Restaurant kitchen prep
Prep plan
River North kitchen
River North lunch is pacing 22% above plan. Increase prep and notify the shift lead?

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Start running plays.

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Checkout pricing
Burger combo margin is below target. Push a direct-channel price test to 5 stores.
POS price$12.49 → $13.24
Stores5 selected

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Card reader payment at a counter
Orders
POS + checkout
Restaurant kitchen team at work
Inventory
Kitchen + stock
Pepperoni pizza menu item
Products
Menu + merchandise
Cafe operator behind the counter
Delivery
Marketplace demand
Pandal
Small business interior
Loyalty
Customers + offers
Retail operator in her shop
Labor
Teams + schedules
$
Price test
5 stores queued
↗
Prep update
Lunch batch adjusted
%
Promo change
Weak stores paused
∿
Inventory plan
Kitchen list synced
Restaurant menu item
Market context
Weather + events

Actions that drive revenue, margin, and scale.

Pandal continuously monitors the business, identifies what needs attention, and turns opportunities into coordinated operating plans.

Hamburger and fries menu item
Burger combo is underpriced in 5 lunch stores.
+$2,340 / moLaunch price test
Margin check
Burger combo · direct
5 stores
CurrentTest+$2,340 / mo

Pricing optimization

Channel-specific pricing recommendations grounded in elasticity. Pandal projects volume and margin impact before you commit.

Card reader payment at a counter
Almond milk attach is 41% lower in-store than mobile.
+$890 / wkAdd POS prompt
Prompt gap
Almond milk · counter
last 7 days
Mobile31%
Counter14%
Add prompt →+$890 / wk

Modifier & attach optimization

Pandal tracks attach rates at the modifier x channel x location level and surfaces the gaps with the recommended fix and the expected weekly lift.

Folded merchandise t-shirts
Hoodie launch is profitable in 12 stores and weak in 3.
+$6,200 / wkPause underperformers
Net lift
Hoodie launch · week 2
42 stores
Actual vs baseline+$6,200 / wk

Promotional effectiveness

Counterfactual measurement on every promotion. Incremental lift, cannibalization, and net profit by channel and location, before the post-mortem.

Restaurant open kitchen
Tuesday lunch demand is pacing 22% above prep.
+187 expectedUpdate prep plan
Prep forecast
Tuesday lunch · tomorrow
Lincoln Park
Mon
Tue
Wed
Thu
Fri
7–11a
11–2p
2–5p
5–9p
Prep gap+187 expected

Demand intelligence

Modifier-level demand forecasts so labor and inventory are sized to what’s actually coming through the door.

Built for operators.

Most tools stop at reporting. Teams pipe data into warehouses, clean it, model it, build dashboards, and still depend on someone to ask the right question. Pandal brings commerce, labor, inventory, marketing, finance, customer, and external context together to move the business from data to decision to execution.

Pandal

Heads up, Lincoln Park weekday lunch delivery is tracking 17.2% below baseline this week (203 → 168 orders). I found three drivers and a recoverable execution gap:

  1. 1The almond milk modifier stopped capturing on the delivery channel for ~6 hours starting 11:43am, affecting ~23 orders and suppressing attach revenue.
  2. 2Local competitive data shows a nearby store launched a delivery promo Tuesday morning.
  3. 3Weather: 38°F and steady rain historically reduce weekday delivery volume by ~8%.

About 9 points of the decline are recoverable. Recommended plan: push the modifier config fix now, notify the shift lead, and add it to tomorrow’s briefing.

Push fix nowSend to opsAdd to briefing
Push the fix. Also show the revenue lost to similar execution gaps across all stores over the last 30 days.
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