Data science in supply chain

The applications for machine learning to create precise demand predictions are diverse. Whether optimized resource management, inventory reductions, increasing service levels, minimizing supply challenges or improving transportation planning, better predictions have a positive effect on end-to-end supply chain and logistics planning.

Risk prediction is yet another important aspect of a data-driven supply chain. With analysis of historical data and the use of advanced statistical models, potential supply chain risks can be recognized and evaluated early. This enables businesses to proactively avoid potential disruptions or bottlenecks and increase the resilience of their supply chains. With precise risk predictions, businesses can better respond to disruptive events and continually optimize their business processes.

In addition to data analysis and machine learning, 4flow’s data science toolbox includes mathematical optimization. Customized optimization algorithms offer solutions for business-specific logistical challenges – and increase overall supply chain efficiency. 4flow uses advanced algorithms and data-driven approaches for route optimization to help businesses improve their route planning. As a result, businesses see shortened delivery times, reduced transportation costs and an overall more efficient supply chain. With targeted analysis of transportation data and integration of machine learning solutions, 4flow supports its customers to optimize their logistics processes and secure a competitive advantage.

Multi-level supply chains create large amounts of data and metadata – suppliers, transportation service providers and other stakeholders contribute data with countless IT systems with a multitude of interfaces. Product-specific factors add to this data. The ability to store and process these vast amounts of data can reveal new information and potential. Most companies are aware of the potential of supply chain data. But usually, they lack the right approach to source and use it, the ability to evaluate and interpret it correctly, or the capacity to address the issue. 4flow, as an expert on big data in supply chain, uses artificial intelligence to enable businesses to make use of this potential in a targeted and efficient way.

4flow supports its customers by developing customized solutions, improving strategies and processes to leverage supply chain data, or implementing third-party software solutions from our partners.

4flow uses process mining, a technology to visualize processes using event-based log data, to enable customers to increase supply chain visibility and understanding of their supply chain processes.

Hand in hand with our consultants, the 4flow Data Science team applies state-of-the-art methods and technologies to comprehensively support client decisions by using both internal client data as well as industry-specific benchmarks.