AR by Location
Aging Mix
13-Week AR Trend
Total AR by aging bucket • line = past-due %
Location Summary
| Location | Total AR | Current | 1-30 | 31-60 | 61-90 | 90+ | Past Due | PD % | 60+ % | Invoices | Customers |
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Aging by Location
Top 10 Customers
60+ Day Exposure — Top Customers
| Customer | Location | Salesperson | Total AR | 61-90 | 90+ | 60+ Total | 60+ % |
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Collections Priority Queue
Ranked by urgency score — use as weekly call agenda
| Score ⓘ | Tier | Action | Customer | Plant | Salesperson | Total AR | Past Due | 60+ | 90+ | Avg DTP ⓘ | Risk Factors | Note |
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Aging Change — Last 6 Months
Top 30 customers ranked by Total AR · All others grouped
Rank by:
Detail Table
| Customer | Site | Salesperson | Total AR | Now ↓ | ← Monthly Change | ||||
|---|---|---|---|---|---|---|---|---|---|
| Customer | Plant | Salesperson | Inv. | Total AR | Current | 1-30 | 31-60 | 61-90 | 90+ | Past Due | Avg DTP | Note |
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⚠ Some invoices have no salesperson assigned. These appear as "Unassigned".
AR by Salesperson
| Salesperson | Plant | Customers | Total AR | Current | 1-30 | 31-60 | 61-90 | 90+ | Past Due | PD % |
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| Direction | Customer | Plant | Invoice # | From Bucket | To Bucket | Prev Balance | Curr Balance | Change |
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ⓘ AR-derived billings data. Figures are based on invoiced amounts from accounts receivable records using
net_revenue where available, falling back to invoice_total. This is not a substitute for audited revenue or financial reporting.
Billings Over Time
By Location
Daily Billings — MTD
Top Customers by Billings
| Customer | Plant | Billed | Invoices |
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By Salesperson
| Salesperson | Plant | Billed | Invoices |
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Monthly Collections
Amount collected by month
Avg Days to Collect
By location over time
On-Time vs Late Payments
Collections Efficiency by Plant
% paid on time, avg DTP, late breakdown
Top Customers by Collections
Ranked by amount collected in selected period
| Customer | Plant | Collected | Invoices | Avg DTP | On Time | Late |
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Notes
New Note
Monthly Shipped Revenue
All entities · Jan 2024 – Apr 2026
Bookings vs Shipments
Book-to-ship ratio · backlog indicator
Monthly Billings vs Collections
BV + KG · WB has no collections data
Methodology — Two-layer model:
Current invoices (not yet overdue): Expected date = MAX(due_date, invoice_date + customer avg DTP). Each invoice lands in a specific forecast week.
Overdue invoices: Distributed across near-term weeks using a decay curve — heavier weight in early weeks, tapering off. Conservative scenario applies a 15% haircut for potential uncollectables.
Customers with 3+ paid invoices use their own DTP. Others fall back to site avg (BV: 56d · KG: 52d · WB: 68d).
Scenarios: Optimistic = avg − 0.5σ | Base = avg | Conservative = avg + 0.5σ − 15% haircut on overdue.
Solid bars = current invoices | Faded bars = overdue recovery. Base dates in red in the table are past due.
Collections Forecast
Expected cash in by week
Customer-Level Forecast Detail
Open invoices ranked by expected collection date
| Customer / Invoice | Site | Balance | Inv. Date | Avg DTP | σ | Source | Optimistic | Base | Conservative | Opt. Week | Base Week | Cons. Week |
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