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KwaZulu Natal Department of Transport Indaba

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Durban ICC
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KZN TRANSPORT INDABA 2026 A GATEWAY FOR SMART MOBILITY

07 hours 37 minutes 02 seconds

Thematic Session 1: Green Transport and Climate-Resilient Infrastructure


Rational for discussion on this theme 

The rationale for adopting data insight-based planning lies in the need to move away from fragmented and reactive approaches to infrastructure management towards a more systematic, evidence-driven model. In many cases, infrastructure decisions are made based on limited or outdated information, resulting in inefficient allocation of resources, delayed maintenance interventions and increased long-term costs. By strengthening the collection, integration and use of data, the Department can significantly improve the accuracy of planning, budgeting and decision-making processes.

Data-driven asset management allows for the implementation of predictive maintenance strategies, enabling early identification of infrastructure deterioration and reducing the risk of failure. This not only extends the lifespan of assets but also improves service reliability and optimises expenditure by prioritising interventions where they are most needed. In addition, the integration of data across planning, finance and operations enhances transparency and accountability, supporting better governance and performance monitoring. Ultimately, this approach ensures that infrastructure investments deliver maximum value over their lifecycle

Objectives

  • Use data analytics to inform infrastructure planning, prioritisation, and investment decisions.
  • Improve asset lifecycle management through predictive maintenance and performance monitoring.
  • Establish integrated data systems for transport planning and operations.
  • Enhance evidence-based decision-making and policy development.
  • Increase transparency and accountability through data-driven reporting.

Questions to be answered

  • Use data analytics to inform infrastructure planning, prioritisation, and investment decisions.
  • Improve asset lifecycle management through predictive maintenance and performance monitoring.
  • Establish integrated data systems for transport planning and operations.
  • Enhance evidence-based decision-making and policy development.
  • Increase transparency and accountability through data-driven reporting.

Questions to consider​

Short-Term

  • What asset condition data is available and what is missing?
  • How will a baseline asset condition assessment be completed?
  • What reporting dashboards can be implemented immediately?

Medium-Term

  • How will predictive maintenance models be introduced?
  • What integrated data platform (single source of truth) will be established?
  • How will data be embedded into budget and planning processes?

Long-Term

  • How will the Department achieve fully data-driven decision-making?
  • What lifecycle optimisation targets will be achieved?
  • How will continuous data intelligence systems be maintained?