How First Bowl and Shiok Burger turned paper delivery orders and disconnected systems into decision-ready finance data—with ccMonet as the detailed financial layer.
In a compact restaurant model, margin depends on dozens of small decisions: the cost of every ingredient, labour hours by outlet, purchasing variances, menu pricing and the speed at which managers can react.
“The hardest part was that our digital foundation was very thin. Deeper analysis was almost impossible.”— First Bowl leadership team
SKUs can sit inside a single supplier delivery order.
sales channels once lived in separate ordering systems.
invoice total was all the old finance system retained.
The issue was not a lack of software. It was that the information needed to run the business arrived late, lost detail, and remained separated across systems.
May purchasing could remain unclear until late June. By the time a traditional P&L was ready around the 20th of the following month, managers were explaining history rather than changing outcomes.
A paper delivery order might contain 20 SKUs, each with its own specification, quantity and price. The old scan captured only one total—leaving the business unable to analyse ingredient-level COGS.
POS transactions, supplier purchases, payroll, staff scheduling and customer feedback lived in different tools. No single platform had enough context to answer an operating question end to end.
When labour efficiency dropped or a promotion lifted sales, the team struggled to isolate why. Without detailed source data, forecasting became assumption-heavy and corrective action came late.
ccMonet digitises the source documents at their useful level of detail, organises the financial records, and makes the history accessible for analysis alongside operating data.
Delivery orders, invoices and expenses
SKU, quantity, specification and price
P&L, payroll and cost records
Sales and scheduling data
Outlet-level management response
“The biggest daily change is speed. We can react faster.”— First Bowl leadership team
From waiting until around the 20th for the prior month’s P&L to building an early view on Day 1–2.
From one invoice total to the detailed purchasing records needed for deeper COGS analysis.
Compare outlet-level labour hours and sales per labour hour, then challenge a scheduling issue while the month is still fresh.
Investigate ingredient price or quantity movements instead of accepting a single supplier total.
Separate the effect of a new set meal from delivery-channel growth and judge the action more accurately.
Combine detailed historical finance records with current sales and scheduling signals for an earlier P&L estimate.
The group did not expect a single vendor to own POS, workforce planning, customer feedback and finance. Instead, each specialised tool does its job, while a shared data layer lets the business analyse them together.
Cross-source context for faster operating decisions
Turn operational documents into finance data your team can trace, analyse and use.