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Optimizing Healthcare Logistics: Data Analytics for Timely Delivery of Life-Saving Drugs

About the Customer:

A leading diversified healthcare company based in the United States, providing a range of services including health insurance, data analytics, and healthcare management.

Business Challenges:

  • Required BI (Business Intelligence) reports to streamline the delivery process and reduce the turnaround time for life-saving drugs.
  • Needed to monitor and predict shipment delays to minimise costs of critical healthcare products.

Embitel’s Solution:

  • Developed reporting solutions to monitor real-time shipment tracking.

We built an advanced Business Intelligence (BI) reporting system to track shipments in real time. This solution integrated with the company’s logistics and supply chain management systems, providing a live feed of shipment statuses.

By visualizing this data through interactive dashboards, key stakeholders could access up-to-the-minute information on delivery progress, enabling faster decision-making and immediate action if any shipment was at risk of delay.

  • Implemented predictive analytics to forecast shipment delays, ensuring timely delivery of life-saving drugs.

We introduced predictive analytics algorithms that used historical data, weather patterns, traffic information, and real-time logistics data to anticipate potential delays.

This allowed the company to forecast disruptions before they occurred and take proactive measures to adjust shipments or re-route deliveries.

Embitel Impact:

  • Reduced turnaround time for delivering critical medications.
  • Improved real-time monitoring and prediction of shipment delays.
  • Achieved significant cost savings while ensuring timely delivery of essential healthcare products.
  • By implementing these solutions our customer achieved significant improvements in operational efficiency, data-driven decision-making, and overall business performance.

Tools and Technologies:

  • Database: Oracle, Azure Synapse, Google Big Query, Amazon Redshift
  • Language: SQL, Python
  • Tools and Technologies: Microsoft PowerBI, Tableau, Apache Preset
  • Data Modelling: Erwin, Draw.io
  • Data Catalog: Unity Catalog, Azure Purview
  • Data Quality: Great Expectations
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