How it works
How Gladio works.
Gladio compares your current plan with what sold and proposes the next one. You can check every step against your own records.
Illustration with made-up figures. Four panels for route R-04, one for each step on this page. A data record, a grid of weekdays and hours with the busiest hour marked, a forecast with its range, and a proposal that moves from proposed to approved. The stock that is no longer loaded is in yellow.
- RecordR-04 · leg D–E · 19:22
- AnalysisBusiest hour · Fri 18:00
- ForecastPeak expected · Fri 18:00
- ApprovalProposedApproved 16:24Done
- Before
- Proposal
- Not loaded
What an order records
An order is stored with what was bought, when and where.
Gladio’s software has one view for guests and one for your staff, who also use it to enter trolley and counter sales.
For an order on leg D–E of route R-04, that means the item and quantity, the time and the place.
Load sheets and return lists tell you what went out and what came back, but not when it was sold.
Illustration with made-up figures. One order as a data record. Route R-04, leg D to E, Friday, departure 18:50, time 19:22, 32 minutes after departure. One still water and one sandwich. Name and contact details are not recorded.
- Place
- R-04 · leg D–E
- Departure
- Fri · 18:50
- Time
- 19:22 · 32 min after departure
- Items
- Still water · 1Sandwich · 1
- Name, contact
- not recorded
Here is one order from route R-04 as the software records it.
Where the plan and the sales part ways
Once load sheets and return lists are in, the analysis shows what keeps coming back and what sells out early.
Add the rosters and you also see where shifts stand idle and where the peaks are short-handed.
Illustration with made-up figures. A grid of seven weekdays and nine hours from 06:00 to 22:00. The brighter a cell, the higher the demand at that time. The busiest hour, Friday at 18:00, is outlined.
- Hour →
- least most
- Busiest hour
- Fri 18:00, Busiest hour, Marked on roster
- Sun 06:00, Quiet hour, Prepare less
Friday at 18:00 stands out as the busiest hour, while early Sunday stays quiet.
The forecast
You see the quantities a few weeks ahead, first as a range.
The forecasts are computed from your own order history. A forecast for a Friday evening looks different from one for a Monday morning, and August from November.
As the day gets closer and more sales come in, the range gets tighter.
Illustration with made-up figures. Two curves across the day from 06:00 to 22:00. The dashed line shows the average of recent weeks, the solid line the forecast for Friday with its range. The expected peak in the early evening is marked.
- Average of recent weeks
- Forecast
- Range
- Peak expected
The forecast is built from the Fridays of the past two months.
Who approves
Proposals go to the people who plan this work today.
A proposal gives its reason, for instance that the coffee ran out before D on eight weekday trains in a row.
Approved by
- AirCommercecatering planner
- TrainCommerceonboard services lead
- CruiseCommerceprovisioning officer
- RoomCommercehead chef
- BarCommercerestaurant manager
Your team approves every proposal before anything is loaded or prepared. They can take a proposal as it stands or change it.
Illustration with made-up figures. Six items for route R-04, each with sales, an eight-week trend and a recommendation. Load more still water, keep coffee and sandwiches, load fewer muffins, take out crisps and add fruit. The catering planner approved the proposal at 16:24.
- Still wateroften sold out in the eveningLoad more
- CoffeeKeep
- SandwichKeep
- Muffinsales falling for weeksLoad less
- Crispshardly any salesRemove
- Fruitnewsells on your other routesAdd
- Proposed 16:10
- Approved 16:24 · catering planner
Decision: R-04 · Evening departures · Range proposal · Approved 16:24
The recommendations follow how the items have sold on this route.
Illustration with made-up figures. Five proposals from five industries, each with its status.
- AirCommerce R-09 · Rotation 3 · Trolley 6 stays on the ground Approved 05:25 New
- TrainCommerce Train 06:10 · Section B–C · First round forward Approved 04:45
- CruiseCommerce Voyage 12 · Provisions · Fruit order set to forecast Done
- RoomCommerce Floor 4 · Breakfast · Eggs to order from 09:30 Approved 05:52
- BarCommerce Zone T · Sat 12:15 · Salads ready before the rush Proposed
Data protection
The analysis is about orders and never needs a name.
Orders without accounts
There are no guest accounts, and order data holds no names.
Your data stays yours
We use your figures only for your own analyses and forecasts. We do not sell them, and we only share them with service providers who process them on our behalf, such as for hosting.
Payment stays with you
Card details never reach us, because payment is still taken by your staff or at your till.
Your till keeps working
If our software stops, you carry on selling as you do now.
Sources (16)
- 1Rodrigues, Miguéis, Freitas and Machado, Journal of Cleaner Production, vol. 435, January 2024. A back-test on past data from three canteens. doi.org
- 2McKinsey & Company, article, February 2022. An estimated range for supply chains in general. www.mckinsey.com
- 3CBRE Hotels Research, article, November 2025, based on the operating statements of 2,669 US full-service, resort and convention hotels. www.cbre.com
- 4IATA, fact sheet “Cabin Waste and Single Use Plastic Products”, June 2026, from IATA’s cabin waste audits. www.iata.org
- 5IATA, thought piece on sustainability, December 2023. The trolley weight is for a typical catering trolley. www.iata.org
- 6Ryerson, Hansen, Hao and Seelhorst, “Should Maximum Contingency Fuel be Regulated for U.S. Civil Aviation?”, policy digest, Kleinman Center for Energy Policy, University of Pennsylvania, November 2015. A US simulation with several aircraft types, which puts the extra fuel at about 0.03 kg per kilogram carried per 1,000 km. kleinmanenergy.upenn.edu
- 7CFMS, impact study “Forecasting Catering Requirements for Improved Passenger Experience”, 13 July 2026. A model for a UK rail catering team, mostly in first class; demand here is the share of passengers who buy from a food category. cfms.org.uk
- 8Smith Institute, case study “Using machine learning to predict catering demand”, 12 April 2024. A projection from a back-test on past data from a public transport operator with mobile catering. www.smithinst.co.uk
- 9Tallink Grupp, corporate factsheet, July 2026, key information for 2025. Restaurant and shop sales on board and ashore were 48% and tickets 29% of revenue of EUR 765 million. company.tallink.com
- 10Carnival Corporation & plc, annual report on Form 10-K for the financial year to 30 November 2025. Food cost USD 1,499 million and fuel USD 1,808 million; the food figure covers guests and crew but not drinks or retail goods. www.sec.gov
- 11EPA Ireland, factsheet on food waste at hotel functions, version 3, 2022, from research in Irish hotels between 2016 and 2018. www.epa.ie
- 12Champions 12.3, business case for reducing food waste in hotels, April 2018. Average of 42 hotels in 15 countries, kitchen waste before the plate, by weight. The figure comes from waste programmes, not from software like ours. www.wrap.ngo
- 13National Restaurant Association, survey median, 10 September 2025. US full-service restaurants, 2024 data, food and non-alcoholic beverage costs. restaurant.org
- 14National Restaurant Association, survey median, 8 October 2025. US full-service restaurants, 2024 data, salaries and wages including benefits, from the 2025 Restaurant Operations Data Abstract with more than 900 operators. restaurant.org
- 15National Restaurant Association, survey median, 20 August 2025. US full-service restaurants, 2024 data, income before taxes. restaurant.org
- 16Champions 12.3 (WRI and WRAP), business case for reducing food loss and waste in restaurants, February 2019. 114 restaurant sites in 12 countries (11 in Europe, plus China), mostly large ones, kitchen waste before the plate. These were waste programmes, not software like ours. champions123.org