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Introducing AI-Powered Smart Receive to End Receiving Chaos and Protect Margin
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Welcome back to Flyntlok Unlocked!
The idea here is to take you behind the scenes, unlocking Flyntlok product insights, with the very people building and implementing the tools you use every day. Thank you for joining us!
I’m your host Jenny Moebius, Flyntlok’s CMO, and today we’re talking about one of the biggest balancing acts inside any dealership: Smart Stocking and How to Take the Guesswork out of Parts Inventory.
How do you stock enough inventory to meet demand… without tying up cash in parts that sit on shelves for months?
Because every dealership has lived both sides of this problem:
And most of the time, purchasing decisions are still being made with spreadsheets, tribal knowledge, and gut instinct.
So today we’re diving into Smart Stocking:
“Better stocking decisions. Better cash flow. Better margins.”
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Host: Jenny Moebius, CMO, Flyntlok
Guest: Dean Frederick, Senior Implementation Consultant, Flyntlok
Every dealership has lived both sides of the same frustrating problem: you either run out of critical parts during peak season, or you walk the warehouse floor staring at shelves full of inventory nobody has touched in a year. It's one of the biggest balancing acts in the business — stocking enough inventory to meet demand without tying up cash in parts that sit collecting dust.
And yet, most purchasing decisions are still being made with spreadsheets, tribal knowledge, and gut instinct.
That's the problem Flyntlok's Smart Stocking tool was built to solve. In Episode 2 of Flyntlok Unlocked, host Jenny Moebius sits down with Dean Frederick — Flyntlok's Senior Implementation Consultant and a twelve-year dealership veteran — to break down what's broken about the status quo, how Smart Stocking works, and what dealerships actually gain when they start letting data drive their purchasing decisions.
Before Dean joined Flyntlok to help dealers implement smarter workflows, he spent over a decade on the dealership side — including time working directly on the parts counter. It's what makes him unusually credible on this topic. He's not just someone who studied the problem. He lived it.
He comes with stories to prove it. In one memorable exchange, Dean described a situation where a customer brought in a machine for parts, provided a serial number, and Dean ordered accordingly — only for the part to come in wrong. Then wrong again. Then wrong a third time. The culprit? The customer was working with a gray market mini excavator — a machine originally sold in Asian markets, with a completely different parts catalog — and had been giving Dean the serial number for a different gray market machine he didn't even own anymore. After all that back and forth, the customer finally got the right part. His response: "Thanks."
"Being on the front lines for quite some time," Dean says, "really gave me some insight to how these challenges can come up."
Most dealerships today rely on what's called a min/max system. You find a part number, decide you always want at least four on hand and never more than ten, set those thresholds, and move on. Multiply that across thousands of part numbers, and you start to see the problem.
"The data is constantly evolving," Dean explains. "One part number might be more frequently sold this year than it was last year. One part hasn't been sold in two years. But whatever those min/maxes were set at the time, they basically hold true and are not evolving with the real world."
It's a set-it-and-forget-it approach — and that's exactly where things go sideways.
Purchasing ends up being reactive rather than strategic. A customer comes in for a part you don't have. They get upset. You set a new min/max so you always have that part on hand going forward — without ever stopping to check whether there's any data behind that decision. Maybe this was the first time that part had ever been sold. Maybe there's no meaningful history to justify stocking it. But you've now committed shelf space and cash to it anyway.
"You end up with all of these one-off parts because you're just reacting to the situation," Dean says. "The customer comes in, they're upset, and you think: I don't want anyone else to be upset with me. But it's not being driven by a larger dataset."
The static min/max problem becomes especially acute when seasons change. Dean uses fuel filters as an example — something dealers in New England sell significantly more of in the winter, when fuel gels in cold weather and machines need to be kept running.
If nobody is actively monitoring and adjusting stocking quantities for seasonal demand, one of two things happens: you're overstocked with filters you don't need during the slow season, or you're caught completely flat-footed when demand spikes. Either way, customers feel it.
"How could you not have fuel filters on hand?" a customer might say. The answer — that nobody adjusted the min/max for seasonality — isn't one that goes over well.
And this problem compounds at scale. Dealerships with multiple locations, multiple brands, and massive parts catalogs don't have the bandwidth to manually account for all of it. The data changes every day. Human attention doesn't scale to match.
At the highest level, Dean puts it simply: "Smart stocking is a math equation."
The system looks at your complete parts sales history and runs a calculation — one that's customized per vendor and updated every single day. Today's activity feeds tomorrow's recommendations. Seasonality is baked in. And critically, it covers every single part number in your system, not just the ones you're currently paying attention to.
During a live demo walkthrough, Dean pulled up Flyntlok's Purchasing Hub to show exactly how Smart Stocking works in practice.
The Purchasing Hub gives a full view of all dealership locations on the left, with vendors and their recommended stock order demand listed alongside. A parts manager overseeing multiple locations can work from a single screen — no jumping between systems.
From there, Dean created a draft stock order for a specific vendor and location, landing on what he calls "a bit of a worksheet screen." Here's what you're looking at, left to right:
And then, on the far right, the "under the hood" columns that drive the recommendation:
That second metric matters more than it might seem. If you sold 100 bolts but they all went to one customer on one invoice, Flyntlok flags that — it's not a pattern that justifies stocking a hundred bolts. Sales volume and sales frequency are both part of the picture.
For seasonality, the system adds two more columns:
So as you move into fall, the algorithm is already looking ahead at what sold last October, November, and December — and adjusting recommendations accordingly. Fuel filter demand in New England winters, for example, gets captured automatically.
The entire design is aimed at achieving what Dean calls "healthy turns" — the industry standard of three to four full inventory cycles per year. Parts shouldn't sit on a shelf for over a year unsold. Smart Stocking helps ensure they don't.
One point Dean is careful to make: Smart Stocking doesn't place orders for you. It gives you intelligent recommendations that you review, adjust, and approve.
"We're not taking that control out of your hands," he says. "We're just providing a tool to help you make decisions."
So if the system recommends ordering a transmission because three were sold in the last year, a parts manager can look at that and say — reasonably — that three transmissions doesn't justify a standing stock order. You can override it. The goal is to surface information you might have missed, not to remove the human judgment that makes a good parts department good.
For multi-location, multi-brand operations, that assist is especially valuable. Managing five vendors with a couple hundred parts each is manageable. Managing ten manufacturers with massive catalogs is not — not without a system that helps you keep up.
Dean says the first thing dealers notice is time. When Smart Stocking surfaces its recommendations, there's an immediate "shock value" — the realization of how much manual effort used to go into this, and how much of that work was producing outdated results.
"They see these recommendations and they start making sense," Dean says. "Oh, these are the parts I would regularly stock." Parts they hadn't thought about in a while show up. The hours that used to go into manually updating min/maxes — work that was already out of date the moment it was done — start coming back.
A month or two in, the dollar impact becomes visible. Cash flow improves because purchasing is no longer reactive. Money isn't tied up in parts that were ordered on instinct or in response to a single upset customer. What's on the shelves is actually moving.
And on the customer side, fewer stockouts mean fewer frustrated conversations at the parts counter. Customers who regularly buy fast-moving parts know what should be in stock — and they're far more forgiving about genuine one-off special orders than they are about basic inventory gaps.
Jenny posed the question directly: if you took Smart Stocking away from a dealership after thirty days, what would they miss first?
Dean's answer: "It'd be like giving somebody a drill for thirty days and then handing them a screwdriver and saying: alright, keep doing what you were doing."
Smarter inventory decisions ripple outward: less stale and aging inventory, improved cash flow, fewer emergency orders, faster decisions for purchasing teams, and healthier parts margins. In an industry where margins are tight, those downstream effects matter.
Better stocking decisions lead to better cash flow. Better cash flow leads to better margins. That's the core promise of Smart Stocking — and, as Dean would tell you, it's a promise built on math, not gut instinct.
Thanks to Dean Frederick for joining us this episode. Tune in next time for more behind-the-scenes conversations on the tools, workflows, and operational challenges shaping modern dealerships. Keep the world going around.
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