In honor of Valentine’s Day, I have two numbers for you:

$93.07

It’s an average you may have seen somewhere (online, perhaps in the news) in the past few weeks.

The second number is:

990 million stems

Before I tell you what they represent:

What do you think these are?

Are they connected?

Are they large?

Are they reasonable?

Well, $93.07 is the national average price of a dozen long-stem roses in the United States this year.

Image created by FinanceBuzz.

And 990 million is approximately the number of fresh-cut flowers moving through Miami International Airport in the weeks leading up to Valentine’s Day.

Is This Modeling?

Now… is this modeling? Or is it just an interesting number*? 

If we stop at “Wow, roses are expensive,” we likely haven’t modeled anything.

If we start asking what’s driving that $93.07, look online and find a different price, or start to wonder if it’s possible that Americans spend nearly $8 billion on flowers for one day of the year, we’re getting closer.

Nearly 90% of Valentine’s flowers entering the U.S. pass through Miami. Most come from Colombia and Ecuador. They’re grown months in advance, cut at the right moment, cooled, transported by air, inspected, sorted, distributed, and delivered on a very tight schedule.

That entire system has to work.

If production drops 5% because of the weather, what happens? If transportation costs rise, how quickly does that show up in retail prices? If tariffs change, who absorbs the cost: growers, distributors, or consumers?

At what point does demand push the price up? At what point does price push demand down?

Those are modeling questions. But even here, we should pause. Is this modeling? Or are we just asking good questions? And maybe that distinction is worth sitting with for a moment.

When Someone Says “That’s Not Modeling”

Sometimes when I present something like this, I receive responses such as those mentioned above, and I ask if we were just modeling. Someone will say, “No, that’s not modeling.”

And they’re not wrong.

We haven’t built a model.

We haven’t tested assumptions.

We haven’t quantified relationships.

We’ve just started to notice the structure of a system. And maybe that’s the point.

Modeling begins with recognizing that there is a system, or potentially multiple systems, to investigate.

Nearly a billion flowers moving through one airport in five weeks, and a $93.07 price tag is not arbitrary. There are variables. Constraints. Trade-offs. Risks.

Where Would You Start?

If you wanted to build a model, where would you start?

Would you begin with the total number of flowers?

With cost per stem?

With transportation capacity?

With consumer demand elasticity?

Would you try to predict next year’s Valentine’s Day price?

Or test how sensitive the system is to disruption?

And maybe an even more uncomfortable question: Is $93.07 too high? Or does it make sense once we understand what’s driving it?

The Ordinary Is Not Simple

What I like about this example is that it feels familiar.

Nearly $100 for a dozen roses may not feel relatable to everyone, but we all recognize flowers, especially when they’re tied to Valentine’s Day.

But it’s also international trade, supply chain logistics, optimization, behavioral economics, and risk management, all sitting underneath something we experience as a simple (but seemingly expensive) bouquet.

The mathematical modeling mindset isn’t about solving the problem immediately. It’s about shifting from “That’s expensive” to realizing we have the opportunity to ask, “What’s going on here?”

It’s about recognizing that behind almost any everyday number, there’s a structure waiting to be explored.

And sometimes the first step toward modeling is simply asking:

Is this modeling? Or are we still just warming up?

And we haven’t even started to talk about the chocolates.

*Check out how numbers in the news can be used in your class.