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Order Contents Dump Report Documentation

Menu Location: Reports > Orders > Order Contents Dump

Access Level: Manager and above

Last Updated: 2026-03-01

Overview

The Order Contents Dump provides a comprehensive, detailed export of all items in orders for a specified time period. This granular data is essential for inventory reconciliation, supplier reporting, financial analysis, and operational auditing.

Primary Functions:

  • Export detailed order-level product data
  • Reconcile inventory usage
  • Generate supplier reports
  • Audit order accuracy
  • Analyze product distribution
  • Support accounting and financial reporting

Page Layout

Header Section

  • Report Title: "Order Contents Dump"
  • Date Range Selector: Choose period to export
  • Filter Options: Status, route, customer type
  • Export Format: CSV, Excel, or PDF
  • Generate Report Button: Create export file

Report Configuration

  • Include Options: Checkboxes for data to include
  • Column Selection: Choose which fields to export
  • Sort Order: Configure data sorting
  • Grouping: Group by order, product, or date

Preview Section

  • Row Count: Total records to export
  • Estimated File Size: Download size
  • Sample Rows: First 10 rows preview

Report Configuration

Date Range Selection

Preset Ranges:

  • Today: Current day's orders
  • Yesterday: Previous day
  • This Week: Monday to today
  • Last Week: Previous full week
  • This Month: Month to date
  • Last Month: Previous full month
  • Custom: Specific date range

Best Practices:

  • Daily reconciliation: Use "Yesterday"
  • Weekly supplier reports: Use "Last Week"
  • Monthly accounting: Use "Last Month"
  • Custom analysis: Use "Custom" range

Filter Options

Order Status:

  • All statuses (default)
  • Closed/Complete only (for accounting)
  • Open only (for current operations)
  • Cancelled (separate analysis)

Route Filter:

  • All routes (default)
  • Specific route (route-level analysis)
  • Multiple routes (regional grouping)
  • Pickup orders only

Customer Type:

  • All customers (default)
  • Retail/subscription customers
  • Wholesale customers
  • Gift recipients
  • One-time purchases

Column Selection

Required Columns (always included):

  • Order ID
  • Order Date
  • Product Name
  • Quantity
  • Unit Price

Optional Columns:

  • Customer Name
  • Customer ID
  • Delivery Address
  • Route
  • Product SKU
  • Product Category
  • Line Item Total
  • Order Total
  • Delivery Fee
  • Tax Amount
  • Payment Method
  • Order Status
  • Fulfillment Date
  • Tracking Number

Custom Columns:

  • Select specific fields needed
  • Reduces file size
  • Faster processing

Data Export Formats

CSV Export (Most Common)

Characteristics:

  • Plain text comma-separated values
  • Opens in Excel, Google Sheets
  • Smallest file size
  • Best for data analysis
  • Universal compatibility

Use Cases:

  • Import to accounting software
  • Pivot table analysis
  • Supplier reporting
  • Inventory systems

Excel Export

Characteristics:

  • Native Excel format (.xlsx)
  • Formatted headers
  • Can include formulas
  • Larger file size
  • Preserves data types

Use Cases:

  • Financial reporting
  • Presentation to stakeholders
  • Complex analysis with formulas
  • Formatted reports

PDF Export

Characteristics:

  • Formatted document
  • Printable
  • Read-only
  • Professional appearance
  • Cannot analyze data easily

Use Cases:

  • Printed reports
  • Archiving
  • Sharing with non-analysts
  • Audit documentation

Data Structure

One Row Per Line Item

Example:

Order ID Date Customer Product Quantity Price Total
10001 2026-03-01 John Doe Apples 2 lbs $3.50/lb $7.00
10001 2026-03-01 John Doe Milk 1 gal $5.99 $5.99
10002 2026-03-01 Jane Smith Apples 3 lbs $3.50/lb $10.50

Structure:

  • One row = one product in one order
  • Same order ID repeated for each product
  • Allows product-level analysis
  • Easy to sum/filter by product or order

Common Use Cases

Use Case 1: Daily Inventory Reconciliation

Goal: Verify physical inventory matches order fulfillment

Steps:

  1. Set Date Range: Yesterday
  2. Filter: Closed/Complete orders only
  3. Select Columns: Product Name, SKU, Quantity, Route
  4. Export as CSV
  5. Open in Excel
  6. Create pivot table: Products (rows) × Sum of Quantity (values)
  7. Total quantities used per product
  8. Compare to inventory decrease
  9. Investigate any discrepancies

Result: Daily inventory accuracy verification

Use Case 2: Weekly Supplier Report

Goal: Send usage report to meat supplier

Steps:

  1. Set Date Range: Last Week
  2. Filter: Closed orders
  3. Select Columns: Product, SKU, Quantity, Product Category
  4. Export as CSV
  5. Filter to Product Category: "Meat & Seafood"
  6. Remove unnecessary columns
  7. Sum quantities by product
  8. Format as supplier-friendly report
  9. Email to supplier

Example Export:

Product SKU Quantity Ordered
Ground Beef 1lb MB001 180 lbs
Chicken Breast MB002 145 lbs
Pork Chops MB003 92 lbs

Result: Supplier visibility into your usage

Use Case 3: Monthly Accounting Reconciliation

Goal: Verify revenue recognition matches fulfilled orders

Steps:

  1. Set Date Range: Last Month
  2. Filter: Closed/Complete only (recognized revenue)
  3. Select Columns: Order ID, Date, Product, Quantity, Price, Line Total, Order Total, Tax, Payment Method
  4. Export as Excel
  5. Pivot table: Date (rows) × Sum of Order Total (values)
  6. Daily revenue totals
  7. Compare to payment processing reports
  8. Reconcile any differences
  9. Provide to accountant

Result: Accurate monthly financial close

Use Case 4: Product Distribution Analysis

Goal: Understand which products go to which routes

Steps:

  1. Set Date Range: Last 90 Days
  2. Filter: All routes
  3. Select Columns: Product, Quantity, Route
  4. Export as CSV
  5. Pivot table: Products (rows) × Routes (columns) × Sum of Quantity (values)
  6. Heatmap of product distribution
  7. Identify route-specific preferences
  8. Optimize route-specific inventory staging

Example Insights:

  • Route 1 (urban): High demand for specialty produce
  • Route 5 (rural): High demand for meats, potatoes
  • Action: Stage inventory by route preferences

Result: Optimized fulfillment efficiency

Use Case 5: Audit Order Accuracy

Goal: Verify customer received what they ordered

Steps:

  1. If customer complaint about missing item
  2. Set Date Range: Specific order date
  3. Filter: Specific customer or order ID
  4. Export all columns
  5. Review line items for that order
  6. Compare to packing sheet
  7. Compare to customer's claim
  8. Determine if item was in order, omitted, or substituted
  9. Resolve customer issue appropriately

Result: Data-backed customer service resolution

Advanced Analysis Examples

Pivot Table: Revenue by Product Category

Steps in Excel:

  1. Import CSV dump
  2. Insert Pivot Table
  3. Rows: Product Category
  4. Values: Sum of Line Total
  5. Sort descending by Sum
  6. Identify top revenue-generating categories

Formula: Average Order Value

In Excel:

  1. Dump includes Order Total column
  2. Remove duplicate Order IDs (one row per order)
  3. Formula: =AVERAGE(Order_Total_Column)
  4. Calculates mean order value

Chart: Products Sold Over Time

Steps:

  1. Import dump with Date column
  2. Pivot: Date (rows) × Product (columns) × Sum of Quantity (values)
  3. Create line chart
  4. Visualize product trends over time

Troubleshooting

Export File Too Large

Solutions:

  1. Reduce date range (export in smaller batches)
  2. Deselect unnecessary columns
  3. Filter to specific routes or categories
  4. Export as CSV instead of Excel (smaller file)
  5. Use file compression (.zip)

Data Appears Incorrect

Check:

  1. Correct date range selected?
  2. Filters applied as intended?
  3. Cancelled orders included/excluded correctly?
  4. Time zone settings correct?

Solutions:

  1. Clear filters, re-apply carefully
  2. Verify date range matches intention
  3. Check filter logic (include vs. exclude)
  4. Spot-check a few orders in admin for accuracy

Excel Won't Open File

Possible Causes:

  1. File too large (Excel has row limits)
  2. File corrupted during download
  3. CSV encoding issues

Solutions:

  1. Break into smaller date ranges
  2. Re-download file
  3. Open in Google Sheets (higher limits)
  4. Use database tool for very large datasets

Missing Expected Orders

Check:

  1. Order status filter (are you excluding some statuses?)
  2. Date range (orders might be outside range)
  3. Route filter (limiting to specific routes?)
  4. Customer type filter

Solutions:

  1. Set Status filter to "All"
  2. Expand date range
  3. Remove route/customer filters
  4. Verify orders exist in system for that period
  • Orders - View individual orders
  • Product Quantities Over Time - Aggregated product trends
  • Bestselling Results - Top products summary
  • Weekly Open to Closed Comparison - Fulfillment tracking
  • Inventory Management - Inventory levels

Best Practices

Regular Exports

  1. Daily: Export previous day for inventory reconciliation
  2. Weekly: Export for supplier reporting
  3. Monthly: Export for accounting close
  4. Quarterly: Archive for historical records

Data Hygiene

  1. Consistent naming: Standard file naming (e.g., "OrderDump_2026-03-01.csv")
  2. Organized storage: Dedicated folder for exports
  3. Archive old exports: Keep 12-24 months accessible
  4. Document filters: Note what filters were applied

Analysis Efficiency

  1. Template pivot tables: Save Excel templates for common analyses
  2. Automated imports: Script regular imports to accounting systems
  3. Saved filter sets: Document useful filter combinations
  4. Share with team: Standardize reports across team

Security

  1. Customer data: Exports contain PII, handle securely
  2. Access control: Only authorized personnel download
  3. Secure storage: Encrypt or password-protect exports
  4. Retention policy: Delete old exports per company policy

Quick Reference Card

Task Action/Location
Daily inventory reconciliation Date: Yesterday, Status: Closed, Export CSV
Weekly supplier report Date: Last Week, Filter category, Export
Monthly accounting Date: Last Month, Status: Closed, All columns
Specific order audit Filter by Order ID or Customer
Product distribution analysis Include Route column, Pivot by route
Revenue by category Include Category + Line Total, Pivot
Customer purchase history Filter by Customer ID or name
Export for Excel analysis Select Excel format
Quick small export CSV format, minimal columns
Professional report PDF format with all details

FAQs

How detailed is the dump?

Line-item level detail - one row per product per order. Most comprehensive data export available.

Can I get customer contact information?

Yes, if you select customer-related columns. Handle this data securely per privacy policies.

How far back can I export?

Typically 2-3 years of historical data. Check with administrator for system's data retention.

Can I schedule automatic exports?

Some systems support scheduled reports. Check Settings > Scheduled Reports or contact administrator to configure.

What's the maximum date range?

No hard limit, but large ranges create large files. For exports >100K rows, consider breaking into smaller batches.

Can I filter to specific products?

Report shows all products in orders. After export, filter in Excel to specific products you want to analyze.

Do totals include tax and fees?

Depends on column selection. "Line Total" is product × quantity. "Order Total" includes tax/fees if you select that column.

Can I see cancelled line items?

Yes, if you include Cancelled orders in Status filter. Cancelled items show status in export.

How do I import to QuickBooks/Xero?

Export as CSV, then use your accounting software's import feature. Map columns to their corresponding fields.

Can I export in other formats?

CSV, Excel, and PDF are standard. For other formats (JSON, XML), may require custom development or export CSV then convert.

Change Log

2026-03-01

  • Initial documentation created
  • All sections completed following template structure

End of Documentation

For additional help, contact your system administrator or Kiva Logic support.