The Root Causes of Poor Cost Estimation in Industrial Projects 

In industrial settings, figuring out the costs of engineering and construction projects is a common but tough problem. Many professionals rely on past data instead of using detailed information from their current project plans. 

These project plans, known as industrial drawings, come in many types like P&IDs (Piping and Instrumentation Diagrams), isometrics, wiring diagrams, and loop diagrams. They often have different resolutions and are usually not in digital formats. This makes it hard to extract useful data from them. 

Estimators have to manually go through physical drawings, counting and highlighting items, which is very time-consuming and not very accurate. To be safe, they often overestimate the costs to cover any uncertainties. This method is difficult and far from perfect.

• Scarcity of Accurate Data: Accurate and relevant benchmark data from comparable projects or organizations is scarce. Differences in standards, scale, and specific project requirements make precise cost predictions difficult.  

• Manual Processes: The manual process of estimating costs by counting items on physical diagrams is time-consuming and prone to human error.  

The Consequences  

• Inaccurate Estimations: Relying on historical benchmarks can lead to cost overruns, delayed schedules, and scope creep. 

•  Low Win Rates: Inaccurate estimates can result in low win rates on lump sum project bids due to padded contingencies.  

Estimators could achieve more accurate results if cost estimation were driven by actual data from industrial drawings, minimizing overall risk and optimizing project activities like bidding, procurement, and construction. 

• Data-Driven Estimations: Utilizing AI to extract data directly from industrial drawings to drive cost estimations.  

• Enhanced Accuracy: Reducing the dependency on historical benchmarks by using real-time data extraction and analysis.  

How Can We Help You?   

HubHead and DataSeer’s AI Service combines human-level understanding with machine speed to build a scalable knowledge data store of engineering designs. By integrating these solutions with your existing EAM/CMMS systems and creating a digital twin, you can enhance decision-making and streamline your maintenance processes. Contact us for a free demo or book a call.