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Enterprise AI for HealthTech: Streamlining Supply Chain Operations
Technology Category
- Analytics & Modeling - Machine Learning
- Functional Applications - Inventory Management Systems
Applicable Industries
- Education
- Equipment & Machinery
Applicable Functions
- Logistics & Transportation
- Warehouse & Inventory Management
Use Cases
- Digital Twin
- Supply Chain Visibility
Services
- Data Science Services
The Challenge
The global HealthTech company, with over 35 manufacturing facilities worldwide, faced a significant challenge due to its complex IT landscape. The company's growth, both organically and through strategic acquisitions, led to a scattered supply chain data across various ERP systems. This complexity hindered the company's ability to gain crucial business insights and answer critical questions such as prioritizing product lines or SKUs, identifying 'lazy inventory' in the supply chain, and optimizing inventory allocation across distribution centers. These challenges became even more critical during the peak of the COVID-19 pandemic, particularly for the company's respiratory ventilator products.
The Customer
Not disclosed
About The Customer
The customer is a global leader in the HealthTech industry, with over 80,000 employees and 35 manufacturing sites worldwide. The company generated over $22 billion in revenue in 2020 and filed over 1,000 new patents in 2019. The company manufactures products in more than 35 facilities worldwide and ships products to customers globally via an extensive network of production and distribution centers. The company has grown organically and through many strategic acquisitions, resulting in a complex IT landscape.
The Solution
The C3 AI team addressed the inventory visibility challenge across the company's respiratory ventilator products. In just four weeks, they configured the C3 AI Supply Network Risk application for 42 critical ventilator SKUs. The team unified disparate supply chain data on the C3 AI Supply Chain Digital Twin and configured five dashboards on the C3 AI Supply Network Risk application to provide end users with a global real-time view across the supply chain. After resolving the visibility challenge, the team configured machine learning algorithms and the application logic to predict order lead times and OTIF (on-time in-full) delivery risks for over 10,000 SKUs. The C3 AI Supply Network Risk was successfully configured and deployed into production in collaboration with a cross-functional team across the HealthTech company and C3 AI.
Operational Impact
Quantitative Benefit
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