Supply Chain Analytics Software and Logistics Analytics Solutions
Turn Supply Chain Data Into Action
Supply Chain Analytics Software Use Cases
Embedded analytics within supply chain software empower companies to gain insight and extract real value from the large amounts of data you’re creating around the procurement, processing, distribution and transportation of goods.
Operations
Improve process planning and forecasting using supply chain analytics solutions
Sourcing
Analyze patterns within SaaS applications and enable customers to use custom data models
Manufacturing
Use IoT sensors to monitor manufacturing logistics equipment and parameters and adapt efficiently.
Warehousing
Make the most efficient use of warehouse space and minimize travel distances.
Transportation
Reduce fuel consumption and improve driving efficiency using analytics and GPS technologies.
Point of Sale
Use RFID for shelf-space optimization, dynamic pricing and out-of-stock prevention.
The Importance of AI
AI and machine learning is changing the face of supply chain analytics platforms. It can automate the analysis of large volumes of historical data and use it to provide real-time insights for forward-looking decision making.
Logistics analytics software can quickly surface patterns and trends and offer embedded decision logic to improve efficiency, increase productivity and dramatically lower costs in everything you do.
Learn More About Qrvey’s Unified Data Pipeline
REDUCE COMPLEXITY
Supply chain analytics from start to finish
Embedded analytics for SaaS applications empowers users of a logistics analytics software application to analyze data in way that fits each business.
Qrvey offers the most complete embedded analytics solution for supply chain companies that includes a native data management layer, workflow automation and dashboards with custom dashboard builders.
Explore The Platform
Built-In Data Lake and ETL
Analyze all of your data sources, including unstructured data, no matter how big it is or where it lives with a data layer built for multi-tenant analytics for SaaS applications.
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Workflow Automation
Monitor your data in real-time and take action the moment conditions change with integrated workflows and user-defined triggers.
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Tools Made for Developers
Software development teams release up to 10x faster with Qrvey. Teams get analytics tools made for software development.
Learn MoreKey Capabilities of Qrvey for Supply Chain Analytics
Real-Time Data Processing
Spot trends in real-time, support rapid decision-making and improve forecasting with real-time data analysis.
Enterprise Scale
Efficiently scale to billions of records and thousands of concurrent users while lowering infrastructure costs.
Integrated AI
AI for predictive analytics, improves forecasting, logistics management and error reduction.
Multi-Tenant Data Lake
Scale analytics offering by combining IoT data into a high performance analytics layer for multi-tenant apps.
Data Governance
Manage data security by ensuring data quality, regulatory compliance, and effective data stewardship.
Integration Ready
Unified data pipeline supporting integrations from enterprise systems, applications, and all data sources.
Self-Service Analytics
Empower users to build their own custom dashboards using Qrvey’s multi-tenant security layer and embedded builders.
Embedded Data Visualization
Interactive ata visualization tools combine intuitive insights and real-time analysis for supply chaining analytics.
Support
Your success is our success. Our award willing support team is with your every step of the way.
Skip the Sales Demo
Want to see Qrvey in action? Check out our interactive demos.
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Analytics for Those Who Want More
Build Less Software. Deliver More Value.
Frequently Asked Questions
Supply chain analytics involves collecting and analyzing data across the supply chain to gain visibility, identify insights, and optimize planning and execution.
- Supply chain analysts/managers
- Logistics and distribution managers
- Procurement and sourcing teams
- Inventory managers
- Operations managers
- Executive leadership
- Demand forecasting and planning – Predict future demand to optimize inventory and production.
- Supplier & risk analytics – Evaluate suppliers on cost, quality, risk factors to improve sourcing.
- Logistics optimization – Analyze shipping routes, modes, costs to enhance delivery efficiency.
- Supply chain visibility – Provide real-time tracking of inventory, orders, shipments.
- Production analytics – Identify bottlenecks, waste, downtime to boost throughput.
- Inventory optimization – Improve levels, locations based on demand trends and forecasts.
- Anomaly detection – Identify abnormalities or outliers to mitigate supply chain disruptions.
- What-if scenario modeling – Assess action scenarios to manage risks and plan continuity.