Using Big Data to reduce capex deviation


This solution uses Big Data based on historical data to reduce capex deviation and make costs changes more predictable. It incorporates an early warning system that predicts unexpected change cost based on the rework intensity of technical designs. In addition, its planning granularity indicator pinpoints the optimal degree of detail that a project plan should contain. Based on an ongoing data project that merges three disconnected data pools, the system can analyse high volumes of historical data from over 2, 000 projects and 700, 000 line items to make accurate predictions and significantly reduce change costs.

Problems solved

Project profitability loss due to unplanned changes


Reduction of costs due to change, early warning indicators

Key facts


Reduction in change costs


big data
data lakes
development and construction
engineering and planning
metals and mining
oil and gas

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