Service

What is Service?

In hospitality, margin is decided by a small number of daily decisions — how much to prep, what to order, who to roster — and the data needed to make them well is usually a week old. Service brings sales, stock, waste and labour into one view per site and across sites, so the pattern behind a bad week is visible while the next week can still be changed. It is an operations tool, not a dashboard: the output is what to order and how many to roster.

Problems it solves

• See profitability by site, day and menu item
• Order stock against expected demand rather than last week's guess
• Plan labour against forecast covers
• Find where waste is concentrated
• Compare sites without rebuilding the report each time
• Spot a margin problem while the week is still changeable

Key capabilities

Inventory Optimisation

Match stock and prep to expected demand, and show the cost of being wrong in each direction.

Forecasting

Project a pipeline, a harvest or a load curve, with the drivers behind the number visible.

Cross-Source Intelligence

Reason across several approved systems at once, so an answer is not limited to whichever database someone happened to open.

Evidence Trail

Every figure carries the record it came from, so a reader can check the answer instead of trusting it.

How it is built

Per-site and cross-site

The same analysis for one venue or a group, without a separate reporting build.

Demand-led ordering

Order quantities derived from forecast covers rather than a standing order.

Waste attribution

Where waste happens, by item and by shift.

How it works

How the work is structured, and what each step's output rests on.

1. 1

   Connect operations data

   Source

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

2. 2

   Establish the baseline

   Observed

   Work out normal, per site and per day.

3. 3

   Forecast demand

   Estimate

   Project covers and item mix for the coming period.

4. 4

   Recommend orders and rosters

   Recommendation

   Translate the forecast into quantities and shifts.

Example use cases

Each example has its own page you can read and share.

Ask Service

Illustrative examples. Results depend on your own data.

• “Which menu items are losing money once labour is included?”
• “How much should I order for next weekend?”
• “Where is waste concentrated across my sites?”
• “Which site is the outlier this month, and on what?”

Questions

Does it work for a single venue?

Yes. Cross-site comparison is available when there is more than one, and is not required.