Supply Chain Analytics – Efficient Inventory and Distribution Management for the Pharmaceutical Industry

Jun 29, 2017

Quantzig’s latest study on supply chain analytics for an established healthcare provider in the US provides strategies for cost optimization, better supply chain visibility, and efficient inventory and distribution management.

Supply Chain Analytics in the Healthcare Industry

The intense competition and stringent government regulations are encouraging healthcare and pharmaceutical companies to revamp their supply chain sector and increase operational efficiency. The continual efforts to update IT systems and network infrastructure will help enterprises in the industry to gain visibility into the inventory and distribution processes. By implementing supply chain analytics, pharma companies can identify opportunities to improve the efficiency of their operational and production systems. The optimization of their supply chain functions will enable them to manage market pressures pertaining to government involvement and FDA approvals. Supply chain analytics help organizations in the pharmaceutical and healthcare industry to monitor, measure, and improve individual business processes and overall performance of the operational cycle. The recent supply chain analytics assessment by Quantzig enables inventory optimization, inbound supply chain visibility for cost reduction, and improved supply chain planning. The study also provides valuable information on efficient inventory and distribution management, cost optimization, and better supply chain visibility.

Pharma companies are implementing supply chain analytics to increase their demand visibility and understand customer preferences in the market. These solutions are designed to help enterprises optimize their sales and operations planning processes through demand forecasting metrics and KPIs. The data analytics solutions aim to improve the strategy, performance, management, and risk associated business decisions for organizations in the industry.

Increasing Manufacturing Efficiencies

The advent of automation and digitalization is boosting the requirement for manufacturing efficiencies. Effective management of filling, replenishing, loading, and troubleshooting processes will result in optimal production and increase sales revenues. The introduction of technological innovations such as 3D printing makes decentralized production cost-efficient at low volume and increases the requirement for supply chain analytics solutions. These cost-effective business operations will revolutionize the pharma industry over the next few years.

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Effective Decision Making

Many organizations in the industry are implementing sensors in the supply chain to offer real-time visibility and effective decision-making. The systems generate information that enables sales and operations teams to make dynamic decisions in response to changing conditions in the volatile market. These solutions also provide data analysis that results in forecast and planning accuracies, reduce risks of over or under stocks, and help healthcare institutions provide better patient care using advanced therapeutics.

Outcomes and Solutions Offered

Quantzig’s supply chain analytics for an established healthcare provider in the US offers comprehensive information on various supplier profiles, invoices, inbound logistic data, order history, inventory data, and operations. Some of the solutions offered are as follows:

  • Streamlined the order processing to enable easier access to valuable supply chain information
  • Improved inventory management through central and regional warehouses
  • Provided solutions to effectively manage safety stock levels for critical SKUs and supply chain costs
  • Improved the administrative cost savings and reduced the inventory replenishment cycle time
  • Monitored the delivery times of materials from suppliers to out-patients for cost reimbursements

The complete case study on supply chain analytics reduces inventory costs for an established healthcare provider is now available.

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