Know what is likely to happen before it hits the site.
Forward-looking operational intelligence built from actual APG evidence, future booking demand, recent site behaviour and transparent forecast rules. Forecasts support decisions; they do not replace programme, commercial or safety controls.
How many people are likely to be on site, on which days, and when are they likely to leave?
Whole-site workforce forecast built only from innDex / turnstile attendance. APG Labour and DABS are deliberately not substituted for project workforce.
Loading turnstile evidence…
Where is the workforce likely to concentrate across the building?
Uses physical Headcount evidence to learn level concentration, then reconciles it with the whole-site turnstile workforce forecast. APG keeps an explicit unlocated reserve rather than pretending every forecast person can be assigned to a floor.
Predicted level concentration · pressure day
Forecast people by level from observed spatial behaviour.
Forecast location coverage by day
How much of the predicted workforce APG expects to be physically locatable from Headcount behaviour.
Subcontractor spatial tendency
Where the most frequently observed companies have historically concentrated.
Evidence strength
Physical Headcount coverage is scored separately from whole-site workforce confidence.
What could disrupt the forecast?
Operational programme proxies derived from workfaces, incoming materials, vertical logistics demand, labour pressure and delivery clustering.
Forward activity risk
Constraint radar · top 5
Potential programme exposure is a calculated planning proxy, not a contractual delay assessment.
Workforce, Hoist and level pressure.
Forecasts combine weekday behaviour, recent trend, upcoming booked materials and actual site demand patterns.
Labour demand by day
Hoist demand by day
Logistics pressure forecast by level
Predicted Hoist journeys, level direction and journey time.
Forecasts use measured Hoist journeys to predict both movement TO each level and movement FROM each level, alongside journey duration and load behaviour. Journey P50 and P80 remain separate.
Predicted vehicle visits by day, likely arrival times, booking behaviour and dwell.
Forecasts use historic weekday volumes and actual arrival-time behaviour to show roughly how many vehicles are expected each day, when they are most likely to arrive, and their predicted booked, not-booked, early, late and dwell behaviour.
What bin load is likely on each level, and what waste type is most likely?
Uses the latest hourly counted set per level for each historical day, then applies weekday behaviour and a small, transparent incoming-material pressure adjustment. No extra data request is required.
Company intervention requirement, ranked by evidence.
Operational risk and evidence confidence are separate. High workforce or Hoist use is treated as pressure, not failure. Missing evidence cannot inflate a company to 100.
Company risk register · all evidenced companies · highest intervention requirement first
Trade behaviour comparison
Compact comparison of the same company evidence. Open only when you need to scan the whole list.
Open comparison
Trade behaviour comparison
Compact comparison of the same company evidence. Open only when you need to scan the whole list.
Three moves to protect the forecast.
The highest-value actions from predicted workforce, deliveries, Hoist demand, level pressure, Waste and Crane interaction.
How ready is the site for the forecast pressure?
Workforce, Delivery, Hoist, material readiness, interface pressure and constraints are scored separately before being combined.
Drivers reducing readiness
Materials, companies, likely destinations and arrival pressure.
Uses booked-delivery descriptions, explicit destination clues and recent company destination patterns. Inferred destinations are clearly labelled.
Turn live-project evidence into a preconstruction scenario.
Fast scenario model for anticipated deliveries, Hoist movements, peak labour and logistics management demand. This is a benchmark model, not a contractual estimate.
Model scales observed LSE logistics intensity by floor area, vertical complexity, duration and programme-intensity factors. Use it to challenge assumptions and size the logistics strategy, then validate against the tender programme.
What is measured, derived and forecast.
The module separates ACTUAL evidence, DERIVED metrics and FORECAST outputs. Confidence falls where evidence coverage is thin.