LONDON--(BUSINESS WIRE)--Quantzig, a leader in delivering scalable analytics solutions and data science services, today announced the completion of its recent article that offers comprehensive insights into the role of advanced planning and scheduling optimization in the pharmaceutical industry. Drug manufacturers face several challenges when it comes to sustaining on-time-deliveries and reducing inventory costs. This article illustrates how advanced planning and scheduling optimization solutions can help pharma companies to orchestrate different manufacturing functions to reduce inventory holding costs, avoid production delays, and improve cash flow.
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In the current business setting, drug manufacturing companies face several challenges that curtail the ability to enhance drug discovery and development. The real challenge, however, lies in responding to unexpected events like pandemic outbreaks, demand surges, and changes in customer priorities. Besides, the growing pressures to reduce prices coupled with inefficiencies in advanced planning and scheduling optimization can have a huge impact on drug manufacturing. Since drug discovery and development is a resource-heavy process, drug manufacturers must look for reliable ways to reduce costs while ensuring compliance and quality standards.
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According to Quantzig’s scheduling optimization analytics experts, “Quantzig’s unique approach to planning and scheduling optimization helps track resource availability and equipment utilization rates to optimally allocate raw materials and streamline manufacturing processes to meet the demand.”
How Quantzig’s Advanced Planning and Scheduling Optimization Can Help Your Business
Quantzig’s unique approach to planning and scheduling optimization helps track resource availability and equipment utilization rates to optimally allocate raw materials and streamline manufacturing processes. Adopting a data-driven approach to optimizing production schedules can enable better resource planning, shift alignment, and capacity allocation based on the current availability of manpower to ensure that priority products are manufactured in adequate quantities to meet the market demand. Besides, we offer end-to-end solutions for labor planning and resource scheduling with near-real-time dashboards for providing prescriptive insights that ensure there is minimum time lost in planning and mitigating pandemic-induced risks.
Our advanced planning and scheduling optimization solutions have helped our clients to achieve the following benefits:
- 30-45 percent increase in plant productivity
- 70-80 percent reduction in scheduling labor overhead
- Up to 25 percent reduction in raw material and WIP
Our scheduling optimization analytics platforms integrate customizable modules to deliver superior efficiency and better outcomes at a lower cost. Book a FREE solution demo to explore our modular analytics platforms designed to help pharma companies.
At Quantzig, we understand the challenges faced by drug manufacturers across the globe and to help them we offer end-to-end scheduling optimization analytics solutions that help drive manufacturing efficiency and better outcomes. Read the complete article for comprehensive insights.
Recent Articles from Quantzig’s Pharma Supply Chain Analytics Series:
- Pharmaceutical Supply Chain Trends 2020: Predictions for A Post-Covid19 World
- Dynamic Demand Forecasting in Pharma: Analyzing Its Role in Accelerating Product Success
- How Important Is Warehouse Location Optimization for Pharma Companies?
- 5 Pragmatic Recommendations for Improving Pharma Logistics Optimization
About Quantzig
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal
