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Produce Reports Alpha Documentation

Menu Location: Reports > Products > Produce Report (Alpha)

Access Level: Manager / Administrator

Last Updated: 2026-03-01

Overview

⚠️ EXPERIMENTAL FEATURE: This page is a work in progress and is currently in alpha testing. Data and calculations may change as the feature is refined.

The Produce Reports Alpha page provides historical analysis of produce and product inventory movements across weekly cycles. Track opening inventory, closing inventory, changes, pricing, and wholesale costs over time for any product classification. This helps with purchasing decisions, waste reduction, and pricing strategy.

Primary Functions:

  • Analyze product inventory trends week-by-week
  • Track opening vs closing inventory levels
  • Calculate inventory change percentages
  • Monitor retail pricing and wholesale costs over time
  • Identify seasonal patterns in product movement
  • Support purchasing and pricing decisions

Page Layout

Header Section

  • Page Title: "Viewing: Produce Report"
  • Alpha Warning Banner: Black banner indicating this is a testing feature
  • Product Selector: Dropdown to choose which product to analyze

Filter Section

A single dropdown menu to select the product classification you want to analyze.

Report Table

Weekly breakdown showing:

  • Week identification and dates
  • Opening inventory levels
  • Closing inventory levels
  • Percentage changes
  • Retail pricing
  • Case costs and quantities
  • Wholesale cost per unit

Product Selection

Choosing a Product

Steps:

  1. Click the "Select Product..." dropdown
  2. Browse alphabetically sorted product list
  3. Click desired product classification
  4. Click "Select" button
  5. Report generates for all historical weeks

Product List: Shows all product classifications from your product catalog (items that have a parent category, indicating they're actual products rather than top-level categories).

Examples:

  • Apples, Red Delicious
  • Tomatoes, Roma
  • Milk, Whole
  • Bread, Sourdough

Report Data & Columns

Column Description Calculation/Source
Week ID Unique identifier for weekly cycle System-generated sequential number
Date Delivery date for that weekly cycle Weekly cycle date field
Opening Inventory Total quantity ordered for the week Sum of menu_qty from all orders for that week
Closing Actual quantity after cancellations Sum of menu_qty excluding cancelled orders (status != 5)
Change Percentage change from opening to closing ((Opening - Closing) / Opening) × 100
Retail Retail price per unit From menu.retail_price for that week
Case Cost Cost per case purchased From menu.case_price for that week
Case Quantity Units per case From menu.case_quantity for that week
Wholesale Cost/unit Cost per individual unit Case Cost ÷ Case Quantity

Understanding Inventory Metrics

Opening Inventory

The initial quantity based on all orders placed for that week, before any cancellations or modifications. This represents your initial demand forecast.

Closing Inventory

The final quantity after accounting for cancelled orders. This represents actual delivered quantity and real demand.

Change Percentage

Shows how much inventory changed from opening to closing:

  • Negative %: Indicates cancellations (closing < opening)
  • Zero: No cancellations
  • Positive %: Unusual, but possible if orders added late

Example:

  • Opening: 100 units
  • Closing: 85 units
  • Change: -15% (15 units were cancelled)

Wholesale Cost Per Unit

Calculated by dividing case cost by case quantity. Useful for:

  • Determining true product cost
  • Calculating profit margins
  • Making purchasing decisions
  • Comparing supplier pricing

Actions & Operations

Generate Report for Product

Purpose: View historical inventory data for a specific product

Steps:

  1. Navigate to Reports > Products > Produce Report
  2. Click "Select Product..." dropdown
  3. Choose product from list
  4. Click "Select" button
  5. Review weekly data in table

Requirements:

  • Product must be in product classification system
  • Product must have been included in at least one weekly menu
  • Historical menu data must exist

Common Use Cases

Use Case 1: Identify Products with High Cancellation Rates

Goal: Find products that customers frequently cancel to reduce waste

Steps:

  1. Select a product you suspect has high cancellations
  2. Review the "Change" column
  3. Look for weeks with large negative percentages
  4. Count how many weeks show significant cancellations
  5. If pattern is consistent, consider: reducing order quantities, improving quality, or adjusting product offering

Example: Organic kale shows -20% to -30% change most weeks. This indicates customers are canceling kale orders frequently. Consider ordering less or replacing with a more popular green.

Use Case 2: Monitor Seasonal Demand Patterns

Goal: Understand how demand for a product changes throughout the year

Steps:

  1. Select product with suspected seasonality (e.g., strawberries)
  2. Scroll through entire year of data
  3. Note opening inventory levels by season
  4. Identify peak demand periods
  5. Use insights to adjust future ordering

Example: Strawberries show 200 units/week in summer but only 50 units/week in winter. Plan purchasing accordingly.

Use Case 3: Evaluate Pricing Strategy Changes

Goal: See how retail price changes affected demand

Steps:

  1. Select product where price was recently changed
  2. Find week where "Retail" column changed
  3. Compare opening inventory before and after price change
  4. Look at change percentages before and after
  5. Assess if price increase led to more cancellations

Tips:

  • Compare multiple weeks before and after price change
  • Account for seasonal effects
  • Consider overall customer base growth/shrinkage

Use Case 4: Calculate Product Profit Margins

Goal: Determine actual profitability of specific products

Steps:

  1. Select product to analyze
  2. Find most recent week (top of table)
  3. Note Retail price
  4. Note Wholesale Cost/unit
  5. Calculate: (Retail - Wholesale) ÷ Retail = Margin %
  6. Compare to target margins

Example:

  • Retail: $4.50
  • Wholesale cost/unit: $2.25
  • Margin: ($4.50 - $2.25) ÷ $4.50 = 50%

Use Case 5: Track Supplier Cost Changes

Goal: Monitor how your supplier costs have changed over time

Steps:

  1. Select product
  2. Review "Case Cost" column historically
  3. Note any jumps in pricing
  4. Compare "Wholesale Cost/unit" trends
  5. Identify when to renegotiate with supplier or adjust retail pricing

Example: Tomatoes' case cost increased from $15 to $18 over 8 weeks. Wholesale cost/unit went from $0.75 to $0.90. Consider retail price increase to maintain margins.

Understanding the Data

What Gets Counted

Opening Inventory:

  • All menu items ordered, regardless of order status
  • Includes orders later cancelled

Closing Inventory:

  • Only confirmed orders (excludes status 5 = cancelled)
  • Real demand after cancellations

Why They Differ: Customers cancel orders, reduce quantities, or orders get cancelled by admin. Opening represents initial projection; closing represents reality.

Data Limitations (Alpha Version)

⚠️ Current Limitations:

  • Only shows products with menu history
  • Calculations may change as feature is refined
  • Some fields may show empty if data not recorded historically
  • Table shows raw data without advanced filtering
  • No export function currently

Use With Caution: This is an experimental tool. Verify critical business decisions with other reports or data sources.

Troubleshooting

No Data Showing After Selecting Product

Symptoms: Table is empty after clicking Select

Solutions:

  1. Verify product has been included in weekly menus
  2. Check that product has a product classification assigned
  3. Try a different, more commonly used product
  4. Confirm historical weekly cycle data exists

Common Causes:

  • New product with no history
  • Product not properly classified in system
  • Product never added to any weekly menus

Strange or Inconsistent Numbers

Symptoms: Data doesn't seem to make sense or match expectations

Check:

  1. Remember this is ALPHA—data calculations may have bugs
  2. Verify you selected the correct product
  3. Compare to other reports for validation
  4. Consider reporting inconsistencies to Kiva Logic

Note: This is a testing feature. Known issues may exist.

Retail, Case Cost, or Case Quantity Empty

Symptoms: Some columns show no data

Causes:

  • Information wasn't recorded for that week
  • Product wasn't formally added to menu system (ad-hoc addition)
  • Historical data not complete

Solutions:

  • Focus on weeks with complete data
  • Ensure future weeks have all pricing fields filled in menu builder
  • Menu Builder (menu_builder.php) - Where retail prices, case costs, and quantities are set
  • Menu Inventory (menu-inventory.php) - Current week's inventory levels
  • Weekly Cycle (weekly_cycle.php) - Weekly cycle configuration
  • Product Quantities (product-quantities.php) - Real-time product quantity report
  • Products (products.php) - Product classification and setup

Typical Workflow:

  1. Produce Report → Identify trends → Menu Builder → Adjust pricing/ordering
  2. Produce Report → Notice high cancellations → Products → Adjust product offering
  3. Menu Builder → Set prices → Produce Report → Monitor impact weeks later

Permissions & Access

Required Access Level: Manager or higher

Access Level Capabilities:

  • Customer Service: Cannot access produce reports
  • Manager: View reports, analyze trends, inform purchasing decisions
  • Administrator: All Manager capabilities plus product classification management
  • Kiva Admin: All features plus system configuration

Best Practices

Analysis Approach

  1. Start with high-volume products for meaningful data
  2. Look at 8-12 weeks minimum for trend identification
  3. Account for seasonal variations
  4. Compare similar products to understand relative performance
  5. Cross-reference with customer feedback

Data Quality

  1. Ensure menu builder is consistently used for all products
  2. Fill in retail prices, case costs, and quantities every week
  3. Keep product classifications up-to-date
  4. Record pricing changes with effective dates noted

Decision Making

  • Don't make major decisions based solely on this alpha tool
  • Validate findings with other reports
  • Consider multiple factors beyond just inventory movement
  • Test theories with small adjustments first

Things to Avoid

  • ❌ Relying on this tool for critical decisions without validation
  • ❌ Assuming data is 100% accurate (it's alpha/experimental)
  • ❌ Comparing products with very different sales volumes
  • ❌ Ignoring seasonal context when analyzing trends

Quick Reference Card

Task Action/Location
Access produce reports Reports > Products > Produce Report
Select product to analyze Click dropdown, choose product, click Select
View historical trends Scroll through table after selecting product
Find most recent data Look at top rows of table (sorted by week ID descending)
Calculate profit margin (Retail - Wholesale Cost/unit) ÷ Retail
Identify cancellation patterns Review "Change" column for negative percentages
Track pricing changes Compare "Retail" column week-to-week
Monitor supplier costs Review "Case Cost" and "Wholesale Cost/unit" trends

FAQs

Why is this marked as "Alpha" and "Work in Progress"?

This feature is still being developed and refined. The calculations, data sources, or display may change based on testing and feedback. It's available for use but should be validated against other data sources for important decisions.

What's the difference between this and Product Quantities report?

Product Quantities report shows current/recent week data in detail. Produce Reports Alpha shows historical trends over many weeks. Use Product Quantities for "what's happening now" and Produce Reports for "what's the pattern over time."

Can I export this data?

Not in the current alpha version. If you need to export, take screenshots or manually transcribe data of interest. Export functionality may be added in future versions.

Why doesn't my new product show in the dropdown?

New products must: (1) be added to product classification system, (2) have a parent category, and (3) appear in at least one weekly menu. If just created today, it won't have historical data yet.

How far back does the data go?

As far back as you have weekly cycle data and menu configurations in the system. This varies by business but may go back months or years.

What should I do if I find a bug or data that seems wrong?

Document what you're seeing (screenshots help), note which product and which week, and contact Kiva Logic support. Since this is alpha, feedback helps improve the feature.

Will this feature change in the future?

Yes, likely. As an alpha feature, expect ongoing development. New columns may be added, calculations may be refined, and display may be improved based on user feedback and testing.

Change Log

2026-03-01

  • Initial documentation created
  • Documented current alpha state of feature
  • Included appropriate warnings about experimental nature

End of Documentation

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