Objectives

The primary objective is to procure, configure, integrate, implement, and deliver knowledge transfer for an existing Advanced Safety Data Analytics Solution. The initiative aims to enable proactive, intelligence-led railway safety regulation by leveraging predictive modelling, machine learning, safety risk forecasting, anomaly detection, and intelligent decision support. The solution must seamlessly integrate with the Railway Safety Regulator’s existing data infrastructure to consolidate information and drive evidence-based regulatory actions.

Scope

The successful bidder will supply, configure, integrate, and implement a pre-existing analytics platform. Extensive custom software development is explicitly excluded. The scope encompasses:

• Initial deployment, configuration, and integration with existing systems.
• Provision of 50 hours of post-implementation enhancement, support, and maintenance.
• Comprehensive knowledge transfer to client personnel.
• Alignment with Phase 2 modules of the National Integrated Information Management System (NIIMS), scheduled for operational deployment in December 2026.

Technical Requirements

The solution must meet stringent functional, analytical, and security specifications:

• Integration & Connectivity: Must interface with NIIMS and the Enterprise Data Repository System (EDRS) via APIs, direct database connectivity, and automated scheduled data synchronisation.
• Reporting & Visualisation: Dashboard visualisation, descriptive/diagnostic analytics, trend/correlation analysis, root cause/statistical analysis, self-service and scheduled reporting, drill-through capabilities, and export functions to PDF, Excel, and Word.
• Advanced & Predictive Analytics: Machine learning-driven predictive modelling, safety occurrence trend forecasting, anomaly detection, operator risk profiling and scoring, emerging risk identification, inspection prioritisation based on predictive outputs, pattern recognition using railway safety data, and predictive decision support.
• Security & Administration: Role-based access control, comprehensive audit logging, secure authentication protocols, standard security controls, and full administrative configuration tools.
• Evaluation Threshold: Bidders must achieve a minimum of 70 points across reference letters, team capacity, and data science capability assessments to qualify for the solution demonstration and price evaluation phases.

Skills & Qualification Requirements

Bidders must demonstrate proven expertise and qualified personnel across three key evaluation areas:

• Proven Experience (40 points): Valid reference letters from clients within the past ten years confirming successful delivery of similar enterprise analytics, business intelligence, data platform, AI, or machine learning solutions.
• Core Analytics Team (30 points): CVs and certified qualifications (issued within six months) for Data Analytics Specialists, Business Intelligence Specialists, or Data Engineers. Candidates must hold relevant degrees/diplomas in Computer Science, Data Science, Statistics, or related fields, plus recognised BI or Data Engineering certifications.
• Data Science & Machine Learning Team (30 points): CVs and certified qualifications for Data Scientists or Machine Learning Specialists. Candidates must hold relevant degrees/diplomas in Computer Science, Artificial Intelligence, Machine Learning, IT, Informatics, Statistics, or Mathematics, plus certifications in Predictive Analytics or Machine Learning.

Note: Each proposed specialist may only be evaluated under one designated role. Points are automatically forfeited if either the CV or the certified qualifications are missing for any candidate.

Key Terminology Explanation

• COTS (Commercial Off-the-Shelf): Pre-packaged, ready-to-deploy software designed for broad market use, requiring configuration and integration rather than bespoke development.
• SaaS (Software-as-a-Service): Cloud-hosted software delivered via subscription, eliminating local installation, hardware dependencies, and routine maintenance overhead.
• NIIMS & EDRS: The Railway Safety Regulator’s centralised information management and enterprise data repository systems, which serve as the primary data sources and integration targets for the new analytics platform.
• PPPFA Preference Point System: A South African public procurement framework that allocates up to 80 points for competitive pricing and 20 points for socio-economic transformation goals, such as ownership by black individuals, women, youth, or persons with disabilities.