Every kitchen has a prep list. Most of them are wrong.

Not catastrophically wrong — wrong enough to cost you $200-400 a week in wasted product. That's $10,000-20,000 a year walking straight into your bin, and most operators don't even notice because it happens slowly, one over-prepped mise en place at a time.

The "same as last week" trap

Here's how most prep lists get built: someone opens a notebook, looks at what they prepped last week, adjusts a couple of things based on gut feel, and writes it on the board. Maybe they add a bit more because "it's going to be busy" or pull back because "Tuesdays are always slow."

The problem is that last Tuesday and this Tuesday are not the same day. Last Tuesday there was no event at the town hall. This Tuesday there's a sold-out concert that lets out at 9pm. Last Tuesday it rained. This Tuesday it's 24 degrees and your patio is going to be full.

A prep list that doesn't account for tonight's specific conditions is just an expensive guess.

What over-prep actually costs

Let's say your kitchen preps 6 proteins for dinner service. On a normal night, you use about 80% of what you prep. That 20% buffer feels safe — better to have it than run out, right?

But that 20% buffer across 6 proteins at $15-25 per kg adds up fast:

Monday: 2kg unused duck breast → $45 waste
Tuesday: 1.5kg unused salmon → $30 waste
Wednesday: 3 portions of lamb rack → $38 waste
Thursday: Over-prepped risotto base → $15 waste
Friday: Extra dessert components → $20 waste

That's $148 in one week from just five small over-preps. None of them feel significant in the moment. All of them compound over a year to $7,700.

And that's just proteins. Add sauces, garnishes, bread production, and prep ingredients, and the real number is usually double.

The fix: demand-driven prep

A good prep list starts with one question: how many covers are we doing tonight, and what are they likely to order?

If you know you're doing 85 covers and your sales data shows that 35% of Saturday dinner guests order the ribeye, you prep 30 ribeyes. Not 40 "just in case." Not 25 because you're feeling conservative. Thirty, because that's what the data says.

This requires two things:

1. A covers forecast you trust

You need to know — not guess — how many people are walking through your door tonight. Historical averages for this day and shift, adjusted for weather and local events. We covered this in detail in our [covers forecasting guide](/blog/how-to-predict-tonights-covers).

2. Sales mix data

You need to know what percentage of your guests order each dish. This comes from your POS data. If you've been logging dish-level sales (not just total revenue), you can calculate your sales mix for each shift:

Ribeye: 35% of dinner covers
Salmon: 22% of dinner covers
Chicken: 18% of dinner covers
Vegetarian: 15% of dinner covers
Specials: 10% of dinner covers

With 85 predicted covers and these percentages, your prep list writes itself.

The buffer question

"But what if we run out?"

This is the fear that drives over-prep. And it's valid — 86ing a main at 8:30 on a Saturday is painful. But the answer isn't to prep 30% more of everything. The answer is to be strategic about your buffer:

High-margin, easy-to-store items: prep a 15% buffer. If you don't use it, it keeps until tomorrow.

Expensive proteins with short shelf life: prep to forecast. If you hit 100% sell-through, that's a win, not a failure. Your server can guide the last few tables toward dishes you have depth on.

Sauces and bases: prep to forecast plus one batch. Sauces hold well and can be repurposed.

Garnishes and delicate items: prep to forecast exactly. These don't hold and they're often the things that get wasted most invisibly.

How Mise handles this

When you generate a service brief in Mise, the AI looks at your sales history for this specific day and shift, predicts covers based on historical patterns plus live weather and events data, then calculates expected portions for each dish on your menu.

The output isn't "prep more salmon." It's "predicted 30 portions of salmon based on 85 covers and a 22% historical order rate for Saturday dinner, adjusted up from 28 because weather is ideal for your patio and salmon is your top patio seller."

That level of specificity is what turns a prep list from a habit into a strategy.

Start today

Even without software, you can improve your prep list tonight:

Check your predicted covers (use your average for this day/shift)
Look at your POS data for your top 5 sellers — what percentage of covers order each one?
Multiply predicted covers by each percentage
Prep to those numbers, not to "what feels right"
After service, compare what you prepped to what you sold

Do this for a week and you'll see exactly where your money has been going.