Supplier Risk Prediction
AI-based Vendor Portfolio Optimization
Vigilo® Supplier Risk Prediction provides comprehensive information and visibility into the risks and impacts of disruption throughout the supply chain using AI based proprietary algorithms. It helps improve supplier planning and supplier portfolio management and create appropriate redundancy, backup, and recovery options where needed.

Use Cases
Identifying and prioritizing sources of raw materials and components
Supplier portfolio management
Predicting potential disruptions in supply chain
Inventory and financial planning using the portfolio of suppliers
Vigilo Serves
Logistics and
Packaging industry
Construction
industries
Industrial Plant
& Equipment firms
Supply Chain
teams across
organizations

Vigilo®
Automated Vendor Risk Optimization to Mitigate High Risk in Supply Chain
Supplier Risk Prediction by Scry Analytics is based on data-driven analytics to predict potential for disruption to parts, labor, and shipments and generate recommendations and options for management teams to support decision making.
More DetailCollatio has been built using
the following technologies
Bayesian networks
Reinforcement learning
Generic rule-based machine learning
Heuristic algorithms
Data mining
Big data integration
Big data analytics
Reverse engineering
Key Differentiators &
Business Benefits
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Pre-built connectors
40+ scrapers & connectors for ingesting external data from online platforms
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External Data Enhancement
Integrates externally gathered data including weather and associated transport disruption risks as well as news alerts
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Customizable Dashboards
Provides visualization in real-time to identify alerts regarding critical inventory levels and their root causes
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Optimized Vendor Planning
Multiple scenario analysis of the likelihood of internal and external disruptions for improved visibility of critical uncertainties like seasonal demands, quality, etc
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Enhanced Supply Chain Visibility
Enhanced long-term supply chain planning visibility via consistent and comprehensive data aggregation
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Improved Customer Satisfaction
Higher quality items and improved timeliness to the customer because of improved SLAs
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