📊 Analytics Dashboard Overview
The Analytics Dashboard offers insights into invoice processing performance, accuracy, and efficiency, tracking metrics across vendors and time periods for data-driven improvements.
🔍 Filters
Vendor Filter: View metrics for a specific vendor or all vendors.
Date Range: Select a start and end date to filter the data displayed.
📈 Key Metrics (Expanded)
Metric | Description |
Perfectly Hydrated Documents | % of invoices where all fields were auto-filled accurately with no edits needed. |
Documents Synced | Total number of invoices successfully synced with your accounting or project system. |
Documents Archived Before Syncing | Invoices manually archived before they were synced. |
Total Volume Processed | Total dollar amount processed through the platform during the selected period. |
Average Total Amount Error (WMAPE) | Weighted Mean Absolute Percentage Error between extracted and actual totals. |
Mean Processing Time | Average time from upload to final sync. |
Median Processing Time | The middle value of processing times, excluding outliers. |
Vendor ID Match | Accuracy of matching vendor identifiers across systems. |
Project ID Match | Accuracy of matching project identifiers. |
Commitment ID Match | Accuracy of matching commitment IDs (e.g., POs or contracts). |
Average Match Trend | The chart shows the average accuracy of AI matching across the different data types. |
Perfect Match Trend | Displays the number of perfectly matched invoices with 100% match on specific days, weeks, and months. |
📦 Match Accuracy Panels
✅ Line Item Match
Average Match: 81.80% — reflects how accurately line item data matches expectations.
Match Distribution:
0–50%: 20.0%
51–85%: 20.0%
86–100%: 60.0%
✅ Invoice Number Match
Average Match: 100.00% — shows that invoice numbers were perfectly matched.
Match Distribution:
0–50%: 0.0%
51–85%: 0.0%
86–100%: 100.0%
Each of these shows:
Average Match % (e.g., 100.00%)
Match Distribution breakdown:
Red: 0–50%
Orange: 51–85%
Green: 86–100%
In your example, all three ID match categories show 100.00% accuracy, with 100% of matches falling in the 86–100% range.
✅ Understanding ID Match Metrics
The ID Match panels help you evaluate how accurately the system identifies and links critical identifiers on your invoices—such as vendor, project, and commitment IDs.
🔍 What Each Metric Means
Match Category | Description |
Vendor ID Match | Verifies whether the vendor on the invoice was correctly identified and matched to an internal record. |
Project ID Match | Measures how accurately the system matched the invoice to the correct project. |
Commitment ID Match | Confirms that the invoice is linked to the appropriate contract or purchase order (PO). |
📊 Match Score and Distribution
Each match category includes:
Average Match %: Overall average accuracy for that field.
Match Distribution Bar: Shows the percentage of documents falling into each accuracy range.
Match Range | Color | Description |
86–100% | 🟢 Green | Excellent match; little or no correction needed. |
51–85% | 🟠 Orange | Moderate accuracy; review recommended. |
0–50% | 🔴 Red | Low confidence; likely needs correction. |
✅ Example from Image
In this case:
Vendor ID Match: 100.00% average accuracy
Project ID Match: 100.00% average accuracy
Commitment ID Match: 100.00% average accuracy
Distribution: All documents fall in the 86–100% range for each field (🟢 100.0%), with 0.0% in orange or red ranges.
This indicates flawless system performance in identifying and linking vendor, project, and contract data.
📊 Key Metrics Summary (Based on Trend Chart)
Metric Category | Description | Observed Performance (Example) |
Line Item Match | Accuracy in matching invoice line items to expected fields or budget codes. | 50% on 03/23, 100% on 04/02–04/03 |
Invoice Number Match | Accuracy in capturing invoice numbers from documents. | 100% consistently |
Vendor Match | Match accuracy of vendor IDs between the document and system records. | 100% consistently |
Project Match | Match accuracy for linking documents to the correct project. | 100% consistently |
Commitment Match | Accuracy of PO/contract (commitment) matches. | 100% consistently |
Perfect Match Rate | % of documents with 100% match across all fields (line item, vendor, etc.). | 100% on 04/02, 04/03, 04/13 |
Notes:
The Average Match Trend chart shows full accuracy (100%) across all fields on April 2 and 3.
A dip in Line Item Match occurred on March 23, showing only ~50%.
The Perfect Match Trend confirms flawless extraction on April 2, April 3, and April 13.
📋 Invoice-Level Accuracy Table
The Invoice Accuracy Table provides a document-by-document view of AI extraction results, helping users quickly identify issues or confirm successful processing.
🔢 Columns & Descriptions
Column | Description |
Invoice Number | Unique identifier for each invoice. |
Creation Date | The upload or document processing date. |
Vendor | The vendor name extracted or selected. |
Invoice Link | A clickable link to view the full invoice. |
Total Amount | The dollar value recorded on the original invoice. |
AI Total Amount | The amount extracted by the AI engine. |
AI Line Item Score | Score (0–100%) indicating how accurately line items were matched. |
Invoice Number Score | % match confidence for the invoice number. |
Vendor ID Score | % accuracy in matching the vendor ID. |
Project ID Score | % accuracy in matching the project ID. |
🧠 AI Line Item Score Colors
🟢 100% – Full match, no manual edits required.
🟠 51–85% – Partial match, review recommended.
🔴 0–50% – Low match, manual verification required.
📌 Example Insight from Image
Invoices like
1807-383110,2717-899843, and1807-381904show 100% match across all fields—ideal processing performance.Invoices
2717-100553(50%) and1807-385143(59%) show lower AI Line Item Scores, flagged with red/orange indicators—these likely need manual checking or field adjustments.Despite AI line item issues, Invoice Number, Vendor ID, and Project ID scores remain at 100%, indicating metadata was accurately matched.
🔍 1. Accuracy Metrics (Match Rates & Scores)
Why it matters: These metrics show how well the system extracts and maps key data points (e.g., invoice number, vendor ID, line items) from uploaded documents.
Impact: High match rates reduce the need for manual corrections, minimize errors, and build trust in automation.
What to watch: Drops in match scores (especially line item or commitment matches) may indicate issues with document formats, vendor inconsistencies, or configuration gaps.
⚙️ 2. AI Performance (Hydration & Total Amount Error)
Why it matters: Hydration refers to the AI’s ability to auto-fill invoice fields without human intervention.
Impact: A high percentage of perfectly hydrated documents means your team spends less time reviewing and editing, which speeds up approvals and reduces risk.
WMAPE (Error %) helps identify if the extracted total is off from the actual invoice amount—critical for financial accuracy.
⏱️ 3. Processing Time (Mean & Median)
Why it matters: These metrics indicate how long it takes invoices to move through the system.
Impact: Fast, consistent processing leads to quicker approvals, better vendor relationships, and improved cash flow.
Mean vs. Median: Median gives a more accurate picture of typical performance by excluding outliers.
📊 4. Trends Over Time (Average & Perfect Match Trend)
Why it matters: These charts track performance day by day, helping you detect issues, improvements, or slowdowns over time.
Impact: Identifying spikes or dips allows you to intervene quickly, whether it’s a faulty document type, an underperforming vendor, or an internal bottleneck.
📋 5. Invoice-Level Breakdown
Why it matters: Seeing line-by-line scores for each invoice helps you quickly identify which documents are high-confidence and which need review.
Impact: Enables precise auditing, faster troubleshooting, and cleaner historical records.
📌 Summary
Together, this analytics data helps you:
Ensure financial accuracy across systems
Reduce operational overhead with automation
Improve turnaround times and processing speed
Build confidence with stakeholders, auditors, and vendors
Continuously optimize your workflows with measurable insights
Last updated: May 13, 2025