A venue is a thirty-year bet on where the audience can get to. Living Lab shows which shortlisted site the routes, roads and rooms can deliver an audience to, and what it will draw across the year.
One model of each candidate site and its catchment: the drive-time bands and isochrones, the routes in and their seat capacity, the hotel supply and rate nearby, the calendar the venue would compete in, and the search interest and sentiment in each audience market. Signal137 measures what an opened venue actually drew against its case. Demand137 tests each shortlisted site on what the demand can reach and what the venue would sustain.
What an opened venue drew: the catchment it reached by drive-time band and route, attendance by origin, utilisation across the year, spend in the venue and in the surrounding district, GVA, tax, and jobs, net of displacement. Where the case held and where it depended on one route or one anchor event. Year over year, on one method.
Which site on the shortlist the demand can reach: the access ceiling for each, by drive-time band, route, and last mile. Modelled utilisation across the year against the calendar the venue would compete in. Hotel supply and transport capacity on event nights. Base and downside cases with the interval stated. The cost of the wrong site priced before the land is bought. Every number marked observed, derived, or inferred.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Which site to choose from a shortlist | Demand catchment, connectivity, and comparable-venue utilisation for each option | Sites ranked by modelled demand and access, not land cost alone |
| Demand137 | What scale and configuration can the site sustain? | Modelled utilisation across the likely event and business mix, including seasonality | Capacity sized to a sustainable operating model, not an aspirational one |
| Demand137 | Is the operating model viable once built? | Demand-linked revenue scenarios tested against realistic operating costs | The financial case settled before capital is committed |
| Demand137 | Can the delegates and spectators actually get there? | Catchment by realistic travel time and mode, not an administrative boundary | The site chosen where the market can reach it often enough to sustain it |
| Demand137 | Can this tell us a site is not viable? | Yes. If the catchment cannot sustain the scale, or connectivity is too weak for the event mix, that is the result | The model does not favour the preferred site |
| Demand137 | Does the site depend on a transport link not yet built? | The dependency mapped and dated | Go or no-go conditioned on the link being secured first |
| Signal137 | What did the venue we opened actually draw? | Catchment and utilisation measured against the case | The next site decision starts from what the last one did |
| Signal137 | Is the venue creating demand or hosting it? | Gross attendance through counterfactual and displacement to attributable local value | The subsidy case rests on demand created, not on a full calendar |
| Both | Does this replace our planning or real-estate due diligence? | No. It answers the demand and viability question those processes do not | Land-use, planning, and cost due diligence run beside it |
| Both | How is commercially sensitive site information handled? | Under a confidentiality standard agreed in scope, particularly where the shortlist is not yet public | The shortlist stays private until you choose otherwise |
Each site tested against the catchment by mode: road, rail, air, and public transport.
Hotel and short-term rental supply mapped within the travel-time radius. A venue whose accommodation matches its catchment keeps multi-day events that would otherwise go elsewhere.
The proposed venue’s format, scale, and event profile tested against existing venue utilisation. Where it competes and where it fills a gap.
Actual catchment, utilisation, and event profile compared to the business case. Where the venue beats its plan and where the demand assumptions need updating.
Event frequency tested against transport capacity, accommodation supply, and resident tolerance. The sustainable calendar for the site, not the maximum.
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.
