- Big Data analytics important part of new “DHL Resilience360” solution
- DHL trend report on Big Data points out further potential applications
- The full report can be downloaded for free here
DHL implements initial findings from the recently released trend report “Big Data in Logistics” and utilizes a comprehensive data pool for the early detection of potential risks in supply chains. With the launch of “Resilience360”, an instrument for supply chain risk management enabled by Big Data analytics, DHL can provide its customers with an overview over potential disruptions of their individual supply chains. Further applications coming out of the trend report such as the “DHL Parcel Volume Prediction” model or “DHL Geovista” are currently being piloted.
“Resilience360 is a perfect example of the economic benefits of Big Data analytics in logistics. Aggregating and evaluating data safeguards and improves the efficiency of supply chains. Thus, business operation is maintained and customer satisfaction optimized sustainably”, explains Dr. Markus Kückelhaus, Head of Trend Research, DHL Customer Solutions & Innovation. “Our report also shows two other potential applications of Big Data analytics: the improvement of operational efficiency and the possibility of exploring new business models.”
Supply chains to be more resilient and less failure-prone
Another part of the trend report, dealing with the improvement of operational efficiency, covers the correlation analysis of weather conditions, influenza outbreaks and the online shopping behavior of individuals. The “DHL Parcel Volume Prediction” model, for example, can facilitate the volume planning of parcels to be transported by factoring in the correlating data. In this case, Big Data models help to optimize processes and improve customer service.
Finally, Big Data offers logistics providers promising starting-points for the development of new business models, such as providing geo marketing instruments for small and medium sized enterprises (SMEs). Using the “DHL Geovista” model, which provides detailed analysis and evaluation of complex geo data, logistics providers can forecast the sales figures of SMEs.