PRD Template for Supply Chain Products

Example: "Average order fulfillment time is 7.2 days against a customer expectation of 3 days. Stockout rate runs at 8.3%, causing an estimated $2.1M in lost revenue per quarter. Demand forecasting accuracy sits at 62% at the SKU level, forcing a 45-day safety stock buffer that ties up $14M in working capital. Manual purchase order creation takes 2.3 hours per order across 400 orders monthly, consuming 920 hours of procurement team capacity annually."

Example: "Primary: Reduce average order fulfillment time from 7.2 days to 3.5 days without increasing inventory investment. Inventory: Reduce safety stock from 45 days to 25 days while maintaining 97% fill rate. Forecast: Improve SKU-level demand forecast accuracy from 62% to 80% (MAPE). Automation: Automate 80% of routine purchase orders based on reorder point triggers. Visibility: Achieve real-time tracking for 95% of in-transit shipments."

Example: "As a demand planner, I want to see a 12-month demand forecast broken down by SKU, region, and channel with confidence intervals so that I can set appropriate safety stock levels and communicate capacity needs to suppliers. Acceptance criteria: forecast updates weekly with latest POS and order data; confidence intervals displayed at 80% and 95% levels; override capability for planned promotions and known events; historical accuracy tracked and displayed per SKU. As a warehouse manager, I want real-time inventory positions across all warehouse locations so that I can direct picking to the optimal location and identify misplaced stock before it causes a stockout."

Example: "FR-1: Inventory system supports multi-location, multi-lot tracking with FIFO, FEFO, and LIFO allocation strategies configurable per SKU category. FR-2: Reorder point calculation uses rolling 90-day demand, supplier lead time (average + 1 standard deviation), and target service level to determine optimal reorder quantity and timing. FR-3: Order orchestration engine selects fulfillment location based on: inventory availability, proximity to delivery address, shipping cost, and current warehouse capacity utilization. FR-4: Demand forecast uses ensemble model (exponential smoothing + ML) with automatic promotion lift detection. FR-5: EDI 850 (PO), 855 (PO Acknowledgment), 856 (ASN), and 810 (Invoice) support for all major suppliers."

Example: "IR-1: Bidirectional ERP integration (SAP/Oracle/NetSuite) for: master data sync (items, suppliers, customers), PO sync, receipt sync, and financial postings. Sync frequency: real-time for transactions, hourly for master data. IR-2: WMS integration via API for: inbound receiving, putaway confirmation, pick/pack/ship confirmation, cycle count adjustments, and real-time inventory positions. IR-3: TMS integration for: rate shopping, shipment booking, tracking updates, and proof of delivery capture. IR-4: E-commerce platform sync (Shopify/Magento) for: order ingestion within 60 seconds of placement, inventory availability push every 5 minutes, and shipment tracking push to customer. IR-5: Supplier portal for: PO delivery, ASN submission, invoice submission, and scorecard visibility."

Example: "SV-1: Real-time tracking for all in-transit shipments with carrier-provided GPS updates at minimum 15-minute intervals. SV-2: Predictive ETA calculation using historical transit times, current weather, port congestion, and customs processing times. Accuracy target: within 4 hours for domestic, 12 hours for international. SV-3: Automated exception alerts when: shipment deviates from planned route, ETA exceeds commitment, temperature excursion detected (cold chain), or customs hold initiated. SV-4: Control tower dashboard showing all active shipments, exceptions, and predicted on-time delivery rate."

Example: "Service: Order fill rate. Baseline: 91.7%. Target: 97%. Perfect order rate (on-time, in-full, damage-free, correct documentation). Baseline: 84%. Target: 92%. Inventory: Inventory turns. Baseline: 6.2. Target: 8.5. Days of supply. Baseline: 45. Target: 25. Cost: Freight cost per unit shipped. Baseline: $3.40. Target: $2.80. Supplier: On-time delivery rate. Baseline: 78%. Target: 90%. Supplier lead time variability (coefficient of variation). Baseline: 0.35. Target: 0.20."

Example: "Phase 1 (Months 1-3): Core inventory management and ERP integration for primary warehouse. Milestone: Real-time inventory accuracy above 98%. Phase 2 (Months 4-5): Demand forecasting module with 12-month historical data import. Milestone: Forecast accuracy exceeding 70% MAPE at SKU level. Phase 3 (Months 6-7): Purchase order automation and supplier portal for top 20 suppliers. Milestone: 60% of POs auto-generated. Phase 4 (Months 8-9): Shipment tracking and visibility across all carriers. Milestone: 90% of shipments trackable in real time. Phase 5 (Months 10-12): Rollout to additional warehouses and remaining suppliers."

Example: "Risk: ERP integration causes inventory discrepancies between systems. Likelihood: High. Impact: Critical (orders fulfilled against incorrect inventory). Mitigation: Automated reconciliation running every hour with alerts on discrepancies above 1%; designated ownership of each master data field; rollback procedure tested and documented. Owner: Integration lead. Risk: Warehouse staff resist new system due to workflow changes. Likelihood: High. Impact: High. Mitigation: Involve warehouse supervisors in design phase; deploy on mobile devices familiar to staff; run parallel operations with performance comparison; provide 2 weeks of on-site training."

Example: "Dependency 1: SAP S/4HANA — ERP. Integration: IDoc and BAPI interfaces. Migration difficulty: Very high. Dependency 2: Manhattan Associates — WMS. Integration: REST API. Migration difficulty: High (6-month reimplementation). Dependency 3: project44/FourKites — multi-carrier visibility platform. SLA: 99.5%. Integration: API + webhooks. Dependency 4: SPS Commerce — EDI translation and supplier network. Dependency 5: Snowflake — analytics data warehouse for demand forecasting model training."