VesselBot

𝗠𝗼𝘀𝘁 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗕𝗔𝗙 𝘀𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝗷𝘂𝘀𝘁 𝘁𝘄𝗼 𝗶𝗻𝗽𝘂𝘁𝘀: 𝘁𝗵𝗲 𝗰𝗮𝗿𝗿𝗶𝗲𝗿'𝘀 𝘁𝗮𝗿𝗶𝗳𝗳 𝘁𝗮𝗯𝗹𝗲 and 𝗮 𝗯𝘂𝗻𝗸𝗲𝗿 𝗽𝗿𝗶𝗰𝗲 𝗶𝗻𝗱𝗲𝘅.

That is the entire basis on which most procurement teams assess their 𝗕𝗔𝗙 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲.

What sits behind those two data points is a different picture entirely:
• 𝘁𝗵𝗲 𝘃𝗲𝘀𝘀𝗲𝗹 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱 on the service
• 𝘁𝗵𝗲 𝗿𝗼𝘂𝘁𝗲 𝘀𝗮𝗶𝗹𝗲𝗱, including diversions
• 𝘁𝗵𝗲 𝘀𝗽𝗲𝗲𝗱 𝗽𝗿𝗼𝗳𝗶𝗹𝗲
• 𝗽𝗼𝗿𝘁 𝘄𝗮𝗶𝘁𝗶𝗻𝗴 𝘁𝗶𝗺𝗲
• 𝗧𝗘𝗨 𝘂𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻
• 𝘁𝗵𝗲 𝗽𝗼𝗿𝘁𝘀 𝘄𝗵𝗲𝗿𝗲 𝗯𝘂𝗻𝗸𝗲𝗿𝗶𝗻𝗴 𝗼𝗰𝗰𝘂𝗿𝗿𝗲𝗱 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗽𝗿𝗶𝗰𝗲𝘀 𝗽𝗮𝗶𝗱 𝘁𝗵𝗲𝗿𝗲
• 𝘁𝗵𝗲 𝗳𝘂𝗲𝗹 𝗰𝗼𝗻𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 generated by all of those variables combined

𝗡𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗮𝘁 𝗶𝘀 𝘃𝗶𝘀𝗶𝗯𝗹𝗲 𝗶𝗻 𝗮 𝘁𝗮𝗿𝗶𝗳𝗳 𝘁𝗮𝗯𝗹𝗲.
𝗡𝗼𝗻𝗲 𝗼𝗳 𝗶𝘁 𝗰𝗮𝗻 𝗯𝗲 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁𝗹𝘆 𝗮𝘀𝘀𝗲𝘀𝘀𝗲𝗱 𝗳𝗿𝗼𝗺 𝗮 𝗯𝘂𝗻𝗸𝗲𝗿 𝗽𝗿𝗶𝗰𝗲 𝗶𝗻𝗱𝗲𝘅.

And in a market shaped by 𝗥𝗲𝗱 𝗦𝗲𝗮 𝗿𝗲𝗿𝗼𝘂𝘁𝗶𝗻𝗴 and the effective closure of the 𝗦𝘁𝗿𝗮𝗶𝘁 𝗼𝗳 𝗛𝗼𝗿𝗺𝘂𝘇, voyage ex*****on has become more variable than at any point in recent history.

As a result, 𝘁𝗵𝗲 𝗴𝗮𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝘄𝗵𝗮𝘁 𝘁𝗵𝗼𝘀𝗲 𝘁𝘄𝗼 𝗱𝗮𝘁𝗮 𝗽𝗼𝗶𝗻𝘁𝘀 𝘀𝘂𝗴𝗴𝗲𝘀𝘁 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗮 𝘃𝗼𝘆𝗮𝗴𝗲 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗰𝗼𝘀𝘁 𝗶𝗻 𝗳𝘂𝗲𝗹 𝘁𝗲𝗿𝗺𝘀 𝗵𝗮𝘀 𝗻𝗲𝘃𝗲𝗿 𝗯𝗲𝗲𝗻 𝘄𝗶𝗱𝗲𝗿.

VesselBot's 𝗙𝘂𝗲𝗹 𝗦𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝗶𝗻𝗴 𝗜𝗻𝗱𝗶𝗰𝗲𝘀 were built to close that gap. By combining 𝗔𝗜𝗦-𝗯𝗮𝘀𝗲𝗱 𝘃𝗲𝘀𝘀𝗲𝗹 𝗺𝗼𝘃𝗲𝗺𝗲𝗻𝘁𝘀, 𝗿𝗼𝘂𝘁𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻, 𝗽𝗼𝗿𝘁 𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆, 𝗧𝗘𝗨 𝘂𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝘃𝗲𝘀𝘀𝗲𝗹-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘁𝘄𝗶𝗻 𝗳𝘂𝗲𝗹 𝗰𝗼𝗻𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗯𝘂𝗻𝗸𝗲𝗿 𝗺𝗮𝗿𝗸𝗲𝘁 𝗱𝗮𝘁𝗮, they provide an 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝘃𝗶𝗲𝘄 of what a fuel surcharge should reflect under actual voyage conditions.

If fuel surcharges are a material cost in your organization but remain difficult to validate, 𝘁𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝘁𝗼 𝘀𝘁𝗮𝗿𝘁.

👉

Fuel Surcharge Benchmarking Indices | VesselBot Bring transparency to BAF, EFS, EU ETS pass-throughs and green fuel premiums with ex*****on-based marine fuel surcharge benchmarking indices from VesselBot.

𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗴𝗿𝗼𝘄𝘁𝗵, 𝗰𝗼𝘀𝘁 𝗰𝗼𝗻𝘁𝗿𝗼𝗹, 𝗮𝗻𝗱 𝗔𝗜 𝗿𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀. Three enterprise priorities, and all three depend on the same thing: 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆.

At the Gartner Supply Chain Symposium/Xpo™ in Barcelona, Gartner identified the supply chain capabilities that enable these enterprise outcomes:
• 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 to drive revenue growth
• 𝗰𝗼𝘀𝘁-𝘁𝗼-𝘀𝗲𝗿𝘃𝗲 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 to enable cost control
• 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 to scale AI

But none of these capabilities operate effectively on 𝗳𝗿𝗮𝗴𝗺𝗲𝗻𝘁𝗲𝗱, 𝗱𝗲𝗹𝗮𝘆𝗲𝗱, 𝗼𝗿 𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲𝗱 𝗹𝗼𝗴𝗶𝘀𝘁𝗶𝗰𝘀 𝗱𝗮𝘁𝗮.

𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 depends on real-time visibility into what is actually moving, where, at what cost, and across every carrier, mode, and trade lane.

𝗖𝗼𝘀𝘁-𝘁𝗼-𝘀𝗲𝗿𝘃𝗲 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆 requires data granular enough to isolate where margin erosion is actually occurring, by carrier, lane, dwell time, and mode. Not where averages suggest it should be.

𝗔𝗜 𝗮𝗻𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 deliver on their promise only when the operational data feeding them is 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲, 𝗰𝘂𝗿𝗿𝗲𝗻𝘁, 𝗮𝗻𝗱 𝗴𝗼𝘃𝗲𝗿𝗻𝗲𝗱. Deploying AI on historical or aggregated logistics data does not produce intelligent decisions.
𝗜𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝘀 𝗳𝗹𝗮𝘄𝗲𝗱 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻𝘀 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲.

This is the data foundation VesselBot's Logistics Intelligence Platform is designed to provide: 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗳𝗿𝗲𝗶𝗴𝗵𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 across carriers, modes, emissions, cost, and network performance.

If closing that operational data gap is on your agenda, talk to the VesselBot team.

𝗕𝗔𝗙 𝘂𝘀𝗲𝗱 𝘁𝗼 𝗯𝗲 𝗮 𝗹𝗼𝗴𝗶𝘀𝘁𝗶𝗰𝘀 𝗹𝗶𝗻𝗲 𝗶𝘁𝗲𝗺.
𝗧𝗼𝗱𝗮𝘆, 𝗶𝘁 𝘀𝗶𝘁𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗖𝗙𝗢’𝘀 𝗮𝗴𝗲𝗻𝗱𝗮.

Sustained rerouting around the 𝗖𝗮𝗽𝗲 𝗼𝗳 𝗚𝗼𝗼𝗱 𝗛𝗼𝗽𝗲 and the 𝗛𝗼𝗿𝗺𝘂𝘇 𝗲𝗻𝗲𝗿𝗴𝘆 𝘀𝘂𝗽𝗽𝗹𝘆 𝗰𝗿𝗶𝘀𝗶𝘀 have sharply increased fuel exposure across ocean freight.
𝗟𝗮𝘆𝗲𝗿𝗲𝗱 𝗲𝗺𝗲𝗿𝗴𝗲𝗻𝗰𝘆 𝘀𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲𝘀 have made fuel-related costs materially larger and harder to predict.

The impact reaches beyond logistics teams. It affects 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗴𝗼𝗼𝗱𝘀 𝘀𝗼𝗹𝗱, 𝗯𝘂𝗱𝗴𝗲𝘁 𝗽𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝘀 and 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

The issue is not that surcharges exist.
𝗧𝗵𝗲 𝗶𝘀𝘀𝘂𝗲 𝗶𝘀 𝘁𝗵𝗮𝘁 𝘀𝗵𝗶𝗽𝗽𝗲𝗿𝘀 𝗵𝗮𝘃𝗲 𝗻𝗼 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 to validate whether the number on the invoice reflects what actually happened on the voyage.

A new analysis from VesselBot's Founder and CEO, Constantine Komodromos explores:
• why 𝗕𝗔𝗙 𝗺𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝗶𝗲𝘀 cannot be standardized across carriers
• how 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 is shaping surcharge governance
• and what 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝗶𝗻𝗴 provides to procurement, finance, and sustainability teams.

👉 Read the full analysis here: https://www.vesselbot.com/blog/baf-surcharge-what-shippers-miss-on-fuel-costs/?utm_source=Social+media+&utm_medium=post&utm_campaign=BAF+May+blog

𝟲.𝟲% 𝗼𝗳 𝘁𝗵𝗲 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗳𝗹𝗲𝗲𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝟰𝟭.𝟮% 𝗼𝗳 𝗮𝗹𝗹 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁 𝘄𝗼𝗿𝗸 𝗶𝗻 𝗤𝟭 𝟮𝟬𝟮𝟲.
Meanwhile, 𝗳𝗲𝗲𝗱𝗲𝗿 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀𝗵𝗶𝗽𝘀, the industry’s smallest vessel category, carried out 𝟲𝟰.𝟱% 𝗼𝗳 𝗮𝗹𝗹 𝘃𝗼𝘆𝗮𝗴𝗲𝘀 but generated just 𝟭𝟭.𝟰% 𝗼𝗳 𝘁𝗼𝘁𝗮𝗹 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁 𝘄𝗼𝗿𝗸.

That is not an anomaly.
𝗜𝘁 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝘀 𝗵𝗼𝘄 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝘀𝗵𝗶𝗽𝗽𝗶𝗻𝗴 𝗶𝘀 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹𝗹𝘆 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲𝗱 and it has direct implications for how emissions are measured, allocated, and acted on.

𝗡𝗲𝗼𝗣𝗮𝗻𝗮𝗺𝗮𝘅 𝘃𝗲𝘀𝘀𝗲𝗹𝘀 and 𝗩𝗲𝗿𝘆 𝗟𝗮𝗿𝗴𝗲 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗦𝗵𝗶𝗽𝘀 operate on major long-haul corridors, moving large cargo volumes at high utilization levels.
𝗙𝗲𝗲𝗱𝗲𝗿 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀𝗵𝗶𝗽𝘀 serve regional networks, carrying smaller loads over shorter distances with materially higher emissions intensity.

𝗪𝗵𝗲𝗻 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗿𝗲𝗱𝘂𝗰𝗲𝗱 𝘁𝗼 𝗳𝗹𝗲𝗲𝘁-𝘄𝗶𝗱𝗲 𝗮𝘃𝗲𝗿𝗮𝗴𝗲𝘀, 𝘁𝗵𝗼𝘀𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿.

A shipper moving cargo on Asia-Europe routes and a shipper moving freight on short regional services end up looking at the same benchmark, one that accurately describes neither shipment.

𝗪𝗵𝗲𝗻 𝘁𝗵𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗴𝗮𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝘃𝗲𝘀𝘀𝗲𝗹 𝗰𝗹𝗮𝘀𝘀𝗲𝘀 𝗶𝘀 𝘁𝗵𝗶𝘀 𝘄𝗶𝗱𝗲, 𝘁𝗵𝗲 𝗼𝗻𝗹𝘆 𝗱𝗮𝘁𝗮 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲𝗹𝘆 𝗿𝗲𝗳𝗹𝗲𝗰𝘁 𝘆𝗼𝘂𝗿 𝘀𝗵𝗶𝗽𝗺𝗲𝗻𝘁 𝗶𝘀 𝗱𝗮𝘁𝗮 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝗱 𝗮𝘁 𝘁𝗵𝗲 𝘃𝗼𝘆𝗮𝗴𝗲 𝗹𝗲𝘃𝗲𝗹.

This is one of the findings from 𝗩𝗲𝘀𝘀𝗲𝗹𝗕𝗼𝘁’𝘀 𝗗𝗲𝗰𝗼𝗱𝗶𝗻𝗴 𝗠𝗮𝗿𝗶𝘁𝗶𝗺𝗲 𝗘𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗤𝟭 𝟮𝟬𝟮𝟲 report, based on 𝟴𝟮,𝟮𝟭𝟮 𝘃𝗼𝘆𝗮𝗴𝗲𝘀 across 𝟲,𝟭𝟴𝟳 𝘁𝗿𝗮𝗰𝗸𝗲𝗱 𝘃𝗲𝘀𝘀𝗲𝗹𝘀, with analysis by vessel class, age group, major fronthaul routes, and carrier performance.

The report highlights why 𝘀𝗵𝗶𝗽𝗺𝗲𝗻𝘁-𝗹𝗲𝘃𝗲𝗹 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 is becoming a prerequisite for accurate reporting, carrier assessment, and operational decision-making.

👉 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝘁𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁: https://registration.vesselbot.com/decoding-maritime-emissions-q1-2026-efficiency-under-pressure

“𝗗𝗼 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝘆𝗼𝘂𝗿 𝘁𝗿𝘂𝗲 𝗳𝘂𝗲𝗹 𝘀𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲 𝗰𝗼𝘀𝘁 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗮𝗰𝗿𝗼𝘀𝘀 𝗮𝗹𝗹 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁𝗮𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝘀?”
That was one of the central questions Constantine Komodromos, CEO and Founder of VesselBot, raised during VesselBot’s discussion with Bart A. De Muynck, former VP Analyst at Gartner, at the webinar 𝗧𝗵𝗲 𝗕𝗔𝗙 𝗕𝗹𝗮𝗰𝗸 𝗕𝗼𝘅: 𝗡𝗮𝘃𝗶𝗴𝗮𝘁𝗶𝗻𝗴 𝗦𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲𝘀 𝗶𝗻 𝗮𝗻 𝗘𝗿𝗮 𝗼𝗳 𝗗𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻.

It is a useful financial exercise because most organizations underestimate how much 𝗕𝗔𝗙 𝗮𝗻𝗱 𝗳𝘂𝗲𝗹 𝘀𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲 accumulates across carriers, trade lanes, and contract periods, and how directly it impacts the income statement.

𝗕𝘂𝘁 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝘁𝗵𝗲 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗶𝘀 𝗼𝗻𝗹𝘆 𝘁𝗵𝗲 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗽𝗼𝗶𝗻𝘁.

The discussion examined what becomes possible when shippers can benchmark fuel surcharge exposure against an 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 built from 𝘃𝗲𝘀𝘀𝗲𝗹-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗳𝘂𝗲𝗹 𝗰𝗼𝗻𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗮𝗰𝘁𝘂𝗮𝗹 𝘃𝗼𝘆𝗮𝗴𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀, 𝗿𝗼𝘂𝘁𝗶𝗻𝗴 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿 and 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗯𝘂𝗻𝗸𝗲𝗿 𝗽𝗿𝗶𝗰𝗲𝘀

Not only to understand exposure, but to act on it:
• in procurement discussions
• in carrier negotiations
• in financial planning and cost governance

The webinar also explored how to 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝘀𝘂𝗿𝗰𝗵𝗮𝗿𝗴𝗲𝘀 𝗮𝘁 𝗰𝗮𝗿𝗿𝗶𝗲𝗿 𝗮𝗻𝗱 𝘀𝗲𝗿𝘃𝗶𝗰𝗲 𝗹𝗲𝘃𝗲𝗹, and what changes operationally when procurement and finance teams move from 𝗮𝗰𝗰𝗲𝗽𝘁𝗶𝗻𝗴 𝗳𝘂𝗲𝗹 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻𝘀 to 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁𝗹𝘆 𝗮𝘀𝘀𝗲𝘀𝘀𝗶𝗻𝗴 𝘁𝗵𝗲𝗺.

🎙️ 𝗧𝗵𝗲 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗿𝗲𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝗶𝘀 𝗻𝗼𝘄 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗼𝗻 𝗱𝗲𝗺𝗮𝗻𝗱: https://app.livestorm.co/p/bbc35f06-d40c-472d-bbc1-0e750b05bc7b?utm_source=LinkedIn+&utm_medium=post&utm_campaign=BAF+Webinar+on+demand

𝗚𝗮𝗿𝘁𝗻𝗲𝗿 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗦𝘆𝗺𝗽𝗼𝘀𝗶𝘂𝗺/𝗫𝗽𝗼™ | 𝗗𝗮𝘆 𝗼𝗻𝗲
The VesselBot team is on the ground in Barcelona, actively participating in the sessions and conversations shaping the supply chain agenda for the year ahead.

𝗥𝗲𝗻𝗲𝘄, 𝗿𝗲𝘁𝗵𝗶𝗻𝗸, 𝗿𝗲𝗰𝗼𝗱𝗲. The theme sets the right direction.

From 𝗔𝗜 𝗿𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀 to 𝗰𝗼𝘀𝘁 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝘂𝗽𝗽𝗹𝘆 𝗰𝗵𝗮𝗶𝗻 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, these are topics VesselBot works on every day with global shippers, and the team is here to contribute to the discussion.

If any of these priorities are on your agenda, book a meeting with 𝗩𝗲𝘀𝘀𝗲𝗹𝗕𝗼𝘁 𝗖𝗘𝗢 Constantine Komodromos.

📍 𝗠𝗮𝘆 𝟭𝟴–𝟮𝟬 | 𝗕𝗮𝗿𝗰𝗲𝗹𝗼𝗻𝗮, 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻 𝗖𝗲𝗻𝘁𝗲𝗿
🎯 𝗕𝗼𝗼𝗸 𝘆𝗼𝘂𝗿 𝟭:𝟭 𝗺𝗲𝗲𝘁𝗶𝗻𝗴 👉 https://meetings.hubspot.com/ckomodromos/conferences-europe?uuid=19b2b08c-aa80-4c7e-9097-caebb45960%E2%80%A6&utm_id=97758_v0_s00_e0_tv4_a1demo0icqugrk&fbclid=IwY2xjawR35D5leHRuA2FlbQIxMABicmlkETBTWGFUZFVPdlpGNU9DM1dSc3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHjlBj1z327BChwAHW-ew-UwQ6DWifYq0uNG3IeUFKmGxfQg5NPWv7SE5MT1B_aem_1acLybdSNA4FCuTbnw2okA

𝗦𝗮𝗺𝗲 𝗿𝗼𝘂𝘁𝗲. 𝗦𝗮𝗺𝗲 𝗾𝘂𝗮𝗿𝘁𝗲𝗿. 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗰𝗮𝗿𝗿𝗶𝗲𝗿 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲.
One carrier recorded an emissions intensity of 65.6 g CO₂e per TEU km.
Another recorded 79.7. 𝗧𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗰𝗮𝗺𝗲 𝗱𝗼𝘄𝗻 𝘁𝗼 𝘂𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗽𝗼𝗿𝘁 𝗼𝗳 𝗱𝗲𝗽𝗮𝗿𝘁𝘂𝗿𝗲.

This is one of the findings from 𝗩𝗲𝘀𝘀𝗲𝗹𝗕𝗼𝘁’𝘀 𝗗𝗲𝗰𝗼𝗱𝗶𝗻𝗴 𝗠𝗮𝗿𝗶𝘁𝗶𝗺𝗲 𝗘𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗤𝟭 𝟮𝟬𝟮𝟲 report, covering 82,212 containership voyages across 6,187 tracked vessels.

The analysis examines how emissions intensity changes across 𝗏𝗲𝘀𝘀𝗲𝗹 𝗰𝗹𝗮𝘀𝘀𝗲𝘀, 𝗰𝗮𝗿𝗿𝗶𝗲𝗿 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀, 𝗺𝗮𝗷𝗼𝗿 𝗳𝗿𝗼𝗻𝘁𝗵𝗮𝘂𝗹 𝗿𝗼𝘂𝘁𝗲𝘀, and 𝗽𝗼𝗿𝘁-𝗽𝗮𝗶𝗿 𝗰𝗼𝗺𝗯𝗶𝗻𝗮𝘁𝗶𝗼𝗻𝘀, and why 𝗳𝗹𝗲𝗲𝘁-𝘄𝗶𝗱𝗲 𝗮𝘃𝗲𝗿𝗮𝗴𝗲𝘀 cannot capture the operational conditions that actually shape emissions outcomes.

Among the findings:
• Emissions intensity ranged from 𝟱𝟱.𝟮 𝗴 𝗖𝗢₂𝗲 𝗽𝗲𝗿 𝗧𝗘𝗨 𝗸𝗺 for Very Large Container Ships to 𝟮𝟲𝟲 for feeder containerships in the same quarter
• 𝗨𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 remained the 𝗽𝗿𝗶𝗺𝗮𝗿𝘆 𝗱𝗿𝗶𝘃𝗲𝗿 𝗼𝗳 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 across voyages
• On major fronthaul routes, 𝗰𝗮𝗿𝗿𝗶𝗲𝗿 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 shifted materially depending on 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆, 𝗰𝗮𝗿𝗴𝗼 𝘂𝘁𝗶𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗽𝗼𝗿𝘁-𝗽𝗮𝗶𝗿 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻

The report illustrates why 𝘃𝗼𝘆𝗮𝗴𝗲-𝗹𝗲𝘃𝗲𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 matters when decisions about carriers, cost exposure, and emissions need to reflect how shipments actually move, not how industry averages assume they move.

👉 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝘁𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁 : https://registration.vesselbot.com/decoding-maritime-emissions-q1-2026-efficiency-under-pressure?utm_source=LinkedIn&utm_medium=announcement+post&utm_campaign=Decoding+Maritime+Emissions+Q1+2926

𝗚𝗮𝗿𝘁𝗻𝗲𝗿 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗦𝘆𝗺𝗽𝗼𝘀𝗶𝘂𝗺/𝗫𝗽𝗼™ 𝗶𝗻 𝗕𝗮𝗿𝗰𝗲𝗹𝗼𝗻𝗮 𝗶𝘀 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵𝗶𝗻𝗴 𝗮𝗻𝗱 𝗩𝗲𝘀𝘀𝗲𝗹𝗕𝗼𝘁 𝘄𝗶𝗹𝗹 𝗯𝗲 𝘁𝗵𝗲𝗿𝗲.

The agenda covers the four conversations every 𝗖𝗦𝗖𝗢 is navigating right now: 𝗔𝗜 𝗮𝗻𝗱 𝗲𝗺𝗲𝗿𝗴𝗶𝗻𝗴 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆, 𝗰𝗼𝘀𝘁 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗿𝗶𝘀𝗸 𝗮𝗻𝗱 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝘂𝗽𝗽𝗹𝘆 𝗰𝗵𝗮𝗶𝗻 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻.

𝗧𝗵𝗲𝘀𝗲 𝗮𝗿𝗲 𝗼𝗳𝘁𝗲𝗻 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗲𝗱 𝗮𝘀 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝗲𝘀. Operationally, they are deeply connected. Because supply chains that cannot access 𝗴𝗿𝗮𝗻𝘂𝗹𝗮𝗿, 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲, 𝘀𝗵𝗶𝗽𝗺𝗲𝗻𝘁-𝗹𝗲𝘃𝗲𝗹 𝗱𝗮𝘁𝗮 will struggle to:
• 𝗠𝗮𝗸𝗲 𝗔𝗜 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹𝗹𝘆 𝘂𝘀𝗲𝗳𝘂𝗹
• 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗰𝗼𝘀𝘁𝘀 𝘄𝗶𝘁𝗵 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲
• 𝗥𝗲𝘀𝗽𝗼𝗻𝗱 𝘁𝗼 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻 𝗯𝗲𝗳𝗼𝗿𝗲 𝗶𝘁 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱𝘀
• 𝗦𝘂𝘀𝘁𝗮𝗶𝗻 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲

In VesselBot's collaboration with global shippers, these four challenges consistently converge on the same issue: 𝗔 𝗱𝗮𝘁𝗮 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗯𝘂𝗶𝗹𝘁 𝗳𝗼𝗿 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗶𝘀 𝗻𝗼𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗮𝘀 𝗼𝗻𝗲 𝗯𝘂𝗶𝗹𝘁 𝗳𝗼𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

Closing that gap is where 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗳𝗿𝗲𝗶𝗴𝗵𝘁 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 becomes operationally relevant; not only for sustainability and compliance, but across procurement, planning, resilience, and operational ex*****on.

The conversations on the agenda this year are ones where VesselBot has a 𝗰𝗼𝗻𝗰𝗿𝗲𝘁𝗲 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 𝘁𝗼 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲, grounded in how logistics networks actually operate.

𝗜𝗳 𝘆𝗼𝘂’𝗹𝗹 𝗯𝗲 𝗶𝗻 𝗕𝗮𝗿𝗰𝗲𝗹𝗼𝗻𝗮, 𝘆𝗼𝘂’𝗹𝗹 𝗵𝗮𝘃𝗲 𝘁𝗵𝗲 𝗰𝗵𝗮𝗻𝗰𝗲 𝘁𝗼 𝗺𝗲𝗲𝘁 𝗼𝘂𝗿 𝗖𝗘𝗢
📍 𝗠𝗮𝘆 𝟭𝟴–𝟮𝟬 | 𝗕𝗮𝗿𝗰𝗲𝗹𝗼𝗻𝗮, 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻 𝗖𝗲𝗻𝘁𝗲𝗿
🎯 𝗕𝗼𝗼𝗸 𝘆𝗼𝘂𝗿 𝟭:𝟭 𝗺𝗲𝗲𝘁𝗶𝗻𝗴 👉https://meetings.hubspot.com/ckomodromos/conferences-europe?uuid=19b2b08c-aa80-4c7e-9097-caebb45960%E2%80%A6

𝗧𝗵𝗲 𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗚𝗛𝗚 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹’𝘀 𝗻𝗲𝘄 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗶𝘀 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴𝗹𝘆 𝗰𝗹𝗲𝗮𝗿: 𝗦𝗽𝗲𝗻𝗱-𝗯𝗮𝘀𝗲𝗱 𝗮𝗽𝗽𝗿𝗼𝘅𝗶𝗺𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝘀𝘂𝗽𝗽𝗹𝗶𝗲𝗿 𝗮𝘃𝗲𝗿𝗮𝗴𝗲𝘀 𝘄𝗶𝗹𝗹 𝗻𝗼𝘁 𝗯𝗲 𝗲𝗻𝗼𝘂𝗴𝗵.

The draft 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗠𝗮𝗿𝗸𝗲𝘁 𝗜𝗻𝘀𝘁𝗿𝘂𝗺𝗲𝗻𝘁𝘀 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱 introduces three reporting statements alongside the existing Physical GHG Inventory:
· 𝗧𝗵𝗲 𝗠𝗮𝗿𝗸𝗲𝘁 𝗕𝗮𝘀𝗲𝗱 𝗚𝗛𝗚 𝗜𝗻𝘃𝗲𝗻𝘁𝗼𝗿𝘆 covers instruments such as SAF and biofuel certificates.
· 𝗧𝗵𝗲 𝗚𝗛𝗚 𝗜𝗺𝗽𝗮𝗰𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 is designed to quantify the impact of specific decarbonization actions.
· 𝗡𝗼𝗻-𝗚𝗛𝗚 𝗜𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿𝘀 cover supporting metrics not expressed in CO₂e that may influence decarbonization decisions.

𝗪𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 is that both the 𝗠𝗮𝗿𝗸𝗲𝘁 𝗕𝗮𝘀𝗲𝗱 𝗚𝗛𝗚 𝗜𝗻𝘃𝗲𝗻𝘁𝗼𝗿𝘆 and the 𝗚𝗛𝗚 𝗜𝗺𝗽𝗮𝗰𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 depend on the Physical GHG Inventory as their reference point.

𝗔𝗻𝗱 𝘁𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝗲𝗿𝗲 𝘁𝗵𝗲 𝗹𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗼𝗳 𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲𝗱 𝗦𝗰𝗼𝗽𝗲 𝟯 𝗱𝗮𝘁𝗮 𝘀𝘁𝗮𝗿𝘁 𝘁𝗼 𝗯𝗲𝗰𝗼𝗺𝗲 𝗺𝗼𝗿𝗲 𝘃𝗶𝘀𝗶𝗯𝗹𝗲.

The issue with spend-based methodologies, supplier averages, and proxy data is not only precision. 𝗜𝘁 𝗶𝘀 𝘁𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗰𝗮𝗻𝗻𝗼𝘁 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗮 𝗰𝗼𝘂𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝘁𝘂𝗮𝗹.

Claiming an emissions reduction in a 𝗚𝗛𝗚 𝗜𝗺𝗽𝗮𝗰𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 (from a carrier switch or a routing change) requires demonstrating what emissions would have been without that action.
𝗗𝗮𝘁𝗮 𝗯𝘂𝗶𝗹𝘁 𝗼𝗻 𝘀𝗽𝗲𝗻𝗱 𝗿𝗮𝘁𝗶𝗼𝘀 𝗮𝗻𝗱 𝗵𝗶𝘀𝘁𝗼𝗿𝗶𝗰𝗮𝗹 𝗮𝘃𝗲𝗿𝗮𝗴𝗲𝘀 𝗰𝗮𝗻𝗻𝗼𝘁 𝗺𝗮𝗸𝗲 𝘁𝗵𝗮𝘁 𝗰𝗮𝘀𝗲.

A formal public consultation on the draft standard is planned for Q3 2027.
The final standard is expected by end of 2028.

𝗧𝗵𝗮𝘁 𝘁𝗶𝗺𝗲𝗹𝗶𝗻𝗲 𝘀𝗼𝘂𝗻𝗱𝘀 𝗱𝗶𝘀𝘁𝗮𝗻𝘁. 𝗜𝘁 𝗶𝘀 𝗻𝗼𝘁 for companies whose Scope 3 data infrastructure still depends on approximations.

𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 𝗲𝘀𝘁𝗮𝗯𝗹𝗶𝘀𝗵 𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻 𝗯𝗲𝗳𝗼𝗿𝗲 𝗲𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗮𝗿𝗿𝗶𝘃𝗲𝘀. The companies building 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗴𝗿𝗮𝗱𝗲 𝗲𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 now will be materially better positioned than those waiting for compliance requirements to force the transition.

Bunker Adjustment Factors (BAF) surcharges are based on internal carrier calculations. 𝗧𝗵𝗲𝗿𝗲 𝗶𝘀 𝗻𝗼 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺 to assess whether what shippers are charged reflects the actual fuel cost surcharges of their shipments.

On 𝗠𝗮𝘆 𝟭𝟯, Constantine Komodromos, CEO and Founder of VesselBot, and Bart A. De Muynck, Head Thinker of Better Supply Chains / ex-VP Analyst at Gartner, will examine how this can change.

Specifically, whether an 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗼𝗻, that combines vessel-specific fuel consumption models, ex*****on patterns, and real-time fuel prices, can provide a 𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝗲 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗳𝗼𝗿 𝗕𝗔𝗙.

𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲 https://app.livestorm.co/p/bbc35f06-d40c-472d-bbc1-0e750b05bc7b to join the discussion.