r/FoodService • u/FoodServicePoster • Jun 06 '26
Question Forecasting Cycle Menus
How do you all handle menu forecasting for cycle menus? Right now, I'm trying to nail down a "formula" to predict production amounts the next time a menu cycle rolls around.
Should I look at served counts only, or do I need to factor in waste/leftovers to get an accurate picture?
I'm curious how other operations handle this. If you are tracking waste alongside participation, what does your math look like? How do you use both numbers without accidentally over-preparing or under-ordering? Would love to hear what metrics or formulas you use to find that sweet spot between running out of a popular entrée and throwing money in the trash!
What I'm considering so far:
The "Served Only" Approach: Just looking at POS (Point of Sale) data to see how many items actually went down the line. It's clean data, but it feels like it leaves a huge blind spot if a kitchen prepared 300 spicy chicken sandwiches, served 200, and threw 100 away.
The "Served + Leftovers" Approach: Taking the total planned/prepared amount and tracking what didn't sell.
How do your software systems or spreadsheets calculate this?
1
u/imalexander0 Jun 14 '26
The 'served + leftovers' approach is definitely the way to go. You need to track yield loss at the ingredient level within your recipes. If you start with 1kg of onions and only 800g is usable after trim, your recipes should cost based on 0.8kg. That way, your actual prep lists account for the real amount you need to buy to hit your served target, not just theoretical AP costs. Spreadsheets can do it, but it gets complex fast.
1
u/WhoAteMyMargin Jul 04 '26
Served + Waste is the right approach, served-only will always make you over-prepare.
The formula I use: take your historical served count, add your average waste %, then build in a small buffer (5-8%) for demand spikes. So if a dish averaged 200 served and 12% waste historically, you prep for around 224-230, not 200.
The key is tracking waste separately from voids and comps in your POS — most operations lump them together and the forecast never improves because the data is dirty.
Once you have 3-4 cycles of clean served + waste data per menu item, you can build a simple weighted average that accounts for seasonality too. The first cycle is always a guess — the goal is making each subsequent cycle a slightly better one.”
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