agreements? | No. Public and licensed market data plus the site, unit mix, and dependencies to be tested | Financial modelling built on the output stays with your own team |
Demand by origin, timing, purpose, and price sensitivity at the specific location. This is the demand this building can reach, not a regional average or a comparable set from another city.
Living Lab tests the market report against observed hotel pricing, event-driven demand, flight capacity, and search signals at the location. Where the report and the signal disagree, the developer sees it before committing.
Peak-year scale, sustained-demand scale, and phased release modelled against the demand curve. The developer sees what load factor justifies each stage and what triggers the next phase.
GVA, tax, jobs, and retained visitor spend stated on the same method the authority uses for any other public interest assessment.
Events create demand spikes and routes set the origin markets, and together they shape occupancy, seasonality, and average rate. A hotel next to a circuit with ten event weekends a year has a different demand profile from one serving a business district. Living Lab models the difference.
A hotel, a resort, or a mixed-use scheme fails underwriting when a single route, a single annual event, or a single source market turns out to be carrying more of the demand case than the committee realised. The dependency is the risk, and it can be measured before signature.
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.
Manchester United’s proposed stadium is a £2bn, 100,000-seat ground by Foster + Partners, with a target opening of 2030-31. The club and the regeneration case cite £7.3bn a year for the economy and 92,000 jobs. Those are the promoters’ projections. Here is what to test before believing them.
The owners of the Bulls and the Blackhawks are putting a reported US$7bn into 55 acres around the United Center: housing, a music hall, a hotel, retail, a park. The arena already hosts more than 200 events a year. The question a developer should ask is what the other 165 nights are worth.
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.
