AI Insights: a daily Claude-generated wage cost briefing covering
month-to-date pace vs budget, prior-month/prior-year comparison,
rota-vs-actual variance by department, a rota-informed forecast to
month-end, employee-level anomalies, and wage cost as a % of revenue.
Runs on a configurable daily schedule or on demand, gated by a manual
5-minute rate limit and a daily token budget. Uses the Anthropic key
configured centrally in Portal → Settings → Integrations.
Also includes the rota-vs-repeat-pattern forecast method (published/
draft rota tiers with same-weekday fallback) already built into the
Weekly/Monthly views, and adds a .gitignore for node_modules/dist.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Same fix as maintenance/reports/room-planner: manifest scope was the
app's own base path instead of "/", and AuthGate unconditionally
hard-navigated window.top to the central /login on session expiry
even when not embedded in the portal iframe — together these dropped
an installed/standalone wages PWA into the portal's framed browser
view instead of staying in its own window.
AuthGate now only bounces to central login when actually embedded
(passing ?from= so it returns here afterwards); standalone or
directly-opened tabs get an in-app login form and never navigate
away. Also wired up the previously-dead inactivity auto-logout timer.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Sidebar was missing the account info + sign-out control that every
other app's sidebar has; it showed a static hotel-name label instead.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Legend was sorted to mirror bar stack order, making it hard to tell
segments apart at a glance; reverse it. Tooltip also rendered behind
the legend div when they overlapped — raise its z-index above it.
syncActuals() recomputes the full date range from Workforce on every run
but only ever upserted rows, so a shift that moved department or was
edited/deleted since the last sync left its old wage_actuals_detail row
in place — showing a "ghost" employee in the dept breakdown whose cost
no longer matched the (correctly overwritten) department total.
Now deletes existing wage_actuals/wage_actuals_detail rows for the
synced date range before reinserting, so removed/reassigned shifts
don't linger.
Rolling12Months: current month's budget wasn't prorated at all, so
%Budget compared MTD actual against the FULL monthly budget — always
looked artificially favorable. Now prorates by elapsed PY DOW-matched
sales share (flat day-count fallback), reusing already-fetched data.
Rolling12Weeks: budget was prorated, but the elapsed-day count mixed a
real timestamp with Math.ceil(...)+1, always overstating elapsed days
by one and inflating the budget denominator. Rewrote to sum per-day
budgets by date string (no fractional-time bug), and applied the same
PY DOW-weighting as the Weekly page, sourcing each day from its own
calendar month so weeks spanning a month boundary split correctly.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Distributes the monthly wage budget across days proportionally to each
day's share of last year's same-day-of-week sales, so pacing on Weekly/
Monthly views reflects real demand shape (e.g. weekend-heavy) rather than
an even calendar split. Falls back to the old flat day-count split when
PY sales data is unavailable. Weekly also now sources each day's budget
from its own calendar month, so weeks spanning a month boundary split
correctly across both months' budgets.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
The forecasting API's total.otb is booked-to-date only; total.forecast adds
expected pickup and equals otb for past dates anyway. Using otb-only for
future days understated expected net sales in the current-week/month
forecast sections. Relabelled "(OTB)" cards to "(Forecast)" to match.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Both views already showed % Net Sales with a PY % sub-line, but lacked a
raw-£ Net Sales card with PY value + delta% — the style already used for
past weeks/months. Adds it consistently across current-period, forecast,
and past-period sections in both views.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Fixes an edge case where days more than 7 days past the actual cutoff had no
valid prior-week source day (itself a forecast day), silently contributing
£0. Now walks back in 7-day steps until landing on an actual day, so the
last complete actual week tiles forward for the rest of the month.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The shifts endpoint omits employer NI from cost_with_oncosts for some employees.
The timesheets/on/{date}?include_oncosts=true endpoint includes NI, matching
WF's native 'Cost by Location and Team' Timesheet exc. leave figure exactly.
June 2026 verification: B.shiftLevel.oncostTotal = £51,005.72 = WF target.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Fetches all active users with salary field set whose report_department_id
is in a No 4 department. Reports raw salary field shape, prorated period
cost, and combined (shifts oncostExLeave + prorated salary) to test whether
salaried staff account for the gap vs WF native report.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Without this parameter, nested shifts[] only return shift.cost with no
cost_with_oncosts field. The FD's PBI uses show_costs=true on timesheets
and may also require include_oncosts=true to get employer oncost fields.
This is the missing parameter that may explain the B.oncostTotal == baseCost issue.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The timesheets/on/{date} response has total_cost at the timesheet level,
not cost or cost_with_oncosts. Previous code was reading undefined and
summing zeros.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
B now also sums cost/cost_with_oncosts at the timesheet parent object level (not just
nested shifts[]) — reveals whether PBI is using a timesheet-level field we're missing.
compareEndpoints now returns:
- A (existing): shifts API + report_location_id + client dept filter by location_id
- A2 (new): same shifts, client filter broadened to location_id OR report_location_id
- A3 (new): same shifts, no client-side dept filter (trust API filter only)
- extra_depts_via_report_location_id: departments in A2 but not A
- B: per-day timesheets with both shiftLevel and timesheetLevel cost sums
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The timesheets/on/{date} endpoint nested shifts don't return cost_with_oncosts
— oncostTotal == baseCost in all results. The shifts endpoint does return it.
Hypothesis: shifts endpoint, leave filtered, cost_with_oncosts ≈ £51k:
- A (shifts, report_location_id, all): £47,607 (shift.cost, includes leave)
- B (timesheets, dept filter, ex-leave): £40,845 (shift.cost only, no oncosts)
- Estimated A_ex_leave × cost_with_oncosts: ~£44.7k × 1.14 ≈ £51,005 ✓
syncActuals reverted to shifts endpoint, adds leave_request_id filter,
uses cost_with_oncosts as total_cost (was using shift.cost before).
compareEndpoints A now shows both baseCostExLeave and oncostExLeave so
we can confirm the £51k match directly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Key findings from diagnostic runs:
- timesheets/on/{date} returns only that DATE's shifts (not the whole
week), so weekly-step fetch only samples 6 days of a 30-day month
- user.report_department_id filter too strict: only 32 staff have it
set, missing many valid No 4 employees → £15k instead of £51k
- Correct approach: per-day fetch (all 30 days), dedup by shift.id
(robust against any duplicate timesheet records), filter by
shift.department_id → location_id (matches WF "by Location and Team")
Also includes inactive users (show_inactive=true) to catch staff who
left mid-month but still have timesheets in the date range.
Compare endpoint now shows baseCost (shift.cost) and oncostTotal
(shift.cost_with_oncosts) so we can confirm which matches WF's £51k.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1. Weekly fetch step (not per-day): timesheets/on/{date} returns the
whole weekly period for any date in that week, so fetching 30 days
counted each weekly timesheet ~7x. Now fetches one date per 7-day
step from 'to' backwards (PBI pattern), deduplicates by timesheet.id,
and filters shifts by sh.date to the requested window.
2. Filter by user.report_department_id not shift.department_id: shared
departments (HR, Management, etc.) have a single location assignment
(No 4) but staff from all hotels clock into them. Filtering by the
employee's HOME department (report_department_id) correctly isolates
No 4 staff. Mirrors the PBI model join: timesheet → user →
report_department_id → department.location_id → hotel.
Both fixes applied to syncActuals and compareEndpoints diagnostic.
Target: B.cost = WF "Timesheet exc. leave inc. allowances" (~£51k June).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Uses /api/v2/timesheets/on/{date} per day (no location param), expands
nested shifts[], skips leave (leave_request_id!=null), and post-filters
to this hotel's departments via location_id match on the departments
list. This mirrors exactly what the FD's Power BI query does and should
give the correct £51k timesheet figure for June.
Also simplifies compareEndpoints to two variants: A (old shifts method)
vs B (new timesheets method) so the discrepancy is immediately visible.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Timesheet per-day fetch returns 3,269 records with £0 — cost fields are
named differently. Adds tsBaseCost()/tsTotalCost() helpers that try multiple
field names (cost, timesheet_cost, base_cost, employee_cost, etc.). Adds
sampleFields to E result so we can see the actual field names on a live
record. Also samples a shift record (variant A) for confirmation.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Sequential day-by-day caused 504 on month-long ranges. Switching to
Promise.all over all dates so 30 concurrent calls complete in ~3-5s.
Route timeout bumped to 120s to give the parallel calls room to land.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds four endpoint variants (A-D) to isolate the location filter discrepancy:
report_location_id vs location_id vs no filter vs timesheets range. If the
timesheets range 404s, auto-falls back to per-day /timesheets/on/{date} fetch
(variant E) so we can see timesheet totals regardless of API version.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Monthly: fetches previous month actuals; adds % delta vs prior month full
alongside existing vs PY column in the dept breakdown table.
Weekly: expanded 14-day actuals fetch (prev+current week) so prior-week
per-dept data is available for both forecast and comparison. Two-row summary
cards for current week (WTD actuals + full-week forecast). Past weeks keep
single-row layout. Dept table gains vs PY and vs Prev Wk delta columns;
budget columns use WTD pro-rata for current week, 7-day proportion for past.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Shows (actual_mtd - PY_MTD) / PY_MTD for current month rows,
(actual - PY_full) / PY_full for past months. Red if wages up vs PY,
green if down. Total row uses same basis. Matches department by ID
against pyDepts so departments with no PY data show —.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Both Weekly and Monthly now cut off actuals at yesterday (not today) to avoid
partial clockins and open timesheets skewing the WTD/MTD figures and % net sales.
PY comparison periods also cap at the equivalent yesterday for fair comparison.
Monthly rota forecast removed — all future days use prior-week same-day actuals
from yesterday back, which is more reliable than partially-published future rotas.
Monthly summary cards split into two rows for current month:
Row 1 (MTD to yesterday): Actual MTD · Budget pro-rata · % Budget MTD · % Net Sales MTD
Row 2 (Full month): Forecast EOM · Monthly Budget · % Budget (Forecast) · % Net Sales (OTB)
Net sales fetched for full month so row 2 % net sales uses OTB forecast revenue.
Past months show one row (full month actuals only).
Weekly: budget pro-rata now counts days Monday to yesterday for current week;
dept totals filtered to yesterday for current week.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Rota forecasting: only trust Workforce rota for the current Mon–Sun week —
beyond that use prior-week actuals to avoid incomplete next-week rotas
deflating the EOM forecast.
% vs Budget cards (Weekly + Monthly): show as coloured headline number
(green/amber/red) instead of small pct-badge chip, matching other cards.
Forecast EOM: PY sub-label shows full prior-year month total + % delta,
replacing the static "rota + prior-week actual" note once PY data exists.
Achieves this by fetching the full PY month rather than MTD-capped range,
then deriving both MTD (for Actual MTD card) and full-month (for EOM card).
Backfill depth: 13 → 25 months so past months in Rolling 12 have PY wage
data available (viewing Dec 2024 needs Dec 2023 = 19 months ago).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Hide sidebar on mobile (≤640px), show fixed bottom nav bar instead
- Cards get overflow-x: auto so wide tables scroll horizontally
- Summary grid forces 2-column on mobile
- Reduce content padding to 12px, clear 68px for bottom nav
- Summary card values shrink to 18px on mobile
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Stores per-employee shift costs in wage_actuals_detail (APPROVED shifts
only). Sync fetches employee name map from /api/v2/users alongside dept
names. Clicking any dept row in Weekly or Monthly opens a modal showing
Employee · Shifts · Cost · % of Dept, fetched on demand.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Stores full PY department breakdown from already-fetched pyActRes.
A toggle button (collapsed by default) expands an inline table showing
PY wages per dept, % of PY total, and % of PY net sales. Label adapts
to PY WTD / PY MTD for current partial periods.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Shows prior year equivalent % (wages/net sales) as a sub-label under the
current period value — labelled PY WTD/MTD for current partial periods,
PY for complete past periods.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Weekly: cap pyToStr at elapsed days (not full Mon-Sun), and filter
py_sales to past days only — both give WTD vs WTD. Labels show
'PY WTD' for current week, 'PY' for complete past weeks.
Monthly: pyToStr already capped at same day-of-month; salesTo already
capped at today. Labels now show 'PY MTD' for current month, 'PY' for
complete past months.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Show PY value + % change as a subtitle line under the period card,
same pattern as the original PY sales sub-label.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Weekly/Monthly: PY Wages summary card (fetches equivalent week/month last year)
- Weekly/Monthly: PY Net Sales as its own card (was a sub-label, now prominent)
- Weekly/Monthly: dept table gains '% of Total' column
- Monthly: PY comparison caps at same day-of-month for fair PYTD comparison
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Schedules endpoint has same 7-day limit as shifts. The 14-day forward
window was being fetched in one call — split into two 7-day batches.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
toISOString() returns UTC — in BST (UTC+1) dates computed from new Date()
land one day early. Replace with local date components via fmt()/localStr().
Affects Weekly, Monthly, Rolling12Weeks, Rolling12Months.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
