Reports: where to find revenue, shifts, kitchen and stock figures

Start with the question you want to answer. In cenaly.ge, money, kitchen activity and menu visits live in different sections. The same word, “orders”, does not always mean the same set of records.

What you need to get started#

Sign in as the owner or an employee with access to the relevant sections and locations. The role must allow Finance, Statistics and any other sections you use, with read access or higher. Access comes from the role assigned to the employee, not from a label on their profile: roles are set up in Staff → Roles & access, see Roles, permissions and till restrictions.

Check the selected location. Finance supports one location or all accessible locations; Statistics shows the selected location. An employee with a restricted location scope cannot see the whole network.

Kitchen reports need tickets moving through preparation statuses; inventory reports need recorded receipts, write-offs and products. Traffic needs a connected Google Analytics property and a working collection job. Enable Dashboard separately through its card in Extensions.

Revenue for a day, week or month#

For the formula behind each figure, see Report metrics.

1. Open Finance → Overview and select a location.
2. Choose Today, Yesterday, 7 days, 30 days, 90 days or 12 months.
3. Read revenue, order count, average check and the comparison label. Then open Sales: payment methods and channels explain the sales mix.
4. For the network, select all locations. Location comparison appears when at least two locations have data. It also provides Download CSV.

The result is a total for the selected window and an explanation of which location or channel drove the change. Review delivery availability separately under Delivery channels, and order attribution under Order sources.

Reading the comparison: 7, 30 and 90 days are compared with the immediately preceding window of the same length. Today and Yesterday are compared vs the same day last week. The 12-month preset does not compare against the previous year.

Common mistake: treating the last 30 days as a calendar month, or revenue as profit. Revenue minus purchases and Purchases / revenue use purchases in the period, not the cost of dishes sold. Open Expenses & P&L to review expenses.

If a total looks wrong, check the window, currency and location scope. Do not manually add different currencies together. See Finance and Analytics for calculation details.

What happened during a cashier’s shift#

1. Open the X-report in POS to inspect the current shift without closing it.
2. When work is finished, use Close shift (Z) and enter the cash you actually counted.
3. To review a closed shift, open Finance → Cash shifts, select the location and a period containing the shift.
4. Compare the cashier, cash and card sales, expected cash, counted cash and discrepancy.

The result is a cash reconciliation and a specific shift to investigate. See Cash shift for the workflow and printing.

Common mistake: comparing all sales with cash in the drawer. Card payments do not add banknotes; cash deposits, withdrawals and the opening float affect the drawer balance.

If a shift is missing, check that it was closed, then check the location and period. Do not close an active shift just to inspect it: use the X-report.

Who cancelled orders, issued refunds or gave discounts#

1. Open Statistics → Risky operations.
2. Select the location and period, such as 7 days for a weekly review.
3. Check the breakdowns by cashier and operation type, then inspect an event’s time, amount, details and approval.

The result is a list of actions to review with the employee. The feed helps identify unusual runs of refunds or discounts. See Statistics and Loss control.

Common mistake: treating the amount at risk as a proven loss or proof of misconduct. A refund may be justified and a discount approved.

If an event is missing, check the period and allow data to refresh. Permission to read a report does not automatically grant permission for every related action.

Where the kitchen is slowing down#

1. Open Statistics → Kitchen and select the location and period.
2. Compare average cooking time, the late percentage and the late threshold; find problem hours on the heatmap.
3. Check Slowest dishes to cook and Wasted prep — cancelled items whose preparation had already started.
4. Under Promised vs actual, check the share of orders ready by the promised time and the average delay of late orders.

The result is a list of dishes and hours to investigate. Promised vs actual treats an order as ready when its last dish is ready; only orders with a promised time are included.

Common mistake: interpreting the late percentage as a breach of an individual dish’s standard cooking time. The full ticket cycle is compared with one common late threshold. The guest promise is a separate measure.

If the report is empty, check that staff actually update preparation statuses. See Statistics for the report and KDS for recording stages.

What is left in stock and what to order#

1. Open Inventory → Stock for the location. Low stock highlights products to consider for replenishment.
2. In Procurement, check requirements and supplier orders. In Forecast, choose a planning horizon and review demand based on sales history.
3. Before ordering, check Shelf life (if the shelf-life option is connected), Losses and Network stock: products may expire soon, differ from recorded stock or be available at another location.
4. To explain a stock change, open the movement log under History and select the month. Review losses for the cycle between posted stocktakes.

The result is a checked replenishment list that accounts for current stock. Detailed instructions are in Inventory.

Common mistake: treating the forecast as a guaranteed order or the movement log as a historical stock balance. Forecasts depend on sales history; current balances depend on complete transaction records.

If figures differ, check receipts, write-offs, units and stocktakes. Do not change stock just to make a report look right.

Which dishes perform well and which need reviewing#

1. Open Dish Statistics and choose a period, such as 30 days.
2. Compare quantities, revenue, ABC and margin; review the change from the previous period.
3. Use menu engineering to consider popularity alongside margin.

The result is a shortlist for price, recipe or menu placement changes. See Analytics and Menu engineering.

Common mistake: removing a dish just because it is in group C. Low revenue in a short window does not necessarily mean poor margin or no seasonal demand.

If margin is missing, check the recipe and purchase prices. Missing cost is not zero cost.

How many people visited and where they came from#

1. Open Statistics → Traffic and select a location.
2. Compare sessions and visit duration over the fixed 7- and 28-day windows. The page’s general period selector does not change these windows.
3. Review traffic sources, channels, devices, cities and the 28-day conversion funnel.

The result shows where guests come from and where they stop ordering. These are website and menu visits, not people seated in the dining room.

Common mistake: expecting Refresh to immediately show a visit that just happened. Google Analytics data arrives through background collection; check the update time.

This tab requires a Google Analytics property connected to the platform: collection is filtered by the location’s domain. Entering your own tracking code in location settings does not by itself connect an arbitrary GA property to this report. Allow the first collection to run (usually within 24 hours of connection); contact support if the report still does not appear. Traffic collection is not connected on cenaly.ru yet: this does not mean zero traffic. See Statistics.

Six months of trends by location and your own chart#

1. If the section is missing, enable Dashboard in Extensions and check access to it.
2. In the chart editor, select a data source and metric. Set a window of the last six months or exact From/To dates.
3. Choose the Location dimension, a suitable Bucket, such as month, and Compare with previous period.
4. Save the chart and check that its source, filters and period match your question.

The result is a reusable chart for monitoring trends. See Dashboard for configuration details.

Common mistake: changing Bucket to change the whole period. A bucket is one interval on the chart; the window is the complete date range.

If the window is too large for the bucket size, choose a coarser bucket: a chart is limited to 400 time intervals. Comparison uses the previous period, not an independently selected second date range.

Limitations#

• Finance has no arbitrary date range or arbitrary comparison period. The 30-day preset is a rolling window; exact dates for a custom chart belong in Dashboard.
• There is no separate revenue-by-employee report here. Tips by waiter in Sales and the cashier’s name on a shift do not replace one.
• There is no historical restaurant occupancy report by hour and day. Current floor status and the daily per-table heatmap are different tools.
• Inventory reports do not provide balances on an arbitrary past date or a turnover statement with opening and closing balances. The movement log does not replace them.
• Kitchen late percentage uses a common threshold, not each dish’s standard. Promised vs actual needs a recorded promised time.
• Google Analytics traffic is not available on cenaly.ru yet. Kitchen, risky operations and cash shifts are supported in both clouds.

Exports depend on the report:

The account archive is a separate tool: Data export. It is not an export of the current report screen.

Troubleshooting#

Frequently asked questions#

Is revenue the money I can take out of the business?#

No. Revenue does not account for every expense and liability. Start with Overview, then review expenses and profit in Finance.

Can I compare this Tuesday with last Tuesday?#

Today and Yesterday do that automatically. Finance does not let you select any pair of dates.

Does one guest equal one session?#

No. Sessions represent website visits. One person may return several times, and a seated guest may never open the menu on their phone.

Related sections#

• Report metrics — formulas and a worked example.
• Analytics — sales and menu metrics.
• Statistics — traffic, kitchen and risky operations.
• Finance — money metrics.
• Cash shift — X/Z reports and cash reconciliation.
• Inventory — stock, purchases and movements.
• KDS — preparation stages.
• Dashboard — custom charts.
• Roles, permissions and till restrictions — section and location access.
• Timesheets — hours, plan vs actual and labor cost.
• Discounts, promo codes and points at the till — where discounts in Risky operations come from.
• Stocktaking — where stock Losses come from.
• Supplier orders — acting on the demand shown in Purchases.