Find where the margin actually goes

The challenge

Gross margin per dish looks healthy until labour and waste are counted, and by then the menu is printed.

The scenario

An operator suspects two popular dishes are losing money once prep time is included, but the data lives in three systems.

What goes in

Sales data

Item-level sales by site and day.

Cost data

Stock, waste and labour.

What you can ask

Illustrative prompts. Results depend on your own data and are not deterministic.

• “Which menu items lose money once labour is included?”Copy
• “Which site is the outlier this month?”Copy
• “Where is waste concentrated?”Copy

How Clearception approaches it

How the work is structured. Each step shows what its output is grounded in.

1. 1

   Combine the sources

   Source

   Bring sales, stock, waste and labour into one view.

2. 2

   Allocate cost

   AI-inferred

   Attribute labour and waste to items and shifts.

3. 3

   Rank by true margin

   Observed

   Order items by margin after all attributed cost.

What you get

The shape of what comes back — not a promised result.

• True margin by item

  Observed

  Items ranked by margin after labour and waste, with the data behind each.

Why it matters

Menu decisions on real numbers

The dish that loses money is identified before the next print run.

Comparable sites

One method makes cross-site comparison meaningful.