SupplyChainTalk: How goods movements insights can deliver competitive advantage 

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A digitalised supply chain provides the foundation for applying artificial intelligence (AI). To increase visibility and resilience, digitalisation focuses heavily on fixing foundational data challenges, such as data completeness and correctness and using this data for critical business decision-making. Leading organizations are going further, by leveraging AI to automate decisions entirely, which enables the orchestration of supply chains by integrating applications, data and new automation technologies into truly agile operations.

 

Potential issues that orchestration raises must be anticipated and mitigated by technology providers with the help of good quality data. Linear planning doesn’t enable the resilience and responsiveness required in a fast changing environment. The increasing use of agentic AI and artificial intelligence in general calls for new infrastructure and a robust data foundation. To ensure multiple data layers, a business must find the right data partners for demographic, political, economic and mobility data.  

 

Leveraging mobility data for decision making 

Mobility data incorporating traffic patterns, seasonal labour market and workforce movement plays a key role in site selection and supply chain planning. Predicting future trends is also essential to planning – the new trend of data centre building, for example, increases property and energy prices, which must also be factored in when considering a location viable in the long term.  

 

By utilising all the different sources of data and applying AI to them, businesses can identify underserved markets and find solutions that can serve them. AI can forecast delays, look at alternative routes or anticipate seasonal spikes.  Harnessing the power of automated orchestration, businesses can build systems that are able to self-correct themselves – if, for example, there is a delay in delivery, agents can identify the next best action and orchestrate it automatically. Redundancy is key to managing disruption in the network and anomalies in, for example, mobility data can reveal that a partner has gone out of business, as well as the necessity to switch to new partners.   

 

The panel’s advice 

• The cost of creating and using digital twins has recently gone down, as it requires now much less expertise. 
• Access to telematics data has been a huge gamechanger for mobility data analytics.  
• Examine how you make a decision without AI and see how the technology can improve that process. If you find gaps in the model, feed it back to your vendor.  
• Asking tough questions can help vendors and data providers come up with the best solution for your use case.