Strabag SE, a global construction company, has partnered with Microsoft to drive digitalization and innovation in the construction industry. Recognizing the need for operational efficiencies through data, Strabag built a Data Science Hub in collaboration with Microsoft. This central entity enabled them to collect and leverage decentralized data for valuable insights.
One notable success is their AI-based risk management solution, which uses algorithms to identify at-risk construction projects. By predicting potential failures, Strabag saves time and reduces financial losses. The algorithm has achieved an impressive 80% accuracy in risk prediction with just three months of data.
Through Microsoft's Intelligent Data Platform, Strabag established a centralized system to connect and analyze data from various sources. This paved the way for developing use cases to improve operational efficiency and reduce costs globally.
What is Strabag SE's approach to risk management?
Strabag SE has developed an AI-based risk management solution that uses algorithms to assess potential risks in construction projects. By comparing new projects against historical data from previously completed projects, the solution can predict risks with an accuracy of 80% after just three months of data. This approach helps the company save time and reduce financial losses by identifying at-risk projects early.
How does Strabag SE leverage data for operational efficiency?
Strabag SE partnered with Microsoft to establish a Data Science Hub that centralizes decentralized data across the organization. This hub allows for better data sharing and analysis, enabling the development of use cases that demonstrate the value of data. The company aims to optimize operations and improve efficiency by leveraging insights gained from this centralized data approach.
What challenges does Strabag SE face in digitalization?
Strabag SE faces challenges related to the traditional nature of the construction industry, where data sharing and collaboration have not been prioritized. Employees often need multiple logins to access data, which can hinder efficiency. Additionally, there is a need to address employee anxiety regarding new technologies, as the company aims to reshape the culture around data and innovation to enhance overall productivity.