How Members Use FLOW

FLOW data has wide-reaching utility. Some of the most common ways the data could be used include: 

1. Throughput Reporting and Visualization – Quantify and monitor current regional logistics capacity, utilization, and throughput across different logistics modes. This can provide transparency into the current conditions of logistics networks, identifying sources of congestion, while tracking changes in throughput and variance over time.
2. Demand Forecasting – Aggregated PO information represents manufacturing orders that will transition to logistics demand. Participants could use demand forecasts to inform resourcing and procurement decisions.
3. Throughput Forecasting – Predict how incoming demand will impact regional logistics throughput. Historic demand, capacity, and throughput data can be used to help quantify how throughput and variance are affected by capacity and demand. When combined with future aggregated PO information, this could be used to forecast transit/cycle times across different modes within a region. 
4. Service Optimization – Participants could use FLOW data to optimize how logistics capacity matches demand while maintaining low variance (i.e., maximizing on-time arrival). Further related use cases related to service optimization could include:
   • Setting contract and spot-market freight resourcing levels 
   • Setting service-mix expectations 
   • Linking dynamic pricing with service commitments 

Member Use Case Examples

ELION is a real estate private equity firm that deals with industrial/logistics real estate. They have been considering using FLOW data to forecast demand for warehouse space around US ports.  

ELION believes that adding new warehouses to port communities where logistics real estate demand will soon outmatch supply, could help make American supply chains more resilient. How are they doing this? Through forecasting warehouse demand/supply using local consumer spending indicators.

You can read the full use case slide deck to learn more.
 

DCLI is the largest container chassis leasing and chassis pool provider to the U.S. intermodal industry.

DCLI is considering using FLOW data to help improve their forecasts of demand for chassis at US ports. The company began by comparing FLOW data with their own internal to data to check for consistency.  Going forward, the company intends to leverage FLOW data to identify demand surges that may not be visible using only company data.  DCLI believes that by improved chassis demand forecasting can alleviate chassis shortages can reduce service disruptions for marine terminals, rails, motor carriers, and end customers.

You can read the full use case slide deck to learn more.