The Starbucks Mobile Order Timing Problem That Chick-fil-A Already Solved

The whole point of mobile ordering is that your drink is ready when you arrive. You order ahead, you show up, you grab it and go. Less waiting for you, less congestion at the register, a smoother experience for everyone. That's the promise.

Here's what actually happens a lot of the time.

You place your order from the car, five or ten minutes away. You walk in, and your latte has been sitting on a crowded counter long enough to cool down. Or your iced drink is sweating through the cup. Or your Frappuccino is halfway to a milkshake. The app says “Ready for pickup!” — and technically it is. It's just not the drink you wanted anymore.

Or the opposite: you arrive and your drink isn't ready. You stand around scanning the counter, trying not to get in the way. The baristas are slammed. Nobody makes eye contact. You wait. Five minutes. Ten. You wonder why you didn't just order at the register.

The drive-thru version might be worse. I've had this happen: I place a mobile order, pull up to the window, and get asked to drive around and wait because the drink isn't ready yet. At that point, what exactly did mobile ordering buy me? I could have ordered at the speaker box and gotten the same result — maybe faster, since at least then they'd start making my drink when I'm clearly there.

The promise of mobile ordering is that you're trading a wait in line for a seamless pickup. But when the drink is made at the wrong time — too early or too late — you're not saving time. You're just relocating the wait and getting a worse drink for the trouble.

That's the cost of the current system from the customer side. From behind the counter, it looks different but feels just as bad.

Baristas are producing drinks with no idea when — or whether — the customer will show up. They're making 15, 20 beverages that pile up on the pickup counter, many of them unclaimed. They're fielding questions from people who can't find their order. They're apologizing for delays they didn't cause. They're remaking drinks that sat too long. If a customer complains, the barista absorbs it — even though the system set them up to fail.

Nobody is slacking. The baristas are working hard within a process that gives them almost no useful information about when to make what.

What Problem Are We Trying to Solve?

Before jumping to any solution, it's worth sitting with the problem a little longer.

The visible symptom — the crowded pickup counter, the lukewarm lattes, the confused customers — isn't the root issue. The core problem is a mismatch between when drinks are produced and when customers arrive to pick them up. Starbucks seems to be making drinks based on when orders are placed, with no information about when customers will actually show up.

From a Lean perspective, that's one type of overproduction (making something before it's needed). Not because anyone is doing something wrong, but because the system is producing finished goods before the customer is ready to receive them. The drinks become finished goods inventory — sitting in queue, losing value with every passing minute. Quality degrades. Counter space fills up. And the baristas end up managing the consequences.

So the question isn't “how do we make drinks faster?” The baristas are already working hard. The question is: how do we make drinks at the right time?

What Would “Right Time” Even Mean?

If you could design the ideal mobile order process from scratch, you'd want the drink to be finished just as the customer walks through the door or pulls up to the window. Not five minutes before. Not five minutes after. Just in time.

That phrase — “just in time” — isn't just a buzzword. In manufacturing, it describes a production philosophy built around matching output to actual demand rather than forecasted demand. You don't build inventory ahead of time and hope someone comes to claim it. You produce in response to a real signal that someone needs it now.

Now, Starbucks does have to order supplies and ingredients to the stores based on a forecast. And when there's a gap between forecasted needs and actual, that's when items or beverages become “out of stock.”

The signal Starbucks currently uses appears to be the order itself. I don't know the actual production logic — Starbucks hasn't published how stores sequence mobile orders (or I haven't found it), and it may well vary from store to store (although I doubt is does), like so many other things in their process.

But from what I can see as a regular customer, drinks seem to get made in roughly the order they're placed. Whether that's official policy or just the default behavior of a busy queue, the effect is the same: the system has no information about when I'll actually arrive. I might be in the parking lot. I might be 15 minutes away. Both orders enter the queue the same way.

A better signal would include proximity — how far the customer is from the store and roughly when they're expected to arrive. That would let the store sequence drink production not by who ordered first, but by who's arriving first.

This Isn't a Hypothetical — Others Are Already Doing It

What makes this worth writing about isn't just the idea. It's that other large chains have already built exactly this. This is a solvable problem. I mean, a solved problem.

Chick-fil-A uses geofencing in its app so that when customers enable location services, the app detects when they're approaching the restaurant and signals the kitchen to start preparing the order. They tested it at 100 locations and found that customers' wait times dropped by one to two minutes, while estimated wait times were accurate more than 90% of the time.

McDonald's has a similar program they call “Ready on Arrival.” Their app notifies the restaurant when a mobile order customer is within about three minutes of the location, prompting the crew to start preparing the food. McDonald's reported a 62-second reduction in wait times for mobile pickup customers and is expanding the program to additional markets in 2026.

Target's Drive Up system takes it even further for retail pickup. When customers opt in to location sharing, the app updates the store team on the customer's estimated arrival as they approach. The team starts preparing the order based on that proximity signal rather than the moment the order was placed.

None of these companies had to invent new technology. They connected location data they were already collecting to the production process that needed it.

Starbucks Already Has the Data

Here's what's puzzling. Starbucks already uses GPS-based location data in its app — for finding nearby stores, for sending promotional push notifications when you're near a location. They're using my location to market to me. They're just not using it to make my drink ordering and pick up experience better.

The Starbucks app also already sends status notifications — “Order received,” “Being prepared,” “Ready for pickup.” Those updates require manual input from baristas on a tablet, adding to their workload without adding much value. (I've often had my drink in hand before the “Ready for pickup” notification arrives.)

The information needed to improve drink sequencing is already flowing through the system. It's just not connected to the process that would benefit from it.

How This Would Help the People Behind the Counter

I covered the barista experience at the top of this post, but it's worth connecting it to the system design question. The stress baristas feel isn't a morale problem or a training problem. It's an information problem.

Right now, baristas are producing into a void. They don't know if the customer is walking through the door or still sitting in their driveway. A proximity-based signal would change that. It would give them a reason to believe that the drink they're about to make is for someone who's actually about to pick it up.

That's less wasted effort, less rework, and fewer frustrated interactions — for customers and for staff.

In Lean terms, that's respect for the people doing the work. You're giving them better information so they can do a better job — not asking them to work harder within a broken system.

It's a Software Problem, Not an AI Problem

I think there's a tendency to label anything involving algorithms and data as “AI.” What I'm describing here is closer to basic software logic: if you know how far the customer is, estimate when they'll arrive, and use that estimate to sequence drink production. That's a scheduling algorithm, informed by GPS data the app already collects.

Could you use machine learning to improve the estimates over time — accounting for traffic patterns, time of day, or customer behavior? Sure. That might make it incrementally better. But the core improvement doesn't require anything fancy. It requires connecting a data source (customer location) to a process (drink production sequencing) that currently ignores it.

McDonald's calls their version “Ready on Arrival.” Chick-fil-A just calls it geofencing. Neither company describes it as AI. It's process improvement enabled by software — which is something Lean thinkers have been doing for decades, just with different tools.

And Then There's the Nitro Cold Brew Question

This connects directly to the Nitro Cold Brew inconsistency I've written about before — first in my observations about pickup variation across stores, and again when Starbucks got a new CEO and acknowledged the experience was broken.

Some stores follow what's said to be the offical policy of not pouring Nitro until the customer arrives, because they believe the drink “goes flat” (it doesn't, but that's a separate conversation). Other stores pour it the moment the order hits the queue. There's no standard.

If the app knew I was three minutes away, the system could signal the barista to start the pour at the right time — no awkward announcements, no empty cups on the counter, no guessing. The barista wouldn't need to wonder if I'm in the store or still driving.

That would also eliminate the bizarre situation I've described before — standing inside the store, having ordered through the app, and being told “we wait until you're here” while I'm literally right there. The system would know.

So Why Hasn't This Happened?

Starbucks has the app infrastructure, the customer location data (for those who opt in), and the store-side technology. Two of their biggest fast-food competitors are already doing this at scale.

My guess is that the obstacle is organizational, not technical. The team that manages the app's marketing features — location-based promotions, push notifications — probably doesn't sit in the same room as the team that designs store operations and drink production workflows. The data exists in one silo. The process problem lives in another.

That's a pattern worth paying attention to, because it shows up everywhere — not just at Starbucks. The information that would improve a process is often already being collected somewhere in the organization. It's just not reaching the people who need it.

What would it take for someone at Starbucks to connect what the app already knows to what the baristas actually need?