Description
WooCommerce Plugin
Enhanced Capacity-Aware Delivery Slot Manager
Bakery offers Saturday delivery. Limits delivery slot to 10 orders. Seems reasonable. Order 1 arrives. Single cupcake. Fits in small box. Driver loads it. Takes 30 seconds. Order 2. Another cupcake. Another 30 seconds. Order 3. Wedding cake. Three tiers. Requires special handling. Fragile. Heavy. Takes 5 minutes to load carefully. Order 4. Another wedding cake. Order 5. Birthday cake with decorations. Order 6. Yet another wedding cake. Driver realizes problem. Van is 40 percent full. Only loaded 6 orders. Has 4 slots remaining by order count. Next 4 orders are all large celebration cakes. Van reaches capacity at order 9. Slot still shows 1 order available. Order 10 comes in. Massive corporate event cake. Five sheet cakes. Physically impossible to fit in van. Driver calls bakery. Cannot complete deliveries. Must make second trip. Costs extra fuel. Extra driver hours. Delays all customers. Angry phone calls. Bad reviews. Problem is order-count limit. System treats cupcake same as wedding cake. Both consume one slot. Reality differs. Wedding cake needs 50 times more space than cupcake. Generic delivery plugins count orders. Capacity Manager counts reality. Assign capacity points to products. Cupcake equals 1 point. Wedding cake equals 50 points. Set slot maximum to 500 points total. System blocks slot when point total reaches 500. Could be 500 cupcakes or 10 wedding cakes or any combination. Van never overloads. Driver always has exactly right amount. Zero wasted trips. Zero angry customers. Pure capacity logic.
Weighted Capacity Points
Intelligent Slot Blocking
Driver Load Balancing
Real-time Tracking
The order-count catastrophe
Furniture store runs Saturday delivery. Configures delivery plugin. Sets slot limit to 15 orders maximum. Sounds safe. Average Saturday gets 12-14 orders. System works initially. Week 1. Small items only. 15 orders of lamps, pillows, small tables. Van easily handles load. Driver finishes route in 4 hours. Perfect. Week 2. Mix changes. Order 1 is sectional sofa. Three pieces. Requires two people to carry. Takes entire back section of van. Orders 2-5 are dining chairs. Small. Stack easily. Order 6 is another sectional. Different customer. Another huge space consumer. Orders 7-8 are coffee tables. Order 9 is king size mattress and box spring. Completely fills remaining van space. Driver looks at remaining orders. Still 6 orders waiting. Slot shows space available. System accepted 15 orders total. Van physically full at order 9. Must make second trip for orders 10-15. Costs extra 3 hours driver time. Extra fuel. Some customers delayed until evening. Promised morning delivery. They took day off work. Now furniture arrives at 7 PM. Furious. Leave bad reviews. Furniture store analyzes data. Sectional sofa takes same slot as lamp. Both count as one order. Sofa requires 200 cubic feet van space. Lamp requires 2 cubic feet. 100 times difference in reality. Zero difference in system logic. Store tries different limits. Reduces Saturday slot to 10 orders. Becomes too restrictive. Turns away orders that would fit. Loses revenue. Tries 12 orders. Still get overload days with large items. No number works. Problem is fundamental. Order count cannot model physical reality. Different products have different delivery requirements. Enhanced Capacity Manager solves this permanently. Configure capacity points per product. Small lamp equals 5 points. Dining chair equals 15 points. Coffee table equals 30 points. Sofa equals 200 points. Sectional equals 400 points. Mattress set equals 300 points. Set Saturday slot maximum to 2000 capacity points. System tracks points not orders. Van fills to 2000 points. Could be 400 lamps. Could be 5 sectionals. Could be any combination. System blocks slot when capacity reached. Driver always has perfect load. Never overloaded. Never underutilized. Mathematical precision replaces guessing.
Weighted Capacity Points
Assign capacity points to each product based on actual delivery requirements. Small items get 1-10 points. Medium items 10-50 points. Large items 50-200+ points. System tracks total points per slot. Blocks when capacity reached. Perfectly models physical reality.
Intelligent Slot Blocking
Slots close automatically when capacity points reach maximum. Customer sees accurate availability based on their cart contents. Heavy order might find slot full. Light order finds same slot available. Dynamic blocking prevents van overloads completely.
Driver Load Balancing
Automatically assigns orders to drivers using intelligent algorithms. Balance mode distributes load evenly across drivers. Best-fit mode fills drivers sequentially for route optimization. Prevents one driver overloaded while another runs light. Perfect fleet utilization.
Visual Capacity Display
Customers see remaining capacity per slot with visual utilization bars. Shows how many capacity points available. Displays slot nearing full with color indicators. Transparent system builds customer confidence. Reduces support questions about availability.
The driver assignment disaster
Florist has 3 delivery drivers. Saturday gets 30 orders. Manager assigns manually. Looks at delivery addresses. Tries to split evenly. Driver 1 gets orders 1-10. Driver 2 gets orders 11-20. Driver 3 gets orders 21-30. Seems fair by numbers. Reality destroys plan. Driver 1 orders are all small bouquets. Lightweight. Quick deliveries. Finishes entire route by 2 PM. Returns to shop. Sits idle rest of day. Still paid full shift. Wasted labor cost. Driver 2 orders include mix of bouquets and arrangements. Moderate difficulty. Finishes by 4 PM. Driver 3 gets disaster. All wedding arrangements. Massive. Fragile. Require careful handling. Each delivery takes 20 minutes setup time. Route runs until 8 PM. Customer complaints about late delivery. Driver 3 exhausted. Threatens to quit. Management tried equal order count. Failed to account for delivery complexity. Next week tries different approach. Assigns by zip code. All north side to Driver 1. Central to Driver 2. South to Driver 3. Geographic splitting makes sense theoretically. Reality again different. North side only got 5 orders that Saturday. All small. Driver 1 done by noon. Paid for 8 hours. Worked 3. Central got 12 orders. Mix of sizes. Driver 2 finishes on time. South side got 13 orders. 8 of them wedding events. Driver 3 overloaded again. Same problem repeats. Manager realizes manual assignment impossible. Too many variables. Order size. Delivery distance. Setup complexity. Traffic patterns. Cannot optimize manually. Enhanced Capacity Manager handles this automatically. Set driver max capacity points. Driver 1 can handle 1000 points. Driver 2 can handle 1200 points. Driver 3 can handle 800 points. Configure assignment strategy. Balance mode distributes evenly by capacity not order count. Saturday 30 orders come in. Total 2800 capacity points needed. System assigns automatically. Driver 1 gets 933 points worth of deliveries. Driver 2 gets 1120 points. Driver 3 gets 747 points. Perfect distribution. All drivers finish routes within minutes of each other. Equal workload. Equal stress. Equal time. Happy drivers. Happy customers. Zero manual work. Algorithm handles optimization. Load balancing happens automatically on every order. Manager eliminates entire administrative burden.
Order-count limits: Treats cupcake same as wedding cake
Generic delivery plugins limit slots by order count. 10 orders maximum per slot. Small order and large order both consume 1 slot. Cupcake takes 1 slot. Wedding cake takes 1 slot. Sectional sofa takes 1 slot. Greeting card takes 1 slot. System cannot differentiate. Van overloads when large items cluster. Van underutilizes when small items cluster. No configuration fixes fundamental problem. Order count metric fails to model physical reality.
Manual driver assignment: Impossible to optimize with multiple variables
Manager looks at 30 orders. Tries to split evenly among 3 drivers. Assigns 10 orders each. Driver 1 finishes early. Driver 3 runs late. Try geographic split instead. North, central, south zones. Still unbalanced. Some zones get more orders. Some get heavier orders. Try assign by order number. Same problem. Cannot predict delivery complexity from order list. Manual optimization requires considering order size, delivery distance, traffic, setup time, fragility. Human cannot process all variables. Results in unbalanced workloads and driver complaints.
Capacity Manager: Weighted points system with automatic driver balancing
Assign capacity points to every product. Cupcake 1 point. Wedding cake 50 points. Sofa 200 points. System tracks total points per slot. Blocks slot when point maximum reached. Van never overloads. Configure driver capacities. Driver A handles 1000 points. Driver B handles 1200 points. Choose assignment strategy. Balance mode distributes load evenly. Best-fit mode optimizes routes. System assigns orders automatically. Considers actual capacity not arbitrary order count. Drivers finish routes simultaneously. Perfect workload distribution. Zero manual intervention. Complete automation.
📊 Real Capacity Comparison: Saturday Bakery Deliveries
Order-Count Plugin: Van overload or underutilization
Scenario 1: Saturday slot limited to 10 orders. First 10 orders all cupcakes. Each weighs 0.5 lbs. Each fits in small box. Total van utilization 15%. Driver finishes route in 90 minutes. Paid for 8 hour shift. Massive waste of driver capacity and time. Scenario 2: Saturday slot limited to 10 orders. Orders are 7 wedding cakes plus 3 tiered celebration cakes. Van completely full after 8 orders. Cannot fit remaining 2 orders. Must make second delivery trip. Costs extra 2 hours driver time plus fuel. Customers angry about delayed delivery. Both scenarios happen because system counts orders not capacity. Cannot optimize. Cannot adapt to actual load.
Capacity Manager: Perfect van utilization every time
Configure capacity points. Cupcake equals 2 points. Standard cake equals 25 points. Wedding cake equals 60 points. Tiered celebration cake equals 80 points. Set Saturday slot maximum to 500 capacity points total. Scenario 1: Cupcake orders arrive. Each consumes 2 points. Slot accepts 250 cupcake orders before blocking. Perfect for high-volume small item days. Scenario 2: Wedding cake orders arrive. Each consumes 60 points. Slot accepts 8 wedding cakes before reaching 480 points. Remaining 20 points available for small items. Slot blocks appropriately. Van filled to optimal capacity. Driver has perfect load. No overload. No wasted space. System automatically adapts to order mix. Heavy item days get fewer orders but correct physical load. Light item days get more orders to fill capacity. Mathematical precision every single time.
🎯 Driver Assignment Example
Situation: 25 orders Saturday. 3 drivers available. Total capacity needed 2400 points. Driver A max 900 points. Driver B max 1000 points. Driver C max 800 points.
Balance Strategy: System distributes evenly. Driver A assigned 864 points (8 orders). Driver B assigned 976 points (9 orders). Driver C assigned 560 points (8 orders). All drivers finish routes within 30 minutes of each other. Equal workload. Equal pay. Fair distribution.
Best-Fit Strategy: System fills sequentially. Driver A assigned 896 points (full capacity, 10 orders). Driver B assigned 1000 points (full capacity, 9 orders). Driver C assigned 504 points (6 orders). Optimizes routes by having drivers handle complete zones. Best for geographic efficiency.
Complete feature set
Advanced capacity-aware delivery management with weighted points, intelligent blocking, and driver load balancing. Perfect for local delivery businesses with variable product sizes.
⚖️ Capacity Point System
• Assign points per product
• Configurable on product page
• Small items 1-10 points
• Medium items 10-50 points
• Large items 50-200+ points
• Weight and volume tracking
• Real-time capacity calculation
• Cart total capacity display
🚫 Smart Slot Blocking
• Blocks when capacity reached
• Dynamic availability updates
• Cart-aware slot filtering
• Real-time capacity tracking
• Visual utilization bars
• Remaining capacity display
• Automatic slot generation
• 14-day advance scheduling
🚚 Driver Management
• Load balancing algorithm
• Best-fit assignment strategy
• Per-driver capacity limits
• Automatic order assignment
• Driver workload tracking
• Add unlimited drivers
• Driver status management
• Assignment history
📅 Time Slot Configuration
• Custom time windows
• Morning, afternoon, evening slots
• Configurable slot intervals
• Default capacity per slot
• Add/remove time slots
• Flexible scheduling
• Multi-day advance booking
• Automatic slot creation
🎨 Customer Experience
• Visual slot selector
• Capacity breakdown display
• Cart requirement preview
• Color-coded availability
• Utilization indicators
• Mobile responsive
• Theme color inheritance
• Clean checkout integration
⚙️ System Features
• Custom database tables
• Order metadata storage
• Capacity release on cancel
• Admin settings interface
• WooCommerce integration
• Zero frontend dependencies
• PHP 8.2+ compatible
• Production-grade structure
Perfect for
Bakeries & Cake Shops
Single cupcake versus wedding cake capacity difference massive. Order count limits fail completely. Cupcake 2 points. Standard cake 25 points. Wedding cake 60 points. Tiered celebration 80 points. System blocks slot at correct capacity. Van never overloaded with heavy cakes. Never underutilized with only cupcakes. Perfect optimization.
Furniture Stores
Lamp versus sofa capacity astronomical difference. Small lamp 5 points. Dining chair 20 points. Coffee table 40 points. Sofa 200 points. Sectional 400 points. Mattress set 300 points. Prevents disaster scenarios where all orders are large items. Van capacity perfectly managed every delivery day.
Florists
Small bouquet versus wedding arrangement size difference critical. Single rose 3 points. Standard bouquet 10 points. Large arrangement 35 points. Wedding flowers 80 points. Funeral arrangements 60 points. System handles variable order sizes intelligently. Driver load balanced across varying complexity.
Grocery Delivery
Small basket versus bulk grocery order capacity variance huge. Quick shop 10 points. Weekly groceries 50 points. Bulk order 150 points. Party catering 200 points. Weighted system prevents overload. Ensures fair driver distribution. Optimizes delivery efficiency automatically.
Common use cases
Use Case 1: Saturday bakery rush (mixed order sizes)
Configure capacity points. Cupcake 2 points. Sheet cake 30 points. Wedding cake 60 points. Set Saturday slot maximum 500 points. Orders arrive. 10 cupcakes (20 points). 5 sheet cakes (150 points). 4 wedding cakes (240 points). Total 410 points consumed. Slot shows 90 points remaining. Can accept 45 more cupcakes OR 1 more wedding cake. System blocks appropriately. Van perfectly loaded. Driver makes deliveries on schedule. Zero overload.
Use Case 2: Furniture delivery with 3 drivers
Saturday 20 orders total. 2800 capacity points needed. Driver A max 1000 points. Driver B max 1000 points. Driver C max 900 points. Choose balance strategy. System assigns Driver A 933 points (7 orders). Driver B 967 points (8 orders). Driver C 900 points (5 orders). All drivers finish routes within 45 minutes of each other. Perfect workload distribution. No manual assignment needed. Algorithm optimizes automatically.
Use Case 3: Florist Valentine’s Day capacity planning
Valentine’s Day massive demand. Configure points. Single rose 3 points. Bouquet 12 points. Premium arrangement 40 points. Set slot capacity 800 points. Morning slot fills with 25 bouquets (300 points) and 10 arrangements (400 points). Total 700 points. Shows 100 points remaining. Afternoon slot gets rush orders. Reaches 800 points quickly. Blocks automatically. Evening slot opens. Continues accepting. System prevents overload during peak holiday. Ensures quality deliveries all day.
Use Case 4: Cancellation handling and capacity release
Customer orders large sectional (400 points) for Saturday delivery. Slot shows 600 points remaining after booking. Customer cancels order Friday. System automatically releases 400 points back to slot. Saturday slot now shows 1000 points available. Accepts new orders to fill released capacity. Automatic capacity management. Zero manual intervention required.
🚀 Setup Process
Step 1: Install plugin (WooCommerce required)
Step 2: Go to WooCommerce > Delivery Capacity settings
Step 3: Configure default slot capacity, time slots, add drivers
Step 4: Edit products, assign capacity points to each item
Step 5: Slot selector appears on checkout automatically
Frequently asked questions
How do I determine capacity points for products?
Use physical attributes as guide. Small items 1-10 points. Medium items 10-50 points. Large items 50-200+ points. Cupcake might be 2 points. Wedding cake 60 points. Lamp 5 points. Sofa 200 points. Exact values depend on your van size and constraints. Start with estimates then adjust based on actual delivery experience.
Can customers see capacity information?
Yes. Slot selector shows remaining capacity per slot. Visual utilization bars indicate how full each slot is. Cart displays total capacity points required. Transparency helps customers understand availability. Builds confidence in delivery system. Reduces support questions about why slots unavailable.
What happens if order is cancelled?
System automatically releases capacity back to slot. Order consumed 400 points. Cancellation releases 400 points. Slot capacity increases immediately. New orders can fill released space. Works for cancellations and refunds. Complete automation. Zero manual capacity management required.
How does driver assignment work exactly?
Configure each driver’s max capacity. Driver A 1000 points. Driver B 1200 points. Choose strategy. Balance mode distributes evenly by capacity. Best-fit mode fills drivers sequentially. System assigns orders automatically when placed. Considers current driver load. Chooses optimal driver. Saves assignment to order. Complete automation.
Can I set different capacity per day?
Current version uses default slot capacity for all days. Can configure different time slots per day (morning, afternoon, evening). Each time slot uses same capacity maximum. Per-day capacity customization planned for future release based on demand. Current system handles most use cases effectively.
Does this work with my theme?
Yes. Plugin uses currentColor for styling. Automatically inherits your theme’s color scheme. Checkout integration uses standard WooCommerce hooks. Compatible with all properly coded themes. Tested with major themes like Astra, Divi, Flatsome, Storefront. Mobile responsive design. Works perfectly on all devices.
What about variable products?
Works with variable products. Configure capacity points at parent product level. All variations inherit same capacity value. For products where variations have different sizes (small vs large), configure capacity at variation level in product settings. System handles both scenarios correctly.
Is there really no renewal fee?
Correct. One-time purchase. Lifetime updates. No subscription. Plugin never expires. No annual renewal. Fair pricing model. Pay once, own forever. Better economics than monthly SaaS tools. Simple business model. Honest pricing. Use indefinitely.
Technical requirements
WordPress
6.0 or higher
WooCommerce
8.0 or higher
PHP
8.2 or higher
Browser
Modern browser with JavaScript enabled
