Logistics already heavily integrates optimization, but with the help of big data analytics, supply chains are able to make intentional changes to create more streamlined delivery sequences and more positive customer experiences. In such a data heavy department, analytics can be applied to nearly every aspect to create more cohesive manufacturing and delivery of products.

Analytics in Supply Chain, Logistics, and Inventory Management

Supplier Networks & Network Data Flow

  • Expand and integrate role of supplier networks through contextual knowledge sharing and collaboration through data analytics.
  • Understand supplier processes in order to make internal delivery more effective and efficient.

 

Optimization of Supply Chain Structure

  • Use real-time analytics to measure performance and shortcomings, and adjust for optimal outcome.
  • Use data to identify inefficiencies in supply chain, and implement tactics to improve on pain points.

 

Geoanalytical Optimization

  • Merge regional networks and delivery data to maximize delivery speeds.
  • Save time and money by analyzing real-time data and ensuring factors such as traffic or weather conditions do not pose obstacles.
  • Optimize delivery sequence to save time, money, and make an impact on customer satisfaction.

 

Customer Feedback

  • Maximize customer experience by gaining comprehensive understanding of their wants and needs.
  • Understand shortcomings in product placement and ensure a positive, unique brand experience.