PRD Template: Notion for Logistics & Supply Chain
Logistics product development requires PRDs that account for physical-world constraints: vehicle capacity limits, delivery time windows, warehouse layout dependencies, carrier API variability, and the cascading impact of delays across an entire supply chain. A feature that works perfectly in a test environment may fail when a truck breaks down or a warehouse runs out of dock space.
This Notion template provides a structured framework with linked databases for tracking logistics-specific requirements, carrier integrations, and operational constraints alongside your standard PRD sections.
Template sections
5 sections covering the complete prd workflow.
Operational Context and Physical Constraints
Document the physical-world constraints that bound your feature: vehicle types and capacity, warehouse throughput limits, dock door availability, shift schedules, and seasonal volume variations. Create a Notion database linking each constraint to the feature requirements it affects. Logistics features must be designed for peak volume, not average, because the consequences of failure during peak season are disproportionately expensive.
Last-mile delivery optimization feature must handle: 47 box trucks (26ft, 1,800 cubic ft capacity), 12 sprinter vans (450 cubic ft), and 8 cargo bikes for urban zones. Peak season (Nov-Dec) volume is 3.4x average. Current on-time delivery rate: 87% average, 71% during peak. Target: 94% average, 88% during peak. Constraint: drivers must take 30-min break after 8 hours per DOT regulations.
Tips
- Create a Notion database of physical constraints linked to requirements that depend on them
- Include seasonal volume multipliers in every capacity calculation
- Document DOT, FMCSA, and local regulations that constrain operations
- Add a Constraints section to every Notion PRD page with a linked database view
Carrier and Partner Integration
Logistics products integrate with carriers (FedEx, UPS, USPS, regional carriers), warehouse management systems, transportation management systems, and ERP platforms. Each integration has different API capabilities, rate limit constraints, and data freshness guarantees. Your PRD must specify which carriers are in scope, what API operations are required, and how you handle carrier-specific limitations and outages.
Multi-carrier rate shopping integrates with FedEx (REST API, 5 req/sec rate limit, real-time rates), UPS (REST API, 10 req/sec, 15-min cached rates), USPS (Web Tools API, 3 req/sec, real-time), and 4 regional carriers (EDI 204/990, batch file exchange twice daily). Rate comparison must complete within 3 seconds for checkout UX. Caching strategy: pre-compute rates for top 500 origin-destination pairs nightly.
Tips
- Create a Notion table comparing carrier API capabilities, rate limits, and SLAs
- Document fallback behavior when a carrier API is unavailable or slow
- Include carrier-specific data mapping tables in the Notion PRD
- Plan for carrier API versioning and deprecation (FedEx and UPS change APIs every 2-3 years)
Route Optimization and Delivery Windows
Route optimization is a constrained optimization problem with multiple competing objectives: minimize distance, maximize on-time delivery, respect time windows, balance driver workload, and account for vehicle capacity. Your PRD must specify the optimization objectives, constraints, and acceptable tradeoffs. Include the expected computational complexity and whether the feature requires real-time or batch optimization.
Dynamic route optimization for 200 daily deliveries across 15 drivers. Constraints: 4-hour delivery windows promised to customers, 50-lb weight limit per package, maximum 12 hours per driver shift, and refrigerated items must maintain cold chain (below 40 degrees F). Optimization runs every 30 minutes to incorporate new orders and traffic data. Target: reduce total route miles by 18% while maintaining 94% on-time rate. Current solver: Google OR-Tools with 30-second time limit per optimization run.
Tips
- Specify optimization objectives in priority order (on-time rate > total miles > driver balance)
- Document the computational budget (how long the optimizer can run before returning a solution)
- Include re-optimization triggers: new orders, traffic incidents, driver unavailability
- Create acceptance criteria that test edge cases: single-stop routes, maximum-capacity vehicles, tight time windows
Real-Time Tracking and Visibility
Logistics stakeholders (shippers, receivers, dispatchers, customers) all need real-time visibility into shipment status, but each audience needs different information at different update frequencies. Your PRD must specify the tracking data model, update frequency by audience, and the notification triggers for each shipment lifecycle event. GPS tracking accuracy, cellular coverage gaps, and battery life on tracking devices are physical constraints that affect feature design.
Real-time tracking dashboard for B2B shippers. GPS updates every 60 seconds from Samsara telematics units on trucks. Customer-facing tracking page updates every 5 minutes with ETA recalculation. Dispatcher view updates in real-time via WebSocket. Notification triggers: departed warehouse, arrived at stop, delivery completed, exception (delay > 30 min from ETA). Offline handling: when truck enters cellular dead zone, buffer GPS points on device and bulk-upload on reconnection.
Tips
- Specify update frequency per audience (dispatchers need real-time, customers need periodic)
- Document offline/connectivity gap handling for tracking devices
- Include ETA calculation methodology and accuracy targets
- Create a Notion database of tracking events mapped to notification rules per audience
Exception Handling and Contingency Flows
Logistics operations generate exceptions constantly: failed deliveries, damaged goods, address errors, vehicle breakdowns, weather delays, and customs holds. Your PRD must document the top 10 exception types by frequency, the handling workflow for each, and the escalation path when automated handling fails. Exception handling often represents 30-40% of the engineering work but is frequently underspecified in PRDs, leading to manual workarounds that do not scale.
Top exceptions by volume: Failed delivery attempt (32% of exceptions) - leave at door/reattempt next day/redirect to pickup point. Address not found (18%) - driver calls customer, 3 attempts then return to warehouse. Package damaged (12%) - photograph damage, file carrier claim, ship replacement. Vehicle breakdown (8%) - reassign remaining stops to nearest available driver within 30 minutes.
Tips
- Create a Notion database of exception types with frequency, handling workflow, and escalation rules
- Include exception rate targets in success metrics (e.g., reduce failed deliveries from 8% to 4%)
- Document the cost per exception type to prioritize automation investments
- Write separate Notion requirement blocks for each exception flow with acceptance criteria
Copy-paste template
# [Feature] PRD — Logistics (Notion) ## Operational Constraints | Constraint | Value | Impact | |---|---|---| | [Constraint] | [Value] | [Which requirements affected] | ## Carrier Integrations | Carrier | API Type | Rate Limit | Data Freshness | |---|---|---|---| | [Carrier] | [REST/EDI/Batch] | [Limit] | [Real-time/Cached] | ## Route Optimization - **Objectives (priority order):** [List] - **Constraints:** [List] - **Solver:** [Algorithm/Tool] - **Time budget:** [Seconds] ## Tracking | Audience | Update Frequency | Data Elements | |---|---|---| | [Audience] | [Frequency] | [Fields] | ## Exception Handling | Exception | Frequency | Automated? | Handling | |---|---|---|---| | [Type] | [% of exceptions] | [Yes/No] | [Workflow] |
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