Strabag SE builds a risk management solution to improve efficiency using Microsoft Intelligent Data Platform
Strabag SE, a global construction company, partnered with Microsoft to build a Data Science Hub to centralize decentralized data and leverage it for insights. This initiative led to the development of an AI-based risk management solution that uses algorithms to pinpoint at-risk construction projects, resulting in significant time and cost savings.
The Business
Strabag SE, a global construction company, partnered with Microsoft to build a Data Science Hub to centralize decentralized data and leverage it for insights. This initiative led to the development of an AI-based risk management solution that uses algorithms to pinpoint at-risk construction projects, resulting in significant time and cost savings.
Strabag SE · Europe · Approximately 75,000 employees.
Before AI
Data was decentralized, stored in single units and business fields with no connection, making it difficult to leverage insights. Risk management was likely less efficient and proactive.
What Changed
Strabag SE built a Data Science Hub to centralize decentralized data and developed an AI-based risk management solution. This solution uses an algorithm to pinpoint at-risk construction projects.
The Result
The AI-based risk management solution saves the organization "huge amounts of money and time" by identifying potential risks in construction projects, reducing financial losses and improving operational efficiency.
Why this matters
AI Transforms Traditional Industries by Centralizing Data for Predictive Risk Management
Many traditional industries, often characterized by decentralized data and established manual processes, face significant challenges in modernization. Strabag SE's journey demonstrates that even in sectors like construction, centralizing data with a dedicated Data Science Hub can unlock AI-driven insights. This approach allows for the development of highly impactful, targeted AI solutions, such as predictive risk management, that directly address long-standing inefficiencies and prevent substantial financial losses. The focus on establishing a foundational data infrastructure before deploying advanced AI is a transferable blueprint for any company looking to innovate in a legacy industry.
Technology Used
Used for:
Source
Results are reported by the identified source/company and have not necessarily been independently verified by AI YAI YAI.
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