Estimating, planning and delivery often take place in different systems. Connecting this information provides an up-to-date view of costs, progress and capacity. Deviations become visible earlier, along with their impact on the expected project outcome.

Historical project data adds a forward-looking perspective. Forecasts show how costs and schedules are likely to develop. Scenario analysis can then be used to calculate the impact of changes in phasing, material choices or capacity allocation.

A wealth of information is already available in project records, procurement data, planning tools and BIM models. Weather data, market developments and supplier information can also affect delivery.

A data platform brings these sources together in consistent reports. This makes risk indicators and deviations visible sooner. AI identifies patterns in historical and current project data, helping to improve the accuracy of forecasts.

Profitability starts before a contract is awarded. Historical project data and scenario analysis show whether a tender fits the organisation’s available capacity and risk profile. The scope available within defined sustainability parameters also plays a role.

This information supports an informed tender decision and speeds up estimating. It becomes clear sooner which projects are both feasible and profitable.

Conclusion connects data from project administration, planning, procurement and BIM. This provides reliable information for decisions on tender selection and project control. Sector specialists work alongside experts in data, AI and integration.