By: Johan Potgieter - Cluster Industrial Software Lead at Schneider Electric

In a CSIR research paper, Leading logistics performance, the organisation cites the performance of South Africa logistics system is both an enabler of growth and an indication of economic health. When the system fails, the economy is at risk of failing, and vice versa. 

This close relationship clearly emphasises the need to understand systemic performance, respond timeously to changes, and to gain access to information that enables proactive decision-making.

And it here where tremendous opportunity lies; digitalisation offers fantastic value where visibility is weakest and decision-making is slowest. For example, in complex logistics environments, delays are rarely caused by a single failure; it results from fragmented information, disconnected stakeholders, and a lack of system-wide awareness.

Where digitalisation delivers real impact

A control tower model forms an important part of gaining the most digitalisation with transport and logistics. It is an AI-driven, centralised platform that provides real-time visibility, coordination, and decision-making across its global supply chain. 

These models integrate IoT, analytics, and automation to optimise multimodal logistics networks by bringing together data from ports, rail, road, warehousing, and customers into a single, real-time operational view. 

Schneider Electric’s control tower models for example offers:

• AI-Driven Logistics Control Tower (LCT):
• Built to manage a multimodal network (road, sea, air, rail).
• Uses IoT-enabled to connect operational technology (OT) with informational technology (IT).
• Provides end-to-end visibility across 100+ countries.
• Ranked number one in Gartner’s 2025 Supply Chain Top 25 for innovation and resilience.
• Real-time monitoring of shipments and warehouse operations.
• Digital twins for scenario planning and risk simulation.
• Energy-efficient automation to reduce logistics costs and carbon footprint.

Within the South African context, this could mean rerouting containers around congested berths or recalibrating rail-to-road transfers in hours rather than days, a critical shift in an environment where time and predictability directly affect cost.

Adding to the above is automated and semi-automated warehouses which are becoming an indispensable infrastructure across e-commerce, FMCG, and cold-chain logistics. These environments create richer data ecosystems where inventory accuracy, throughput, safety, and energy performance can be continuously monitored and improved. 

The result is not only greater efficiency, but also resilience in the face of fluctuating demand and constrained infrastructure.

Then, predictive maintenance adds another layer of operational stability. By deploying sensors and analytics across fleets, materials-handling equipment, and depot assets, operators can reduce unplanned downtime and extend asset lifecycles. 

As the African Continental Free Trade Area (AfCFTA) continues to take shape, digital customs platforms and secure, blockchain-enabled documentation also have a role to play. Again, by reducing friction at border posts and improving transparency, these tools support stronger working-capital cycles and more dependable regional supply chains across SADC and beyond.

Integration, skills, and trust: the real obstacles

Unfortunately, many logistics environments still operate on a patchwork of ERP (Enterprise Resource Planning) TMS (Transportation Management Systems), WMS (Warehouse Management System), and telemetry systems that were never designed to work together. 

Integrating these into a secure, unified architecture often proves more complex, and more time-consuming, than the technology deployment itself.

What is required is not complete reinvention under the banner of ‘Industry 4.0’, but steady, disciplined progress rooted in operational reality. The most effective starting point is a clear, end-to-end view of value streams: identifying the most critical bottlenecks and deploying targeted digital interventions to remove them.

For one operator, this may involve implementing a logistics control tower that harmonises existing data sources. For another, it may mean modernising a flagship warehouse through smarter automation, integrated energy monitoring, and predictive maintenance.

From there, long-term success depends on building an open, connected backbone rather than another layer of siloed systems. Interoperable architectures that link operational technology on the warehouse floor with enterprise IT systems create the foundation for advanced analytics, artificial intelligence, and digital-twin applications.

Ultimately, digital transformation in logistics is not about technology for its own sake. It is about relevance and resilience. The operators that can see clearly, respond quickly, and collaborate effectively will help shape the continent’s evolving trade corridors.