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
Event calendar optimisation. Living Lab connects booking and demand data across candidate and committed events, venue and workforce capacity, and hotel and short-term rental supply, so overlap becomes visible before it becomes a clash. Reference data is published by the OECD.
Attributes what each committed event delivered: jobs, tax, GVA, room nights, and retained value, net of displacement, on one method. Every event in the calendar ranked on the same terms, so the next round of choices starts from real results rather than each bid’s own promise. A drumbeat of evidence, every season, not a study in a drawer.
Tests which combination, timing, and sequencing of events builds the strongest calendar. Net incremental demand each event adds once the rest of the calendar is counted. Where two bids draw on the same source market, sponsors, volunteers, or rooms. Where a shoulder week with open capacity is worth more than a peak week that displaces demand already there. Demand137 paces the calendar to absorptive capacity, so the local supply chain grows into demand rather than losing it to imports.
| Product | Your question | You get | What it changes |
|---|---|---|---|
| Demand137 | Which combination of events to commit to across the calendar | Net incremental demand each event adds once the rest of the calendar is accounted for | The mix that maximises calendar-wide value, not the sum of individual bids |
| Demand137 | When and where to sequence events across the year | Seasonal demand pattern and capacity headroom by month, with the shoulder weeks priced | Events placed where they fill genuine gaps or defend genuine strength |
| Demand137 | Does this new bid duplicate or reinforce an existing event? | Overlap in source markets, sponsors, venues, and audience with events already committed | The bid accepted, adapted, or declined on its net effect on the calendar |
| Demand137 | How do we sequence so the supply chain grows with the calendar? | A calendar paced to absorptive capacity: caterers, ground transport, airlift | Local firms scale into the demand instead of losing it to imports |
| Demand137 | How far ahead can a calendar be planned this way? | One to three years where bids, venues, and hotel supply are defined; scenario-based beyond that, and stated as such | The horizon is honest about where certainty ends |
| Signal137 | What did last year's calendar deliver, event by event? | Every event ranked on jobs, tax, GVA, room nights, and retained value, on one method | The productive events supported; the mix optimised for retained value |
| Signal137 | Did the two spring events cannibalise each other? | Displacement between events in the same catchment and window, measured | The clash seen in the data before it is repeated |
| Signal137 | How does the flood compare with the tide? | The one-off tournament beside a full year of the ordinary calendar, on one method | The next bid priced against what the calendar already pays every year |
| Both | Does this replace our bid-evaluation process? | No. Your process tests whether one event stands up; this tests whether the approved mix makes a strong calendar | The two run side by side |
| 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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