Ep. 6 - Fixing Freight Rates with Data Ownership | With Sam Tibbs

About this episode

What happens when a Navy nuclear power alum and finance PhD turns his focus to trucking? Sam Tibbs joins us to make a bold case: freight doesn’t have a tech problem, it has an incentive problem. He traces the unlikely route from teaching and data science to building the tools that exposed lane-level profit and drove the most-used variables in Sonar, then explains why today’s rate products miss the mark. If your pricing relies on paperwork extracted after delivery and guesses that fill in missing details, you’re driving with fogged windows.

We dig into the real bottleneck: timely, detailed data at the moment of booking. Sam argues that brokers create the signal, yet pay to buy back their own data days later, stripped of nuance like stops, hazmat, or lead time. His answer is refreshingly practical and familiar to anyone in finance: build a neutral, broker-owned data layer, much like how MasterCard aligned competing banks, where contributors are rewarded for high-quality inputs. With ownership and governance in place, the incentives flip, participation rises, and the rate product can finally show distributions that move with the market instead of stale averages.

Along the way, we contrast “great data plus a good model” with “good data plus a great model,” explore why LLMs can’t rescue missing truth, and outline where competitors should cooperate versus where they should battle. The near-term payoff is a cleaner rate signal and fewer pricing mismatches; the long-term vision is brokers turning a cost center into a profit center while shippers and carriers benefit from sharper, faster decisions. If you care about freight pricing, data quality, or building markets that actually work, this conversation maps a credible path forward.

If this resonates, follow the show, share it with a colleague, and leave a quick review so more folks in freight can find it. What's your take: should brokers own the data layer or keep buying it back?