Supply Chain
Use Cases
Automate MRO Supplier Discovery with Generative AI
Automate Supply Chain ESG and Disruption Risk Monitoring
Automate delivery to customer eg via drone or self-driving vehicle
Consider automation of delivery and other transportation cases through drones and other automated vehicles
Automate inventory management for products
Inventory Management - helping company calculate how many units are required where and when. This is precisely the sort of complex, data-rich, prediction-heavy closed loop where AI can potentially excel if the data tracking is accurate - so long as the unexpected does not intervene.
Automate warehouse
Identify opportunities to use robotics to automate warehouses. Use of robots to support retail deliveries is one of the fastest growing use cases for the machines.
Build AI for Enterprise Procurement Spend Analytics
Build AI for Supply Chain Carbon Footprint Tracking and Reduction
Build AI-Powered Supply Chain Decision Intelligence Platform
Build Supply Chain Digital Twin with AI-Powered 3D Simulation
Capture 3rd party or internal data for price comparison and supplier relationship overview
Comparable data across multiple suppliers (or internal relationships) can allow for potentially significant negotiation power and cost reduction opportunities. Automated data aggregation and comparison from multiple sources significantly reduces the challenges to getting an aggregate and normalised view across organisations and suppliers.
Deliver anticipatory logistics through demand forecast
Anticipatory logistics are based on predictive algorithms running on big data. The practice allows logistics professionals to improve efficiency and quality by predicting demand before a consumer places an order. A cost-efficient and effective returns system is a key element in the value chain. Returns to scale are usually key to making this work economically.
Deploy AI Demand Sensing with External Signals for Supply Chain
Deploy AI for Agricultural Supply Chain Traceability
Deploy AI for Predictive Inventory Management in Pharmaceutical Retail
Determine root causes for quality issues originating outside of manufacturing eg in the supply chain
Determine root causes for quality issues originating prior to the manufacturing process. This might include supply sources or logistic process issues. Close human analyst oversight recommended.
Ensure inventory availability by predicting demand and triggering appropriate action
Predict likely demand for products and model rapidly changing scenarios (e.g. weather) to limit out of stock situations.
Identify and predict supplier performance characteristics such as reliability
Identify and predict which suppliers meet performance characteristics such as cost effectiveness, timeliness, order completeness, quality, regulatory compliance and social responsibility. Determine most cost effective and optimal suppliers.
Identify physical properties of scanned images
Use scanned images - often from portable cameraphone - to identify physical properties. a key function of this is the potential for mobile apps, greatly increasing the potential specific use situations.
Identify the right match for transplant patients and donors
Optimising matches between transplant patients and donors benefits all patients across the transplant waiting list as it results in more saved lives. For example, through paired kidney donations, AI is able to identify potential donors and recipients who are biologically suited for one another and can take into account certain criteria to optimise the service such as prioritising the hardest to match patients.
Monitor supplier decommits and recommits
Supplier decommits/recommits analytics understand optimal production capacities of suppliers and contract manufacturers in order to properly rebalance manufacturing needs caused by supply chain disruptions (strikes, storms, wars, raw material shortages).
Monitor supplier network performance
Supplier network analytics triage product and supplier problems more quickly by understanding the dynamics of the underlying supplier and contract manufacturer relationships and inter-dependencies.
Optimise purchasing mix across suppliers and locations to lower input costs
Optimise purchasing mix across suppliers and locations should enable better pricing negotiations and reduced wastage on purchased product.
Optimise supply chain
Use historic data to model supply chains to identify and predict the way potentially complex and opaque demand patterns ripple through the system under different scenarios (e.g. weather changes). This can be used to predict potential pricing.
Predict and Automate Returns Processing for Logistics
Predict migration patterns based on a variety of indicators
Predict migration volume based on different data sources and indicators. This can aid country policymakers and NGOs to prepare for changing migration patterns.