• September 30 - October 2, 2024
  • Inland Distribution
  • September 29 - October 1, 2025 | The Westin Chicago River North

Ken Adamo

DAT Freight & Analytics

Chief of Analytics and Vice President of Strategy

Ken Adamo, Chief of Analytics and Vice President of Strategy at DAT Freight & Analytics, oversees strategy, customer engagement, and industry analysis. Before DAT, he led pricing and decision science teams at FedEx, crafting innovative models using internal and external data to enhance decision-making and profitability.

Recognized as an authority on freight market trends in esteemed publications like the Journal of Commerce and the Wall Street Journal, Ken leads a team of experts studying all aspects of logistics to provide top insight to customers. He was named a Pro to Know in 2021 by Supply and Demand Chain Executive.

Ken holds a bachelor's degree in Finance from the University of Akron and an MBA from The Ohio State University.

Sessions With Ken Adamo

Tuesday, 1 October

  • 09:30am - 10:00am (CST) / 01/oct/2024 02:30 pm - 01/oct/2024 03:00 pm

    One-on-One: A Conversation with DAT Freight & Analytics' Ken Adamo

     A flood of data on the truckload market presents an interesting conundrum for shippers and brokers. While more is better than less, too much can also be a bad thing. In other words, sorting through all the noise to find the signal that matter for an individual business can be a herculean task, one that is sometimes beyond the scope of a transportation department. And yet, each shipper and broker in the market needs to understand these signals to make critical pricing and service decisions. In this session, Ken Adamo, DAT Freight & Analytics' chief of analytics and vice president of strategy, will help attendees drill down to the data points that matter when dissecting the current and future states of the truckload market. The session will touch on: specific metrics that are important to track when it comes to truckload rates, service, and capacity; how to formulate a diversified but manageable data strategy; and determining whether data science capability should be handled in-house or outsourced.

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