Deep Dive

Current state

Without effective supply chain geomapping, companies lack a critical visual tool for understanding their global network's spatial dependencies and risks. This absence of geographical insight makes it challenging to assess the impact of localized events, such as natural disasters, political instability, or infrastructure failures, on specific suppliers or transportation lanes.

It can lead to a reactive approach when disruptions occur, causing delays in identifying affected areas, inefficient rerouting, and a slower response to maintain supply continuity. The inability to visualize interconnected risks can result in unforeseen bottlenecks, increased costs and ultimately, interruptions in the delivery of essential medicines to patients.

Solution

Supply Chain Geomapping involves visualizing the entire supply network on an interactive geographical map, pinpointing the physical locations of all critical assets, suppliers, manufacturing sites, distribution centers, and transportation routes.

This visual representation integrates data to provide spatial awareness of the supply chain's footprint, enabling companies to identify geographical concentrations of risk, optimize logistics, and enhance responsiveness to localized disruptions.

Comprehensive data integration

Effective data integration is paramount for successful Supply Chain Geomapping. This requires breaking down data silos and connecting disparate systems across the supply chain, including:

• Enterprise Resource Planning (ERP)
• Transportation Management Systems (TMS)
• Geospatial Information Systems (GIS)

Key data points include supplier locations, shipping routes, inventory levels, production sites, and shipment tracking information from all tiers.

Technologies such as IoT sensors for real-time monitoring of goods in transit, and AI-powered analytics for identifying risks and optimizing performance can be added to unlock further insights across complex, multi-tiered supply chains.

Strong supplier collaboration and data-sharing agreements are essential to ensure the accuracy and completeness of information from all participants.

Benefits of geomapping with AI

The benefits of AI-enabled supply chain geomapping are significant, enabling advanced predictive analytics and automated risk identification. AI algorithms can analyze vast amounts of geospatial and operational data to identify complex, non-obvious correlations between geographical factors and supply chain performance or risk.

This enables predictive modeling of potential disruptions based on weather forecasts or geopolitical shifts, automated alerts for high-risk zones, and optimized site selection for new facilities based on risk exposure.

AI can also simulate the impact of various geographical scenarios on the supply chain, allowing for proactive risk mitigation and the development of more resilient network designs.