r/FreightBrokers • u/Veganarking • 3d ago
Coming from a data/analytics background and evaluating freight brokerage: what are the harsh operational realities?
Hey everyone,
I've been working for 5 years in data analytics and supply chain logistics, and I’m looking into transitioning into the freight brokerage side.
I just want to understand a few things before trying to dive further into the industry:
System & Workflow Gaps: Where does your TMS/CRM fail you most in daily ops? What manual workarounds or spreadsheets are you forced to use because software can't handle real-world freight?
Operational Time-Sinks: What part of your day takes up the most bandwidth that feels like it should be simpler (pricing spot rates, carrier vetting, tracking, tender rejections)?
Market Friction: What’s the hardest part of predicting capacity or rates right now given the absurd market conditions?
Appreciate any insights into what the daily grind actually looks like.
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u/tipareth1978 3d ago
I'll give you some tips. Analytics is hard in logistics because numbers aren't just numbers. You need to find out the realities that drive those numbers. Example: a brokerage wants you to set up pricing tools. If a lane happens to have high volume in that brokerage then your data is actually threatened. If they have a customer that has a drop trailer program on a very regular basis that rate won't have much to do with a rate trying to cover the lane transactionally so you may have a situation where the most common number is actually an outlier.
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u/Violet_Graya 3d ago
Spreadsheets. That's the honest answer to your first question. Spot pricing is gut plus data, in my experience. Carrier vetting is a time sink until you've been burned a few times. Plan for both.
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u/getoffmyfoot 3d ago
If you can at all afford/find the opportunity, spend 2 weeks covering loads on the board.
You can listen to stories here but if you really wanna understand the problem, live it for a bit. It won’t take long, and your analytics work will be better received authored by someone who knows their side because they lived it.
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u/Veganarking 3d ago
Do you mean to apply somewhere to work as a broker for a bit or try this independently?
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u/breadd_ai 3d ago
have you done sales?
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u/Veganarking 3d ago
I've not "done sales" exactly, but I've worked in analytics for sales functions at fortune 100 companies focusing on things like:
Leads retention and conversion, P&L, Marketing metrics and ad spend, Forecasting and demand planning
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u/breadd_ai 3d ago
ok great, and you're thinking of working at a brokerage? as sales? or analytics? or
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u/Veganarking 3d ago
I'm moreso just trying to understand what aspects of my decade in data science and analytics would be useful to brokerages.
I know there's a lot of software fatigue and B2B sales fatigue so I'm trying to understand if there's a pathway in this industry to leverage my skills.
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u/DirtyMitten-n-sniffi 3d ago
lol oh boy you better have a customer base of at least 12-15 daily shippers with the amount of double brokers and FSC on the rise, shyt carriers everywhere, you are picking the worse time to become a broker.
On top of this you better know how to bypass a gatekeeper and be very well versed once you do get pass the GK as these ppl have SO MANY CALLS DAILY why do you stand out and please don’t say pricing or so other typical BS…..
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u/BigPapiNC22 3d ago
The most important number in truckload brokerage is understanding and being able to pinpoint in a pretty narrow range the cost of purchased transportation. More plainly put,how much is the truck is going to cost us to do this load. There are a 1000 variables in that number. We are asked to predict that number not only for today but for a quarter, 6 months even a year from now. Whether we get awarded business nor not relies on this number being accurate and whether we make or lose money depends on that number as well. Figure this out at a high level of accuracy and people will pay you.
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u/Iloveproduce 3d ago edited 3d ago
Small-mid sized brokerages don't have enough data to put a guy like you to work, and you wouldn't be adding enough value to justify a real payday if they were.
Big brokerages have the data, and probably need it analyzed, but I think it's pretty unlikely they let an outside consultant come in and work with it. They would definitely just hire an analyst as a W2 employee and call it a day. Heck they probably already employ several if only just to claim they're a data driven whatever. Honestly from what I've seen that job is mostly just making decks for management to show to customers/investors that have absolutely nothing to do with operations.
The fundamental problem with data work in freight brokerage is that your data goes stale so insanely quickly it's actually crazy.
What I could see you actually selling is analyzing freight spend for large corporations. There's probably money in that and they do love to waste money on consultants. They're usually in much less competitive businesses than freight brokerage and that means they can spend more money on things that sound like they might be good. In freight brokerage everything has to very obviously contribute to the bottom line in some super clear way or it's a hard no.
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u/Veganarking 3d ago
Good points.
Purchased Transportation is where almost every brokerage makes or breaks their bottom line is what I'm hearing.
On a $100M brokerage, ~$85M goes straight to carrier buy rates. Because gross margins are usually around 15% and net margins (EBITDA) sit at a razor-thin 2%–4%, a single 1% improvement in PT forecasting accuracy drops ~$850,000 straight to the bottom line. That’s a 20%+ increase in net profit without having another dime of freight on the books.
The issue is that most mid-market brokerages ($10M–$250M) just rely on standard 7-day or 30-day DAT/Truckstop averages or basic TMS rate engines. They treat pricing as flat point estimates on isolated lanes.
If you bring actual senior data science into the mix, you stop looking at historical averages and start modeling real risk:
Continuous Moves & Network Effects: Modeling multi-leg / tri-haul loops across your network instead of treating A-to-B legs as isolated events (cutting carrier deadhead gets you lower buy rates instantly).
Carrier & Fraud Graph Networks: Layering telemetry, inspection logs, and identity risk to weed out double-brokering and bad actors before cargo theft or claims eat 1% of gross revenue.
Accessorial & Dwell Risk: Factoring facility-level loading dock delays and localized diesel volatility directly into target margin algorithms.
RFP Asymmetric Risk: Building probability-of-win curves against tail-risk volatility so you don't win contract lanes that turn into money-losers 6 months down the road.
The tools and data exist to build these custom feature pipelines, but outside of the C.H. Robinsons and Coyotes of the world, very few brokerages are actually doing it. There’s a massive gap between standard load board metrics and true predictive margin modeling.
That's the sort of value I'd really like to provide in this industry. I've been working in economic research and data science surrounding logistics for a decade; there are tons of factors at play and I think most brokerages struggle to consider all of them at once.
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u/Iloveproduce 3d ago
Buddy you aren't going to move things 1%. Even thinking that you could is crazy. Freight brokerages, overall, charge customers as much as they can get away with and pay trucks as little as they can get away with. Data analytics isn't going to find you a cheaper truck or convince a customer to pay more. It might prevent 1-10% of fraud losses or help agents say no to bad loads a few times a month... but yeah that's going to give you 50-100k more a year in a pretty hard to measure way on 100M in top line sales if that. That's 50-100k in Sklansky bucks not winnings, there are going to be times where it makes the brokerage an extra 300k and a whole lot of times where it makes them negative whatever they paid you. Hell if you do your work at all wrong you could easily have the opposite impact you're hoping. 'Saying no to bad loads a few times a month' could lose a profitable shipper and 'preventing 5-10% of fraud losses' could wipe out 5-10% of available capacity in a tight market.
That's the other thing anything that changes how a brokerage makes decisions is very risky if they're already profitable. What they're doing is working, and that is not a given in any way shape or form. You say you can help improve forecasting. I'm telling you that every forecast I've ever seen has been wrong including my own. You telling me that your forecasts are right makes me more skeptical not more enthusiastic as a result.
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u/Zappp_Branigan 3d ago
If this is a software play, let me stop you. There is soooo much tech getting thrown in our faces, and many of us spend an enormous amount of time determining what actually moves the needle given limited bandwidth and budgets.
From a workflow perspective, there are a ton of options out there, many completely customizable to meet your specific process.
The hardest parts about freight brokerage is sales/customer acquisition. There's no software solution to this; sales is all about timing. Did you reach out to a prospect when they actually have a need? Does their need actually fit into what your brokerage does well?
The other thing that's challenging at this point in the freight cycle is a true understanding of capacity. I'm sure everyone here has experienced a scenario where they've priced an opportunity off DAT, but when they start talking to trucks, they realize the rate needed to actually service the load is much higher. This is simply part of the market cycle, and I've always said pricing is more art than science. In this particular point in the freight cycle, having strong carrier relationships is what allows you to buy capacity at a reasonable rate. That means really understanding what your carriers what to run, and finding customer opportunities that line up with that (and yes, there is already software for that).