Reducing workplace violence with data science

Key stats

• 700k daily passengers
• 45 day faster reporting
• 69 minute earlier alerts

Overview

Reducing workplace violence with data science

Industry: Transportation / Rail Operations
Company Size: 1,000–5,000 employees
Location: London, United Kingdom

Since opening in May 2022, the Elizabeth line’s passenger number have increased to 700,000 passengers a day. Its popularity has increased operational risk and information demands. MTR Elizabeth line identified an opportunity to improve threat and risk awareness and selected SIRV as its solution partner.

Services Provided:

• • Provision of urban and suburban passenger rail services under Transport for London (TFL)

  • Operations and management of the Elizabeth line

  • Customer service, station management, train crew services, and performance optimisation

The challenge

• Fragmented data: Internal data sets reflected different operational needs. There was untapped value in aggregating and mapping them to understand risk across the network.

• Dynamic threat picture: Risks in and around stations change quickly. A clearer view of ambient activity around each location was needed to improve situational awareness.

• High effort to use external data: Identifying, ingesting, cleansing and presenting relevant external data was time-consuming.

• Manual monitoring load: Live threat scanning across London and beyond required heavy manual effort. Introducing automation and AI would reduce time and improve consistency.

Goal: Deliver consistent, structured and timely data for immediate operations, near-term planning and longer-term reporting.

Solution

• • Discovery and scoping: Clarified objectives and launched a data discovery process to identify relevant open, closed and proprietary sources.

  • Data readiness: Accessed, cleansed and stored internal and ambient datasets for reliable use.

  • Operational visualisation: Built clear, role-appropriate views for immediate operations, near-term planning and longer-term analysis.

  • AI operational feed: Deployed an AI model to surface real-time operational intelligence and present actionable insights.

  • Delivery approach: A five-month mobilisation with weekly steering meetings and periodic management updates. The team comprised MTR operations and project leads with SIRV data and computer scientists.

Results and benefits

• Faster reporting: ~45-day reduction in time to report, improving workforce deployment.

• Richer risk picture: Deeper understanding of threats to staff and passengers, including comparative insights showing where reporting practice could improve.

• Better decisions: Evidence-based decisions supported across immediate, near and long-term horizons.

• Earlier awareness: Live threat and risk feed established; for example, the London Heathrow power cut was detected 69 minutes before mainstream media.

• Control room value: Real-time intelligence gives operators foresight to respond quickly.

• Agentic AI readiness: Workflows primed for automation.

• On-plan delivery: Key mobilisation milestones met.

Locations of interest

During mobilisation, a new data layer was added to highlight locations of interest. This supports safeguarding by drawing attention to areas used by more vulnerable passenger groups.

By combining intelligence from within the Elizabeth line and industry partners, SIRV helps decision-makers optimise deployment of resources such as BTP and contractors, improving the targeting of crime hot spots. The timely combination of internal and ambient data establishes a clearer, more accurate picture of threats and risks, so mitigation measures are better targeted.

Client testimonial

“The SIRV system allows for multiple data sets to be seen in a single application. It allows for Strategic, Operational, and Analytical overviews, which in turn influences our decision making processes and thereafter assists with managing risk within operations. We look forward to future system developments which we are sure will bring additional benefit.
Andrew and the SIRV team have been exceedingly understanding of our operational requirements and delivered in a professional and accommodating manner throughout.”

— Glen Higbee, Security Operations Manager, MTR Elizabeth line

Key takeaways

• Data science helps reduce workplace violence by revealing patterns and enabling targeted interventions.

• Artificial intelligence offers both automation and new operational opportunities.

• Reducing time to report has a significant impact on decision making and resource deployment.

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