DTN fills critical data gap with fuel demand intelligence

Refined Fuels Demand eliminates delay of critical market-level volumetric information from eight weeks to real-time delivery

MINNEAPOLIS (January 19, 2021) – In a marketplace where pricing and supply data changes in mere seconds, DTN, a leading data, analytics and technology company, now delivers market-level intelligence that drives educated decisions based on the most current data available. Previously, organizations in the downstream oil and gas industry relied on two-month old market-level data to make pricing and supply decisions, limiting their ability to optimize decisions across their supply chain.

With DTN, Refined Fuels Demand, customers across the oil and gas supply chain leverage the intelligence from DTN to better understand their market share and make more confident, real-time operational and pricing decisions. For instance, managing the timing and placement of product during seasonal spec changes will be exponentially easier when operations managers are informed by daily market level demand numbers. These same insights can enhance decision-making when timing product availability for export or going in and out of storage.

“Current market-level data has been a long overdue need in the fuel industry,” said Heather Killough, senior vice president-energy at DTN. “With our solution, we have eliminated the eight-week lag and brought the data into a near real-time state. This enables our customers to make the most informed and confident decisions, giving them a competitive edge and positively impacting their bottom line.”

DTN offers the intelligence at both PADD and rack city levels, using volumetric data from nearly 85 percent of all downstream energy transactions in the United States. The service reports daily wholesale gasoline and diesel demand, in gallons, by grade, at more than 300 cities nationwide. DTN currently publishes demand daily at 3:30 a.m. CST for midnight-to-midnight local terminal liftings. Refined Fuels Demand also offers access to historical data for trending and analysis.